Role of the FOXO-FOXM1 axis in the progression of metastatic breast cancer

Thesis submitted by Laura Bella To Imperial College London For the degree of Doctor of Philosophy

Department of Surgery and Cancer

Page | 1

Declaration of originality I hereby declare that all the work included in this thesis is my own unless otherwise stated, and has been referenced accordingly.

The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work.

Page | 2

Abstract

Lack of available therapies to combat and prevent tumour progression have rendered tumour metastasis one of the primary causes of mortality in cancer. Interestingly, the insurgence of tumour resistance to cytotoxic chemotherapy has been linked to tumour relapse and death. This project aimed to characterise the phenotypical and behavioural alteration that breast cancer cell lines adopt when developing resistance to the anthracycline (epirubicin) and the taxane (paclitaxel). It then aimed to associate these alterations with varying levels of the Forkhead Box proteins FOXO- FOXM1 expression, to determine whether these transcription factors, extensively characterised for their role in both the development of drug resistance and individual aspects of cancer progression, could cause the changes noted in these cell lines. Using a combination of in vitro techniques and the novel in vivo zebrafish embryo model, developed during this project, the drug resistant MCF-7 breast cancer cell lines were shown to have undergone the epithelial to mesenchymal transition and possess significantly increased capacities to migrate and form mammospheres in vitro as well as induce neoangiogenesis and metastasize in vivo, when compared with their parental MCF-7 WT cells. More in depth analysis demonstrated FOXO3 endogenous suppression was key to the loss of E-cadherin expression, whilst the overexpression of FOXM1 could be directly linked to the increased cancer progression capacities noted in the resistant cell lines. Then, KIF20A was identified as a critical FOXM1 down-stream effector that could regulate all aspects of cancer progression through a hypothesized structural interaction with the cytoskeleton. Alternatively, SOX4 was shown to possess a completely novel angiogenic function, which could, when inhibited, completely prevent breast cancer induced angiogenesis in vivo. In conclusion, this project unveiled a novel rate-limiting role for FOXO-FOXM1, as well as KIF20A and SOX4 as prognostic markers and potential drug targets to combat the cancer progression of breast cancer.

Page | 3

Acknowledgments

First and foremost, I would like to express my gratitude to Prof. Eric Lam, for his guidance and support throughout the project. I have learned more than I could ever imagine (about both science and gin!) and your supervision and friendship have made these years fly by.

I would then like to acknowledge Dr. Laurence Bugeon, Prof Jonathan Lamb and Prof. Maggie Dallman. You were always there to guide me through whichever conundrum I was faced with, with both patience and helpful suggestions, and I would never have made it without you.

Thank you to the ever changing Lam lab group. Writing your names would take hours, as I’ve had the pleasure to work with so many of you, but you know who you are. Thank you for all the fun, making me survive day after day in the lab.

Grazie alla mia mafia italiana. Francesca e Stefania, mi avete letteralmente salvato piu` di una volta. Speriamo che un giorno potremo lavorare insieme di nuovo.

A special thank you goes to Cat, my first student and mischief companion. You helped me more than you know.

Thank you to my fish ladies, Nathalie, Fränze, Marie, and Kathryn. You fed, harvested and bred those fish for me week after week, and didn’t complain a single time. But mostly, you kept me entertained during those tedious microinjections; I wouldn’t have survived without you.

Thank you to all the Imperial friends who came and went during the years. Thank you for the coffees, Friday drinks and chats in the corridors. I’m so happy to have you in my life.

Thank you to Jimmy, my personal post-doc. There aren’t enough words to thank you enough, but we both know that I am where I am because of you.

And finally, thank you to my family, mamma, papa`, Claudio, Davide and Daniele. Grazie per esservi arrabbiati quando mi trattavano male e avermi fatto fare questa pazzia. Siete, e sarete sempre, le mie persone preferite.

Page | 4

To my family,

To Jimmy,

And, as promised,

To Milly.

Page | 5

Contents Abstract ...... 3 Acknowledgments ...... 4 Tables and Figures ...... 10 List of Abbreviations ...... 13 Chapter 1: Introduction ...... 15 1.1 Cancer ...... 15 1.2 Breast cancer ...... 16 1.3 Triple negative breast cancer treatment ...... 19 1.4 The insurgence of drug resistance ...... 21 1.5 Cancer progression ...... 22 1.5.1.1 Epithelial to mesenchymal transition ...... 23 1.5.1.2 The epithelial to mesenchymal transition in breast cancer ...... 28 1.5.2.1 Tumour induced angiogenesis ...... 30 1.5.2.2 Tumour induced angiogenesis in breast cancer ...... 34 1.5.3.1 The cancer stem cell phenotype ...... 36 1.5.3.2 Breast cancer stem cells ...... 37 1.5.4.1 Cancer cell migration and invasion ...... 43 1.5.4.2 Migration and invasion in breast cancer ...... 46 1.5.5.1 Cancer metastasis ...... 47 1.5.5.2 Breast Cancer metastasis ...... 49 1.6 The phosphoinositide 3-kinase (PI3K) pathway ...... 51 1.7. The Forkhead Box transcription factors...... 53 1.7.1 The Forkhead Box transcription factors: FOXO...... 55 1.7.2 The Forkhead Box transcription factors: FOXM1 ...... 56 1.7.3.1 FOXO-FOXM1 in tumour induced angiogenesis ...... 58 1.7.3.2 FOXO-FOXM1 and the epithelial to mesenchymal transition...... 60 1.7.3.3 FOXO-FOXM1 and the cancer stem cell phenotype ...... 61 1.7.3.4 FOXO-FOXM1 in migration and invasion ...... 62 1.7.3.5 FOXO-FOXM1 in metastasis ...... 63 1.8 Thesis outline and aims...... 64 1.9 Thesis hypothesis ...... 65 Chapter 2: Materials and Methods ...... 66 2.1 Cellular culture ...... 66 2.2 Cell line storage ...... 67 2.3 Cell culture drugs ...... 67

Page | 6

2.4 Cellular transfections ...... 67 2.5 Small interfering RNA transfection ...... 67 2.6 Co-transfection ...... 68 2.7 Cellular drug treatment ...... 68 2.8 Preparation of total protein lysates ...... 68 2.9 SDS-page gel electrophoresis and Western Blotting ...... 69 2.10 RNA extraction ...... 69 2.11 Real-time Quantitative PCR (RTq-PCR) ...... 70 2.12 Primer optimisation ...... 71 2.13 Chromatin immunoprecipitation (Chip) ...... 71 2.14 Luciferase reporter assay ...... 72 2.15 Transformation and culture of bacteria ...... 72 2.16 Plasmid mini- and maxi-prep ...... 73 2.17 Immunofluorescent staining ...... 73 2.18 Cell invasion and migration assays ...... 73 2.19 Wound-healing assay ...... 74 2.20 Mammosphere formation assay ...... 74 2.21 Sulphorhodamine B (SRB) assay ...... 74 2.22 Sub-cellular fractionation ...... 75 2.23 Zebrafish maintenance ...... 75 2.24 CM-DiI labelling optimisation ...... 76 2.25 CM-DiI cell labelling ...... 76 2.26 Microinjection of human tumour cell lines ...... 76 2.27 Zebrafish embryo live imaging ...... 77 2.28 Statistical and data analysis ...... 77 Chapter 3: Results ...... 78 Chapter 3.1: The cancer progression of drug resistant cell lines ...... 78 3.1.1: Epirubicin and paclitaxel resistant breast cancer cell lines display acquired mesenchymal characteristics...... 81 3.1.2: Anthracycline and taxane resistant cell lines have significantly higher migratory abilities in vitro compared to the sensitive counter-parts...... 83 3.1.3: Drug resistant MCF-7 cells display increased stem-like cell populations...... 85 3.1.4: Drug resistant cell lines can induce more neoangiogenesis in vivo...... 89 3.1.5: Epirubicin and paclitaxel resistant MCF-7 cells are able to metastasize in vivo in zebrafish embryos...... 95 3.1.6: Discussion ...... 100 Chapter 3.2: FOXO3 and the cancer progression of drug resistant cell lines ...... 108

Page | 7

Chapter 3.2.1: FOXO3 mimics E-cadherin expression in sensitive cell lines ...... 109 Chapter 3.2.2: Sub-cellular fractionation displays a similar FOXO3 expression pattern between sensitive and drug resistant MCF-7 cells...... 115 Chapter 3.2.3: Chip reveals FOXO3 capacity to bind E-cadherin is significantly impaired in resistant cell lines ...... 119 Chapter 3.2.4: FOXO3 transient overexpression is unable to revert the mesenchymal phenotype of the resistant cell lines...... 121 Chapter 3.2.5: FOXO3 can alter the mammosphere formation in both sensitive and epirubicin resistant cell lines ...... 124 Chapter 3.2.6: Discussion ...... 127 Chapter 3.3: The role of FOXM1 in the cancer progression of drug resistant cell lines ...... 130 Chapter 3.3.1: FOXM1 is overexpressed in epirubicin and paclitaxel resistant cell lines ...... 131 Chapter 3.3.2: FOXM1 can modulate the directional migration of MDA-MB-231 cell lines ...... 133 Chapter 3.3.3: FOXM1 inhibition can diminish MDA-MB-231 migration in a Boyden-Chamber assay ...... 135 Chapter 3.3.4: FOXM1 overexpression enables parental MCF-7 WT cells to display enhanced migration...... 137 Chapter 3.3.5: FOXM1 silencing inhibits the migration of epirubicin resistant MCF-7 cells and of paclitaxel resistant MCF-7 cells...... 139 Chapter 3.3.6: FOXM1 can modulate MCF-7 mammosphere formation ...... 142 Chapter 3.3.7: FOXM1 silencing hinders the stem-like potential of MCF-7 TaxR and EpiR ...... 145 Chapter 3.3.8: FOXM1 knock-down diminishes MDA-MB-231 metastasis in vivo ...... 148 Chapter 3.3.9: FOXM1 silencing can inhibit the metastasis of the resistant cell lines in vivo ...... 150 Chapter 3.3.10: Discussion ...... 153 Chapter 3.4: The role of KIF20A in the cancer progression of drug resistant cell lines ...... 158 Chapter 3.4.1: Selection of FOXM1 downstream targets ...... 160 Chapter 3.4.2: KIF20A pattern follows that of FOXM1 ...... 163 Chapter 3.4.3: FOXM1 controls KIF20A through direct transcriptional regulation ...... 165 Chapter 3.4.4: KIF20A is overexpressed in aggressive MDA-MB-231 cells as well as in drug resistant MCF-7 cells ...... 168 Chapter 3.4.5: KIF20A can control the directional migration of MDA-MB-231 cells ...... 169 Chapter 3.4.6: KIF20A silencing significantly inhibits the migration of MDA-MB-231 cells ...... 172 Chapter 3.4.7: KIF20A influences the migration of both epirubicin and paclitaxel resistant cell lines 175 Chapter 3.4.8: KIF20A is essential for the mammosphere formation of MCF-7 WT cells ...... 175 Chapter 3.4.9: KIF20A silencing can inhibit the mammosphere formation of both drug resistant cell lines ...... 178 Chapter 3.4.10: KIF20A overexpression can increase tumour induced angiogenesis in vivo ...... 181 Chapter 3.4.11: KIF20A silencing can inhibit the metastasis of MDA-MB-231 ...... 185

Page | 8

Chapter 3.4.12: KIF20A inhibition can abolish the metastatic potential of both drug resistant cell lines...... 187 Chapter 3.4.13: KIF20A inhibition can abolish the metastatic potential of both drug resistant cell lines...... 190 Chapter 3.4.14: KIF20A silencing alters the microtubule dynamics in both sensitive and drug resistant cell lines ...... 193 Chapter 3.4.15: Discussion ...... 198 Chapter 3.5: SOX4 and the regulation of tumour induced angiogenesis ...... 203 Chapter 3.5.1: SOX4 silencing can inhibit tumour induced angiogenesis ...... 204 Chapter 3.5.2: SOX4 induction can cause tumour neoangiogenesis ...... 206 Chapter 3.5.3: SOX4 regulates angiogenesis through endothelin-1 ...... 211 Chapter 3.5.4: SOX4 and FOXM1 ...... 212 Chapter 3.5.5: Discussion ...... 215 Chapter 4: Conclusions and Future Work ...... 218 References...... 230

Page | 9

Tables and Figures

Table 1 1. Tumour type, prevalence and hormonal receptor expression…………………………………………15

Figure 1 1. Primary signalling pathways……………………………………………………………………………………………23

Figure 1 2. Tumour induced angiogenesis……………………………………………………………………………………….30

Table 1 2. Summary of different signalling pathways and their role in the promotion and maintenance of breast cancer stem cells………………………………………………………………………………………...37

Table 1 3. Biomarkers for the isolation of breast cancer stem cells………………………………………………….38

Figure 1 3 FOXO-FOXM1 signalling pathway…………………………………………………………………………………….51

Figure 1 4. FOXM1 can control essential processes in cancer progression……………………………………….55

Figure 3.1 1 Drug resistant cell lines have lost the epithelial markers………………………………………………77

Figure 3.1 2. Both epirubicin and paclitaxel resistant MCF-7 cell lines are more able to migrate than their sensitive counterparts……………………………………………………………………………………………………………..81

Figure 3.1 3. Epirubicin and paclitaxel drug resistant cell lines have higher cancer stem cells properties than their sensitive counterparts……………………………………………………………………………………85

Figure 3.1 4. Development of the sub-intestinal vessel (SIV) complex in zebrafish embryos…………….89

Figure 3.1 5. Drug resistant cell lines induce more angiogenesis than their sensitive counterparts. …91

Figure 3.1 6. Optimisation of zebrafish embryo metastasis model…………………………………………………..95

Figure 3.1 7. Drug resistant cell lines metastasize in vivo in a zebrafish embryo model……………………96

Figure 3.2 1. FOXO3 regulation of E-cadherin in sensitive and resistant cell lines…………………………..107

Figure 3.2 2. FOXO3 and E-cadherin increase in expression during epirubicin drug treatment……….108

Figure 3.2 3. FOXO3 regulation of E-cadherin in sensitive and resistant cell lines…………………………..109

Figure 3.2 4. FOXO3 and E-cadherin increase in expression during paclitaxel drug treatment……….110

Figure 3.2 5. Subcellular fractionation reveals FOXO3 activation in MCF-7 EpiR cells……………………. 113

Figure 3.2 6. Subcellular fractionation reveals FOXO3 activation in MCF-7 TaxR cells…………………….114

Figure 3.2 7. Chromatin immuno-precipitation shows less FOXO3-E-cadherin binding in resistant cell lines……………………………………………………………………………………………………………………………………………….116

Figure 3.2 8. Effect of FOXO3 transient alteration in MCF-7 WT cells……………..………………………………118

Figure 3.2 9. Effect of FOXO3 transient alteration in MCF-7 EpiR cells……………………………………………119

Figure 3.2 10. FOXO3 can regulate mammosphere formation……………………………...……………………….122

Figure 3.3 1 FOXM1 is over-expressed in the resistant cell lines…………………………………………………….130

Figure 3.3 2. Inhibition of FOXM1 reduces MDA-MB-231 directional migration…………………………….132

Figure 3.3 3. Silencing of FOXM1 or KIF20A significantly inhibits MDA-MB-231 cell migration……….134

Page | 10

Figure 3.3 4. FOXM1 overexpression enables MCF-7 WT cells to acquire higher migration abilities………………………………………………………………………………………………………………………………………….136

Figure 3.3 5. FOXM1 silencing significantly impairs EpiR cell migration………………………………………….138

Figure 3.3 6. FOXM2 silencing significantly impairs TaxR cell migration…………………………………………139

Figure 3.3 7. FOXM1 overexpression promotes mammosphere formation and size increase in MCF-7 WT cells…………………………………………………………………………………………………………………………………………141

Figure 3.3 8. MCF-7 WT FOXM1 silencing can inhibit mammosphere formation………………………….142

Figure 3.3 9. FOXM1 silencing impairs EpiR ability to form mammospheres………………………………….144

Figure 3.3 10. FOXM1 silencing reduces mammosphere formation and size in MCF-7 TaxR cells…..145

Figure 3.3 11. FOXM1 silencing can reduce MDA-MB-231 metastasis in vivo in zebrafish embryos………………………………………………………………………………………………………………………………………..147

Figure 3.3 12. FOXM1 silencing can inhibit MCF-7 EpiR metastasis in vivo in zebrafish embryos……149

Figure 3.3 13. FOXM1 silencing can inhibit MCF-7 TaxR metastasis in vivo in zebrafish embryos……150

Figure 3.4 1. Selection of FOXM1 down-stream targets based on behavioural similarities upon epirubicin treatment………………………………………………………………………………………………………………………162

Figure 3.4 2. Effect of FOXM1 alteration on potential down-stream target expression………………….164

Figure 3.4 3. FOXM1 regulates by binding directly to its promoter region……………………………………..167

Figure 3.4 4. KIF20A expression across different breast cancer cell lines……………………………………….169

Figure 3.4 5. Inhibition of FOXM1 reduces MDA-MB-231 directional migration…………………………….170

Figure 3.4 6. Silencing of FOXM1 or KIF20A significantly inhibits MDA-MB-231 cell migration……….171

Figure 3.4 7. KIF20A silencing significantly impairs MCF-7 EpiR migration……………………………………..173

Figure 3.4 8. KIF20A silencing significantly impairs MCF-7 TaxR cell migration………………………………174

Figure 3.4 9. KIF20A overexpression can increase number but not size of mammospheres in MCF-7 WT cells…………………………………………………………………………………………………………………………………………176

Figure 3.4 10. KIF20A silencing impairs MCF-7 WT mammosphere formation……………………………….177

Figure 3.4 11. KIF20A silencing impairs MCF-7 EpiR ability to form mammospheres……………………..179

Figure 3.4 12. KIF20A silencing impairs MCF-7 TaxR ability to form mammospheres……………………..180

Figure 3.4 13. KIF20A overexpression increases MCF-7 WT neoangiogenesis…………………………………182

Figure 3.4 14. KIF20A can alter breast cancer proliferation but not VEGF expression…………………….183

Figure 3.4 15. KIF20A can impair MDA-MB-231 metastasis in vivo…………………………………………………186

Figure 3.4 16. KIF20A silencing can inhibit MCF-7 EpiR metastasis in vivo in zebrafish embryos…….188

Figure 3.4 17. KIF20A silencing can inhibit MCF-7 TaxR metastasis in vivo in zebrafish embryos……189

Figure 3.4 18. KIF20A can over-ride FOXM1 control of MCF-7 EpiR migration………………………………..191

Page | 11

Figure 3.4 19. KIF20A and FOXM1 are essential for MCF-7 TaxR migration…………………………………….192

Figure 3.4 20. KIF20A silencing impairs tubulin cytoskeleton formation in MCF-7 WT cells……………195

Figure 3.4 21. KIF20A silencing impairs tubulin cytoskeleton formation in the MCF-7 EpiR cells…….196

Figure 3.4 22. KIF20A silencing impairs tubulin cytoskeleton formation in MCF-7 TaxR cells………...197

Figure 3.5 1. SOX4 silencing impairs MDA-MB-231 angiogenesis……………………………………………………203

Figure 3.5 2. SOX4 induction triggers HMLE neoangiogenesis………………………………………………………..205

Figure 3.5 3 Silencing of endothelin-1 impairs SOX4 neoangiogenesis……………………………………………207

Figure 3.5 4. SOX4 interaction with FOXM1 varies according to cell line………………………………………..211

Page | 12

List of Abbreviations

4-OHT, 4-hydroxitamoxifen LB, lysogeny broth ATM, Ataxia-telangiectasia mutated MAPK, mitogen activated protein kinase BCSC, breast cancer stem cell MB, methylene blue BRCA1, breast cancer associated gene 1 MDM2, murine double minute 2 BRCA2, breast cancer associated gene 2 MDR, multidrug resistance protein BSA, bovine serum albumin MEF, mouse embryonic fibroblast CDK, cyclin dependent kinase MEK, MAPK/ERK kinase CDH1, E-cadherin Min, minute cDNA, complementary DNA miR, Micro-RNA Chip, chromatin immunoprecipitation MMP, matrix metalloproteinase Ctrl, control mTOR, mammalian target of rapamycin DMEM, Dulbecco modified eagle serum NF-κB, nuclear factor kappa B DTT, dithiothreitol NSL, nuclear localization signal EDTA, Ethylenediaminetetraacetic acid NSC, non-specific control EGFR, epidermal growth factor receptor PAGE, polyacrylamide gel electrophoresis ER, estrogen receptor PARP1, Poly-ADP-ribose polymerase 1 ET-1, endothelin-1 PBS, phosphate buffer saline EpiR, epirubicin resistant PBST, phosphate buffered saline tween FACS, fluorescent activated cell sorting PDGF, platelet derived growth factor FCS, foetal calf serum PDK1, Phosphoinositide-dependent kinase 1 FGF, fibroblast growth factor PI3K, Phosphatidylnositol-3 kinase FHRE, Forkhead response element PIP2, Phosphatidylnositol 4,5-biphosphate FOX, forkhead box PKC, Protein kinase C GFP, green fluorescent protein PMSF, Phenylmethylsulfonyl fluorid h, hour PR, progesterone receptor HDAC, histone deacetylases pRB, retinoblastoma protein HIF-1α, hypoxia inducible factor -1α PTEN, phosphatase and tensin homolog JAK2, janus kinase 2 RAS, rat sarcoma L19, ribosomal protein L19

Page | 13

ROS, reactive oxygen species TaxR, taxanes resistant RT, room temperature TBS, Tris buffered saline tween RTK, receptor tyrosine kinase TBST, tris buffered saline tween RTq-PCR, real quantitative polymerase TCA, trichloroacetic acid chain reaction TGFβ, transforming growth factor β SDS, sodium dodecyl sulphate TRAIL, TNF-related apoptosis inducing Sec, seconds ligand siRNA, small interfering RNA UV, ultraviolet SIV, sub-intestinal vessel VEGF, vascular endothelial growth factor SOX4, SRY-Box 4 VEGFR, vascular endothelial growth factor receptor STAT, signal transducer and activator of transcription WT, wild-type TAD, transactivation domain

Page | 14

Chapter 1: Introduction

1.1 Cancer Cancer is a neoplastic disease derived primarily from the uncontrolled proliferation of cells. This disease encompasses a complexity in the cancerous tissue, presenting a multitude of cell types within the primary tumour mass, as well as heterotypical interactions between the tumour and the surrounding tumour-associated stroma, which portrays an active role in tumourigenesis (Hanahan and Weinberg, 2011). Cancer cells break the most basic rules of behaviour by which multi-cellular organisms are built and maintained. Functional abnormalities of proteins involved in DNA repair, cell signalling, cell cycle control, programmed cell death, and tissue architecture have been identified to lead to cancers (Alberts 2002).

According to the International Agency for Research on Cancer (IARC), regardless of gender and cancer type, the prevalence of cancer is on the rise, estimated to have presented 14,067,894 new cases world-wide in 2012, with overall cancer related deaths tolling 8,201,575. Amongst cancer types, lung displayed the highest prevalence, with 1,824,701 cases in 2012. This was quickly followed by breast, with 1,671,149 cases, colorectum with 1,360,602 and prostate, with 1,094,916 cases world-wide in 2012. Unsurprisingly, lung was portrayed as the biggest killer, causing 28.5% of total cancer related deaths. Other cancers causing high mortality were liver, stomach and colorectum, each sharing 13% of the burden of cancer mortality. Breast cancer ranked 5th for cancer mortality, accounting for 9.4% of deaths (IARC 2016).

The tables are swiftly undone when the focus is placed on the female population. In this case, breast cancer becomes the most prevalent cancer, accounting for a massive 35.3% of cancer cases world-wide, and 20.8% of total cancer mortality. This is also higher than the female mortality from lung cancer, which remains slightly smaller at 19.6%. When looking at the five-year prevalence, breast cancer displays an astounding 45.6% (IARC 2016). Globocan web-site for cancer incidence, mortality and prevalence world-wide predicts that in 2020 the incidence of new cancer cases will affect 17,113,588 people, evenly distributed between people above and below the 65 year mark, with a slight predominance for the male population. In terms of total cancer deaths, Globocan estimates a massive 10,046,745, in this case with a significant despondence for the population aged above 65 years and a slight predominance for the male population. For the female population, breast cancer is estimated to have had an incidence of 1,979,022 of new cases in 2012,

Page | 15 predominantly affecting women below 65 years of age. Of these, there will be an estimated world- wide mortality of 622,676 cases (Globocan, 2016).

1.2 Breast cancer As mentioned previously, breast cancer is the most prevalent cancer in women, displaying the highest morbidity amongst women and the fifth highest mortality when disregarding gender distinctions. Breast cancer had an estimated 1.38 million new cancer cases diagnosed in 2008, prevailing in both developed and non-developed areas, with an estimated 1:4 people affected. Incidence rates are diverse according to region, varying from 19.3 per 100,000 women in eastern Africa, to 87.9 cases per 100,000 women in Western Europe, remaining more frequent in developed countries when compared to developing countries (with the exception of Japan). Breast cancer mortality is instead more varied, with higher survival rates and more favourable outcomes directly correlated to the regions development status. Thus, breast cancer is ranked as the fifth cause of cancer mortality world-wide, despite it being the most common cancer in women in both developing and developed worlds, with its overall deaths comparable to those from lung cancer (Gangopadhyay et al., 2013).

Breast cancer presents different categorisations, depending on the purpose of the classification. For instance, breast cancer can be subdivided according to its grade (appearance of cancer cells when compared to normal breast cells), its stage (TNM, T for describing tumour, N for lymph nodes involved and M for potential metastasis), its histopathological type or its genetic profile. A summary of general traits in breast cancer classification can be found in Table 1.1.

Genetic profiling has identified the most prevalent genetic markers which could act as predicting biomarkers for the insurgence of breast cancer, as well as for estimating the response to neoadjuvant- or chemo-therapy. This predominantly heterogeneous disease generally harbours several genetic mutations, but different hereditary prediction markers have been identified. These include breast cancer type 1 (BRCA1) and breast cancer type 2 (BRCA2) susceptibility proteins, as well as p53, which are inherent of a predisposition to the development of both breast and ovarian cancers. However, these only account for a minority of breast cancer cases(Miki et al., 1994)(Wooster et al., 1995). Alternatively, breast cancer patient prognosis can be differentiated into low, medium and high risk according to both clinical and biological factors, such as age at diagnosis, tumour grade, size and histology, lymph node status and the expression of oestrogen (ER), progesterone (PR) receptors and HER2-status (Goldhirsch et al., 1998). Diagnosis upon detection will determine the type of treatment the patient

Page | 16

Table 1.1 Tumour type, prevalence and hormonal receptor expression. Table depicting breast cancer tumour sub-types, with the respective expression of endocrine receptors, and over- all prevalence. ER: Oestrogen Receptor, PR: Progesterone receptor HER2: Human epidermal growth factor receptor 2.

Subtype These tumours tend to be: Prevalence (approximate)

Luminal A  ER-positive and/or PR-positive 30-70%

 HER2-negative

 Low Ki67

Luminal B  ER-positive and/or PR-positive 10-20%

 HER2-positive

 HER2-negative with high Ki67

Triple negative/  ER-negative 15-20% basal-like  PR-negative

 HER2-negative

HER2 type  ER-negative 5-15%

 PR-negative

 HER2-positive

Page | 17 will receive. This will vary between radio-, hormone-, chemo- and adjuvant- therapy, as well as surgery.

Predictive markers are essential for the estimate of treatment outcome and eventual disease relapse. Some of the markers which have been identified for breast cancer include ER, PR and HER-2. Breast cancer has since been classified according to their expression. Notably breast cancers can now be classified in one of 5 distinct groups: luminal A and B (positive for ER and PR), HER-2 over-expressing, basal-subtype and normal basal-like group (each noted for its general lack of expression of either ER, PR or HER2, with the exception of few tumours) (Sørlie et al., 2001). Basal-like subgroups lacking expression of ER, PR or HER2, are known as triple negative breast cancers, and characteristically exhibit a poor clinical outcome (El-rehim et al., 2005). Around 80% of breast cancers display expression of ER or PR, with the remainder generally over-expressing HER-2. These are treated with endocrine therapy, as these markers are predictors of good clinical outcome (Burcombe et al., 2005).

E belong to the superfamily of nuclear hormone receptors. The ER, which is subdivided into ER -α and –β, responds to the binding of its ligand 17β estradiol. Upon activation, ER initiates a signalling cascade which ultimately leads to cell proliferation, angiogenesis and metastasis, as well as survival to apoptosis (Herynk and Fuqua, 2016). In healthy individuals, oestrogen contributes to the normal development of breasts. However, abnormal exposure to endogenous and exogenous oestrogen has since been shown to be one of the promoters of not only breast cancers, but also ovarian, prostate and endometrial cancers (Deroo and Korach, 2006)(Hankinson, Colditz, & Willett, 2004)(Henderson and Feigelson, 2000). This is thought to be through the instigation of oxidative stress, of which accumulation can lead to genotoxic stress, and eventually cancer. The importance of ERα for the treatment of breast cancer has been highlighted due to the high incidence of breast cancers (around 70%) which display and abnormal increase in ERα expression, and rely on it to attain the unlimited proliferative potential (Hayashi et al., 2003). Therefore ERα has become one of the primary targets for endocrine therapy, which was commonly administered as adjuvant therapy, in cases of ER positive breast cancers. Examples include tamoxifen and fulvestrant, which prevent oestrogen from binding to its receptor, thus inhibiting its activation. Other commonly used endocrine therapies include aromatase inhibitors such as letrozole and exemestane: these instead function by preventing the endogenous oestrogen synthesis (Mauri et al., 2006).

HER-2 (neu or c-ErbB2) is a transmembrane receptor tyrosine kinase, over-expressed in around 20-25% of breast cancers (Bartlett et al., 2001). HER-2 overexpression is usually a predictor of

Page | 18 tumour aggressiveness, of higher chance of tumour recurrence and poorer patient survival. Patients diagnosed with HER-2 over-expressing tumours usually benefit from anthracycline adjuvant therapy to enter the disease-free survival stage (Muss et al., 1994). In recent years, research has discovered new targeted therapy options for patients with HER-2 over-expressing tumours, notably trastuzumab (Herceptin), and lapatinib (Browne et al., 2009). Bevacizumab is instead an option for HER-2 negative breast cancers.

1.3 Triple negative breast cancer treatment Tumours which display a non-responsive phenotype to endocrine or targeted therapy are generally treated with a systematic cytotoxic chemotherapeutic agents, which can be used as single agents or in combination. These include taxanes (paclitaxel and docetaxel) and anthracyclines (Epirubicin and Doxorubicin; Ali & Coombes, 2002; Wenzel et al., 2002).

Anthracyclines begun in the 1960s, when they were extracted from the pigment producing Streptomyces peucetius. They quickly entered the market to become one of the most effective anti- cancer drugs. However, as with most cytotoxic chemotherapies, doxorubicin administration was soon hindered due to its disruptive effect on healthy tissues, as well as its causing cardiomyopathy and congestive heart failure. Epirubicin was developed as an attempt to overcome the severe toxicity of doxorubicin. This semi-synthetic doxorubicin derivative only differed from the original molecule in the orientation of the C-4 hydroxyl group on the sugar. This slight structural alteration proved effective in the reduction of cardiotoxicity upon administration, granting the possibility of administering double the dose of epirubicin than that for doxorubicin, while still limiting the toxicity and not affecting its effectiveness (Weiss, 1992)(Robert, 1994).

To date, the mechanism of anthracycline activity remains incompletely understood. However, evidence has pointed to its creation of DNA damage via the inhibition of the activity of the topoisomerase II. Topoisomerases are ubiquitous enzymes which are crucial for DNA replication and transcription, as they regulate the winding and unwinding of the DNA structure to create transient single-stranded (Topoisomerase I) or double-stranded (Topoisomerase II) breaks in the helix, for the insertion of new DNA strands, only to be covalently resealed by the same enzymes(Froelich-ammon & Osheroff, 1995). Anthracycline particularly target Toposiomerase II to accelerate the rate of insertion of double-stranded breaks, while refraining the enzyme from its re-sealing capacity. To enhance their disruptive activity, anthracyclines simultaneously intercalate within the DNA strands and cause the formation of reactive oxygen species (ROS), as well as activating ataxia teleangiectasia mutated kinase (ATM), provoking p53 nuclear translocation, and eventually leading to cell cycle arrest and apoptosis (Minotti et al., 2004)(Zhou and Elledge, 2000).

Page | 19

Alternatively, anthracyclines can also induce apoptosis in p53 and ATM independent manners, notably by causing the release of cytochrome c from the mitochondria, and inhibiting downstream activity of signalling pathways such as PI3K/AKT (Clementi et al., 2003)(Laurent and Jaffre, 2016).

Paclitaxel, a key member of the taxanes family, first emerged as the earliest compound able to stabilize microtubules. Unlike anthracyclines, taxanes function primarily during the G2/M phase of the cell cycle. These exert their cytotoxic function through impairment of the centrosome, induction of abnormal spindle morphology and disruption of normal spindle dynamics, ultimately causing cell cycle arrest. Paclitaxel is generally used in combination to anthracycline to maximise effectiveness (Laurentiis et al., 2005). However, continual use, even in combination, generally results in the insurgence of tumour resistance to their effect. Thus, the cancers are able to recur. Further limitation to the use of these drugs is the development of a metastatic phenotype.

The insurgence of resistance to chemotherapies has instigated the development of targeted therapies, thanks to the novel understanding of the drugs mechanism of action and more specific knowledge of molecular targets. For instance, Trastuzumab (Herceptin) was developed to specifically bind to and inhibit HER-2 mediated signalling (Yarden and Sliwkowski, 2001). Lapatinib was also developed to target HER-2, but it was made to simultaneously inhibit EGFR (HER-1), thus disrupting both signalling pathways at once (Moy and Goss, 2006). Unfortunately, despite their usefulness in the treatment of more aggressive forms of breast cancer, these targeted therapies only offer a response rate of approximately 30% when used as single agents, which usually fades within one year of their use, suggesting the insurgence of further mutational mechanisms to counteract their activity. Furthermore, these can only be used in cases of HER-2 positive breast cancers(Nahta and Esteva, 2006).

According to statistical analysis, approximately 10% of breast cancer patients present advanced or metastatic disease at diagnosis, with the percentage rising to 30-50% of advanced and metastatic cases appearing despite early cancer diagnosis and the administration of chemo-, adjuvant- or radio-therapy. Thus, despite recent advances in the treatment options for this disease, breast cancer relapse and resistance to treatment prevails with time, with 40% of cases presenting relapse, and 60-70% of relapse cases displaying a metastatic nature. Breast cancer resistance to therapy and metastasis have therefore become the prevailing causes of breast cancer mortality (Gangopadhyay et al., 2013).

Page | 20

1.4 The insurgence of drug resistance Despite the advancement in the development of anti-cancer therapies, the insurgence of drug resistance remains a major hurdle in the effective eradication of breast cancer. Resistance to chemotherapeutic drugs can develop in one of two manners, intrinsic or acquired: intrinsic resistance develops prior to the cancers exposure to the drug; acquired resistance arises from repeated drug exposure over time (Giaccone and Pinedo, 1996). In some instances, cancer cells develop resistance to multiple drugs simultaneously. This process is termed multidrug resistance, and encompasses loss of sensitivity to a range of drugs which differ in their chemical structure and mechanism of action. In general, multi-drug resistance can arise in two different manners: through the reduction of the cellular intrinsic drug concentration, or through the development of pathways that can counteract the drugs molecular cytotoxic effects (Polgar and Bates, 2005).

Cancer cells promote drug efflux, and limit the amount of intrinsic drugs, in two main fashions, which depend upon the hydrophilic nature of the drug: the first is based on a reduction of either the expression or the activity of the surface proteins responsible for the uptake of hydrophilic chemotherapeutic drugs, and works for drugs such as cisplatin and folate agonists; the second alternates the functioning of transporters which regulate the efflux of hydrophobic chemotherapeutic drugs, such as taxanes and anthracyclines (Gottesman et al., 2002). The latter transporters vary from P-glycoproteins (a.k.a. MDR1, PgP and ABCB1), the multidrug-resistance- associated protein (MRP1), or the breast cancer resistance protein (BCRP). The importance of these transporters is highlighted by their frequent overexpression in breast cancers (Longley and Johnston, 2005).

Alternatively, cells can alter their proliferation and survival signalling pathways to counteract the activity of the drugs. For instance, this can be through the alteration of the expression of cell cycle checkpoints, apoptotic mechanisms or the activation of oncogenes, as well as via the augmentation of the DNA damage repair response, mutation in the drug targets, or the variation in drug metabolism (Raguz and Yagu, 2008)(Stavrovskaya et al., 2016).

Resistance to taxanes generally arises from defects present in one of its targets. These encompass β-tubulin, Aurora A, Bcl-2 and Tau (Noguchi, 2006). Alternatively, differential metabolism of cytochrome P450 (CYP3A4 and CYP2C8), or other enzymes could reduce the amount of active drug, ultimately diminishing taxanes activity.

Resistance to anthracycline is the epitope of multiple processes, such as increased expression of P-glycoprotein coupled with the breast cancer resistance protein (BCRP) (Faneyte et al., 2002)(Fojo and Menefee, 2007), mutations in its primary target, topoisomerase II, increased

Page | 21 expression in proteins regulating DNA damage repair, inhibition in apoptotic pathways, such as mutations in p53 (Minotti et al., 2004).

Understanding the mechanisms of resistance to endocrine therapy is also crucial for the elucidation of adequate breast cancer therapy. For instance, loss of responsiveness to oestrogen agonists, such as tamoxifen, is primarily mediated through the loss of ERα expression (Gutierrez et al., 2016), or through the much rarer instance of insurgence of mutations in the ERα structure (Herynk and Fuqua, 2016). However, even in the first case, only 15-20% of breast cancer cases exhibit this modification. Instead, most cases of acquired endocrine resistance encompass modifications in the downstream signalling events which are activated upon the binding of the ligand to the ER, such as between the receptor tyrosine kinase signalling which includes that of HER-2 (Laurentiis et al., 2005). Alternatively, overexpression of the epidermal growth factor receptor (EGFR) or PI3K functioning has also been shown to contribute to endocrine resistance (Jordan et al., 2004). In other instances, patients may present polymorphisms in the cytochrome P4502D6 (CYP2D6), a cytochrome which is responsible for converting tamoxifen into endoxifen, its active metabolite (Guchelaar et al., 2009).

Resistance to anti-cancer therapies has unfortunately been reported for almost all anti-cancer drugs. Overall, the insurgence of resistance to anti-cancer therapies, whether it would be cytotoxic chemotherapy, or endocrine therapy, encompasses both physical alterations in the efflux or receptor pathways, coupled with alterations in the molecular response to the drugs effect. In this thesis, I will focus primarily on resistance to the most commonly administered chemotherapeutic drugs anthracycline and taxanes. A better understanding of resistance mechanisms could contribute to the prediction of tumour response, as well as to the identification of novel targets to combat breast cancers.

1.5 Cancer progression Cancer is a neoplastic disease which arises from the abnormal proliferation of a cell. To date, cancer is one of the predominant causes of death in the western hemisphere, accounting for more than 1 in 4 deaths in the United Kingdom (Cancer Research UK). Cancer mortality is prevalently caused by the progression of the tumour to a metastatic state, rendering it difficult to treat and virtually impossible to excise (Saxe C et al., 2013). To date, relatively few anti-cancer therapeutics are available for metastatic neoplasms, and most inevitably result in the insurgence of drug resistance, leading to relapse and death. It is therefore imperial for the mechanisms behind cancer progression to be properly defined, so as to overcome the limitations of the existing therapies, and develop new more targeted anti-cancer therapeutics which might limit cancer progression.

Page | 22

The process of cellular metastasis can be discernible in several distinct steps. These include loss of cellular adhesion, acquisition of motility and invasiveness capacities, local invasion, intravasation into surrounding lymphatic and hematogenous systems, and survival in the circulation, extravasation in the parenchyma of new tissue, formation of small micrometastases, and growth into macroscopic tumours equivalent to successful colonization of the distant site (Gupta and Massagué, 2006) (Hanahan and Weinberg, 2011). This depiction encompasses a succession of cell- biologic alterations, including the acquisition of a sufficient blood supply which enables the tumours survival and sporadic growth, as well as the procurement of motile and self-renewal capabilities, such as those attained during the epithelial to mesenchymal transition (EMT), and typically expressed by cancer stem cells (Herschkowitz et al., 2010). For the purpose of this project, the process of cancer metastasis will be subdivided into tumour induced angiogenesis, EMT, the acquisition of a cancer stem cell phenotype and cancer metastasis.

1.5.1.1 Epithelial to mesenchymal transition In order for primary malignant tumours to disseminate to distant organs, they need to be able to manipulate the components of their cell-cell and cell-matrix adhesion. EMT is a process naturally occurring during the developmental stages of embryos, particularly for the formation of the mesoderm in amniotes, the neural crest in vertebrates, as well as for the heart cushion, and the palate. Both EMT and its reverse process, MET, are essential for the formation of most adult tissues: with the combination of these two processes, epithelial cells are able to form close contacts with their neighbouring cells as well as an apicobasal polarity axis through the sequential organisation of the adherens junctions, desmosomes and tight junctions (Thiery et al., 2009).

Cancer cells re-activate signalling pathways which are normally reserved for cells in embryogenesis, and co-opt them to attain the increased motility necessary for cancer progression. EMT is a reversible phenotypical change whereby epithelial cells lose their typical cell-cell adhesion and their polarity, only to re-organise their cytoskeleton, acquire resistance to anoikis, motility and switch from keratin to vimentin type cytoskeletons (Klymkowsky and Savagner, 2009)(Gangopadhyay et al., 2013). Crucially, unlike during the developmental processes, neoplastic cells undergoing EMT will display inherent genetic abnormalities that will progressively lead them to lose their sensitivity to the presence growth factors, and instead acquire the capability to evolve. This instability will be one of the sources of tumour heterogeneity, displaying phenotypically different sub-populations within a tumour, with signals received from the tumour stroma microenvironment only influencing this process, and promoting EMT and MET programmes (Polyak and Weinberg, 2009). Importantly, expression of markers unique to EMT has been associated with poor clinical

Page | 23 outcomes, principally due to the aggressive properties it will confer to a primary tumour (Sabbah et al., 2008). Furthermore, EMT has recently been linked to both the progression of cancer to a metastatic state, as well as the development of stem-cell qualities. Thus, cancer cells having undergone EMT will be able to metastasize using their acquired invasive and migration properties, as well as spawn into macroscopic metastases using their self-renewal potential (Herschkowitz et al., 2010).

The EMT programme can be initiated by a series of extracellular signals, with considerate crosstalks between intracellular signalling pathways and transcription factors, as well as concomitant feedback loops. EMT can be activated via extracellular signalling of collagen or from growth factors, such as the epidermal growth factor (EGF), fibroblast growth factor (FGF), the transforming growth factor-β (TGF-β), hepatocyte growth factor (HGF), bone morphogenic proteins (BMPs), Wnts and Notch (Barrallo-Gimeno & Nieto, 2005). A summary of the interaction between different signalling pathways and their influence over EMT can be seen in Figure 1.1. Epithelial tumour cells are stimulated by heterotypical signals released by mesenchymal cells present in the tumour stroma. Of all the signalling pathways described to date, the transforming growth factor-β (TGF-β) family of cytokines is the most prominent for its regulation of EMT, namely due to its crucial control of embryonic development, wound healing, fibrotic disease and cancer pathogenesis. One of the many pathways through which TGF-β can control EMT is through direct phosphorylation via ligand-activated receptors of SMAD transcription factors, as well as through specific cytoplasmic proteins regulating cell polarity and the creation of tight junctions(Massagué, 2008). TGF-β can also impact on the activity of several other signal transduction pathways which have a role in the promotion of the EMT programme. These include: Notch, Wnt or integrin signalling. Particularly, Wnt signalling pathways can lead to EMT by inhibiting the phosphorylation mediated by glycogen synthase kinase-3β (GSK3β) which would otherwise induce β-catenin cytoplasmic degradation. Active β-catenin would instead be able to translocate to the nucleus, where it can act as a transcription factor subunit to prompt the expression of several genes, encompassing transcription factors which can induce EMT, should it be accompanied by concomitant proteins (Polyak and Weinberg, 2009).

Cell adhesion in vertebrates is mediated via three different types of molecules: tight junctions, adherent junctions or desmosomes. These junctions define how a cell integrates within a tissue, and thus mediate its functions. Cadherins are the major components of tight junctions and desmosomes, and are generally located at points of cell-cell interaction in solid tissues. The family of cadherin glycol-proteins has been subdivided into classical and non-classical cadherins. Classical

Page | 24

Figure 1.1 Primary signalling pathways. Notch, transforming growth factor-β (TGF-β), receptor tyrosine kinase (RTK), endothelin A receptor and Wnt can individually promote EMT through different signalling pathways, depicted in the image. Briefly, Notch can activate hairy and enhancer of split (H/E (Spl)), which can in turn activate transcription factors present in the nucleus. Alternatively, TGF-β can act through the Smad proteins to their nuclear effectors. Both RTK and ETAR can instead regulate a MAPK/Ras/PK3CA protein complex, which can activate transcription through Akt. Both the latter, and WNT instead act by inhibiting GSK3β, which would otherwise initiate transcription through β-catenin. Transcription factors responsible for the initiation of EMT include the nuclear factor NF-κβ, hypoxia inducible factor 1 (HIF1), Snail Family Zinc Finger 1 and 2 (SNAI1 and SNAI2), Zinc Finger E-Box Binding Homeobox 1 (ZEB1) and 2 (ZEB2), and the Twist Family Transcription Factor 1 (Twist1). Adapted from Polyak & Weinberg, 2009.

Page | 25 cadherins include cadherins which are involved in calcium-dependent cell-cell adhesions, whilst the latter are components of desmosomes. To date, very little has been found on the functional role of non-classical cadherins in malignant tumours, so for the purpose of this thesis, the focus will be placed on classical cadherins. Structurally, classical cadherins are defined as single-span trans-membrane-domain glycoproteins. Their main role is to establish specific cell-cell adhesion by creating homophilic protein-protein interactions between two cadherin molecules of adjacent cells. Specifically, this interaction has been found to be mediated by particular amino-residues present in the most amino-terminal cadherin domain, notably between the histidine-alanine-valine (HAV) domains or between trypophan residues and hydrophobic pockets. Interestingly, cadherins display an exquisite specificity for their almost exclusive binding to other identical cadherins present on different cell’s surfaces (Cavallaro and Christofori, 2004).

Crucial to the EMT programme is the loss of tight junction glycoprotein E-cadherin, upon which significant research has focused. For tumours which originate from epithelial tissues, E-cadherin is a crucial cadherin, as it regulates cellular polarity and maintains an organised epithelium. Not surprisingly, E-cadherin expression is lost as tumour progresses to a malignant state, with its expression presenting an inverse correlation to tumour grade (Heuberger and Birchmeier, 2010). Loss of E-cadherin has thus become a pre-requisite to tumour progression, with its reinstitution in a mesenchymal cell line often resulting in the cell lines reverting to an epithelial phenotype. E- cadherin is regulated at the transcriptional level by multiple pathways, such as the zinc-finger containing proteins Snail, Slug and SIP1, as well as the helix-loop-helix transcription factor E12/E47. Of these transcription factors, Snail is particularly known for its repression of E- cadherin, and consequent induction of the EMT phenotype, both during development and tumour progression. On top of promoting EMT, Snail genes have also been found to be major regulators of resistance to apoptosis when in absence of survival stimuli or in response to apoptotic stimuli. Emerging evidence seems to indicate that Snail proteins mainly function in the promotion of cell motility, and that the induction of EMT is mainly a mechanism by which they do this (Barrallo- Gimeno and Nieto, 2005). The Snail gene was discovered in 1987 in the Drosophila Melanogaster, for its role in the regulation of the mesoderm (Boulay et al., 1987). It was first associated with the EMT process by Nieto et al., in 1994, where they noticed Snail-2 loss of function in chick embryos led to the failure of mesoderm formation (Nieto et al., 1994)(Barrallo-Gimeno and Nieto, 2005).

E-cadherin, the primary component of adherens junctions, functions by creating haemophilic interactions with nearby E-cadherin molecules on surrounding cells in a calcium dependent manner. On the cytoplasmic end, E-cadherin is secured to the actin cytoskeleton via α- and β- catenin (Lombaerts et al., 2006). Namely, for it to display functional adhesion activity, E-cadherin

Page | 26 must be associated with both β- and γ-catenin, which serve to link the carboxy-terminal cytoplasmic tail of E-cadherin to α-catenin. Αlpha-catenin will then bind to the actin cytoskeleton, either directly or via alpha-actinin (De Leeuw et al., 1997). E-cadherin can be inhibited in several manners. For instance, the E-cadherin gene locus can be epigenetically silenced by hyper- methylation, inhibiting its activity. Alternatively, its proteolytic degradation can be mediated by matrix metalloprotease (MMP) MMP2, MMP9, MMP14. Matrix metalloproteinases are a class of proteolytic enzymes which function by degrading most types of extracellular matrix (ECM) components. These are secreted as latent proenzymes, which become activated following proteolytic cleavage. MMP cleavage of E-cadherin results in the secretion of the cleaved/soluble E-cadherin fragment (sE-cadherin), which can in turn up-regulate the expression of MMP in lung cancer (Nawrocki-Raby et al., 2003)(Cavallaro and Christofori, 2004). Notably, there have been two ways through which E-cadherin functioning is silenced, namely by mutational or epigenetic inactivation (Lombaerts et al., 2006; Onder et al., 2008). Despite the complexity of Notch signalling, and its ambiguous role as both a tumour suppressor and an oncogene varying according to cell type, Notch can prompt EMT by either activating the nuclear factor-κβ (NF-κβ) signalling pathway, or by modulating TGFβ signalling (Wang et al., 2006).

By co-opting processes generally used during embryogenesis, transformed cancer cells, originally immotile, can acquire attributes essential for motility and invasion by undergoing the EMT. The EMT programme can either be permanently activated or transiently. To date, it is not clear what causes cancer cells to undergo EMT. Scientists have speculated that, as with cells during embryogenesis, signals triggering EMT may come from nearby tumour-associated stromal cells (Brabletz et al., 2001). Aggressive carcinomas are also known to have an increase in the expression of markers typically expressed during embryogenesis. For instance, N-cadherin is associated with migrating neurons and mesenchymal cells during organogenesis; its expression is up-regulated in aggressive tumours (Hanahan and Weinberg, 2011). As part of EMT, cells are prone to the suppression of cell death (so activate molecules such as Snail, via TGF beta) or senescence (by regulating Twist1 and Twist2). This combined effect can influence the survival of micrometastases generated from mesenchymal cancer cells, which will thus be able to avoid premature senescence and apoptosis (Thiery et al., 2009).

N-cadherin (Cadherin-2, CDH2, neural cadherin) is a transmembrane homophilic glycoprotein which is crucial to EMT. Encoded by the cluster of differentiation 325 gene, or CDH2, it belongs to the calcium-dependent cell adhesion molecule family. In healthy tissues, N-cadherin is essential to the functioning of the cardiac muscle, whereby it mediates adherens junctions of intercalated discs, thus mechanically and electrically coupling adjacent cardiomiocytes. As a classical cadherin,

Page | 27 this protein of 906 aminoacids in length is composed of five extracellular cadherin repeats, responsible for the homophilic interactions between adjacent cells, a transmembrane region and a cytoplasmic tail, which interacts with the actin-cytoskeleton through binding to catenins. The N- cadherin complex interacts with other N-cadherins present on the surface of neighbouring cells by binding in an anti-parallel conformation, thus creating an adhesive ‘zipper’ structure between cells. This protein plays an essential function during gastrulation, with high expression in the mesoderm sustained through to adulthood. Originally named for its role in neurons, this protein is now under intensive studies for its contribution to tumour metastasis, where it has been shown to provide a mechanism for transendothelial migration. During both developmental and pathogenic EMT, N-cadherin replaces E-cadherin, whilst Vimentin and fibronectin replace cytokeratins. Thus, a polarised epithelial cells can shed the interactions with its basement membrane and undergo the morphological changes which enable it to display a mesenchymal phenotype, which include increased resistance to apoptosis, higher production of extra-cellular matrix components, and the crucial capability to both migrate and invade. Migrating cells necessitate to disassemble the static actin structures in order to achieve motility, so as to obtain a fine actin network capable of flexibility to form membrane protrusions (lamellipodia) (Grant and Kyprianou, 2013)(Serrano-Gomez et al., 2016).

1.5.1.2 The epithelial to mesenchymal transition in breast cancer Several pathways have been discovered to lead to the EMT in breast cancer cell lines. For instance, TGF-β1, hepatocyte growth factors, and PDGF are some of the up-stream growth factors which can regulate EMT. These link back to and activate a series of transcription factors which can independently activate EMT, such as Snail 1, Snail 2 (slug), the basic helix loop helix protein Twist 1, the Forkhead Box proteins FOXC1, and FOXC2, as well as the E-box binding zinc finger proteins Zinc1 and Zinc2 (Sip1)(Herschkowitz et al., 2010).

One study has attempted to determine whether an ‘EMT core signature’ exists in breast cancer. To do this, each signalling pathway was activated individually to determine which activated genes are common to all the pathways. Thus, a panel of 159 genes was found to be down-regulated in a breast mammary epithelial cell line (HMLE) and 87 genes were up-regulated. Importantly, E- cadherin was one of the genes which was down-regulated, and N-cadherin, Vimentin, and MMP2 were up-regulated. Other genes which appeared to be crucial for the switch were Zeb1, which was commonly up-regulated (Herschkowitz et al., 2010). Another study comparing mutations in E- cadherin in breast cancers originating from different tissues (namely, infiltrating lobular carcinomas, infiltrating ducto-lobular carcinomas and infiltrative ductal carcinomas), concluded

Page | 28 that 56% of infiltrating lobular breast carcinomas presented E-cadherin inactivation mutations, while the other histopathological breast cancer subtypes presented none (Berx et al., 1996). Further studies revealed that E-cadherin expression in lobular breast carcinomas presented mutational inactivation, which are also accompanied by loss of α- and β-catenin expression. In 50% of the cases, this is also accompanied by the loss of function of γ-catenin. This pattern indicates that simultaneous loss of E-cadherin, and related catenins may not only be important for the formation of lobular breast carcinoma in situ, but also for the progression to an invasive phenotype. Furthermore, this study concluded that in 84% of lobular breast carcinomas reported a complete loss of E-cadherin protein expression. Thus it was revealed how all the components of the tight junctions are necessary for its proper functioning, and that a mutation in either could result in the loss of function of E-cadherin, even when E-cadherin is still detected (De Leeuw et al., 1997).

Loss of E-cadherin can contribute to cancer progression via the β-catenin nuclear translocation, which in turn activates the Wnt signalling pathway. Evidence of this phenomenon has been noted in cases of mutated adenomatous polyposis coli (APC), a major tumour suppressor in colonic cancer. In a study performed on diffuse colonic cancer, CDH1 mutations were found in 50% of all cases, in a cluster between exons 7 and 9 (Kaurah et al., 2007). Amongst these, there was a mutation in the wild-type allele, which was attributed to promoter hypermethylation in 83% of cases (Grady et al., 2000). Similarly, in lobular breast carcinoma, E-cadherin expression has been found to be absent in 85% of sporadic invasive cases. Lobular breast carcinoma is distinctive for its infiltrative cancer cells, which are generally highly dispersive and isolated (Berx and Van Roy, 2001). In 56% of sporadic LBC cases, a CDH1 mutation has been detected. Contrarily, in invasive ductal carcinoma cases, somatic CDH1 mutations are not present, and the tumour is generally not characterised by a complete loss of E-cadherin expression (Berx et al., 1996). Comparative analysis between sporadic LBC and DGC have noted that LBC generally presents nonsense or frameshift mutations, which lead to the formation of non-functional proteins (Berx et al., 1998). Alternatively, DGCs display splice-site or in frame mutations. Furthermore, these two tumour types also differ in the localisation of their mutations, which tend to be scattered throughout the CDH1 gene in LBC and clustered in DGCs (Schrader et al., 2008).

E-cadherin can be inactivated in multiple manners: these include somatic mutations, chromosomal deletions, proteolytic cleavage or silencing of the CDH1 promoter. Silencing can be induced by DNA hypermethylation, or a transcription factor, such as Slug, Snail or Twist (Onder et al., 2008). Its targeted promoter hyper-methylation, results in the inhibition of the E-cadherin gene expression, or mutational inactivation of the gene. However, a thorough study on mammary cell lines, including aggressive breast cancer tumour cells, has determined that it is CDH1 gene

Page | 29 promoter hypermethylation that is the precursor to EMT, and not its mutational inactivation. (Lombaerts et al., 2006).

Loss of E-cadherin has a wide-range of implications: not only does it allow cells to lose their tight junctions, but it also activates a wide-range of signalling pathways which in turn initiate the EMT cascade. A study conducted on non-metastatic breast cell lines, revealed that E-cadherin silencing was sufficient to cause cells to undergo EMT, as well as to progress towards the metastatic phenotype by increasing their migratory and invasive potential, and resistance to apoptosis. Amongst the 19 transcription factors highly induced subsequent to E-cadherin loss, Twist and ZEB-1 were highlighted, as these act as E-cadherin suppressors: their up-regulation upon E- cadherin overexpression causes a feed-forward signalling loop, promoting the EMT, as well as the maintenance of the mesenchymal phenotype (Onder et al., 2008). Despite the crucial role in the induction of EMT, knock-down of E-cadherin alone is not sufficient for the formation of malignant lesions in breast cancer murine models. Contrarily, restricted CHD1 inhibition only caused cells to undergo apoptosis. However, when this was coupled with p53 inactivation, cancerous lesions began to form. However, E-cadherins function as a tumour suppressor means that it’s loss can not only promote the cell line motility, thus kick-starting the metastatic process, but evidence has shown that it can also promote its angiogenic potential, as well as its resistance to anoikis, allowing the travelling cells to survive the non-adherent environment present in blood and lymphatic vessels. (Derksen et al., 2006). E-cadherin expression is so crucial in breast cancer, that it’s histological and expression patterns are now used to distinguish between lobular and ductal carcinomas, with the latter expressing E-cadherin, and the lobular lacking it (Korkola et al., 2003; Lehr et al., 2000).

Despite its central role in cancer progression, EMT is only one of the rate-limiting steps in the development of metastasis. Essential to the growth of a primary neoplastic lesion is the process of tumour neoangiogenesis.

1.5.2.1 Tumour induced angiogenesis Tumours, like any other healthy cell, depend upon a constant supply of nutrients and oxygen, as well as an efficient means to expel their waste. However, their unplanned presence and high proliferative output mean that the existing blood vessels will not suffice to sustain their growth. Without a sufficient blood supply, a tumour will not be able to grow beyond the size of 1 mm3 in volume, and consequently succumb to apoptosis and necrosis, while arresting it’s growth (Fidler, 2002; Hart and Fidler, 1980). In adults, the process of angiogenesis is only transiently activated to accommodate for rare busts of tissue regeneration, with the vessels maintaining a state of quiescent

Page | 30 for the remainder of the time. Tumours are able to activate angiogenesis in a permanent fashion, inducing the blood vessels to grow to their proximity from pre-existing blood vessels. The so called ‘angiogenic switch’ is a crucial step which results in an avascular hyperplasia, also known as a dormant tumour, becoming a vascularised tumour full of potential of transforming into a malignant lesion. All this step entails is the ‘switch’ from a majority of anti-angiogenic factors to pro-angiogenic factors (Bergers and Benjamin, 2003).

It was Judah Folkman who first introduced the concept of a tumour angiogenic switch in 1971, by simultaneously proving the existence of angiogenic factors and their role in inducing angiogenesis in a rabbit eye assay. In this first report, he postulated that angiogenesis in tumour specimen was defined by the size and numbers of the tumour induced blood vessels, the expression of pro- and anti-angiogenic factors and the presence of particular receptors. It was determined that the angiogenic switch occurred early on in the progression of a tumour and even before tumour formation (Hanahan and Weinberg, 2008).

Tumour angiogenesis is stimulated from the secretion of angiogenic factors by tumour cells and their surrounding stromal cells (Figure 1.2). To date, the most established angiogenesis inducing and repressing genes are the vascular endothelial growth factor (VEGF-A, inducing) and the thrombospondin-1 (TSP-1, repressing). VEGF acts via three ligands, including VEGF receptor (VEGFR) 1, 2, and 3. This tyrosine kinase signalling controls angiogenesis both through-out embryonal development, adult tissue regeneration and pathological events such as cancer, and can promote both the proliferation and differentiation of endothelial cells. VEGF-A belongs to the genetic family which includes other growth factors such as the placental growth factor (PlGF, as well as other VEGF members, such as VEGF-B, -C,-D and –E. Each of these has a specific binding affinity to the VEGF tyrosine kinase receptors 1, 2 and 3 (Ferrara et al., 2003). The resulting effect of the binding of the growth factor to its respective receptor depends on the combination. For instance, VEGF-A binding to VEGFR-2 (predominantly present on blood vessel endothelial cells), induces blood vessel angiogenesis; Alternatively, VEGF-C or –D binding to VEGFR-3 (expressed on lymphatic endothelial cells), induce lymphangiogenesis (Alitalo et al., 2005) (Wicki and Christofori, 2008). Other pro-angiogenic factors include the fibroblast growth factor (FGF) -1 and -2, the platelet-derived growth factor (PDGF)-B and –C and angiopoietins. FGF and PDGF families can trigger endothelial cell proliferation and migration by binding to their respective receptors on the endothelial cell surface. Alternatively, angiopoietins promote angiogenesis by working in combination with other angiogenic factors, and ultimately bind to the Tie-2 tyrosine kinase receptor present on the surface of endothelial cells. While Ang-1 induces the final steps of vessel maturation, thus thwarting angiogenesis, Ang-2 works by antagonizing the

Page | 31 activity of Ang-1, thus allowing the developing blood vessels to maintain a degree of receptiveness to alternate angiogenic stimulus (Augustin et al., 2009) (Wicki and Christofori, 2008).

Figure 1.2 Tumour induced angiogenesis. Diagram depicting the process of tumour induced angiogenesis whereby the tumour mass (pink) releases growth factor (blue arrows) which induce the quiescent blood vessel (green) to extend new protrusions to irrigate the tumour mass. In addition to its role in endothelial cell proliferation, VEGF has also been reported to act as a mitogenic factor for cancer cells. Indeed, in colon cancer cells, VEGF is transcriptionally activated by butyrate through its kinase insert domain receptor (KDR, a.k.a. VEGFR-2) initiating a VEGF:KDR autocrine growth loop. This is believed to act through FOXM1 (Serpa et al., 2010). This interaction was also reported in a study on acute primary myeloid leukaemia, where the VEGF/KDR autocrine loop was shown to act both internally and externally. Indeed, VEGF binding to KDR could cause its nuclear translocation and consequent activation of the PI3K/Akt, MAPK/Erk and NF-κB signalling pathways (Santos and Dias, 2004). Interestingly, singular blockage of the VEGF/KDR autocrine loops was not sufficient to achieve remission in non-solid tumors. Indeed, a study demonstrated that the inhibition of both the VEGF autocrine and paracrine loops was necessary (Dias et al., 2001). Breast cancer cells have been reported to express both VEGFR-1 and -2, as well as VEGF-A to –C. The initiation of an autocrine VEGF-A VEGFR-2 loop through VEGFR-2 tyrosine phosphorylation was associated with the regulation of cell growth, apoptosis, survival and differentiation. This study also reported the presence of VEGFR-2 on breast cancer cell surface which could respond to external VEGF-A stimulation (Weigand et al., 2005). Similar results were reported in ovarian cancer cells, where VEGF-A and the KDR receptor were revealed to protect the cells from apoptosis in anchorage free growth conditions (Sher et al., 2009).

The degree of tumour neovascularisation has been found to be dependent on tumour type, with tumour induced angiogenesis beginning remarkably early in the tumour development, at a stage

Page | 32 preceding the premalignant phase of the neoplastic progression (Raica et al., 2009)(Hanahan and Folkman, 1996). During tumour induced angiogenesis, the normal vessel hierarchy (arteries, arterioles, capillaries, venules and veins) is mislaid to be replaced with a disordered array of irregular blood vessels. Due to the aberrant signalling released by a growing tumour, the process of tumour induced angiogenesis generally leads to the creation of leaky, malformed enlarged blood vessels, presenting convoluted and extreme branching, with precocious capillary formation. Tumour neovasculature will thus lead to an irregular blood flow, capped by regions of microhemorhaging and of tumour hypoxia, with the constant angiogenic signalling leading to excessive endothelial cell proliferation and apoptosis. Furthermore, insufficient drainage and high tumour glycolytic activity, will result in zones of more acidic pH. Together, the combination will lead to necrosis, ischemia and areas of metabolic failure. Furthermore, tumour induced blood vessels will be unnaturally permeable, allowing high levels of plasma and plasma proteins to extravasate. This will lead to the formation of a cross-link fibrin gel, setting a platform upon which malignant cells will be able to anchor themselves and intravasate into the circulation, in the initial stages of metastasis.

To date, 6 types of tumour vasculatures have been defined. Four originate from proximal healthy blood capillaries and venules (capillaries, glomeruloid microvascular proliferation, vascular malformations and mother vessels), while the remainder originate from arterio-venogenesis from healthy arteries and veins, creating feeder arteries and draining veins. The latter process is poorly understood (Nagy et al., 2010). As normal blood vessels, tumour blood vessels are made of endothelial cells, mural cells (perycites and smooth muscle cells) and basement membrane. However, each of these is anomalous in tumour blood vessels. For instance, tumour vessels don’t possess a tight endothelial layer, typical of normal blood vessels. This is essential for normal barrier functions, and it’s lack renders the blood vessels leaky (Hashizume et al., 2000). Endothelial cells are crucial as they administrate the extravasation of leukocytes, plasma and erythrocytes, as well as control the intravasation of potential metastasizing tumour cells. Pericytes are a type of cell which is found within the vascular basement membrane and are closely associated with endothelial cells. In tumour blood vessels, however, the pericytes are loosely attached to the endothelial cells. The functional implications of these are still unclear. However, it has been speculated that this is a factor that contributes to the leakiness of the tumour associated blood vessels. The basement membrane is composed of a mixture of proteins, glycoproteins and proteoglycans, tightly wound around vascular endothelial cells and pericytes. As with all other components of tumour associated vessels, the basement membrane will present an irregular structure, with irregular thickness, focal holes and broad extensions into the tumour stroma (Baluk et al., 2005).

Page | 33

Adult humans and mice have been found to present endogenous anti-angiogenic factors such as TSP-1, angiostatin and type 18 collagen, naturally in their circulation (Wicki and Christofori, 2008). Most are usually fragments derived from the extra-cellular matrix (ECM) or the basement membrane. For instance, TSP-1 is a large ECM glycoprotein, which can act as a powerful angiogenesis inhibitor (Good et al., 1990). Other angiogenic inhibitors include endostatin, derived from the proteolytic cleavage of collagen XVIII (O’Reilly et al., 1997), canstatin and tumstatin, cleaved from collagen IV (Maeshima et al., 2002; Nisato et al., 2003), or even soluble factors like interferon-α and β, and angiostatin, derived from plasmin (O’Reilly et al., 1994; Sidky and Borden, 1987). These can be revoked without significant damage to the adult tissues, if not for the increase in tumour induced angiogenesis. Alternatively, overexpression of these factors can reduce the vascularisation of the growing tumour (Raica et al., 2009)(Nyberg et al., 2005).

Many cells are important for the adequate development of pathological vasculature. Neoplastic lesions are surrounded by layers of immune cells, stromal cells and epithelial cells, creating a crucial balance often referred to as the ‘tumour microenvironment’ (Raica et al., 2009). These include pericytes, normally part of the outer surface of endothelial tubes (Raza et al., 2010)(Bergers and Song, 2005), as well as a wide repertoire of bone marrow derived immune cells, such as macrophages, neutrophils, mast cells and myeloid precursors. This complex array of cell type will communicate with intricate signalling pathways relying on cytokines, surface adhesion molecules and their respective receptors. Importantly, inflammatory cells will synergise and collaborate with both malignant and stromal cells to stimulate the growth of blood vessels (Raica et al., 2009). These will assemble at the edges of tumours of all stages, and aid in the triggering and maintenance of the angiogenic switch (Qian and Pollard, 2016)(Murdoch et al., 2008)(Palma et al., 2007). Despite the angiogenic switch not being a precursor of tumour invasion (Raica et al., 2009), it will eventually facilitate local invasion in subsequent steps of tumour progression (Hanahan and Weinberg, 2011).

1.5.2.2 Tumour induced angiogenesis in breast cancer Many studies have been performed on breast cancer angiogenesis to determine which angiogenic molecules, amongst the many identified, were more crucial to its progression, as well as to identify useful prognostic markers which could be used to develop more targeted therapies. The crucial role of VEGF in breast cancer neoangiogenesis has been reported repeatedly. Initially, studies correlated VEGF expression with microvessel density in human breast cancer samples: higher microvessel density was associated with increased VEGF expression. Furthermore, the same study reported detection of VEGF transcripts secreted by both cell lines and tissue samples, all highly

Page | 34 mitogenic for endothelial cells(Toi et al., 1994). VEGF was later correlated to hormone receptors: a tissue micro-array of over one thousand breast cancer samples was performed to detect the prognostic value of VEGFR-1 expression. VEGFR-1 expression was prevalently strong in the majority of breast carcinoma specimens, and was generally accompanied by ER or PR expression. This was also strongly correlated with improved overall survival, implying that membrane-bound VEGF-R1 could serve as a prognostic marker to identify cancers which would not benefit from endocrine therapy (Lebok et al., 2016). The interaction between ERα and VEGF was further verified where it was shown to target VEGF directly and induce its transcription. Interestingly, this functioning could be impaired upon BRCA1 activation (Kawai et al., 2002). This study was confirmed in numerous instances, during which the direct positive correlation between 17β- estradiol and VEGF transcription was confirmed (Mueller et al., 2000). Alternatively, a correlation has been recognised between the progesterone receptor and breast cancer angiogenesis. Progesterone is able to increase VEGF secretion in vitro in breast cancer samples. Surprisingly, this effect can also be mediated by progestins naturally present in contraceptives and hormone replacement therapy (Hyder et al., 1998). Finally, HER-2 has also been shown to influence VEGF levels in breast cancer, where up-regulated HER-2 expression has been correlated in vitro to higher VEGF expression, contributing to its poor clinical outcome (Konecny et al., 2004). VEGF has also been shown to be regulated in breast cancer by other transcription factors, such as Notch-1, which can regulate angiogenesis through the activation of NF-κB (Liu et al., 2016).

Although VEGF remains the most abundantly expressed in breast cancer, other angiogenic molecules have been associated with breast cancer angiogenesis. These include cyclo-oxygenases 1 and 2 (COX1 and COX2), enzymes generally associated with prostaglandin biosysthesis (Costa et al., 2002), thymidine phosphorylase, basic fibroblast growth factor, TGFα, TGFβ2 and the epidermal growth factor receptor (EGFR) (Relf et al., 1997), all correlating positively with microvessel density. Alternatively, while VEGF has been associated primarily with vascular neoangiogenesis, VEGF-C and –D have instead been correlated with lymphangiogenesis (Choi et al., 2005).

Anti-angiogenic treatment options are currently being evaluated. For instance, treatment with a selective VEGF inhibitor (mAb A4.6.1) is able to impair breast cancer tumour vascularisation in murine models, as well as tumour proliferation, both when administered alone or in combination with doxorubicin (Borgstrom et al, 1999). Alternatively, 2-methoxyestradiol, an endogenous oestrogen metabolite able to impair microtubule dynamics, is effective in reducing VEGF- and b- FGF- induced angiogenesis in human breast carcinoma in vivo, without toxicity (Klauber N, 1997). Instead, monoclonal antibodies against integrin αβν-3 (LM609), a marker for oncogenic

Page | 35 vasculature, blocked vasculature formation and impaired breast cancer progression (Brooks et al., 1995). Bevacizumab is also currently under investigation due to its selective targeting of VEGF, as a drug to administer in combination to chemotherapy (Cobleigh et al., 2003). Other studies instead suggest vascular inhibiting treatment options should encompass more than one angiogenic target simultaneously, as an average of 6 is generally present at one time in a tumour (Relf et al., 1997).

1.5.3.1 The cancer stem cell phenotype Regardless of the advances in the treatment of cancer, relapse and cancer metastasis continuously instigate cancer mortality. It is believed that understanding the molecular and cellular physiology of cancer stem cells could provide a path towards cancer eradication. The cancer stem cell hypothesis entails that a minority of cancer cells with stem cell properties drives tumour formation, progression and resistance to anti-cancer therapy. Anticancer therapy will only be able to eliminate the bulk of the tumour, leaving CSC unscathed, and able to recreate the tumour over time. These will eventually cause tumour metastasis, which is the primary cause of tumour mortality. Effective eradication of cancer stem cells could therefore be the key to complete tumour eradication. (Saadin and White, 2013)

CSC were first identified approximately 20 years ago, when these were found to be the cause of leukaemia (Lapidot et al., 1994). The last 10 years have comprised of mounting evidence of a distinct role for CSC in solid tumours. In the case of breast cancer, it was initially shown how the capacity to form new tumours was restricted to a small sub-population of cells which presented different surface markers from the tumour bulk (Al-hajj et al., 2003). Upon their injection into nude mice, this sub-population was able to produce cancers with only 100 cells, while cells lacking the markers was unable to create a tumour despite the injection of thousands of cells (Ponti et al., 2005).

One of the main causes behind tumourigenesis is the presence of rare cancer stem cells (CSC), which are able to maintain the tumour via their hierarchical organisation and combination with differentiated tumour cells. These have attracted attention due to their many unique features, such as resistant to treatment, and ability to create differentiated tumour cells, which are believed to be singular key features behind tumour recurrence, metastasis and cancer progression (Bergamaschi et al., 2014). These are believed to originate from stem cells derived from healthy adult tissues, as these are more prone to malignant transformation due to extended lifespan, despite their sequestration in niches and tight signalling control. It is noteworthy how CSCs display characteristics equivalent to these presented by normal stem cells, backing the association. In particular, their ability to self-renewal, would render them able to generate more CSC, and

Page | 36 eventually differentiate into the multiple cell phenotypes typically found in malignant tissues. [3] (Gangopadhyay et al., 2013)

Contrasting opinions believe that the CSC phenotype is derived from the gradual acquisition of different mesenchymal properties, such as these developed during EMT. Other lines of thought argue that mesenchymal CSCs contribute to the initiation of EMT, as well as cancer progression through the production of cytokines and growth factor production (Gangopadhyay et al., 2013).

There are both extrinsic and intrinsic molecular mechanisms behind normal and pathogenic stem cell formation. Intrinsically, there is a hierarchy among oncogenic fusion proteins which can grant differentiated progenitor cells self-renewal abilities, as well as an inhibited differentiation ability. For instance, in haematopoietic malignancies, oncogenes such as MOZ-TIF2 and MLL-ENL are sufficient to incur these changes. However, other genes, such as the BCR-ABL1 in myeloid leukaemia, which are able to promote proliferation and increased survival, are not capable of rendering progenitor cells stem-like (Huntly et al., 2004) (24). This hierarchy supports the hypothesis whereby sequential mutation is required for the acquisition of stem-like properties. However, amongst the genes crucial for cancerous stem cell development are signalling pathways which are involved in embryogenic and developmental CSCs, including Hox genes, Wnt, Sonic Hedgehog and Notch (Miller et al., 2005). It is believed that CSCs maintain their phenotype by proliferating through asymmetrical division, whereby the two daughter cells would be unequal: one would resemble the parental cell, with the self-renewal capabilities, with the latter prone to differentiation. Malfunctioning in genes responsible for self-renewal, such as Bmi-1 and Wnt/β- catenin signalling pathways, can revert this function (Reya et al., 2003). Other pathways influencing these attributes include the PI3K/Akt, through Wnt/β-catenin, HoxB4 and Notch1 (Guo et al., 2006).

1.5.3.2 Breast cancer stem cells Breast cancer cells which present characteristics equivalent to stem cells, such as tumour initiation, self-replication and self-renewal, have been classified as cancer stem cells (BCSCs). BCSCs were first discovered in 2003, with an original report stating that very low amounts of BCSCs were sufficient to induce breast cancer tumourigenesis, and cancer progression (Al-Hajj et al., 2003). It is essential to find new ways to kill BCSCs to completely eradicate the tumour, as current therapies are only able to eradicate non BCSC, leading to tumour recurrence.

The origin of BCSCs remains elusive to date. However, there are three leading speculations: the first believes BCSCs originate from stem cells which are able to utilise their innate self-renewal pluripotency and stem cell regulatory pathways to give rise to all differentiated cancer cells (Allan

Page | 37 et al., 2007); the second believes BCSCs are created from progenitor cells which undergo several mutational events, with the progenitor cells gradually acquiring the capacities necessary to transform from a stem cell to a differentiated cell, which is able to present partial self-renewal abilities upon cytokinesis (Chen et al., 2009); and the last predicts that BCSCs are derived from mature somatic, differentiated cells, which can revert to a de-differentiated state to present stem cell-like characteristics and display self-renewal abilities (Iqbal et al., 2013). Epidemiological evidence has led to the hypothesis that upon exposure to radiation, somatic breast stem cells are able to undergo mutations which can ultimately result in the formation of tumours. The resulting BCSCs would then be able to maintain the stem-like features through the Notch, Wnt/β-catenin and hedgehog (Hh) pathways. Another hypothesis on the origin of BCSCs states that BCSCs originate from non-malignant primary human mammary cells which are altered through the activation of the Ras/MAPK pathway, which causes them to undergo EMT and simultaneously activates few selected oncogenes (Morel et al., 2008). This hypothesis illustrates how new selected targeted therapies could act by aiming to restore the basal expression of these oncogenes, without affecting neighbouring healthy cells. This is of particular importance as recent evidence has displayed how BCSC are not only resistant to available drug and radio-therapies, but also enriched by them: in vitro evidence by Yu et al., displayed how primary breast cancer samples displayed significant enrichment in their mammosphere population following neoadjuvant chemotherapy, compared to chemotherapy-naïve samples(Yu et al., 2007). Despite the general belief that radiotherapy could also actively enrich BCSCs, recent evidence has pointed out that this is not always the case. The fairly new concept of radiosensitive and radioresistant BCSCs still needs better clarification to determine the characteristic which make a BCSCs population resistant or sensitive to radiotherapy, so as to attain better treatment outcomes(Zielske et al., 2011)(Gangopadhyay et al., 2013).

BCSCs can be isolated through their surface markers present on their cellular membranes. A summary of all the biomarkers for BCSCs can be found in Table 1.2. In particular, BCSCs are known to display high levels of the surface marker CD44, and low to no levels of CD24, B38, and Lin. Both CD44 and CD24 are surface adhesion molecules, while B38 is known to be as a breast and ovarian cancer specific markers. Other BCSCs specific characteristics help the correct isolation of these cells, including their capacity to grow and proliferate in serum-free suspension cultures, only to form neural-stem like spheroids, termed mammospheres. Furthermore, these remain in the G0 phase of the cell cycle, and can thus be identified by their retaining of bromodeoxyuridine or H3 thymidine (Cobaleda et al., 2008).

Page | 38

Three distinct pathways have been associated with the development and maintenance of the BCSC phenotype: the Notch pathway, the Hedgehog (Hh) signalling pathway and the Wnt/β-catenin pathway. A summary of each can be found in Table 1.3.

Page | 39

Signalling Role in BCSC: pathway:

Delta/Notch Cell fate regulation, shown to be expressed in both stem cells and early progenitor cells;

Wnt/β-catenin Stem cell self-renewal and cell fate, pro-oncogenic role with overexpression sufficient to promote epithelial and mammary tumours; β-catenin is a downstream target of the Wnt pathway, presenting a pro- oncogenic role;

Hedgehog Essential for normal mammary gland development, as well as malignant outgrowth and cancer progression; Plays a role in regulation of cell fate and embryonic growth.

Table 1 2. Summary of different signalling pathways and their role in the promotion and maintenance of BCSCs. Adapted from Gangopadhyay et al., 2013. The Hedgehog signalling pathway is present in all vertebrates in the form of 3 homologs: Indian hedgehog (Ihh), Desert hedgehog (Dhh) and Sonic hedgehog (Shh). These participate in the regulation of cell fate, proliferation and differentiation by binding to the Patched-1 and Hh receptors present on the cell surface (Pardal et al., 2003). Essential for normal mammary gland development, these pathways are re-activated to cause the development and progression of breast cancers. Numerous studies on the role of the Hh pathway in the regulation of the self-renewal abilities of BCSC revealed that this acts through the regulation of Bmi-1, a polycomb gene, through the regulation of Gli transcription factors (Reya et al., 2001)(Li et al., 2008). Alternatively, the Pitch EGFR receptor has been isolated as a crucial Hedgehog downstream target where it has been shown to regulate both early embryonic tumourigenesis, as well as BCSCs and the formation of mammospheres (Iqbal et al., 2013).

Otherwise, the Wnt signalling pathway has also emerged for its participation in the regulation of breast cancer stemness. As the Hh pathway, this can promote both the development of the mammary gland, and its oncogenesis, particularly through its control of stem cell differentiation (Nakshatri, 2011)(Jeong et al., 2011)(Nakshatri, 2010). Wnt works primarily through its down- stream effector, β-catenin. The latter can regulate different cellular functions according to its subcellular localization: for instance, when β-catenin is sequestered in the membrane, it regulates cellular adhesion with the aid of the cell-cell adhesion molecule E-cadherin, described previously;

Page | 40

Biomarker name Function

ATP-Binding cassette G2 Belongs to the family of drug transporters, capable (ABCG2) of enabling cells to efflux cytotoxic drugs, thus granting drug resistance.

Cluster of Differentiation 44 Cellular adhesion molecule, involved in cell (CD44) migration and metastasis

Cluster of Differentiation Over-expressed in several tumours, this marker is (CD10) an antigen originating from common acute lymphoblastic leukaemia.

ESA Epithelial cell adhesion This marker is characteristic for its expression in molecule/Epithelial Surface tissues and tumours of mammary origin. antigen (EpCAM)

Cluster of Differentiation 29 (1- Membrane receptor regulating cellular adhesion integrin) and metastasis

Cluster of Differentiation 49f (6- Involved in the distribution of basal and integrin) endothelial cells

Cluster of Differentiation 133 Glycoprotein exhibited on cell surface in an (prominin-1) inverse correlation in respect to cellular differentiation.

ALDH1 Regulates stem cell differentiation and is correlated to poor clinical outcome upon expression.

CXCR4 Chemokine receptor that plays a role in metastasis, with an expression which directly correlated to mammosphere formation.

Table 1 3. Biomarkers for the isolation of BCSCs. List of biomarkers which could serve to isolate breast cancer stem cells with their primary functions in BCSC. Adapted from Iqbal et al., 2013.

Page | 41 alternatively, β-catenin cytoplasmic accumulation ultimately leads to its nuclear translocation, where it will activate essential Wnt down-stream targets such as c-Jun, c-Myc, fibronectin and cyclin D1. There are three main types of Wnt signalling pathways: the canonical Wnt pathway, responsible for gene transcription; the non-canonical/planar pathway, which controls cell polarity and can affect cell shape by altering cytoskeleton organisation; and the non-canonical Wnt/calcium pathway, which controls intracellular calcium levels. Each one regulates its specific function by binding to causing the specific Wnt protein ligand to bind to the Frizzled family of receptors. Wnt signalling proteins comprise of a family of highly-conserved lipid-modified signalling glycoproteins, labelled Wnt 1 to 16, with sub-classes defined with letter A-B. Of all the sub-classes, Wnt1 and Wnt3a have emerged as regulators of BCSCs, with the first causing expansion of mammary stem cells in premalignant mammary tissues (Pece et al., 2010), and the latter leading to clonal expansion of isolated mammary stem cells and in vivo mammary gland reconstruction efficiency (Iqbal et al., 2013).

Notch signalling also plays a part in the promotion of mammary stem cells, particularly due to its control of cellular differentiation in distinctive developmental phases of the mammary gland. Like the previous pathways, Notch activation through cellular surface receptors causes it to promote the development and maintenance of BCSCs. Consistently, its targeted inactivation has been shown to be sufficient to curb the BCSCs phenotype, and to revert its resistance to chemotherapeutic drugs. However, the pathways high conservation amongst healthy tissues causes its inhibition to have drastic effects on the surrounding healthy cells (Garber, 2007)(Gangopadhyay et al., 2013).

One key aspect of cancer stem cells, on top of their ability to induce tumour initiation and resistance to both anti-cancer drug and radiotherapy, is their capacity to promote tumour metastasis (Li et al., 2007). It is believed that cancer stem cells are linked to tumour metastasis through their promotion of the EMT, the stage through which epithelial cells acquire the mesenchymal characteristics necessary to render them motile and able to metastasize. When looking at the signalling pathways which govern EMT and CSC, patterns of similarity emerge. For instance, the Wnt pathway, which has been shown to maintain the CSC phenotype, also controls EMT through the regulation of the fibroblast growth factor, Hedgehog, and TGF-β, ultimately regulating both Snail and Twist (Katoh, 2011). Two studies depicted separately how mammary cells made to undergo EMT produced cells which presented stem cell characteristics (Mani et al., 2008)(Saadin and White, 2013). Thus, cancer stem cells are the most dangerous cell population, as they can not only induce tumour formation, recurrence and drug resistance, but also tumour metastasis (Saadin and White, 2013).

Page | 42

1.5.4.1 Cancer cell migration and invasion Cell migration and invasion are an exceedingly organised multistep process that governs embryonic morphogenesis. In adults, cell migration and invasion are employed upon tissue repair and regeneration, as well as pathogenic processes, such as atherosclerosis, arthritis and the progression of cancer. A migrating cell maintains a high polarisation and is orchestrated by spatially and temporally regulated signalling networks, which encompass its morphological alterations (Labrousse et al., 2003).

Cell migration is initiated with the extension of protrusions from the cell membrane. According to the morphological, structural and functional nature of the protrusion, these can be termed filopodia, lamellipodia, and invadopodia/podosomes. The creation of membrane protrusions is driven through actin polymerization at the leading edge, a process tightly regulated both spatially and temporally(Pollard et al., 2003). Lamellipodia are flat membrane protrusions which generate at the leading edge of a migrating cell. These then attach to the substrate and drive the cell body towards it. Lamellipodia are primarily formed by dendritic collections of actin filaments as well as the governing bodies which regulate actin structurally through depolymerisation and polymerisation (Nicholson-Dykstra et al., 2005). Instead, filopodia present more elongated thin structures extending from the membrane, primarily composed of clusters of actin filaments. The precise role of filopodia in cell migration is poorly understood, but opinions converge in depicting a sensory role for these membrane protrusions, whereby they function to direct the course and direction of migration (Yamaguchi and Condeelis, 2007).

Lamellipodia membrane projections begin upon local actin polymerization, which necessitates the creation of free actin filament ‘barbed ends’ at the fast-growing leading edge (a.k.a. the plus end). To do this, de novo nucleation by Arp2/3 complex and formins can occur; coiflin can break existing actin filaments; barbed ends can be uncapped on pre-existing actin filaments(Nicholson-Dykstra et al., 2005). Amongst signalling pathways able to regulate this function is the epidermal growth factor (EGF), which can act as a chemotactic lamellipodia inducing factor in breast cancer cells (Xue et al., 2006). This was shown to be through regulation of WAVE-Arp2/3 complex (Wang et al., 2004).

Unlike lamellipodia and filopodia, invadopodia, or podosomes, enable cell migration through the thick filaments composing the extracellular matrix (ECM). These ventral membrane protuberances possess ECM degrading means. Invadopodia encompass numerous proteins, including actin and actin remodelling proteins, adhesion molecules, membrane remodelling and signalling proteins, as well as matrix degrading enzymes. N-WASP and contractin are signalling molecules essential for

Page | 43 the appropriate functioning of invadopodia. Unsurprisingly, these have been found to be over- expressed in several cancer types. Invadopodia appear to be particularly useful for cancer cells to migrate to and invade the tumour stroma and adjoining blood vessel, thus promoting tumour metastasis (Yamaguchi et al., 2005). As with lamellipodia, invadopodia are also regulated by EGF, this time through the Colony Stimulating Factor-1 (CSF-1)/EGF paracrine loop. Normally activated to regulate the activity of macrophages and vascular endothelial cells, its reactivation can promote oncogenic cancer invasion, migration and intravasation through matrix remodelling (Goswami et al., 2005).

In general, both cell migration and invasion are instigated by extracellular stimuli, such as chemoattractants. Upon binding to surface receptors, these molecules trigger the intracellular signalling pathways which are responsible for the organisation of actin cytoskeleton. To date, several pathways have been identified for their correlation to a migrating or invasive phenotype. These include the Wiskott-Aldrich syndrome protein (WASP) family proteins, the Arp2/3 complex, as well as the LIM-kinase/ cofilin and cortactin signalling pathways (Yamaguchi and Condeelis, 2007).

Upon the reception of an extracellular migratory stimuli, a cell responds by polarising and extending membrane protrusions (in the form of lamellipodia, filopodia or invadopodia, described previously). These protrusions are stabilised through the adherence to the ECM, or to adjoining cells through transmembrane receptors connected to the actin cytoskeleton. The adhesions enable a cell to pull it-self forward until they become at the rear, whereby they disassemble to permit cell disengagement. When a whole sheet of cells necessitates to move, the process only differs in that multiple cells present the protrusions instead of a single cell. The speed and morphology of the protrusions differs according to tissue type and extracellular stimuli, which can alter the migration dynamics (Ridley et al., 2003). Thus, cells reactivate mechanisms normally used by healthy cells, although in this case, they lack the stop signals which would eventually curb their motility (Friedl and Alexander, 2011).

Cells can migrate either individually or in groups. Single cells migrate to position themselves in tissues, as during embryogenesis and cancer, or to infiltrate through tissues, as performed by immune cells. Their migration can be sub-divided into 5 steps: 1) Actin polymerisation re- organises the cytoskeleton to create protrusions at the cells leading edge; 2) The leading edge interacts with the cytoskeleton to form individual adhesive structures, and links extracellular adhesion to intracellular signalling that results in the generation of locomotory force; 3) Behind the leading edge, local proteolysis enables the creation of space through which the cell body can

Page | 44 progress; 4) Myosin II is activated through the Rho GTPase, which initiates intracellular tension upon contraction; 5) Adhesion bonds at the trailing edge are individually removed, enabling the cell body to move forward and the leading edge to protrude further. Morphology of the leading edge is regulated by the small GTPase Rac or Cdc42, which can instigate the growth of filopodia or lamellipodia and their interaction with the ECM (Sanz-moreno et al., 2008). Single cell movement is generally effected in a synchronous pulsatile fashion, so as to enable the extension of the cell body and the creation of grip in an oscillatory manner (Ridley et al., 2003).

For collective migration, cells instead maintain their intercellular junctions as they migrate, and result in tissue reorganisation (Friedl and Gilmour, 2009). Thus, large groups of cells migrate in unison to form the 3-layer embryo in gastrulation (Ridley et al., 2003). Collective migration is distinctive for the preservation of cell-cell junctions throughout movement, the supracellular cytoskeleton organisation that enables the creation of traction force while maintaining cell contacts, and the alteration of the ECM during cell migration, through, for example, the deposition of a basement membrane. Although frequently undocumented, collective cell migration is essential for cancer progression steps such as vasculogenesis and cancer migration (Friedl and Gilmour, 2009).

Cell invasion of host tissue is an essential element in metastasis. One of the primary steps which ensures invasion is the alteration of the cell-cell adhesion and cell adhesion to ECM. For this, the cadherin family, described previously (Chapter 1.4.1.1), plays an important role due to its regulation of cell-cell adhesion: E-cadherin maintains cell junctions, with its downregulation sufficient to initiate cell invasion and migration (Scully et al., 2012). Integrins also mediate the adherence of tumour cells to ECM. These transmembrane receptors bind to ECM constituents such as fibronectin, lamin, collagen, fibrinogen and vitronectin. Cell invasion is preceded the proteolytic degradation and remodelling of the surrounding ECM of healthy tissues. Connected to this process are the matrix metalloproteinases (MMPs) and the urokinase plasminogen activator uPA (Danø et al., 2005). These portray a role in non-pathogenic tissue remodelling (i.e. wound healing) and are co-opted by neoplastic cells. However, activation of either MMPs or plasmin is tightly regulated by the prevalence of specific inhibitors which target plasminogen activators as well as tissue inhibitors of metalloproteinases. In this way, successful tumour invasion necessitates the simultaneous co-operation of several molecules, which is further acerbated by the fact that different cells within the stroma need to secrete individual components (Johnsen et al., 1998). Notwithstanding the numerous attempts to identify the primary pathway governing cellular invasion, this process is not characterised as heterogenesous and adaptive process, whereby individual cells within the growing neoplasm undergo the plasticity required for invasion, and

Page | 45 simultaneously activate the signalling promoting pathways in the surrounding stroma (Friedl and Alexander, 2011). Mesenchymal cells adopt a characteristic spindle-shaped morphology upon cell invasion. This structure incorporates several focal cell-matrix adhesion points containing clusters of integrin and ECM substrate proteolytic capability. Proteases present on the cell surface create micro-tracks through which other migrating cells can follow (Wolf et al., 2007).

1.5.4.2 Migration and invasion in breast cancer Both cell migration and invasion are rate-limiting steps essential for metastasis. Identifying and defining the molecular pathways at play in these processes can provide information of tumour initiation and progression, as well as aid in the understanding of the level of its interaction with the tumour stroma. Thus, novel diagnostic approaches and targeted therapies to prevent metastatic cancer (Wang et al., 2007). Varied information has come to light regarding signalling pathways involved in breast cancer migration and invasion.

In human ductal breast carcinoma the stroma appears to play the more crucial regulatory role in the cancer invasion of the cells: both uPA mRNA and its receptor, uPAR, are only detected in the tumour stroma, as well as in the tumour infiltrating macrophages (Pyke et al., 1993). A similar outlook is detected when looking at the expression of MMP-1, -3,-4, -11 and -14, which are predominantly secreted by stromal fibroblasts, infiltrating macrophages and vascular pericytes (Heppner et al., 1996). This pattern mimics what happens following weaning, during involution of the mammary gland (Lund et al., 1996). In both cases, deficiency in PlG, a plasminogen precursor, could hinder the process, resulting in fewer metastasis or delayed mammary involution (Bugge et al., 1998)(Johnsen et al., 1998). In line with this hypothesis, Karnoub A.E. et al., reported how bone-marrow derived mesenchymal stem cells are recruited to the breast cancer tumour stroma, where they can contribute to cancer progression through paracrine signaling (Karnoub et al., 2007).

One way through which breast carcinomas mediate their migration and invasion capabilities is through miR-21 down-regulation of tissue inhibitor of metalloproteinase-3 (TIM3) at the transcriptional level (Song et al., 2010). Alternatively, extensive research has been performed to characterise the cofilin pathway and its regulation of mammary tumour invasion: cofilin is able to trigger actin polymerisation and cell motility in response to extra-cellular stimuli, particularly through the generation of free barbed ends and actin filament turnover. These could be through the EGF, TGF-α, the stromal cell derived factor -1 (SDF-1) or heregulin, which can activate LIM kinase -1 (LIMK-1) and -2, the skeletal muscle-specific kinase Nik related kinase (NRK) or the testicular protein kinase-1 (TESK1) and -2 (Wang et al., 2007). Moreover, metastatic breast cancer is promoted by the pro-metastatic gene RHOC, through the Twist-induced miRNA (miR-10b)

Page | 46 inhibition of HOXD10 protein synthesis (Ma et al., 2007). Alterations in cadherins levels were also correlated to increased cell migration and invasion. In particular, E-cadherin down-regulation, was reported in lobular breast carcinoma cases (Kotb et al., 2011), as well as shown to correlate directly with breast cancer metastasis(Wendt et al., 2011) and poor clinical outcome (Gould Rothberg and Bracken, 2006). Furthermore, integrin regulators can also affect breast cancer invasion. For instance, uPA was used as a prognostic factors to predict the formation of metastases (Harbeck et al., 2004). Alternatively, uPA silencing inhibited breast cancer invasion and limited MMP9 expression. The latter mediates ECM degradation primarily at the invadopodial front of invasive breast cancer cells (Yamaguchi and Condeelis, 2007). Specifically, integrin α5β1 and α3β1 are able to up-regulate MMP9 expression (Mitchell et al., 2010). Another mediator of cell invasion is heparanase, a β-glucorinidase which facilitates ECM disruption by degrading heparin sulfate proteoglycan, a protein which plays essential structural role in the maintenance of the ECM (Arvatz et al., 2011). Heparanase acts by degrading heparan sulfate, which generally accumulates all the heparin-binding growth and angiogenic factors. Thus, the substances will be released and regulate tumour growth, invasion and angiogenesis (Presta et al., 1989). Evidence of heparanase role in breast cancer progression has been attained where this enzyme was shown to correlate with a tumour’s metastatic potential (Maxhimer et al., 2002), as well as being detected in advanced breast cancer stages (Matsuda et al., 2001).

Further analysis has identified several other candidate genes for the regulation of breast cancer migration and metastasis. For example, the protease-activated receptors (PARs), a class of G- protein coupled receptors, can promote both the growth and invasion of breast cancer cells. Amongst its activators, MMP-1 was shown to be secreted by fibroblasts present singularly in the tumour stroma (Boire et al., 2005). Alternatively, the serine/threonine kinase AKT/protein kinase B isoform, AKT2, was inversely correlated to an invasive phenotype (Cheng et al., 2007). When analysed further, AKT was shown to prevent invasion through the regulation of the nuclear factor of activated T cells (NFAT), a transcription factor known to promote carcinoma invasion (Yoeli- Lerner et al., 2005). Lysyl oxidases (LOX) extracellular remodelling enzymes also portray a role in breast cancer invasion: notably, LOX-like LOXL-2, -3 and -4 were shown to regulate cancer cell invasion, with their respective regulation though to be mediated through fibroblast present in the stroma (Kirschmann et al., 2002).

1.5.5.1 Cancer metastasis

Metastasis is the culmination of all pre-metastatic events depicted previously, and occurs when tumour cells are able to successfully adapt to a tissue microenvironment which differs from its

Page | 47 organ of origin. In each instance, successful metastasis is limited by the sequential events that lead to it, and by the traits displayed by the stroma of the new organ, which could accommodate the growth of the tumour. Throughout the years, the focus has been maintained on the mutations which render a tumour metastatic, instead of keeping into account the alterations which make a distant organ present a permissive environment. Notable evidence has described how a tumour stroma can aid wandering cancer cells in their parasitic colonization, with specific molecular mediators and organ colonization patterns starting to surface. Despite the advances in our understanding, tumour metastasis remains the cause of 90% of solid tumour mortality. (Gupta and Massagué, 2006)

Interestingly, metastasis has been defined as an event instigated by the presence of a genetically varied cancer cell population, forced to survive in a constrictive environment. Thus, millions of tumour cells escape to the vasculature daily, with only a tiny portion completing the metastatic process. The inefficiency of the event can be attributed to the tight homeostatic regulatory mechanism present in different tissues, with a high hostility against these wandering cancer cells. In order to metastasise, tumour cells need to co-opt these mechanisms and barriers, rendering metastasis a process similar to an evolutionary progression, favouring the survival of the most heterogenous cancer sub-population within the organism ecosystem (Gupta and Massagué, 2006).

According to the most recent ‘seed and soil’ hypothesis, metastasis is the outcome resulting from two main principles. The first depicts how neoplasms consist of biological heterogeneous cell sub- populations, each presenting diverse angiogenic, invasive and metastatic assets (Lea et al., 1986). The second displays the selectivity of the metastatic process, whereby only cells able to survive and be successful in invasion, embolization, travelling in the vasculature, arrest in a distant capillary, extravasation and replication in a different organ parenchyma, are capable of metastasis (Fidler and Talmadge, 1986). Despite the still speculative nature of the hypothesis surrounding the process of metastasis, opinions converge towards the theory whereby metastasis is selective in that it favours the growth and survival of limited sub-populations present within the parent neoplasm (Talmadge and Fidler, 1982). Hence, metastasis displays a clonal origin, with different metastasis originating from single cells (Funan et al., 1987). The third hypothesis instead focuses on how the aftermath of metastasis relies upon the cross-talk of metastatic cells with homeostatic mechanisms, which can be supplanted by the cancerous cells (Fidler, 2002). Therapy aimed at metastasis deterrence should therefore not be contained to the fight against the tumour, but also to the prevention of homeostatic factors which could influence cancer cell proliferation, survival, angiogenesis, invasion and metastasis (Fidler, 2002).

Page | 48

1.5.5.2 Breast Cancer metastasis

Breast cancer is a heterogeneous disease. Amongst patients diagnosed with breast cancer, approximately 10-15% will develop metastasis, and these will occur within 3 years of the primary diagnosis. However, detection of metastases even 10 years after diagnosis is not uncommon, causing breast cancer patients to bear a life-long risk of metastasis recurrence (Weigelt et al., 2005). Breast cancer metastasis is diagnosed principally through biopsies, radiological evaluations and examination for serum tumour markers upon clinical manifestations of the spread to other organs. However, these methods are often inept at detecting secondary lesions early on. To try and predict tumour relapse, some studies analyse presence of circulating tumour cells (CTCs) in the patients’ bloodstream. These are analysed for morphological and histological markers to predict eventual relapse and therapy response. However, this fairly new method necessitates better characterisation to enable its wide-spread use (Scully et al., 2012).

Breast cancer primarily spreads to the lungs, liver, bone and brain. About 51% of breast cancer metastatic patients will develop highly aggressive osteolytic bone metastases. This ability is tightly correlated to the expression profile of a subset of genes. It is believed that the primary breast tumour will contain cells which express these genes, and that these will have the tissue-specific metastatic ability. Enrichment and gradual selection of these cells will lead to eventual bone lesion. Genes identified with aiding in breast metastasis include CXCR4, for its role in bone marrow homing and extravasation (Homey et al., 2001), MMP1 and ADAMTS1, involved in pericellular proteolysis and invasion (Egeblad and Werb, 2002), FGF5 and CTGF, for its regulation of angiogenesis(Giordano et al., 1996), follistatin, involved in growth factor regulation (Winter et al., 1996)and proteoglycan-1, which can control extracellular matrix alteration (Timar et al., 2002). These genes are however unable to change the metastatic potential of a breast cancer cell line if over-expressed individually. However, simultaneous overexpression of a minimum of three could enable a breast cancer cell line to attain osteolytic bone metastasis close to that noted in patients. Thus, bone metastasis appears to necessitate the co-operation of more than one signalling pathway (Kang et al., 2003).

Breast cancer lung metastasis is one of the most common sites for breast cancer metastasis, along with bone, and occurs in 17% of metastatic breast cancer cases. However, the gene cohort regulating the two differs substantially. Lung metastatic lesions signature includes growth and survival factors, such as HER/ErbB receptor ligand epiregulin, chemokines, such as CXCL2, cell adhesion receptors, such as ROBO1, extracellular proteases (MMP1), intracellular enzymes, such

Page | 49 as COX2 and transcription factors, such as ID1. Expression of these molecules in a primary breast tumour generally results in poor clinical outcome, both due their promotion of metastasis as well as for their contribution to enhance the growth of the primary tumour. Alternatively, other genes, such as MMPs, are only sporadically expressed in the primary tumour. This is believed to be due to these cells promotion of a virulent behaviour, whereby only a subset of cells can grow and metastasize aggressively without contributing to the primary mass (Minn et al., 2005).

Breast cancer brain metastasis arises in 10% of breast cancer metastatic patients (Weil et al., 2005), and inevitably leads to neurological disability and death in short periods of time. Generally, breast cancer brain lesions appear following a period of remission, indicating that circulating breast cancer cells often do not possess the attributes required to grow under the pressure of this organ microenvironment. In fact, brain metastasis often occurs after established lesions in other organs, and this is thought to depend on the barrier to metastasis which differ according to the organ. For instance, the basement membrane in the capillary endothelial protects the lung, whilst the blood brain barrier (BBB) stops cells invading the brain. Thus, metastasis in the brain lesion will necessitate the usual mediators of extravasation coupled with enhancers to by-pass the BBB (Bos et al., 2009). Amongst genes identified as mediators of this capacity are the prostaglandin- synthesizing enzyme cyclooxygenase-2 (COX2)(Gupta et al., 2007) and heparin binding EGF (HBEGF), genes also correlated with extravasation through non-fenestrated capillaries of both the brain and the lung, as well as ST6GALNAC5, a specific mediator of infiltration through the BBB. Genetic signature analysis also isolated collagenase-1 (MMP1)(Egeblad and Werb, 2002), for invasion and extravasation, angiopoietin-like 4 (ANGPTL4)(Padua et al., 2008), that can disrupt endothelial junctions in response to TGFβ induction, latent TGF-β binding protein (LTBP1)(Adams, 2004), a regulator of TGFβ, as well as fascin-1 (FSCN1)(Saharinen et al., 1999), that can augment cell migration.

Breast cancer liver metastasis has the lowest incidence when compared to the other common locations, detected in only 6% of cases. However, detection of metastatic liver lesions embraces the worst prognosis, with patients’ median survival after diagnosis of one month (Patanaphan et al., 1988). Unfortunately, limited information is available on the molecular pathways which govern liver metastases. Nonetheless, EGFR presence on the tumour cells coupled with TGFα stimulation from the stroma was shown to be a mediator of this particular metastatic lesion (Chambers et al., 2002). Furthermore, NF-κB displayed an influence when up-regulated by paclitaxel administration, through an inflammatory response (Li et al., 2016a).

Page | 50

Breast cancer is a heterogeneous disease to which classification attempts have generated a subset of useful predictive markers. These are used to determine which patients are more at risk of developing metastatic cancer. However, none of these markers have shown a prevalence in instigating the divergence of the tumours, nor have they been successful in eradicating the tumour when targeted alone. Further studies are necessitated to correctly define the action of each gene in each step of cancer progression, so as to predict the best treatment for each neoplastic disease. Lately, the Forkhead Box family, down-stream effectors of the PI3K/Akt pathway, have emerged for their regulation of cancer progression in numerous cancers. Next, the research to date on this pathway and its role in cancer development will be summarised.

1.6 The phosphoinositide 3-kinase (PI3K) pathway The phosphoinositide 3-kinase (PI3K) signalling pathway was first discovered in 1985, and has since been known for its ability to phosphorylate target proteins on their serine/threonine residues. This dual specificity protein and lipid kinase function by catalysing the addition of phosphate to the 3-OH present on the inositol ring of lipids (a.k.a. phosphatidylinositols, Ptdlns) integrated within the intracellular space of cellular membranes, causing phosphatidylinositol 4, 5-biphosphate

(PIP2) to become phosphatidylinositol 3, 4, 5-triphosphate (PIP3). Consecutive phosphorylations enable this subset of enzymes to regulate a multitude of signalling pathways, which converge to control cellular processes such as cell size, proliferation, survival, metabolism, ageing, cytoskeleton organisation, angiogenesis, invasion, metastasis, differentiation, membrane trafficking and chemotaxis (Fruman and Cantley, 2002)(Okkenhaug and Vanhaesebroeck, 2003). The PI3K family of enzymes is distinguished in three main subgroups according to substrate specificity and lipid products (Engelman et al., 2006), of which the first class has been the most extensively characterised. PI3K enzymes present a heterodimeric structure which contains a p110 subunit, which encompasses the catalytic domain, and a p85 subunit, which is responsible for the translocation of the catalytic domain and a regulatory domain (Okkenhaug and Vanhaesebroeck, 2001). Class I of PI3K enzymes are primarily activated by the binding of hormones, cytokines or growth factors. Depending on the trigger, PI3K activation can result in proliferation, survival and/or motility. These are processes essential for a wide variety of cell lines, particularly for the development and function of inflammatory cells, as well as for lymphoproliferative or autoimmune diseases. During cancer, PI3K constitutive activation can lead to proliferation and protection from apoptosis, key aspects in the insurgence and progression of neoplastic diseases (Burgering, 2016). Numerous tumours (including glioblastoma, prostate, endometrial and ovarian cancers) were shown to exploit the benefits of PI3K activation by harbouring mutations in PTEN, a phosphoinositide phosphatase which can regulate the metabolism of Ptdlns, and dephosphorylate

Page | 51

PIP3, thus antagonising PI3K activity. A mutation or deletion of PTEN could render the PI3K pathway constitutively active, promoting abnormal cell proliferation (Maehama and Dixon, 1998).

Upon the binding of a growth stimuli to a cellular extracellular receptor, PI3K is activated and recruited to the plasma membrane, where it can phosphorylate its substrate PIP2 to become PIP3.

PIP3 remains on the plasma membrane and acts as a docking site to attract proteins containing a pleckstrin homology (PH) domain. Protein families which are notable for their PH-domain include cAMP-dependent cGMP-dependent and protein kinase C (AGC) members, of which members include phosphoinositide-dependent kinase 1 (PDK1), atypical protein kinase C (PKC), phospholipase C-γ (PLC-γ) and the threonine/serine kinase (AKT/PKB) (Cantley, 2002)(Padua et al., 2008).

Amongst all targets, AKT activation has been shown to be correlated with increased proliferative potential and higher anti-apoptotic capacities. The family of AKT proteins presents 3 different isoforms, which share 80% homology and are present in all human tissues, with the exception of AKT3, which is only present in the brain and testes (Toker and Yoeli-lerner, 2006). AKT activation is thought to be mediated through PIP3 and PDK1: AKT is recruited and subsequently phosphorylated on threonine residue 308 (T308), which is contained within its catalytic site, or on serine residue 473 (S473), which is part of the C-terminal hydrophobic motif (HM). AKT phosphorylation causes its release into the intracellular space, where it phosphorylates its downstream targets (Engelman, 2009). The differential effect obtained upon phosphorylation on the different sites has so far not been entirely elucidated, but published studies seem to converge towards the theory that phosphorylation on T308 is essential for AKT activation, while phosphorylation on S473 has a role in amplifying the activation signals and determining substrate specificity (Brunet et al., 1999). Upon activation, AKT is translocated to the nucleous, where it can recognise and phosphorylate target genes through the serine and threonine residues present in their consensus motif. In general, AKT phosphorylation causes transcriptional inhibition. Examples of target genes are Forkhead transcription factors (Kops and Burgering, 1999), BH3- containing protein BAD (Datta et al., 1997) and the E3 ubiquitin ligase MDM2 (Mayo and Donner, 2001).

In general, promotion of the cancerous phenotype via the PI3K/AKT pathway is primarily mediated through alterations at the PI3K level, as mentioned previously. Aberrant PI3K functioning ultimately promotes the cancerous phenotype through AKT. Somatic mutations within AKT are limited, and have only been detected in 8% of breast cancer patients. Nevertheless, these enable AKT binding to PI3K regardless of PIP3, thus favouring its activation (Carpten et al.,

Page | 52

2007). Alternatively, studies have correlated AKT2 and HER2 overexpression in breast cancers to pulmonary metastasis (Dillon et al., 2009).

1.7. The Forkhead Box transcription factors The family of Forkhead Box proteins first emerged for their role and a fork-like head structure when deleted in Drosophila. The presence of a winged-helix structure in their DNA binding domain attributed them the name of ‘forkhead’. This domain also has the name of ‘winged helix domain’ due to the 3D structure of the two loops (wings) at the C-terminal, three α-helices at the N-terminal and three β-sheets, creating a formation which resembles butterfly wings (Burgering, 2008). To date, the FOX superfamily of transcription factors encompasses several evolutionarily conserved genes, of which function spans a broad transcriptional repertoire, essential for normal tissue development and homeostasis (Myatt and Lam, 2007). Around 100 forkhead genes have been identified from yeasts to humans, with 46 members having been characterised in humans (Katoh and Katoh, 2004). Over-time, their nomenclature was revised, and the members of this family began to be known under the FOX acronym, to signify Forkhead Box. Forkhead Box genes are now contained within 19 subfamilies, termed FOXA to FOXS, according to sequence analogy or similarities (Kaestner et al., 2000). All FOX transcription factors bind to DNA using the core consensus sequence RYMAAYA (R=A/G, Y=C/T, M=A/C) (Kaufmann et al., 1995). With the exception of FOXP, all FOX proteins bind DNA as monomers (Li et al., 2004). Fox proteins are further classified into two classes, according to the presence or absence of the C-terminal region in the forkhead domain. Mainly, FOX proteins belong to class I, with the exception of FOXH, FOXM, FOXN and FOXP, which are part of class II (Katoh et al., 2004). With antagonistic roles, most FOX genes are primarily active during the developmental stages of the embryo, only to lay dormant in adults; their function then becomes restrained to tissue regeneration events, with its ubiquitous expression only detected in actively proliferating, immortalized or transformed cells (Li et al., 2009a). If aberrantly expressed, these proteins can lead to the initiation and progression of cancers. A summary of their interaction with the PI3K/Akt and other signalling pathways can be found on Figure 1.3.

Page | 53

Figure 1.3 FOXO-FOXM1 signalling pathway. Schematic diagram summarising the principle signalling pathways which can interact with the FOXO-FOXM1 axis. Briefly, FOXO3 inhibits FOXM1, which is regulated upstream by the PI3K/Akt pathway. The latter is in turn regulated by EGFR/PI3K, upon epidermal growth factor binding (EGF), or oestrogen, which can also contribute to FOXM1 regulation at the gene promoter level through a positive feed-back loop. Alternatively, Erα can up-regulate FOXM1 through the steroid receptor co-activator SRC-3 and the transcription factor C/EBPν. Finally, DNA damage activated ATM can also contribute to FOXM1 activation.

Page | 54

1.7.1 The Forkhead Box transcription factors: FOXO The FOXO sub-class of transcription factors were first identified in the nematode Caenorhabditis elegans (C. elegans) for their role in metabolic insulin signalling and longevity (Horst et al., 2006). There are four main FOXO transcription factors in mammals: FOXO1, FOXO3, FOXO4, and FOXO6. Structurally, they are composed of the highly conserved DNA binding domain, upstream of a nuclear localisation signal, with a subsequent nuclear export sequence and a C-terminal transactivation domain. The FOXO sub-family of proteins all share homology in the DNA binding domain (Anderson et al., 1998).

Amongst all FOXO proteins, FOXO3 (a.k.a. FOXO3a) is the most ubiquitously expressed within both embryos and adult tissues (Furuyama et al., 2000), with the highest expression in the brain (Jacobs et al., 2003) FOXO3 knock-down in mice induces premature ovarian failure, a syndrome which is, in humans, correlated to infertility and ageing in females, implying FOXO3 shares a function in the maintenance of resting follicle pool (Tothova et al., 2007). Furthermore, FOXO3 loss also causes spontaneous lympho-proliferation and organ inflammation, as well as hyperactivated helper T cells with higher proliferative and cytokine production capacities (Winter et al., 1996).

FOXO activity is tightly regulated by a range of post-translational processes which include phosphorylation, ubiquitination, acetylation and methylation (Calnan, DR; Brunet, 2008). These are induced by numerous things, such as growth factors, hormones, metals and chemicals. The most extensively described post-translational modification is Akt-mediated phosphorylation, which induced FOXO3 nuclear translocation (Dorman et al., 1995). FOXO members normally contain multiple evolutionarily conserved phosphorylation sites for Akt. In the case of FOXO3, three Akt consensus sequences exist located on T32, S253 and S315 (Takaishi et al., 1999). When FOXO3 is phosphorylated on FOXO3 T32 and S253, chaperone protein 14-3-3 is recruited, and activated the nuclear export signal (Lopez-girona et al., 1999), as well as inhibiting the nuclear import signal in the Forkhead domain (Rena et al., 1999). This inhibits FOXO3 as it causes it to translocate to the cytoplasm (Greer and Brunet, 2005). Alternatively, in the absence of growth factor signalling, Akt is unable to phosphorylate FOXO3: the rate of nuclear import will then exceed that of export, rendering FOXO3 mostly active (Brownawell et al., 2001).

FOXO proteins act by binding to the promoter consensus sequences 5’-GTAAA(T/C)A-3’, and activating or repressing the activity of target genes through the transactivation domain contained within FOXO structure and a plethora of associated co-factors that the protein can recruit (Furuyama et al., 2000). Amongst its functions, FOXOs can regulate cell cycle through binding to

Page | 55 several cyclin/cyclin dependent kinases (CDK), which can in turn regulate substrates required for cell cycle progression (Besson et al., 2008). Alternatively, FOXO is also involved in the regulation of apoptosis, or programmed cell death: for instance, the tumour necrosis factor (TNF) cytokine family member is part of the Akt-FOXO signalling pathway (Brunet et al., 1999), with FOXO3 expression mediating the induction of apoptosis. FOXO3 has been correlated with ERα expression and good prognosis in ER positive breast cancer. Immunohistochemical analysis of patient samples further determined parallel expression of PgR, FOXA1 and p27Kip1, all markers of a favourable outcome (Habashy et al., 2011). Consistently, mutations in the PI3K-FOXO3 signalling pathway contribute to drug resistance, increased proliferation and cancer progression of luminal breast cancer (Chen et al., 2010). Furthermore, FOXO proteins have been shown to mediate several aspects of cancer progression. A subset of its functions are described below.

1.7.2 The Forkhead Box transcription factors: FOXM1 Amongst the members of the forkhead family, FOXM1 (previously known as HNF-3, HFH-11, MPP2, Win, and Trident)(Gomes et al., 2013) has emerged for its oncogenic role in cancers such as breast, colorectum, lung, prostate, liver, pancreas, cervix, blood, and nervous system. Its roles span all areas of cellular homeostasis, including the promotion of DNA damage response, insurgence of drug resistance, cell cycle progression, EMT, tumour induced angiogenesis, cancer stem cells and metastasis.

The FOXM1 gene is made of 10 exons, with alternative spicing of exon Va and VIIa leading to the formation of three distinct isoforms: FOXM1a, FOXM1b and FOXM1c. Only the latter two are active forms as the first is disabled due to the presence of both exons in its structure, causing a malformation in its transactivation domain. Alternatively, FOXM1b, which lacks either exon, and FOXM1c, which contains only exon Va, are capable of transcriptionally regulate a large number of target genes (Li et al., 2009a)(Koo et al., 2012). FOXM1 activity in healthy individuals is restricted to the developmental stages of the embryo and fetus, allowing for the correct development of both epithelial and mesenchymal tissues (Ye et al., 1997), as well as to normal tissue homeostasis, and regeneration in adults, such as that is required during wound healing (Zhao, 2015). Seeing as FOXM1 primordial function entailed the promotion of cellular proliferation and motility, crucial for the correct development of a foetus, it is not surprisingly that its aberrant activation in adult tissues can lead not only to the initiation, but also the effective progression of cancer to a malignant form.

A tissue microarray performed on 236 ER positive breast cancers revealed that FOXM1 expression was correlated with a larger tumour size, presence of metastasis in lymph nodes, and

Page | 56 lymphovascular invasion. These tissues were also prone to develop more advanced tumour stages, with frequent relapse and poor overall survival. Thus FOXM1 proved a useful prognostic biomarker for aggressive phenotypes and poor prognosis, as well as a putative anti-cancer target (Ahn et al., 2015).

In a separate study, tissue microarray analysis of nasopharyngeal carcinoma tissues compared to nasopharyngeal epithelial tissues revealed significant FOXM1 overexpression in the former. FOXM1 overexpression was also associated with metastasis to lymph nodes as well as advanced tumour stage. To counteract its cancer progression, FOXM1 was targeted with thiostrepton in nasopharyngeal carcinoma cells. Thiostrepton was able to inhibit the migration and invasion capacities of the cell lines, through the down-regulation of MMP-2, MMP-9, fascin-1 and paxillin (Jiang et al., 2014a).

FOXM1 functions down-stream of multiple oncogenic signalling pathways. For instance, FOXM1 can be up-regulated by RAS, by inducing cellular levels of reactive oxygen species (ROS). Phosphorylation by cyclin and CDKs, or by polo-like kinase 1 (plk1) are furthermore essential for FOXM1 transcriptional activity. Particularly, phosphorylation of the C-terminal region of FOXM1 is especially crucial, as it permits the recruitment of a histone deacetylase p300/CREB-binding protein, which acts as its co-activator. Another essential part of FOXM1 transcriptional activation is its phosphorylation by the mitogen-activated protein kinase (MAPK) pathway, as this is able to regulate its subcellular localization and consequent transcriptional activation. FOXM1 also functions down-stream of the Wnt signalling pathway, acting as a critical activator of beta-catenin. Specifically, FOXM1 is controlled by Wnt3a, which increases both its expression and nuclear translocation, thus up-regulating its nuclear localization and transcriptional activity(Sambasivarao, 2013).

In addition to functioning under the control of numerous oncogenic pathways, FOXM1 function is also repressed by tumour suppressor genes. For instance, FOXM1 can be repressed by the major tumour suppressor P53, which can inhibit its expression both at the protein and mRNA level. This inhibition was found to be dependent in part by the activity of p21 and retinoblastoma (Rb) proteins. Another tumour suppressor gene which is able to repress FOXM1 function is KLF4, which was found to have a binding site on FOXM1 promoter, repressing its transcription. On top of tumour suppressor genes, a recent body of evidence has revealed that microRNAs could also contribute to FOXM1 repression. In particular, miR-370 was found to bind to FOXM1 mRNA, repressing FOXM1 at the post-transcriptional level (Sambasivarao, 2013).

Page | 57

In recent years, the transcription factor Forkhead Box M1 (FOXM1) has emerged for its distinctive influence over each of these steps in multiple cancer types (summarised in Figure 1.4). In this project, we will focus on how FOXM1 can influence individual steps of cancer progression.

Figure 1.4 FOXM1 can control essential processes in cancer progression. FOXM1 is central to numerous processes which can contribute to both embryonic development and cancer progression. These processes include stem cell expansion and renewal, vasculogenesis and tumour induced angiogenesis, cell cycle, cell migration and metastasis, DNA damage response and EMT.

1.7.3.1 FOXO-FOXM1 in tumour induced angiogenesis Like any other cell, tumours require effective irrigation and means to expel their waste. However, due to their unplanned presence and uncontrolled growth, the surrounding blood vessels will not be sufficient to sustain their development. Without a constant blood supply, a tumours growth

Page | 58 will be stunted at the volume of 1-2 mm³, and the mass will succumb to apoptosis and necrosis. To overcome this obstacle, tumours reactivate the development of surrounding quiescent blood vessels, inducing them to grow towards their proximity. This rate-limiting step has been termed ‘angiogenic switch’, and is essential for an avascular hyperplasia (or dormant tumour) to become a vascularized tumour with the potential to become a malignant lesion(Bergers and Benjamin, 2003; Hanahan and Weinberg, 2011).

Limited information is available on the role if FOXM1 in vasculogenesis and angiogenesis in embryos. However, this portrays an essential function as its knock-down in mice during embryogenesis results in severe defects in the formation of the peripheral pulmonary capillaries (Kim et al., 2005). Consistently, the expression of FOXM1 has been correlated to that of other angiogenic genes in murine placenta during mid-late gestation. Detected genes include BMP4, VEGFA, CAV1, CD36, MMP14, Rhob and angiopoietin 4 (Vaswani et al., 2013).

More extensive research has instead been performed to reveal FOXM1 function in tumour neoangiogensis. FOXM1 overexpression was found to increase expression of the vascular endothelial growth factor (VEGF) in gastric (Li et al., 2009b), breast (Zhang et al., 2015a) and pancreatic cancer (Cai et al., 2013), as well as nasopharyngeal carcinoma (Jiang et al., 2014b) and acute myeloid leukaemia (Zhang et al., 2014). Specifically, FOXM1 can bind to consensus Forkhead Response Element present on the VEGF promoter, thus activating its transcription (Karadedou et al., 2012). As described previously, VEGF is one of the main effectors of tumour neoangiogenesis, therefore one of the primary contributors to cancer progression. FOXM1 can furthermore regulate tumour induced angiogenesis via the direct transcriptional control of the urokinase-type plasminogen activator (uPA) and its membrane-bound receptor uPAR in breast, pancreatic and human hepatocellular carcinoma cells. These in turn can control vascular endothelial cell proliferation, adhesion, migration and microvascular tube formation. (Sambasivarao, 2013). Alternatively, in advanced glioma, FOXM1 up-regulated the expression of Annexin A1 (ANXA1) a calcium/phospholipid-binding protein, which could lead to neoangiogenesis (Cheng et al., 2013).

The role of FOXO3 in vessel formation was first studied to determine its function in postnatal vessel formation and maturation. FOXO3 resulted able to influence the angiogenic response of endothelial cells, particularly controlling sprout formation and endothelial migration through direct transcriptional binding to the eNOS promoter, a gene known for postnatal neovascularisation (Potente et al., 2005). Unsurprisingly, FOXO3 can impair FOXM1 function in tumour induced angiogenesis. Specifically, FOXO3 can bind to the same Forkhead Response Elements to which

Page | 59

FOXM1 binds to on the VEGF promoter, and inhibit its transcription. Thus, FOXO3 diminishes VEGF secretion directly, and indirectly by preventing FOXM1 binding (Karadedou et al., 2012).

1.7.3.2 FOXO-FOXM1 and the epithelial to mesenchymal transition As described previously, the EMT is a crucial developmental process through which epithelial cells lose their polarity and epithelial characteristics, only to obtain mesenchymal markers and increased motility. This process is then co-opted by cancerous cells, rendering EMT a crucial step in cancer progression.

Extensive studies have been performed to characterise FOXM1 role in EMT. Consisted with its proto-oncogenic function, FOXM1 has always been correlated with the promotion of EMT, as well as of the consequent increase in the migratory, invasive and metastatic clinicopathological attributes of different cancer types. For instance, FOXM1 overexpression has been associated with the promotion of EMT in non-small cell lung cancer (Xu et al., 2013), gastric cancer (Cai et al., 2015), liver carcinomas (Park et al., 2011), pancreatic cancer (Sambasivarao, 2013), breast cancer (Xue et al., 2014), and colon carcinoma (Yang et al., 2015). Numerous pathways have been correlated with FOXM1 regulation of EMT. In gastric cancer, FRLnc, a long non-coding RNA, was shown to be a FOXM1 direct transcriptional target, and to regulate EMT through Twist and TGFβ1 (Cai et al., 2015). In non-small cell lung cancer, FOXM1 regulates the phosphorylation of AKT-p70S6K, which can then promote its aberrant action, and consequently EMT (Kong et al., 2014). A similar conclusion was detected in liver carcinogenesis, where FOXM1 increased the activity of AKT potentially contributing to the aberrant AKT noted in multiple tumours. In turn, AKT inhibits GSK-3β, a Snail suppressor and an EMT inducer (Park et al., 2011). FOXM1 is able to regulate EMT by positively regulating mesenchymal markers such as ZEB, Snail and vimentin in pancreatic cancer (Sambasivarao, 2013). Studies on lung adenocarcinoma instead concluded FOXM1 could regulate SNAIL by binding to its promoter (Wei et al., 2015). This regulation appears to be mediated in part through the repression of miR-200. It was later ascertained that this was in part due to the regulation of caveolin-1 expression by FOXM1 (Sambasivarao, 2013). Consistently, human colon cancer tissue immunohistochemistry displayed FOXM1 up-regulation was coupled to that of Snail and Vimentin, as well as to E-cadherin down-regulation (Yang et al., 2015). Alternatively, in breast cancer, endogenous FOXM1 binding to the Slug promoter was found (Yang et al., 2013). Finally, FOXM1 was also shown to contribute to TGF-β signalling activation by interacting with SMAD3. A study in human and mouse breast cancer cell lines displayed how FOXM1 can prevent the E3 ubiquitin-protein ligase transcriptional intermediary factor 1 γ (TIF-1γ) from binding to SMAD3 and mono-ubiquitinating SMAD4, thus stabilising

Page | 60 the SMAD3/SMAD4 complex, and sustaining its nuclear activity. The SMAD3-FOXM1 interaction also enables the TGF-β/SMAD3 transcriptional activity. This also promoted the SMAD3/SMAD4- dependent SLUG up-regulation. By increasing nuclear SMAD3 retention, and enabling a TGF-beta/SMAD3 cross-talk, FOXM1 is able to promote breast cancer cell metastasis (Xue et al., 2014).

Alternatively, FOXM1s functional agonist, FOXO3, showed the opposite role in the regulation of EMT. In both prostate and breast cancer cells, FOXO3 can repress EMT through the Akt- MDM2-FOXO3 signalling pathway. Specifically, this is mediated through FOXO3 direct transcriptional up-regulation of E-cadherin, and repression of mesenchymal markers, such as N- cadherin and Vimentin (Chou et al., 2014). FOXO3 can also prevent EMT by directly inhibiting β-catenin expression, thus preventing β-catenin dependent EMT processes (Liu et al., 2015). Other reports connect PI3K with the regulation of TGF-β and consequent Snail activation, both crucial mediators of EMT (Cho et al., 2007)(Bakin et al., 2000). Consistently, TGF-β was shown to activate Akt, thus influencing FOXO3 subcellular localisation (Naka et al., 2010). In this manner, the most crucial EMT regulating pathways appear to be interrelated with FOXO3, rendering this transcription factor at the centre of EMT regulation.

1.7.3.3 FOXO-FOXM1 and the cancer stem cell phenotype The distinguishing characteristics and signalling pathways involved in the development of the cancer stem cell phenotype has been described above (Chapter 1.5.3). In summary, cancer stem cells are a minute sub-population of cancer cells which are capable of self-renewal. These are believed to be the cause of tumour relapse, and resistance to chemotherapy (Sambasivarao, 2013).

As with other aspects of cancer progression, FOXM1 expression has been shown to influence the cancer stem cell phenotype in several cancers. These include pancreatic cancer (Bao et al., 2011), breast cancer (Bergamaschi et al., 2014), glioma (Gong and Huang, 2012), glioblastoma multiforme (Joshi et al., 2013), and colon adenocarcinoma (Song et al., 2015). Various mechanisms have been described to contribute to FOXM1 action. For instance, in pancreatic cancer FOXM1 can up- regulate the expression of genes previously correlated with the cancer stem cell phenotype. These include ZEB1, ZEB2, Snail2, E-cadherin and vimentin (Bao et al., 2011). Alternatively, in breast cancer, Rho-GTPase emerged as a FOXM1 down-stream effector capable of increasing the stem cell phenotype (Bergamaschi et al., 2014). FOXM1 was also shown to act down-stream of the Wnt/β-catenin signalling in a breast cancer model studying anchorage independent growth (De Luca et al., 2015), as well as in malignant glioma (Zhang et al., 2011). Consistently, FOXM1 interacts directly with β-catenin, promoting its nuclear translocation, and consequently its activity.

Page | 61

This interaction was confirmed in several cancers, including medulloblastoma, colon cancer and hepatocellular carcinoma (Gong & Huang, 2012; Holland, Klaus, Garratt, & Birchmeier, 2013). Further studies on glioblastoma revealed that FOXM1 is dependent on MELK phosphorylation to exert its neurosphere formation promotion (Joshi et al., 2013). In colon adenocarcinoma, FOXM1 was shown to increase mammosphere formation through the up-regulation of the mitochondrial gene peroxiredoxin 3 (PRX3) (Song et al., 2015). Embryonal carcinoma cell analysis further revealed Oct4, Nanog and Sox2 as being putative FOXM1 targets capable of influencing the stem cell phenotype (Xie et al., 2010).

Limited information is available on the influence of FOXM1 antagonist, FOXO3, on cancer stem cells. However, FOXO3 functions in the development of hematopoietic stem cells (HSC), by promoting erythrocyte differentiation as well as stem cell renewal (Miyamoto et al., 2007). Alternatively, several studies depicted how loss of function mutations in FOXO3 could deplete the hematopoietic stem cell pool and cause early embryo lethality (Tothova and Gilliland, 2007). FOXO3 can also control HSC autophagy, which is an essential protective mechanism to prevent metabolic stress (Warr et al., 2013) Other studies suggested FOXO3 may regulate HSC through its upstream control of by phosphatase and tensin homologue PTEN, which can induce the same effect when repressed (Hill and Wu, 2009). When FOXO3 role was verified in prostate cancer stem cells, FOXO3 was shown to inhibit the stem cell population as a primary downstream effector of the PI3K/Akt pathway (Dubrovska et al., 2008). Consistently, in breast cancer, FOXO3 was shown to inhibit BCSC formation through the direct transcriptional repression of CXCR1, the IL-8 receptor (Ginestier et al., 2010).

1.7.3.4 FOXO-FOXM1 in migration and invasion Unsurprisingly, FOXM1 can also mediate cancer cell migration and invasion. Migration and invasion are both crucial for embryogenesis, and re-activated by cancer cells to migrate to and invade neighbouring tissues. Furthermore, these processes are also used for tumour extravasation from the lymphatic or blood circulation into healthy tissues of choice.

Again, FOXM1 has been shown to mediate numerous pathways which regulate both functions. Merlin, a protein encoded by the NF2 gene, is decreased in human pancreatic tumours and cancer cell lines, with its restored expression leading to the inhibition of pancreatic cancer progression. This was found to be due to its upstream control of FOXM1, and consequent regulation of β- catenin. Merlin was found to decrease FOXM1 stability. As mentioned previously, β-catenin functions down-stream of the Wnt signalling pathway, and its activation promotes its nuclear translocation. Thus, proteins such as MMP-2 and -9 are activated. FOXM1 can also contribute to

Page | 62

β-catenin nuclear translocation directly (Quan et al., 2015). This was consistent with findings in prostate, breast, glioma, ovarian, colorectal and pancreatic cancers, where FOXM1 expression was correlated with MMP-2, -7 and -9 expression due to direct binding to their promoter region (Sambasivarao, 2013) (Wen et al., 2014) (Zhang et al., 2015a). Furthermore, in prostate cancer, FOXM1 was shown to regulate the proteolysis related genes uPA/uPAR, genes that have been found to facilitate the degradation of the basement membrane and extracellular matrix (Sambasivarao, 2013). FOXM1b was also found to stimulate LOX and LOX2 secretion in liver carcinogenesis, both in vivo and in vitro: LOX is secreted from primary tumours and accumulates in target organs, to facilitate impending cell invasion (Park et al., 2011). Alternatively, a study on hepatocellular carcinoma unveiled a new FOXM1 direct transcriptional target, the tartare-resistant acid phosphatase 5 (ACP5). ACP5 is able to promote cellular motility by regulating focal adhesion kinase phosphorylation. Its overexpression enables microvascular invasion, poor cellular differentiation and increased tumour node metastasis (Xia et al., 2014).

Research has also been performed to determine the role of FOXO3 in the regulation of cell motility. Studies in urothelial cancer invasion and migration revealed FOXO3 can inhibit Twist-1 and Y-box binding protein (YB-1) (Shiota et al., 2010a). Furthermore, in ERα positive breast cancer cell lines, FOXO3 can inhibit the motility, invasion and anchorage independent growth through the up-regulation of Calveolin-1 (Sisci et al., 2013). Again, in ovarian cancer, FOXO3 expression was inversely correlated to that of NANOG, a gene attributed with cell motility and self-renewal (Siu et al., 2013). Contrasting studies have instead attributed FOXO3 with a proto- oncogenic function in breast cancer cells, whereby its nuclear retention was accompanied by an increase in MMP-9 and -13 expression, and a consequent increased capacity to migrate (Storz et al., 2009).

1.7.3.5 FOXO-FOXM1 in metastasis Metastasis culminates all of the rate limiting steps of cancer progression described previously. Given FOXM1 crucial role in each aspect, governing several signalling pathway simultaneously, it is not surprising that FOXM1 expression can be correlated to the metastasis of different tumours. For instance, FOXM1 expression has been associated with advanced disease and poor clinical outcome in breast (Nestal de Moraes et al., 2015), ovarian (Fan et al., 2015), gastric (Cai et al., 2015), osteosarcoma (Duan et al., 2015), nasopharyngeal (Jiang et al., 2014a), colon (Ju et al., 2015), lung (Li et al., 2012), pancreatic (Li et al., 2014), and hepatocellular (Meng et al., 2015) cancers.

The signalling molecules involved in these aspects vary according to tumour type, and to the level of investigation performed in each type. Furthermore, these often include the same pathways

Page | 63 mentioned above, which control different aspects of cancer progression, as they eventually converge in the promotion of metastasis. Individual studies in breast cancer have isolated XIAP and Survivin (Nestal de Moraes et al., 2015), as well as the cell/mitosis transcriptional regulator TBX2 and Aurora kinase B (Salhia et al., 2014) as FOXM1 effectors contributing to its metastasis. Alternatively, studies in human epithelial ovarian cancers revealed FOXM1 regulates the polo-like kinase 1 (PLK1), aurora kinase B (AURKB), amphiregulin (ARGE), Rho-associated coiled-coil containing protein kinase 1 (ROCK1), plasminogen activator uorkinase (uPA) and its receptor (uPAR) (Fan et al., 2015). The latter had already been described for their role prostate cancer migration. In colorectal carcinoma, the pituitary tumour-transforming gene-1(PTTG1) has emerged as FOXM1 target gene: PTTG1 contributes to tumour invasion, migration and metastasis through the activation of c-Myc, cyclin D3, the basic fibroblast growth factor (bFGF), MMP2 and interleoukin-8 (Zheng et al., 2015).

FOXM1 and ezrin were both correlated to a metastatic phenotype when their expression levels were compared between high and low lymph node metastatic hepatocellular carcinoma cell lines. This study further confirmed FOXM1 regulation of MMP-2 and MMP-9.(Zhang et al., 2015b)

Alternatively, FOXO3 has also been shown to contribute to metastasis. For instance, in breast cancer, FOXO3 has been shown to be inactivated by phosphorylation by the interferon regulatory factor-4 binding protein (IPB), of which expression is generally correlated with malignancy (Chen et al., 2013). Furthermore, in prostate cancer, FOXO3 can inhibit cancer progression, and is inactivated by the astrocyte-elevated gene-1 (AEG-1) through the PI3K-Akt pathway, to permit the advancement of the disease (Kikuno et al., 2007). Β-catenin has also been shown to interfere with the normal tumour suppressor function of FOXO3, whereby elevated nuclear β-catenin levels and concomitant FOXO3 activation can induce colon cancer metastasis(Tenbaum et al., 2012).

1.8 Thesis outline and aims Despite advances in treatment options, breast cancer metastasis remains the primary cause for cancer mortality. This is further hindered by the insurgence of resistance to available therapy, causing disease progression and relapse in patients. It is therefore imperial to understand the molecular basis of cancer metastasis, as well as the morphological and behavioural traits which characterise drug resistant breast cancer cell lines.

In this thesis, I aim to determine if drug resistant breast cancer cell lines are more able to undergo cancer progression than their sensitive counterparts. Furthermore, I intend to analyse the influence of the FOXO-FOXM1 pathway in the promotion or abolition of their metastatic phenotype, to

Page | 64 see if their established role as mediators of the different aspects of cancer progression and insurgence of drug resistance can be applied in this case. Then, I seek to identify novel down- stream effectors of the FOXO-FOXM1 pathway, to facilitate targeting of the axis while limiting toxicity related to its crucial homeostatic cellular functions in healthy tissues. Thus, I hope to discover a new basis linking drug resistance and the development of a metastatic phenotype, as well as novel prognostic markers and drug targets to hinder their progression.

1.9 Thesis hypothesis I hypothesize that breast cancer cell lines which are resistant to paclitaxel and anthracycline chemotherapies will have enhanced migratory, angiogenic, invasive and survival capabilities when compared to their parental sensitive cell lines. I hypothesize that this phenotypical and physical change will be related to their over-expression of FOXM1 and downregulation of FOXO3, two crucial transcription factors which will be inherently upregulated or downregulated to enable the cancer cells to attain essential survival skills, which can allow them to overcome the damage caused by the anti-cancer therapy. I hypothesize that FOXM1-FOXO3 overexpression will have further effects on the cancer cells, and thus regulate the enhanced metastatic abilities developed by these cell lines. I postulate that modifying the expression of FOXM1 and FOXO3 could revert the cancer progression abilities of the resistant cell lines, but that finding a key downstream effectors could effectively inhibit their progression whilst having a more selective approach if administered.

Page | 65

Chapter 2: Materials and Methods

2.1 Cellular culture Human breast cancer cell lines MCF-7 (WT,) MCF-7 Epirubicin Resistant (MCF-7 EpiR), MCF- 7 Paclitaxel Resistant (MCF-7 TaxR), MDA-MB-231 (WT), MDA-MB-231 (EV;empty vector transfected) and MDA-MB-231 shSOX4 cell lines were cultured at a constant temperature of 37.5

°C in Dulbecco’s Modified Eagle’s Medium (DMEM, Sigma, Poole, UK) under a 10% CO2 humidified atmosphere. All media was supplemented with 10% foetal calf serum (FCS, Gibco- BRL, UK), 100 µg/ml penicillin/streptomycin (Sigma-Aldrich) and 4 mM L-glutamine. HMLE WT, HMLE ER:WT and HMLE ER:SOX4 were cultured in Mammary Epithelial Growth Media (MEGM) Bulletkit media (Lonza, c UK) which contained MEBM Basal Medium supplemented with 2.0 ml/0.5 L PBE (Lonza CC-4009G), 0.5 ml/0.5L hEGF (Lonza CC-4017G), 0.5 ml insulin (Lonza CC-4021G), 0.5 ml/0.5 L hydrocortisone (Lonza, CC-4031G), 0.5 ml/0.5 L GA-10000 (Lonza CC-4081G).

MCF-7 EpiR cell lines were established previously by the laboratory via the continuous administration of increasing levels of doxorubicin until the resistance to 17 μM doxorubicin was acquired. Media for MCF-7 EpiR resistant cell lines was supplemented with 17 μM doxorubicin in order to maintain their resistant phenotype. Cellular drug treatments for MCF-7 and MCF-7 EpiR cell lines were performed by adding 1 µM epirubicin (Imperial College Healthcare, UK) to the complete media of the cell lines. MCF-7 TaxR previously established in the lab by gradually exposing MCF-7 WT cells to increasing concentrations of paclitaxel until the cells were able to sustain growth under the administration of 100 µM paclitaxel (Teva UK Limited, East Sussex, UK). MDA-MB-231 EV, MDA-MB-231 shSOX4, HMLE WT, HMLE ER:WT and HMLE ER:SOX4 were kindly provided by Prof. Paul Coffer, University Medical Centre Utrecht, Netherlands (Vervoort et al., 2013).

All MCF-7 derived cell lines and MDA-MB-231 cells were left to grow until the approximate confluency of 75% in adherent cultures. Media was removed by aspiration and cells made to detach with the addition of 1x trypsin-EDTA (Sigma, UK). All HMLE cells are instead washed with the sequential addition of PBS, 1x trypsin-EDTA, PBS and 1x trypsin-EDTA, with each removed before the addition of the next. Two minutes of incubation at 37ºC enable the trypsin to take effect, following which it was inactivated with the addition of the respective complete media. Cells were then collected in a falcon, centrifuged at 1400 rpm, and counted using a haemocytometer and seeded according to experiment.

Page | 66

2.2 Cell line storage Cells were made to disengage from the flask with the addition of trypsin, as described previously. Trypsin was then de-activated through re-suspension in complete media to the flask, following which cells were harvested and centrifuged at 200 x g for 5 minutes to obtain a pellet. This was then re-suspended in 1ml of FCS 10% DMSO and placed in cryotubes, which were then transferred to -80ºC in a freezing container (VWR International) for 24 hours, following which cryovials were kept in liquid nitrogen.

Cells were defrosted by placing desired cryovial in a water-bath pre-heated at ~37ºC until pellet dissolution. Cells were then transferred to a falcon tube for centrifugation at 200 x g for 5 minutes, so as to remove DMSO content from the media. The dry pellet was resuspended in the appropriate fresh supplemented media and placed in the flask according to the instructions on the cryovial.

2.3 Cell culture drugs Paclitaxel, Doxorubicin and Epirubicin were obtained from Imperial College Healthcare, UK (Hammersmith Hospital, East Acton, UK) and kept at 4ºC. Paclitaxel was obtained as a stock solution of 6 mg/ml; Doxorubicin was obtained as 2mg/ml in 0.9% (w/v) sodium chloride; Epirubicin stock solution was of 2 mg/ml 0.9% sodium chloride. Tamoxifen (4-OHT) was instead maintained at -20 ºC and diluted to a stock of 20 mM in absolute ethanol.

2.4 Cellular transfections Gene overexpression was performed with the use of FuGene 6 Reagent according to manufacturer’s instructions. 8 μg of either pCDNA3 FOXM1, pCDNA3 EV, pOBT7 KIF20A, pOBT7 EV, pLPC-FOXO3, pLPC-EV, pCDNA3-HA-SOX4, were transfected per approx.1.7x106 breast cancer cells (MCF-7 WT, MCF-7 EpiR, MCF-7 TaxR according to experiment). RTq-PCR and Western Blotting was utilized to determine transfection success.

2.5 Small interfering RNA transfection All cellular transfections were performed with either 100 nM FOXM1 small interfering RNA (siRNA; Dhamarcon RNA technologies, UK) or 100 nM KIF20A siRNA2 (J-004957-06), or 100 nM ET-1 siRNA (sc-45394, Santa-Cruz Biotechnology Inc., Europe) or the NS (non-silencing) control siRNA, shown to have minimal targeting of known genes (D-001810-10-05). All siRNA were obtained from siRNA SMART- pool reagents purchased from Thermo Scientific Dharmacon (Lafayette, CO, USA). Transient transfections were performed using Oligofectamine Reagent (Invitrogen, Fisher Scientific, USA) reagent according to manufacturer’s instructions. Transfected cells were left to incubate for 48 hours and then viable cells harvested for protein quantification or mRNA extraction.

Page | 67

2.6 Co-transfection For simultaneous transfection of plasmid DNA and siRNA, cells were seeded to obtain 70-90% confluency on day of transfection. A combination of 5 µl Lipofectamin 2000 Reagent (Invitrogen) and 245 µl Opti-mem (Gibco, Thermo Fisher Scientific, UK) was prepared x well of a six-well plate and left to stand for 5 minutes. Simultaneously, 7 µl of DNA (100 ng/µl), 3 µl of siRNA (20 µM), and 240 µl of Opti-mem were mixed. Following the 5 minute incubation, both mixes were combined and left to stand for 20 min at RT. The mix was then added to each well, in media deprived of antibiotics for 6 hours. The media was subsequently replaced with that of regular cellular culture.

2.7 Cellular drug treatment For paclitaxel treatment, 1x106 MCF-7 WT and MCF-7 TaxR cells were seeded in T75 flasks and cultured in DMEM complete with supplements with the exception of paclitaxel for 24 hours. Cells were then treated with 10 nM paclitaxel for individual time-points 0, 8, 16, 24 and 48 hours. For epirubicin treatment, 1x106 MCF-7 WT and MCF-7 EpiR cells were seeded in T75 flasks and left to attach over-night in the appropriate media, with the exception of the lack of epirubicin addition. Each flask was then treated with 1 µM epirubicin for time-points 0, 4, 8, 24 and 48 hours. Each time-point was then harvested as described previously to obtain a dry pellet, which was frozen until mRNA extraction or cell lysis for protein extraction.

2.8 Preparation of total protein lysates Whole protein cell extracts were obtained by harvesting cell lines as described previously. Obtained pellets were centrifuged at 2000 rpm g for 5 minutes and the supernatant discarded. Cell lysis was performed in 2 volumes of NP40 lysis buffer ((1% (v/v) Nonidet P-40, 150mM NaCl2, 50mM Tris-HCl (pH 7.6), 5mM EDTA, 1mM DTT, 1mM NaF, 2mM PMSF, 1mM sodium orthovanadate (Na3VO4) and “Complete” protease inhibitor cocktail), as instructed by the manufacturer (Roche Diagnostics, Burgess Hill, West Sussex, UK) for 10 minutes at 4⁰C. Vortexing and pipetting was employed throughout to facilitate the lysis. The samples were then centrifuged 13000 x g at 4⁰C for 10 minutes and the insoluble lysate material was discarded. Protein concentration was assayed from the supernatant, which was placed in a clean eppendorf prior to measurement.

To determine protein concentration, the Pierce BCA Protein Assay Reagents A and B (Thermo Scientific) was employed according to manufacturer’s instructions. 2 μl of protein solution were combined to 200 μl of a mixture of reagent A and B (1:50 B:A ratio). Subsequent to a 30 min

Page | 68 incubation at 37 ⁰C, absorbance was read at 592 nm. Absorbance readouts were utilized to assay protein concentration according to the equation of absorbance x 25=μg/μl.

2.9 SDS-page gel electrophoresis and Western Blotting Protein separation was obtained by diluting 20 μg of protein lysate to 20 μl of 2xsample buffer (200Mm Tris-HCl pH 6.8, 6% sodium dodecyl sulphate (SDS), 2 mM EDTA, 10% 2- mercaptoethanol, 10 % glycerol, 0.02 % bromophenol blue). To prevent protein denaturation, the solution was heated at 100 ⁰C for 5 minutes and then left to cool prior to loading onto sacking wells. Protein fractionation was performed by SDS-polyacrylamide gel electrophoresis (PAGE) in a Mini-Protean III apparatus (Bio-Rad Laboratories) for 2 hours at 90V in SDS-PAGE Electrophoresis Buffer (25mM Tris base, 250mM glycine, 0.1 % (w/v) SDS). Separated proteins were then transferred onto a 0.45 μm Protran nitrocellulose membrane (Schleicher and Schuell, Whatman, Brentford, UK) in transfer buffer (24 mM Tris base, 193 mM glycine, 20 % (v/v) methanol) for 90 minutes at 90 V at room temperature by using a wet tank blotting system (Bio- Rad laboratories Trans-Blot Cell). Membranes were blocked at room temperature for 30 minutes in 5% (w/v) bovine serum albumin (BSA) in Tris buffered solution with 0.05 % Tween-20 (TBST, pH 7.5). Primary antibody incubation was performed over-night at 4 ⁰C, with antibodies diluted in a 5% BSA-TBST solution. Primary antibodies and respective dilutions used were as follows: FOXM1 (C-20) (Santa-Cruz, SC-502) 1:1000; β-tubulin (Santa-Cruz, H-235) 1:1000; KIF20A (ab104118) 1:2000; KIF2C (SIGMA, WH0011004M1-100UG) 1:2000; PAK4 (Cell Signalling, 3242) 1:1000; N-Cadherin (BD Transduction Laboratories, 610920) 1:2000; E-cadherin (BD Transduction Laboratories, 610182); Lamin-β1 (Santa Cruz Biotechnology, sc-20682); VEGF 1:2000 (Abcam, ab46154), FOXO3 (Millipore, 07-702), pFOXO3 (Thr32) (Cell Signaling, #9464), SOX4 (Diagenode, CS-129-100) 1:3000. Subsequent to incubation in the primary antibodies, excess antibody was removed by washing the membrane 3 times in 50 ml TBS-Tween Buffer pH 7.5 (40 mM Tris-HCl, 300 mM NaCl, 0.05 % (v/v) Tween 20) at room temperature. Membranes were then incubated in their respective secondary anti-bodies (Santa-Cruz Biotech anti-rabbit or anti-mouse) coupled with horseradish peroxidase (Dako, Agilent Technologies, UK) at a 1:5000 dilution for 30 minutes at room temperature. Subsequent to 5 x 10 minutes washes in TBST to remove excess secondary anti-body, membranes were visualized using the ECL detection system (GE Healthcare, Amersham, UK).

2.10 RNA extraction The RNeasy Kit (Qiagen, Crawley, UK) was used to extract total RNA, following manufacturer’s instructions. Samples were harvested to obtain a dry pellet and frozen until the initiation of the

Page | 69 protocol. Pellets were re-suspended in 350 µl buffer RLT 10% β-mercaptoethanol, through vigorous pipetting, following which 350 µl of 70% ethanol were added to the sample. The whole volume was taken and inserted into a spin column contained in a 2 ml collection tube, and centrifuged at 8000 x g for 15 seconds. The ensuing flow-through was removed, and 700 µl of buffer RW1 placed in the RNeasy spin column. Again, the centrifugation was repeated and the flow-through removed. The same process was repeated following the addition of 500 µl of Buffer RPE to the spin-column. Finally, the column was washed with 500 µl of Buffer RPE by centrifugation for 2 minutes at 15000 x g, and the column was placed in a clean collection tube. RNA was eluted by placing 42 µl of DEPC water to the column membrane and centrifuging for 1 minute at 200 x g. Eluted RNA concentration and purity was detected through measurement of the spectrophotometric absorption at 260 nm and 280 nm.

2.11 Real-time Quantitative PCR (RTq-PCR) First strand cDNA was created from 2 µg total RNA though reverse transcription using the Superscript III first strand synthesis system (Invitrogen). An initial mix was prepared containing 1 µl of random primers, 1 µl of 10 mM dNTP mix and 2 µg of total RNA, topped up with RNAse free water to reach a volume of 13 µl. This mix was subjected to denaturing through heating at 65 ºC for 5 minutes, and subsequent incubation on ice for 1 minute. Each mix was then incorporated with 4 µl 5X first strand buffers, 1 µl 0.1 M DTT, 1 µl RNaseOUT and 1 µl Superscript III RT, thus letting it reach a total volume of 20 µl. This was placed in an incubator at 25 ºC for 5 minutes, followed by heating at 50 ºC for 50 minutes and then 70 ºC for 15 minutes. Complementray DNA samples were pooled in equal amounts and then diluted into 4 serial dilutions in RNase free water (1/4, 1/16, 1/64, 1/256) to obtain standard curve points, containing a blank.

Real-time quantitative PCR (RTq-PCR) was performed on 100 ng of cDNA (cell line varied according to experiment) which was added to SYBER-Green Master Mix (Applied BioSystems, Thermo-Fisher Scientific, UK) according to manufacturer’s instructions. Primers were selected to cover an amplicon size of 50-150 bp, so as to span an intron/exon boundary to avoid amplification contamination by genomic DNA. RTq-PCRs were run in 7900 HT Fast Real-time PCR System (Applied BioSystems) on a cycling program of 95 ⁰C for 10 minutes followed by 40 cycles of 95 ⁰C for 3 seconds and 60 ⁰C for 30 seconds. For each sample, three repeats were run and each result was normalized against the detected RNA levels of ribosomal protein L19, an established house-keeping gene. Utilized forward and reverse primers are as listed in appendix 1.

Page | 70

2.12 Primer optimisation Primers were tested to determine the concentration which would enable the highest yield and the lowest unspecific amplification for each cell line. To do this, each primer set was diluted to a range of 50-900 nM, combining different concentrations of forward and reverse primers, and optimized using 10 ng of the selected cell line cDNA. Selected primers presented the lowest Ct value with the standard DNA and highest Ct value with water, and were used in all further experiments.

2.13 Chromatin immunoprecipitation (Chip) Cells were cultured in 10 mm culture dishes until they reached a confluency of 90%. For cross- linking the media was removed and dishes were rinsed with PBS, following which they were subjected to subsequent 1% formaldehyde for 10 minutes at RT, ice-cold PBS rinsing, 5 minute RT incubation with 2.5 M glycine, and 2 ml scrapping buffer (100 mM Tris-HCl, pH 9.4, 01% SDS), the last of which enabled harvesting. In between 5 minutes 13000 x g centrifugation steps, the harvested product was washed sequentially with PBS, Buffer I (0.25 % Triton X-100, 10 mM EDTA, 0.5 nM EGTA, 10 mM HEPES pH 6.5) and Buffer II (200 nM NaCl, 10 mM EDTA, 0.5 mM EGTA. 10 mM HEPES pH 6.5), until it was re-suspended in Lysis Buffer (1% Triton X-100, 2 mM EDTA, 20 mM Tris-HCl pH 8.1) and subjected to sonication at 4º C under optimised conditions (20 minutes, 30 seconds on and 30 seconds off). Following centrifugation, the supernatant was collected and diluted in 300 µl of Buffer D (1% Triton X-100, 2 mM EDTA, 20 mM Tris-HCl pH 8.1, 150 mM NaCl). One hundred µl of the obtained dilution was collected separately and kept at -80º C, to act as the INPUT. Simultaneously, 40 µl Dynabeads Protein A/G were prepared by washing 3 times with 200 µl of TSE I buffer (0.1 % SDS, 1 % Triton X-100, 2 mM EDTA, 20 mM Tris-HCl pH 8.1, 150 mM NaCl), before the addition of 4 µg of an antibody against FOXO3 (06-951, Upstate, Dundee, UK), or 4 µg of rabbit IgG negative control (DAKO, Ely, UK) which had previously been diluted in Buffer D and diluted Dynabeads, for over-night rotation at 4 ºC. The remaining 200µl of the sonicated lysates was mixed with the pre-prepared Dynabeads/antibody dilutions, and rotated over-night at 4 ºC. The obtained mixture was then washed sequentially with TSE I (0.1 % SDS, 1 % Triton X-100, 2 mM EDTA, 20mM Tris-HCl pH8.1, 150 mM NaCl), TE buffer (10 mM Tris-HCl pH 8, 0.1 mM EDTA) and Buffer III (0.25 M LiCl, 1 % NP-40, 1 % deoxycholate, 1 mM EDTA, 10 mM Tris-HCl pH 8.1), before the addition of 100 µl of the elution buffer (0.1 M NaHCO3, 1 % SDS) which was left to rotate for 1 hour at RT. Eluted buffer was collected, and the beads were subjected to a repeated dose of 100µl of elution buffer, and 1 hour rotation and RT. All elution was then pulled together, and the samples made to cross-link by overnight incubation at 65 º C. PCR Purification Kit (Qiagen) was utilised to purify eluted DNA, according to manufacturer’s instructions. Quantification was performed

Page | 71 using RTq-PCR, using the ChiP primers: E-cadherin Forward 5’- GGGTGAAAGAGTGAGACCCC-3’, Reverse 5’-GACCTGGGATCAGAAAGGGC-3’.

2.14 Luciferase reporter assay MCF-7 WT cells were seeded at 10,000 cells per well in a 96-well plate. Transfection was performed via FuGene6 (Roche) with 5 ng/µl CM-Renilla (pRL-TK; Promega, Southampton, UK) luciferase as an internal control and 20 ng/μl of KIF20A PGL3 (KIF20A promoter firefly luciferase) following manufacturer’s instructions. In conjunction, cells were transfected with varying concentrations of FOXM1-pCDNA3 or pCDNA3 empty vector. Concentrations used were 0, 5, 10, 20, 30, 50 and 100 ng/μl. The WT KIF20A and MUT 1 and 2 KIF20A luciferase reporter constructs were created from self-designed gene fragments synthesized by GeneArt (Life Technologies, Darmstadt, Germany). These were then cloned in the XhoI and BglII sites of the pGL3-Basic vector (Promega, Madison, WI, USA).

Cells were harvested following 24 incubation and subjected to LucLite Liminescence Reporter Gene Assay System (Perkin ElmerTM Life Sciences, Coventry, UK), with the addition of coelenterazine (Lux Biotechnology, Edinburgh, UK), following the manufacturer’s instructions. Initially, cells were made to lyse via the addition of 1xLucLite Reagent for 15 minutes at RT. One hundred µl of the obtained lysate was then transferred to a 96-well microplate for measurement of the firefly luciferase activity through the TopCount Luminometer (Perkin ElmerTM Life Sciences). Subsequently, 25 µl of RenLite reagent (Coelenterazine (50 µg/ml) in Renilla Buffer (0.5M HEPES, pH 7.8, 40 mM EDTA) was added to each well, and the plate placed in the dark for 20 minutes at RT prior to measurement of Renilla luciferase activity. Detected firefly luciferase activity was normalized to Renilla luciferase activity. Each condition was performed in six replicates and the assay was repeated 3 times with the statistical analysis performed via Microsoft Excel 2010.

2.15 Transformation and culture of bacteria 1 µl of DNA (<10 ng) was placed on ice for 30 minutes with 20-50 µl of competent cells. Mix was heat-shocked at 42 ºC for 45 seconds and subsequently placed on ice for 2 minutes. Following cellular transformation, the cells were spread on an agar plate pre-treated with the respective selection antibiotic (ampicillin 100 µg/ml or kanamycin 50 µg/ml in water), and left to grow over- night in a humidified incubator at 37 ºC. A single colony was then picked and placed in 250 ml LB broth (Sigma) with the specific selection antibiotic for overnight culture at 37 ºC on a shaker.

Page | 72

2.16 Plasmid mini- and maxi-prep The LB culture grown over-night was subjected to DNA purification using Miniprep Plasmid Purifications Kit (Qiagen), or a Maxiprep Plasmid Purification Kit (Qiagen) according to the desired isolation amount. Both were used according to manufacturer’s instructions.

2.17 Immunofluorescent staining Cells were seeded in four-well chamber culture slides (BD Falcon, Erembodegem, Belgium) at a confluency of 20,000 cells/well. Cells were allowed to grow for 24 hours, following which they were washed three times with cold PBS and fixed in 4 % paraformaldehyde/PBS pH 7.4 at RT for 10 minutes. Paraformaldehyde removed, wells were washed 3 times with PBS for 5 minutes. Cells were then permealised with 0.1% Triton X-100 in 1xsPBS for 10 minutes at RT. PBS washes were repeated three times. To prevent unspecific binding, wells are left at RT for 30 minutes in 1%BSA/1% goat serum/PBS. Blocking buffer was then removed, and the wells covered in the primary antibody anti-α-tubulin (clone DM1A, Sigma-Aldrich) diluted in 1 %BSA/1 % goat serum/PBS solution for 1 hour at RT. Three PBS washes were applied. Desired secondary antibody (Alexa Fluor 555-Conjugated goat anti-rabbit, Invitrogen) was diluted 1/500 in 1 % goat serum/1 %BSA/PBS for 1 hour at RT, taking care to leave the slides in the dark. Following 3 PBS washes, at 5 minutes each, wells were mounted using a drop of DAPI (Invitrogen, 1:1000 dilution in 10% BSA) Vectashield mounting medium (Vector laboratories Inc., Burlingame, CA ). Slides were covered with a glass coverslip, sealed with standard clear nail polish and stored at 4ºC until used. Slides were visualized using a Zeiss confocal laser scanning microscope.

2.18 Cell invasion and migration assays Cell migration assays were performed on 24-well permeable supports with 8 µM pores (Corning) according to the manufacturer’s instructions. According to experiment, cells were pre-transfected to induce the required overexpression or silencing as depicted above. About 24-48 hours subsequent to transfection, cells were harvested and resuspended in serum-deprived media. Approx. 20,000 resuspended cells were then seeded in the Transwell Permeable Support, 8,0 µm polycarbonate membrane, 6.5 mm inserts (Pittsburg Corning, UK). The bottom part of the well was filled with DMEM complete with supplements. After 24-48 hours (according to experiment), cells which had not migrated were removed with the aid of a cotton bud, and the cells which had migrated/invaded were fixed with 4 % PFA in PBS. Inserts containing fixed cells were then washed in PBS to eliminate excess PFA, and then removed with a scalpel, and placed on an imaging slide to stain for 1/1000 DAPI (Invitrogen)/Moviol 4-88 (Sigma-Aldrich) over-night. Migrated cells were then counted with the aid of a fluorescent microscope (EVOS, UK) under the DAPI

Page | 73 filter. For each experiment, cells were seeded in triplicates. In parallel, a sample of each transfected sample was harvested for RTq-PCR analysis to confirm transfection efficiency.

2.19 Wound-healing assay Approx. 500 000 cells were seeded per well in 6-well plates. Cells were transfected with the relative overexpression or silencing protocol according to experiment 24 hours prior to seeding. 24 hours later, when seeded cells reached a <90% confluency resembling a monolayer, each well was scratched vertically with a sterile 200 µl pipette tip (width of approx. 1mm). Wells were washed with PBS to remove cell debris or floating cells, and then cells were placed in serum free medium and incubated at 37º C with 10% CO2 for the duration of the experiment. Wound closure was assessed by taking images at selected time-points (namely 0, 4, 8, and 24 hours) under the bright- field microscope (EVOS Cell Imaging System, Thermo Fisher Scientific). Serum-free media was replaced prior to each imaging procedure. To ensure images were taken of the same location, a permanent marker was used to mark the bottom of the plate at the beginning of the experiment. The degree of cell migration was quantified by comparing the width of the wound at the different time-points (assessed via Image J) to that at time-point 0 to obtain a migration %. For each cellular condition, experiment was performed in triplicates.

2.20 Mammosphere formation assay Selected cell lines were subjected to the desired cellular transfections or treatments according to the experiment, and then harvested subsequent to 24 hours for counting using a haemocytometer. Cells were plated at a density of 500 cells/well in 24-well plate ultra-low attachment surface, flat bottom wells (Corning), with each condition seeded in triplicates. Wells were filled with 2 ml mammosphere media (500 ml MEBM Basal medium (Lonza), 5 ml 100 u/ml penicillin/streptomycin (Sigma-Aldrich) and 5ml 4 mM L-glutamine, 2.5ml of 5µg/ml Insulin, 2.5ml 0.5 µg/ml Hydrocortisone, 100 µl 1µg/ml Heparin, 10 µl 20ng/ml Fibroblast Growth Factor, 10µl 20ng/ml epidermal growth factor and 1ml 50x B27 supplement). Plates were incubated for 5 days at 37ºC in a humidified atmosphere with 10% CO2 to enable spheroid. Mammospheres were then manually counted under the bright-field setting of the EVOSTM Cell Imaging System (Thermo Fisher Scientific, Paisley) microscope, and pictures were taken of the spheroids. Mammosphere size was then measured individually using ImageJ to assess diameter in pixels.

2.21 Sulphorhodamine B (SRB) assay SRB assays were used to determine alterations in cellular proliferations consequent of deviations in gene expressions, and relied on the colorimetric measurement of the bound dye which was

Page | 74 respective to the amount of cellular protein. Assay was performed in 96 well plates, subsequent to cellular transfections, whereby transfected cells were seeded at a density of 3000 cells/well, and left over-night to attach. Having left the desired amount of time to lapse, the cells were fixed using 100 µl of cold 40% (w/v) trichloracetic acid (TCA) for 1 hour at 4ºC. This was then removed by repeated rinsing the plates through slow running tap water, following which 100 µl of SRB solution (0.4% SRB in 0.1 % acetic acid) and left for 1 hour at RT. Unbound dye was removed by sequential washing with 1% acetic acid. Stained plates were allowed to air-dry over-night. Plates were then read through the addition of 100 µL Tris (10 mM) which enabled solubilisation of bound SRB dye following 30 minute rotation, and measured at 492 nm through the Sunrise plate reader (Tecan Group Ltd, Mannendorf, Switzerland).

2.22 Sub-cellular fractionation Subcellular fractionation was performed using the NE-PER Nuclear and Cytoplasmic Extraction Reagents (Perbio, Erembodegem,Belgium). Cells were harvested to obtain a pellet and re- suspended in 200 µl ice-cold CER I solution, complete with protease inhibitors, and subjected to vigorous vortexing at the highest setting for 15 seconds. Samples were then incubated on ice for 10 minutes, following which 11 µl of ice-cold CER II solution were added. Following 5 seconds of vigorous vortexing, the samples were left on ice for 1 minute. The vortexing was then repeated, and the tube centrifuged at 4º C at 13000 x g for 5 minutes. The supernatant was then transferred to a clean, pre-chilled, labelled Eppendorf as the cytoplasmic extract, and the remaining insoluble fraction resuspended in 100 µl ice-cold NER solution, which had been pre-mixed with protease inhibitors. The nuclear mixture was subjected to vigorous vortexing for 15 seconds and incubation on ice for 10 minutes, for a total of 40 minutes. The solution was then centrifuged at maximum speed for 10 minutes, and the supernatant collected in pre-chilled, pre-labelled, clean eppendorfs as the nuclear fraction.

2.23 Zebrafish maintenance Adult zebrafish specimen were kept according to the standard guidelines illustrated in Nüsslein‐ Volhard and Dahm (2002). Fish were upheld in an aquarium containing a self-circulating water system, with the water temperature averaging 28°C and a 14-hours light, 10-hours dark cycle. Adult zebrafish were maintained on a twice a day diet of Hikari micropellets (Kyorin) and brine shrimp.

Zebrafish embryos (1-5 days post fertilisation) were kept at a constant temperature of 28°C in system water (mixture of chlorine deprived tap and distilled water) supplemented with 0.0003% (v/v) methylene blue (antifungal).

Page | 75

2.24 CM-DiI labelling optimisation Each cell line was subjected to Vybrant CM-DiI (Thermo-Fisher Scientific) lipophilic membrane optimisation prior to injections into zebrafish embryos. In each instance, a range of CM-DiI concentrations (1 mM, 5 mM and 7.5 mM) was tested. To do this, the dye was dissolved in DMEM free of solutes. Each cell line was harvested and placed in suspension to which contained the desired Dye concentration in DMEM free of solutes. Approx. 100, 000 cells were used each time. Each DiI concentration was then incubated for 15, 30 or 60 minutes. Cells were then harvested by centrifugation, and the dye suspension discarded. Sequential washing was obtained by alternating pellet resuspension in PBS (Sigma) and centrifugation, to remove excess unbound dye. Cell fluorescence was then verified with Flow cytometry (FACs) analysis using a BD FACSCalibur flor cytometer, and subsequent FlowJo (version 9.3.3) examination. The desired dye concentrations were also tested under the wide-field fluorescent microscope (Olympus CKX41, Southend-on-Sea, UK).

2.25 CM-DiI cell labelling Cells were harvested according to standard protocol to obtain a dry pellet. Pellet was then re- suspended by manual pipetting to ensure pellet dissociation in a 1 ml solution of DMEM free of solutes with 5 µl Vybrant CM-DiI cell labelling solution. Cells were left in incubator at 37ºC and

5% CO2 for 10 minutes, as previously optimised. Cells were then centrifuged and supernatant discarded. The dry pellet was washed sequentially with PBS 3 times to remove unbound dye, with centrifuging sequences in between. Residual PBS was removed by pipetting, leaving a dry fluorescently stained pellet suitable for micro-injection.

2.26 Microinjection of human tumour cell lines At 1 day post-fertilisation, embryos were manually dechorionated. Selected cell lines were then harvested and pre-labelled with CM-DiI, to obtain a dry pellet. Approximately 10 minutes prior to injection, embryos were anaesthetized by placing them in a solution which contained 0.003% tricane (Sigma). Embryos were then placed on an injection mould composed of 3% agarose, in a solution of pre-warmed system water with methylene blue and 0.003% tricane. Injections were performed using a 12 mm gage borosilicate pipette mounted on a Narishige microinjector. All injections were performed in the yolk sac region, with approx. 150-200 cells injected per embryo. Approx. 30 embryos were injected x cell line. All injections were completed within a 1 hour time- frame, after which embryos were replaced in a clean solution of system water and MB and kept in an incubator at 28°C for the duration of the experiment.

Page | 76

2.27 Zebrafish embryo live imaging According to experiment, injected embryos were left to incubate for 2 or 3 days prior to image. Injected embryos were individually imaged under a wide-field fluorescent microscope (Olympus CKX41) in a solution of system water and 0.05% tricaine, to impede embryos movement during live imaging procedures. All pictures were captured using Q Capture-Pro (QImaging), with any modifications to the original image performed using ImageJ Software.

2.28 Statistical and data analysis All data analysis was performed with Microsoft Excel 2010 or Graphpad Prism. Results were reported as means (average value) and standard deviations to measure variability. Averages and standard deviations were calculated using Microsoft Excel 2010. Statistical analysis was performed using ANOVA or Student t-test according to experiment. Student t-test was performed using Microsoft Excel 2010 and ANOVA tests were performed using Prism 4. For the purpose of this study, a 2-tailed with a two-sample unequal variance distribution was assumed. For the ANOVA analysis, one-way ANOVA was performed to determine the statistical significance between the mean of 3 independent groups. The latter was coupled with Bonferroni correction, to compensate for the errors arising from multiple comparisons. P values of less than 0.05 were considered significant.

Page | 77

Chapter 3: Results

Chapter 3.1: The cancer progression of drug resistant cell lines Despite recent advances in the treatment of breast cancer, its effective eradication is often hindered by the insurgence of resistance to the most commonly administered anti-cancer therapies. Chemotherapeutic strategies principally target rapidly proliferating cells of tumours of primarily epithelial nature. Despite their effectiveness in debulking the primary tumour mass, these generally fail at eradicating the disease (Dylla et al., 2008). Statistical analysis has correlated 10% of new breast cancer diagnosis with advanced or metastatic diseases, whereas up to 50% of early stage cases eventually progress to a metastatic state, regardless of the administration of chemotherapy or adjuvant therapy. Tumours positive for the ER are treated with ER modulators, aromatase inhibitors or oestrogen-receptor down-regulators. Popular targeted therapies include the antibody trastuzumab, which has displayed efficiency against HER2-positive tumours, in combination with cytotoxic drugs such as taxanes. Metastatic breast cancer (MBC) remains especially difficult to treat, with modest improvement in the survival rate despite the evolution from anthracycline, to taxanes, to a combination of chemotherapy and targeted therapy (Coley, 2008). Currently, chemotherapy remains the primary therapeutic strategy to overcome MBC, with its effectiveness often hindered by the insurgence of resistance(Gralow, 2005).

Of all available treatments, the sequential administration of anthracycline-based chemotherapy, followed by that of taxanes upon the insurgence of resistance to the first, has displayed particular effectiveness (Lister-Sharp et al., 2000). Anthracyclines, such as epirubicin, are a class of antibiotics which display effectiveness against cancers. Their function is mediated through their interference with enzymes involved in DNA replication, such as topoisomerase II, coupled with the creation of DNA damage and intercalation. This ultimately leads to the development of DNA lesions primarily in the form of double-stranded breaks. Defective DNA damage response causes these lesions to ultimately result in cell death or senescence (Khongkow et al., 2013b). Taxanes are a class of anti-cancer chemotherapeutics which function primarily through the disruption of microtubule dynamics during mitosis: these drugs prevent microtubule depolymerisation by stabilizing the GDP-bound tubulin, effectively disrupting cytokinesis (Khongkow et al., 2015a). Commonly used taxanes for the treatment of solid tumours include paclitaxel and docetaxel. Despite the marginal effectiveness of sequential treatment with anthracyclines and taxanes, response rates to first-line chemotherapy range between 30-70%, with disease progression occurring after 6-10 months (Bonneterre et al., 2004; Vassilomanolakis et al., 2005). Following this

Page | 78 period, response to chemotherapeutic administration falls to 20-30%, with a median response duration of 6 months (Coley, 2008). Inevitably, repeated use of either drug results in lack of responsiveness, leaving the patient with very limited options to combat the MBC further. Understanding the mechanism behind the insurgence of drug resistance and its correlation to a tumour’s metastatic state is therefore essential to generate novel therapies for the treatment of metastatic breast cancer.

So far, the presence of BCSC has been the only established reason behind cancer relapse and drug resistance (Dean et al., 2005), with studies claiming that chemotherapy treatments actively enriches cancer stem cells. Notably, samples attained from first-degree patients displayed a 14-fold increase in mammosphere formation when these were treated with chemotherapy, compared to chemotherapy-naïve samples. In vivo sequential passaging of a breast cancer cell line SKBR3 in nude mice with or without chemotherapy, confirmed these findings upon mammosphere culturing. Again, cells derived from non-treated mice produced significantly fewer mammospheres (Yu et al., 2007). Another study instead correlates the BCSCs phenotype with increased expression of the adenosine triphosphate (ATP) binding cassette (ABC) transporters, which would enable them to efflux drugs, thus rendering them immune to their effect. Alternatively, the inefficiency of chemotherapeutics for the eradication of cancer stem cells has been blamed on the fact that most chemotherapies target cell division, and cancer stem cells remain primarily in the resting stage of the cell cycle (Dean et al., 2005; Zhang et al., 2012b). It remains, however, unclear whether the properties exhibited by cancer stem cells are attained upon their formation, or whether they are gradually acquired during earlier cancer progression steps, such as EMT (Gangopadhyay et al., 2013).

Generally, studies have focused singularly on the properties of cancer stem cells, and how these alone can promote drug immunity, or tumour relapse. No study has analysed the cancer progression abilities of drug resistant cell lines. Instead, I aim to determine what happens to the cancer progression properties of breast cancer cells during the gradual acquisition of drug resistance, so as to determine if the insurgence of drug resistance could be a precursor of the various abilities that promote cancer progression, rather than a consequence. By understanding if the two processes are co-dependent, I

Page | 79

Figure 3.1.1 Drug resistant cell lines have lost the epithelial markers. MCF-7 WT, EpiR and TaxR cells were subjected to: A) Western-Blot analysis to measure variations in E-cadherin expression levels; B) RTq-PCR to compare expression of E-cadherin and N-cadherin, normalised to L19; C) Bright-field microscope photography to analyse physical variations. Data shown in Figure 3.1.1B are mean and SD of n=2 independent experiments (3 replicates each). Data shown in Figure 3.1.1A are representative images of n=2 independent experiments.

Page | 80 can start to unravel the molecular pathway responsible for both alterations, so as to revert both phenotypes simultaneously, thus providing effective means to combat MBC.

3.1.1: Epirubicin and paclitaxel resistant breast cancer cell lines display acquired mesenchymal characteristics. Individual studies have reported how characteristics such as increased proportion of cancer stem cells, or heightened abilities to metastasize, often coincided with the insurgence of resistance to chemotherapeutic drugs. In this report, I used epirubicin and paclitaxel resistant breast cancer cell lines previously developed in the laboratory (Khongkow et al., 2013a; Lara et al., 2011), to determine whether the capacity of a cell line to resist to the effect of chemotherapeutic drugs alone could enable it to advance in cancer progression, or if, instead, the insurgence of drug resistance is a consequence of the presence of a bigger cancer stem cell population, or a more metastatic phenotype. To do this, the epirubicin resistant MCF-7 EpiR cell line, and the paclitaxel resistant MCF-7 TaxR cell line, were subjected to physiological and molecular analysis to gauge their despondence towards cancer progression. In each instance, their capabilities were compared with each other, and with their parental MCF-7 WT cell line, from which these cells were initially created. Assessments were made on their expression of epithelial or mesenchymal phenotypes, their migratory, and stemness properties, as well as an in vivo assessment of their angiogenic and metastatic capabilities. Overall, these individual evaluations allowed me to assess if these cancers were capable of progressing to a metastatic state.

Initially, parental MCF-7 WT, as well as the derived epirubicin resistant (MCF-7 EpiR) and paclitaxel resistant (MCF-7 TaxR) cell lines were subjected to analysis to determine their epithelial/mesenchymal characteristics, so as to define the phenotypical effect of the acquisition of drug resistance. Typically, the process of EMT is elicited through external signalling, in the form of collagen or fibroblast, epidermal or platelet-derived growth factors. EMT causes cells to lose their apical polarity and cell-cell junctions, as well as to attain a more spindle-like morphology through cytoskeleton re-organisation, the up-regulation of mesenchymal markers (e.g. N-cadherin, Vimentin) and the down-regulation of epithelial markers (e.g. E-cadherin) (Gangopadhyay et al., 2013). Overall, the acquisition of mesenchymal characteristics enables cells to migrate to and invade nearby tissues and vasculature, rendering EMT a rate-limiting step in the cancer progression to a metastatic state. Characteristic markers used to assess whether a cell line exhibits an epithelial or mesenchymal phenotype include E-cadherin, β-catenin and N-cadherin and Vimentin, respectively. All cadherins are calcium dependent adhesion molecules which belong to class 1-type of transmembrane proteins. Epithelial-cadherin (E-cadherin, a.k.a. CDH1, Cam 120/80, or

Page | 81 cadherin-1) is a calcium-dependent adhesion molecule, crucial for the formation of adherens junctions and for the creation of catenin-dependent complexes that connect E-cadherin to the actin and microtubule cytoskeleton (Perez-Moreno et al., 2003). As E-cadherin, Neural-cadherin (N-cadherin, a.k.a. CDH2, cadherin-2, CD 325) is a transmembrane protein which mediates calcium dependent cellular adhesion. Unlike E-cadherin, the latter provides a mechanism for transendothelial cell migration, enabling cancer cells to infiltrate the vasculature.

To assess the phenotype of the parental MCF-7 WT and derived MCF-7 EpiR and MCF-7 TaxR cell lines, these were harvested individually and subdivided into two, to simultaneously analyse for protein and mRNA expression via Western-blotting and real-time Quantitative PCR (RTq-PCR) respectively. Additionally, pictures were taken through a bright-field microscope, to visually assess the morphological differences between the cell lines. As seen in Figure 1.1A, both MCF-7 EpiR and MCF-7 TaxR cell lines lacked in protein expression of the epithelial E-cadherin marker. Contrarily, E-cadherin was highly expressed in MCF-7 WT cell lines. Figure 1.1B displays how consistent with the protein expression levels, both resistant cell lines had lost all mRNA expression of epithelial E-cadherin markers, while their parental MCF-7 WT cells displayed a clear, strong E- cadherin expression. Instead, resistant cell lines displayed a strong expression of the mesenchymal markers N-cadherin and Vimentin. The latter two mesenchymal markers were instead absent in the parental MCF-7 WT cells. These results imply that upon the acquisition of drug resistance, MCF-7 EpiR and MCF-7 TaxR undergo the cadherin switch, characterised by the loss of the E- cadherin marker and acquisition typical mesenchymal markers N-cadherin and Vimentin.

Evidence of the cadherin switch implied that the resistant cell lines might have undergone EMT. If this was true, these cells should present physiological alterations such as a spindle/more elongated shape, with loss of cell-cell contacts. These would thus be visually comparable to established mesenchymal breast cancer cell lines, such as the triple-negative MDA-MB-231 cells. In contrast, the parental MCF-7 WT, consistent with their clear E-cadherin expression, should display a more rounded appearance, completed with multiple cell-cell contacts, and a clustered colony formation. For physiological analysis, the cells were seeded at a low confluency and analysed under the bright-field microscope. Surprisingly, the acquisition of the mesenchymal markers did not grant either of the resistant cell lines the characteristic elongated shape, nor the lack of adherence when forming colonies (Fig. 1.1C). Instead, these cell lines displayed a more rounded shape, which was more consistent with their parental MCF-7 cells. Furthermore, MCF-7 EpiR and MCF-7 TaxR displayed a characteristic colony growing pattern, which no loss in cellular adhesions. Alternatively, the MCF-7 WT cells presented a rounded shape, with regular cellular adhesions, consistent with their E-cadherin expression.

Page | 82

The lack of physiological changes in the cellular shape and growing pattern of the drug resistant MCF-7 EpiR and MCF-7 TaxR suggested that perhaps the cells had not undergone full EMT. However, their clear cadherin switch implied there was a clear morphological change from the MCF-7 WT cells. Next, I attempted to determine if the apparent endogenous changes were sufficient to grant the resistant cell lines increased migratory abilities, a trait characteristic of mesenchymal cells.

3.1.2: Anthracycline and taxane resistant cell lines have significantly higher migratory abilities in vitro compared to the sensitive counter-parts. Cell migration is a crucial event essential for the survival of multicellular organisms. It is employed in healthy individuals not only during development, but also in wound-repair and processes of immune surveillance. In pathological instances, migration is crucial for tumour neoangiogenesis and metastasis (Honore et al., 2005). The acquisition of increased migration capabilities would therefore imply a cancer cell line would be more prone to undergo successful tumour metastasis.

To assess the in vitro migratory abilities of the parental MCF-7 and drug resistant MCF-7 EpiR and MCF-7 TaxR cell lines, a Boyden Chamber assay was used. Structurally, Boyden Chambers are constituted of two individual chambers, separated by a porous membrane. Cells are seeded on the top chamber in their typical media devoid of all nutrients; the bottom chamber instead contains the respective media complete with supplements. The aim is for the supplements to act as chemo- attractants, instigating the cells to traverse the membrane to reach the bottom chamber. However, only cells with migration abilities are able to pass through the membrane. Following a time period of 24 hours, membranes are fixed in 4% paraformaldehyde (PFA), and the bottom side of the membrane stained with DAPI, so as to detect the migrated cells. These are then quantified by taking multiple images x well under the fluorescent microscope, and the number of migrated cells counted in each instance with the aid of the ImageJ software. To obtain fold-change in migration, obtained numbers are made relative to the control group. In this case, the control group was represented by the parental MCF-7 WT cells.

Page | 83

Figure 3.1.2 Both epirubicin and paclitaxel resistant MCF-7 cell lines are more able to migrate than their sensitive counterparts. MCF-7 WT, MCF-7 EpiR and MCF-7 TaxR cells were counted and seeded in equal numbers in the top compartment of Boyden Chamber Assay in serum-free media. Media complete with serum was placed in the lower compartment, acting as a chemo-attractant so cells would be prompted to traverse the membrane. Cells were allowed to migrate for 24 hours, and then fixed and stained with DAPI. Migrated cells were then quantified with the use of a fluorescent microscope. A) Number of migrated resistant cells was counted and made relative to that of the sensitive MCF-7 WT cells; Student t-test was performed to determine statistical significance with P<0.05 = * ; P<0.01= ** ; P<0.001=***; P<0.0001=**** B) Representative images of migrated cells. Migrated cells are depicted as black dots. Black line denotes 100 µm. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 84

Figure 1.2 A-B displays the resulting relative migration, comparing the migration pattern of MCF- 7 WT, EpiR and TaxR cells. As shown by the bar-chart (Fig. 1.2A), MCF-7 EpiR displayed a significant increase in fold-migration, consisting of a 3.4-fold ±1.1 rise compared to the MCF-7 WT cells (1±0.38). Alternatively, the MCF-7 TaxR displayed a massive significant increase in fold- migration of 66.59-fold ±7.55 compared to the parental cell line, which was 63.19-fold higher than that displayed by the MCF-7 EpiR cells. This difference was clearly visible even without quantification by comparing the representative images of individual migration patterns (Fig. 1.2 B). These results indicated that despite the lack of physiological attributes typical of mesenchymal cells, both resistant cell lines had in fact undergone a molecular shift which allowed them to increase their migratory abilities in a significant, and, in the case of the MCF-7 TaxR, drastic manner.

Increased migratory capabilities implied there might be other behavioural alterations present upon the insurgence of drug resistance for the MCF-7 EpiR and TaxR cells. I next investigated whether the acquisition of drug resistance was also able to influence the stem cell-like population of these cell lines.

3.1.3: Drug resistant MCF-7 cells display increased stem-like cell populations. Recent evidence has highlighted the importance of cancer stem cells as a cause of resistance to anti-cancer therapies, such as endocrine therapy (Bergamaschi et al., 2014), cyclophosphamide and Irinotecan (Dylla et al., 2008), and a standard range of neo-adjuvant chemotherapy (Yu et al., 2007). Cancer stem cells (CSCs) are a sub-population of cancer cells which are characteristic for their stem-like properties, granting tumours self-renewal properties through the capacity to give rise to differentiated tumour cells, with unlimited propagation and multi-potent differentiation (Bergamaschi et al., 2014). Evidence suggests that drug resistant CSCs may not only be the source of solid tumours, but also the cause for tumour recurrence, metastasis and disease progression (Wang et al., 2014).

Given the established relationship between CSC and resistance to anti-cancer drug and irradiation, I used the epirubicin and paclitaxel resistant cell lines to determine whether their ability to resist drug could be a precursor to the development of the stem-like characteristics, rather than its consequence. To do this, I cultured parental MCF-7 WT and the resistant MCF-7 EpiR and TaxR cells in non-adherent non-differentiated culture conditions to measure their mammosphere formation capacity. Cells capable of survival and proliferation in non-adherent conditions form cell clusters which have been termed ‘mammospheres’. Cellular analysis of these spheroid colonies

Page | 85 displays high enrichment of progenitor cells, with the capacity to differentiate across multiple lineages (in the case of BCSCs, these included luminal, myoepithelial, and alveolar). These cells also present the characteristic CD44high;CD24low markers, which are typically used to sort for the cancer stem cell population using flow-cytometry (Wang et al., 2014). Due to the ambivalence of both techniques, I deemed the mammosphere assay sufficient to analyse the cancer stem cell population of my cell lines.

To study alterations in the mammosphere formation capacity upon the insurgence of drug resistance, parental MCF-7 WT, and derived MCF-7 EpiR and TaxR were seeded in equal numbers in non-adherent culture conditions, in the apposite media. Spheroids were left to grow for five days, following which the number of mammospheres was counted manually under the bright-field microscope. For analytical purposes, obtained numbers were made relative to the control, in this case MCF-7 WT, to achieve a value fir relative mammosphere formation. As shown in Figure 1.3A, MCF EpiR displayed a significant 0.46±0.19 (p=0.05) fold-increment in the mammosphere formation compared to the sensitive counter-parts (1±0.03). Consistent with the migration assay results, the MCF-7 TaxR also showed a significant massive increment in the mammosphere formation ability (2.87±0.17), which was significantly increased in respect to both MCF-7 WT (p=0.002) and MCF-7 EpiR cells (p=0.0007). In the latter case, the MCF-7 TaxR cells presented a quasi-3-fold increment relatively to the parental MCF-7 WT cells.

During imaging, pictures were taken of the formed mammospheres in order to examine any alterations in the size of the spheroids, with representative images displayed in Figure 1.3C. The diameters of individual mammospheres were measured using ImageJ, and plotted in a dot-plot (Figure 1.3B), with every dot representing the diameter, in pixels, of an individual mammosphere. As shown in Figure 1.3B, there was a gradual significant increase in the average mammosphere diameter between MCF-7 WT (60.59±33.75), MCF-7 EpiR (140.5±60.42) and MCF-7 TaxR (181.716±72.94) cells, with the smallest mammospheres being that of the parental cell line, and the largest being of the paclitaxel resistant derived cell line. Statistical comparison via non- parametric analysis of variance (ANOVA) displayed statistical significance between each pair, with WT vs EpiR p= 9.69 E-11; WT vs TaxR p=1.73 E-25; and EpiR vs TaxR p=0.001. Again, these results were consistent with both the migratory pattern and the relative mammosphere formation frequency.

Overall, the mammosphere assay displayed that MCF-7 cell lines acquire distinct properties upon their development of drug resistance, namely increased propensity to form stem cell clusters, a

Page | 86 trait which can not only grant them self-renewal, but also unlimited propagation and multi-potent differentiation.

These are essential qualities which can single-handedly enable a tumour to metastasize. Given the resistant cell lines acquisition of higher migratory abilities and increased stem-cell like characteristics, I next analysed whether they had also acquired the ability to induce neoangiogenesis, another essential trait in cancer progression.

Page | 87

Figure 3.1.3 Epirubicin and paclitaxel drug resistant cell lines have higher cancer stem cells properties than their sensitive counterparts. MCF-7 WT, EpiR and TaxR cells were seeded in equal numbers in non-adherent culture plates and left to grow for 5 days. Spheroid formations were deemed representative on mammospheres and were counted under the bright-field microscope. A) Bar-chart comparing the number of mammospheres between the sensitive and resistant cell lines. Relative mammosphere formation was calculated by making all numbers relative to those quantified with the MCF-7 WT cell line, so as to obtain a fold-increase. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; P<0.0001=**** B) Dot-plot representing the diameter of each mammosphere (measured via ImageJ). Non-parametric ANOVA was used to test the significance of the result with P<0.05 = *; P<0.01= **; P<0.001=***. C) Representative images of mammospheres formed after 5 days in non-adherent plates. White line denotes 400 µm. Data shown are mean and SD of n=3 independent experiments (3 replicates each).

Page | 88

3.1.4: Drug resistant cell lines can induce more neoangiogenesis in vivo. Tumour induced angiogenesis is a rate limiting step in the progression of any tumour. In order to ensure their survival, cells depend upon an adequate supply of oxygen and nutrients, as well as effective waste disposal (Gimbrone, 1997). Generally, oxygen can only diffuse from capillaries to a distance of 150-200 mm, causing the growing tumour mass to rely on its proximity to the blood vessels. Without effective vascularisation, a tumour will be unable to grow beyond the size of 1 mm3 in volume and will instead enter a state of dormancy (Fidler, 2002). To attain adequate irrigation, tumours trigger the process of neoangiogenesis. At a cellular level, angiogenesis consists of the proliferation and migration of local endothelial cells, to initiate the remodelling of the nascent vessel, which could involve the deletion, development or subdivision of the existing vessel (Childs et al., 2002). Tumour-induced angiogenesis is mediated by the release of angiogenic factors secreted by the tumour, such as the VEGF, which stimulate nearby blood vessels to grow towards the proximity of a tumour until irrigation is achieved. The balance of the secretion of pro- angiogenic factors by the tumour and host cells with the lack of anti-angiogenic factors is essential for the creation of an established vascular network between for both the tumour and the surrounding stroma (Fidler, 2002). Unfortunately, due to the tumour uncontrolled growth, the sporadic secretion of growth factors results in the irregular growth of blood vessels. A tumour will be irrigated with an irregular blood flow, coupled with regions of hypoxia. Furthermore, the blood vessel walls will be incomplete in areas, thus facilitating potential cellular invasion in the initial stages of cancer progression.

For the study of tumour induced angiogenesis, several in vitro models have been developed. These generally focus on the analysis of endothelial cell of behaviour, to review the various stages in the angiogenic process. However, these only allow examination of singular processes individually (Chávez et al., 2016). To gain an overview of angiogenesis within an organism, studies have resorted to the use of in vivo models, as they can incorporate all cellular and molecular events. Despite their wide-spread use, available murine models present limited information, namely due to the restrictions of the existing imaging modalities. The most reliable manner to visualise tumour- induced angiogenesis in murine model is based on histological microscopy subsequent to immunohistochemical staining. This allows for the quantification of capillary density (Fallis, 2013). However, the animals always have to be sacrificed to access the tissue of interest. Mainly due to this, general opinion deems the murine models unreliable for the generation of pre-clinical cancer models with the benefits of anti-angiogenic treatments been to date unsatisfactory (Eklund et al., 2013). Furthermore, use of murine models is restricted by strict guidelines and ethical concerns.

Page | 89

The generation of faster, cheaper and more accessible in vivo models for the study of tumour induced angiogenesis is therefore essential.

In this thesis, I developed the novel in vivo zebrafish embryo model for the study of tumour induced angiogenesis, based on the previous zebrafish models available in the literature. Although zebrafish embryos have only been used as in vivo models for the last few years, they offer numerous advantages compared to other available in vivo models. For instance zebrafish larvae develop quickly, reaching full sexual maturity at 3 months. Furthermore, they produce a large progeny and are able to reproduce weekly, with the larvae offering easy genetic manipulation. Off-spring do not develop skin pigmentation for the first week of their life, simplifying the larvae imaging without the need to cull the animal. Zebrafish embryos are particularly apt for the study of the cardiovascular system, as this develops early, and can easily be tracked using transgenic zebrafish lines presenting intrinsic fluorescent labelling of the cells of interest. Furthermore, a drug of interest can be simply added to the fish water, and this will be passively absorbed by the embryo, facilitating the high-throughput screening of compounds. Zebrafish can also be kept in high numbers in relatively small places, making this model advantageous economically. Finally, zebrafish embryos are not classified as living beings until 5 days post-fertilisation (5 dpf) by the Animals Scientific Procedures Act of 1986, a date by which most experiments will be completed. Genetic studies have confirmed the conservation of molecular pathway between mammals and teleosts, making any findings in the fish directly translatable into useful data for the development of therapies in humans (Chávez et al., 2016).

For the study of tumour-related processes, zebrafish embryos offer further benefits. For instance, they do not develop an adaptive immune system until 30 days post-fertilisation (dpf), and do not present a fully developed innate immune system for the duration of the experiment. This prevents the need to create immunocompromised individuals, or of irradiation to annul the functionality of existing immune cells. Desired cancer cells can be easily labelled fluorescently prior to insertion into the embryos, either intrinsically or via the use of fluorescent membrane dyes. This enables their visualisation post-injection into the embryo via the use of a fluorescent microscope. In this thesis, I performed all implantation of tumour cells in the yolk sac of 1 day post-fertilisation embryos (1 dpf). Embryos present large yolk sacs at that stage of their development, as it provides a source of nourishment for the larvae for its first 5 days of life, and I hypothesized it could be used as a source of nourishment for the implanted cells, as well as a means of compartmentalisation. Desired cancer cells were implanted using a standard micro-injector and a glass capillary needle. These were fluorescently labelled using a lipophilic membrane dye prior to injection.

Page | 90

For the study of tumour-induced angiogenesis, I used a zebrafish transgenic fish line which presented intrinsically green-fluorescent protein (GFP)-labelled blood vessels: Tg(fli:GFP). This allowed the monitoring of any structural changes in the embryos vasculature following the injection of the tumour cells. In particular, I monitored the development of the sub-intestinal vessel (SIV) structure, which is localised in the embryos yolk sac, in proximity of the location of cancer cell injection. The zebrafish vasculature originates at the 13 somite stage, where endothelial cell precursors migrate from the lateral mesoderm, creating a single circulatory loop by 24 dpf. The embryos vasculature then branches out from the trunk which contains a single artery and a vein. The SIV sprouts from the artery, specifically from the Duct of Cuvier, at the 2 day post fertilisation (dpf) (Figure 1.4). During the next 48 hours (3-4 dpf) the SIV forms a vascular plexus which covers most of the dorsal and lateral aspects of the yolk sac. This will later irrigate the embryos digestive system (Nicoli and Presta, 2007). In general, zebrafish embryos require the VEGF for the correct development of the SIV, as zebrafish lacking VEGF do not develop the SIV (Childs et al., 2002). For the study of tumour induced angiogenesis, injected embryos were imaged under the fluorescent microscope at 2 days post injection (dpi), which correspond to 3 dpf of the embryo. At 3 dpf, the SIV structure will be composed of a down-ward facing ‘D’, with radial blood vessels connecting the two main segments (Fig. 1.4). It is important to note that at no stage in the embryos development are protrusions extending from the SIV, with its structure remaining contained within its backbone shaped like a ‘D’. In my model, the angiogenic growth factors released from the injected cells altered the formation of the SIV, causing it to display protrusions extending from the SIV towards the implanted cells. Presence of these protrusions were taken to be a sign of tumour induced angiogenesis. In each instance, the development of the SIV was also monitored in non-injected embryos, to account for any natural-occurring variations in its structure.

Following cancer cell injection, tumour-induced angiogenesis was monitored in two ways: by counting the number of sprouting blood vessels extending from the SIV in individual injected embryos and by

Page | 91

Figure 3.1.4 Development of the SIV complex in zebrafish embryos. Diagram depicting the location and development of the SIV complex in zebrafish embryos from 1-4 days post- fertilization (dpf). Top figure displaying the structure of a zebrafish embryo, with the location of the dorsal aorta in dark red and the cardinal vein in light blue. Gradual development of the SIV can be seen in yellow diagrams focusing on the yolk-sac region on subsequent days. Structure of the SIV on each day can be seen in green. Note how at 4dpf, SIV detaches it-self slightly from the lining of the yolk-sac and becomes more intricate, while still lacking the presence of protrusions extending from its structure.

Page | 92 calculating the percentage of embryos presenting any form of angiogenesis. To account for natural variations in the SIV structure, the obtained numbers were made relative to the sprouting detected in non-injected control embryos. For the percentage calculations, an embryo was only incorporated in the study when it presented a number of sprouting blood vessels which was higher than that noted in the control non-injected embryos. Control embryos generally had an average of less than 1 protruding blood vessels.

To determine if the drug resistant cell lines presented an increased ability to induce angiogenesis, the parental MCF-7 WT cells and the derived drug resistant MCF-7 EpiR and TaxR cell lines were harvested individually and injected into the yolk sac of 1dpf Tg(fli:GFP). Prior to injection, the cells were stained with lipophilic membrane dye DiI (Sigma), to grant them a fluorescent red labelling which would distinguish them from the GFP-labelled blood vessels following their injection. Injected embryos were then placed in the incubator at 28ºC, the optimal temperature for zebrafish development. Previous studies allowed me to ascertain that this temperature sustained the survival of the injected tumour cells and did not affect their angiogenic potential. The injected embryos were left in the incubator for 48 hours, following which these were anesthetised and imaged individually under a standard fluorescent microscope. Tumour induced angiogenesis was quantified as described above.

Figure 1.5 C shows a diagram depicting the location of tumour cell injection (asterisk) and the general structure of a 3 day post injection (dpi) embryo. For the study of tumour-induced angiogenesis, all subsequent pictures were taken of the area highlighted by a blue box in the diagram. As shown in Figure 1.5A and C, MCF-7 WT induced an average number of blood vessels of 0.92 with numbers varying from 0 to 3 (1 case only), while MCF-7 EpiR had a significantly higher (p=0.038) average induction of 1.67 sprouting blood vessels per injected embryos (varying from 0 to 5). As in every other assay, MCF-7 TaxR exhibited the highest average number of sprouting blood vessels per injected embryos: these exhibited a significantly higher 2.32 (p=0.0004) sprouting blood vessels per embryo. As seen in Figure 1.5D, non-injected embryos presented a SIV lacking any vascular protrusions extending from its structure. When the percentage of injected embryos was calculated x cell line, both EpiR and TaxR presented a respective 84.72±9.8% and 86.25±11.99% compared to MCF-7 WT presenting an average 58.53±8.04% (Figure 1.5B). Albeit higher, this difference was not significant due to lack of experimental replicates.

Page | 93

Figure 3.1.5 Drug resistant cell lines induce more angiogenesis than their sensitive counterparts. Approx. 150 DiI-stained MCF-7 WT, EpiR or TaxR were injected into the yolk-sac of 1dpf Tg(fli:GFP) zebrafish embryos. Injected embryos were imaged under the fluorescent microscope 2dpi, to detect presence of sprouting blood vessels from the SIV complex, located in proximity to the injected cell lines. Any sprouting towards the implanted tumour was considered to be representative of tumour induced angiogenesis. A) Dot-plot depicting the number of sprouting blood vessels from individual injected embryos; Non-parametric ANOVA was used to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Bar-chart displaying the total percentage of injected embryos presenting any form of angiogenesis; C) Schematic diagram depicting the location of the SIV structure (green) and the area depicted in the images (light-blue square). Location of tumour injection has been high-lighted with an asterisk. D) Representative SIV structure of a 3dpf non-injected zebrafish embryo (green). Note the lack of protrusions extending from its structure. E) Representative images of 2dpi embryos following injection of sensitive and drug resistant MCF-7 cell lines. Sprouting blood vessels (green) have been highlighted by white arrows. Injected tumours are highlighted in red. Data shown are mean and SD of n=2 independent experiments (25 replicates each).

Page | 94

Overall, these results indicated that as in every other in vitro assay, drug resistant MCF-7 EpiR and TaxR cell lines have also acquired increased angiogenic abilities upon their becoming drug resistance. As tumour-induced angiogenesis is a rate-limiting step in the cancer progression of a tumour, I hypothesized that this result would entail that these cells also had a higher metastatic potential than their sensitive counter-parts. Combined with their increased migratory and stem cell properties, and their mesenchymal phenotype, these cells displayed all the characteristics that would enable them to successfully metastasize in vivo. To see if this was the case, I employed the zebrafish embryo model and used it to assess tumour metastasis in vivo.

3.1.5: Epirubicin and paclitaxel resistant MCF-7 cells are able to metastasize in vivo in zebrafish embryos. Cancer progression encompasses all the sequential, interrelated and selective steps which are rate- limiting for the creation of clinically relevant metastatic lesions. Essential is to first attain successful vascularisation of the tumour, following which cancer cells need to invade the organ stroma to reach and penetrate the lymphatic or vascular systems, and then access the circulation. Circulating tumour cells then need to survive immune and non-immune defences, as well as the turmoil of life in the circulation, in order to eventually extravasate in a selected organs parenchyma, and proliferate in receptive organs. Successfully metastasis is classified as the re-establishment of a tumour at sites which differ from its organ of origin (Fidler, 2002).

It is believed that the primary reason behind the failure of eradication of metastasis is the inability to properly encompass the biological heterogeneity of both primary neoplasms and consequent metastases in the treatment options. Furthermore, systematic therapy can also affect the tumour stroma, and its response alter the tumours reaction to the treatment. When devising new anti- cancer drugs, or elucidating the science behind cancer metastasis, it is therefore imperative to incorporate an overview of the systemic, cellular and molecular pathways at play (Fidler, 2003). The discovery of new in vivo models capable of incorporating all the mentioned aspects would therefore be beneficial.

Mammalian models have been the pre-eminent model of choice for the study of human disease, largely due to their remarkable genome homology, as well as the physiological, anatomical and cellular similarities with humans. Furthermore, transgenic approaches have since been developed to purposefully mutate principal disease instigating genes, so as to accurately mimic human diseases, such as cancer. However, recent advances in cancer biology have uncovered a wealth of potential therapeutic targets that require high-throughput validation. The zebrafish in vivo model is now emerging as a functional complement to in vitro and murine model systems, whilst harbouring

Page | 95 the singular potential to work as a platform to evaluate targets on a large scale. This genetically tractable model system offers the advantages of invertebrate models while belonging to the vertebrate realm. While studies are still ongoing on the validity of the zebrafish model for the study of solid tumours developed spontaneously or in response to genetic mutations, substantial validation is emerging on its use as a host for the study of tumour-host interactions through the injection of solid tumour xenografts (Lieschke and Currie, 2007). By exploiting the numerous transgenic fluorescent fish lines and the optical transparency of the model, this methods enables the studying of the signalling pathways of interest through the analysis of the fish response to the secretion of molecules by the implanted xenograft.

To date, very few convincing and functional zebrafish embryo models for the study of cancer metastasis have been described (Lieschke and Currie, 2007). However, the existence of a lymphatic and blood vascular system have already been described, validating the potential of this model (Küchler et al., 2006)(Yaniv et al., 2006). In this thesis, I attempted to create a viable in vivo zebrafish model for the study of human breast cancer metastasis based on the limited available literature, which was then optimised according to its yields.

Prior to studying the metastatic potential of the MCF-7 WT cells and the derived drug resistant MCF-7 EpiR and MCF-7 TaxR, I optimised the parameters on the model, based on the information obtained from the available literature. I maintained the injection location to the yolk sac, due to ease of injection and apparent success in cell survival observed during the previous angiogenesis assays. However, for this assay, I chose the WT zebrafish line, which lacked any intrinsic fluorescent labelling, so as not to interfere with the fluorescence of the implanted cells during imaging. As done in previous reported studies (Teng et al., 2013), I used the lipophilic membrane dye to label the injected cells. During optimisation, I injected separately all available cell lines (MCF-7 WT, MCF-7 EpiR, MCF-7 TaxR and MDA-MB-231) to obtain a broad spectrum of metastatic patterns that would enable me to achieve a universal protocol to apply to all future metastasis assays. Initially, I maintained the injection parameters used for the zebrafish angiogenesis assays: injection of approximately 150 fluorescently labelled cells was performed in 1 dpf embryos, following which embryos were placed in the incubator until subjected to fluorescent microscope imaging. To minimise the risk of analysing fish which were accidentally injected directly in the vasculature, zebrafish were analysed under the fluorescent microscope 1 hour following injections to detect the presence of erroneous injections. Embryos were then imaged once daily, for a total time-frame of 4 days, so as to detect first appearance of cell dissemination and gauge fish survival in response to imaging/appearance of cellular dissemination. As shown in Figure 1.6A, fish survival decreased drastically at 4 days post injection, while remaining above 80%

Page | 96 at 3 dpi. Consistently, cellular dissemination appeared in individual fish at 3dpi (results not shown). As most of the injected embryos presenting cellular dissemination died on day 4 post injection, I decided to limit the incubation period to 3 days, so as to limit the loss of viable information.

Having ascertained that breast cancer cell lines injected into the zebrafish embryos were able to metastasize, I next analysed whether the disseminated cells were able to graft and proliferate within the embryo, to confirm cellular viability and purposefully mimic normal cellular metastasis. To do this, I imaged MDA-MB-231 injected embryos presenting cellular dissemination on two subsequent days (3 and 4 dpi), ensuring analysis of the same embryo at all times. As shown in Figure 1.6B, similar disseminated cell clusters located in analogous regions in tail of the injected embryo displayed a strengthening in the emitted signal following 24 hours (Figure 1.6B). This was taken to be an indicator of cellular proliferation, implying the success of the model. In all subsequent experiments, the same parameters were therefore maintained, and all injected embryos imaged at 3 dpi for the presence of cellular metastasis.

To study the in vivo metastatic properties of the parental MCF-7 and derivative drug resistant cell lines, each cell line was harvested individually to obtain a dry pellet following lipophilic membrane staining with CM-DiI (enabling the cells to be fluorescently red). CM-DiI is a membrane dye which has been designed to pass freely through a cell’s membrane: once inside a cell, this dye is transformed into cell-membrane impermeant reactions and is retained by the cell and passed through subsequent generations. Importantly, cells stained through this dye emit an excitation/emission spectra which is easily detectable through a fluorescent microscope, and the dye is not passed to adjacent cells. As a positive control, MDA-MB-231 cells were injected, as these presented the most metastatic phenotype in in vitro assays. Cells were injected following the parameters defined in the optimisation steps reported previously. At 3 dpi, zebrafish embryos were imaged individually to detect presence of disseminated cells outside of the yolk sac. Notably, the head and tail regions of the embryo were imaged thoroughly, as these were the areas where dissemination had been reported previously (Beloqui et al., 2011; Cock-Rada et al., 2012).

Page | 97

Figure 3.1.6 Optimisation of zebrafish embryo metastasis model. Approx. 150 DiI-stained MCF-7 WT, MCF-7 EpiR, MCF-7 TaxR, or MDA-MB-231 cells were injected into the yolk sac of 1 dpf WT zebrafish embryo. Dissemination of implanted cells was monitored at 2, 3 and 4 dpi, to detect possible signs of metastasis. A) Line-graph depicting survival of the injected zebrafish embryos on subsequent days; B) Images were taken under the fluorescent microscope of embryos with any cell dissemination in the tail and head region. The same fish were then imaged on the consecutive day to monitor the proliferation of disseminated cells. Representative figure displays the proliferation of disseminated cells in the same zebrafish embryo on consecutive days. Top displays bright-field fish image with presence of disseminated MDA-MB-231 cells highlighted in red. Middle image displays the red-fluorescent channel image of the same 3 dpi embryo. Clusters of disseminated cells in the tail region are circled in yellow, green and blue. Tumour cells are visible in white. Lower image displays the same embryo imaged at 4 dpi. Corresponding cell clusters are circled in yellow, green and blue, with tumour cells still visible in white. Data shown are mean and SD of n=2 independent experiments (25 replicates each).

Page | 98

Figure 3.1.7 Drug resistant cell lines metastasize in vivo in a zebrafish embryo model. MCF-7, EpiR and TaxR cell lines were stained with CM-DiI prior to injection into the yolk-sac of 1 day post-fertilisation WT zebrafish embryos. Injected cells were allowed to metastasize for 3 days. Embryos were then imaged under the fluorescent microscope to detect any presence of disseminated cells. Presence of cells outside of the yolk sac region was defined as metastasis. A) Percentage of injected fish presenting any cell dissemination was calculated and compared between the sensitive MCF-7 cells and the drug resistant TaxR and EpiR cells. No embryo injected with MCF-7 cells presented any form of cell dissemination. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Representative images of MCF-7, EpiR and TaxR injected embryos at 3 days post-injection. Left column displays full fish with the implanted tumour depicted in red, and the whole fish displayed under the bright-field light. A small white square indicates the regions that were photographed on the columns on the left, at a higher magnification. Middle column shows disseminated tumour cells in red and bright- field image of the embryo’s head region, to convey location of metastasis. Right column displays only the red-fluorescent channel, with any disseminated tumour cell visible in white. Note that MCF-7 cells did not disseminate outside of the yolk-sac. Data shown are mean and SD of n=3 independent experiments (25 replicates each).

Page | 99

As shown in Figure 1.7, 7.80±2.14% of embryos injected with MCF-7 EpiR cells showed cellular migration to the head of the injected embryo, particularly located in the heart region. Likewise, MCF-7 TaxR cells migrated exclusively to the head region of the embryo. This pattern was observed in 13.48±3.11% of the injected embryos (Fig. 1.7A). Notably, none of the embryos injected with MCF-7 WT cells ever presented any sign of cellular dissemination. Instead, the tumour cells always remained localised in the yolk sac, remaining confined to the site of injection (Fig 1.7 B). Both resistant cell lines thus displayed a significant increase in cellular metastasis in vivo. Furthermore, consistent with their inherently aggressive phenotype, MDA-MB-231 cells metastasized to both the head and tail region of the injected embryos, becoming the only tested cell line to portray this dissemination pattern. This behaviour was noted in 35.95±13.499% of injected embryos.

Taken together, the previous chapters results were consistent with the metastatic patterns discerned in the zebrafish embryos, whereby the MCF-7 TaxR presented the highest metastatic potential, followed by the MCF-7 EpiR. Only the MDA-MB-231 cell line were more metastatic, being able to not only metastasize in more sites, but also displaying this behaviour in more embryos. Again, this was as predicted, due to their documented high metastatic nature. Furthermore, once again the MCF-7 WT displayed a phenotype which confirmed their epithelial nature when these displayed an inability to disseminate. This fact not only implied that the acquisition of drug resistance led to a significant phenotypical alteration in the cell line, rendering it capable of successful metastasis in vivo, but it also provided further confirmation of the validity of the zebrafish model as a tool for the study of cancer metastasis, in its selective granting of metastasis.

3.1.6: Discussion This chapter aimed to characterise the physiological and molecular changes attributed to the acquisition of resistance to epirubicin and paclitaxel treatment in breast cancer cell lines, to determine if this affected their ability to undergo cancer progression. To do this, parental MCF-7 WT cells and derivative epirubicin resistant MCF-7 EpiR and paclitaxel resistant MCF-7 TaxR cell lines were subjected to individual assays to gauge their epithelial/mesenchymal marker expression, migration capacities, stem cell properties, angiogenic aptitude and overall in vivo metastatic potential.

Initial analysis of epithelial/mesenchymal marker expression uncovered a substantial alteration in the expression of the surface cadherins, whereby both the drug resistant cell lines exhibited singularly mesenchymal markers (N-cadherin), and the parental MCF-7 WT cells maintained the

Page | 100 expression of the E-cadherin marker. Notably, both resistant cell lines had completely lost the expression of this epithelial marker, implying the resistant cells had undergone the EMT upon the acquisition of drug resistance. However, when all cells were compared to detect morphological changes, the resistant cell lines did not exhibit the characteristic apolar, elongated cell shape which would be expected from cells which had undergone EMT. Instead, they maintained a round shape, with full cell-cell contacts and the propensity to grow in colonies.

The majority of studies have reported that E-cadherin loss in breast cancer cell lines is a pre- requisite for successful cancer progression, and is accompanied by survival to anoikis, increased migratory and invasive capabilities and angiogenic properties (Derksen et al., 2006)(Nieman et al., 1999). Importantly, these studies always described the concomitant alterations in cell shape attributed to E-cadherin loss. Only limited studies have instead reported on the possibility that E- cadherin loss was not necessarily connected to the ability of cancer cells to progress, with a partial loss of E-cadherin detected in 15% of invasive lobular carcinoma cell lines, and most infiltrating ductal breast cancers through histological grading of ILC (Berx and Van Roy, 2001). Studies by P. Dekerson et al., also showed how loss of E-cadherin alone was insufficient to instigate EMT in invasive lobular carcinoma, converging instead to a spindle-shape morphology and increased metastatic abilities, while retaining expression of CK8 (an epithelial marker), and lacking expression of vimentin (Derksen et al., 2006). Consistently, a study by Sommers C. et al., purposefully altered E-cadherin expression in E-cadherin negative invasive breast cancer cell lines (BT549 and HS578t) to attempt to, unsuccessfully, revert their invasive phenotype. Instead, this did not alter the cellular morphology or its invasive behaviour (Sommers et al., 1994). Similar conclusions were obtained by Nieman et al., where it was again noted that overexpression of E- cadherin was insufficient to revert a mesenchymal phenotype or behaviour, albeit loss of E- cadherin was generally accompanied by a typically elongated morphology, with loss of cell-cell contacts and a characteristic fibroblastic appearance. However, these morphological changes did not alter their invasive capabilities, unless this was accompanied by an increase in N-cadherin expression (Nieman et al., 1999).

Overall, these studies display how a shift in E-cadherin/N-cadherin expression does necessarily that a cell has undergone EMT and that behavioural and morphological changes are dependent on multiple factors. The drug resistant cell lines used in this chapter presented both the loss of E- cadherin and the acquired expression of N-cadherin, but not any morphological changes. This could imply that instead of having undergone full EMT, these cells have entered a stage of partial EMT. The concept of partial EMT, or different EMT stages has been previously described by Klymkowosky et al., whereby EMT can be distinguished into three phenotypes: the first consists

Page | 101 of cells which present loss of cell polarity whilst retaining cohesive cell-cell contacts and keratin expression; the second portrays cells displaying a loss of cell-cell contacts, but retained keratin expression; the third exhibits loss of keratin expression and significant vimentin expression. This study further argues that tumours present a heterogeneous nature, whereby only cells on the invasive front of a tumour mass will display the phenotype 3, corresponding to actively metastasizing cells (Klymkowsky and Savagner, 2009). According to this, the lack of morphological alterations that I noted in the drug resistant cell lines could also be attributed to the fact that at the time where the picture was taken, my drug resistant cells were not actively migrating, but were instead adhesive and proliferating. To see the desired morphological changes, I would therefore need to visualise the cells as they are migrating.

A study similar to mine was performed on colorectal cancer, aiming to assess its morphological changes upon the acquisition of resistance to oxaliplatin. Interestingly, this study noted how upon their acquisition of drug resistance, these cells displayed the characteristic loss of E-cadherin surface expression, spindle-shape morphology, loss of polarity, intercellular separation and pseudopodial formation. In this case, these morphological changes were also correlated with a 8- 15 fold increase in the cell lines migration and invasive abilities (Yang et al., 2006). Despite the lack of morphological changes, my drug resistant cell lines presented a consistent behaviour with the findings presented on this study, when their migratory abilities were gauged using the Boyden Chamber transwell assay, and compared to that of the parental MCF-7 WT: both MCF-7 EpiR and MCF-7 TaxR cells exhibited a significant and important increase in migration, particularly notable for the MCF-7 TaxR cells. Consistently, an assessment of their stem cell phenotype confirmed that both resistant cell lines could create significantly larger and more numerous mammospheres. Again, MCF-7 TaxR presented the most important increase in both aspects. This not only implied that they presented larger cancer stem cell populations, with each cell capable of self-renewal, but that these cell lines also had increased survival capacities, with the capacity of overcoming anoikis, all essential qualities for successful tumour metastasis.

Interestingly, my findings of a direct correlation between the insurgence of drug resistance and an increase in the cancer stem cells populations are consistent with the study which claims that chemotherapy actively enriches the cancer stem cell populations (Dean et al., 2005). However, unlike most studies concluding that cancer stem cells are the cause of drug resistance, my results indicate that, as speculated by Gangopadhyay et al., 2013, cancer stem cells could instead be result of sequential cancer progression steps which are triggered by the acquisition of drug resistance.

Page | 102

The aggressive nature of the drug resistance cell lines was further confirmed when these were injected into zebrafish embryos, and caused a significant alteration in the formation of the nearby SIV structure, in terms of supplementary sprouting of blood vessels protruding to irrigate the implanted cancer mass. This was on average considerably higher than the angiogenic response induced by the parental sensitive cell line, implying that drug resistant cell lines were also more apt at inducing angiogenesis, a rate limiting step in the progression of a tumour. Furthermore, the consistency of these findings with the overall phenotype of both the sensitive and resistant cell lines in other aspects of cancer progression, suggested the validity of the zebrafish model for the study of angiogenesis. With appropriate validation, zebrafish could become the primary model to analyse the angiogenic potential of a tumour. Furthermore, due to their fast and numerous progeny, and facility in drug administration, this model could also present a high-throughput platform to test anti-angiogenic drugs aimed at hindering cancer progression of tissues of choice. However, due to the novelty of the model, these findings will need further confirmation via the use of murine models, specifically through CD31 histological staining to delineate presence of vasculature, or through the in vitro sprouting assay.

Having successfully shown that both resistant cell lines were more able to migrate, induce angiogenesis and presented a larger stem cell population, I then evaluated whether these particular abilities were sufficient to culminate in effective tumour metastasis in vivo. The lack of availability of murine models, combined with the need to develop faster in vivo alternatives which could provide more study replicates in an economical manner, inspired the development of a zebrafish embryo metastasis model.

When placed in the yolk sac of the zebrafish embryos, only the drug resistant cell lines and the malignant MDA-MB-231 cells were able to disseminate outside of the yolk sac. Consistently with previous experiments, sensitive MCF-7 WT cells instead portrayed an epithelial phenotype, which was insufficient to enable their dissemination: they remained contained within the yolk sac for the duration of the experiment. Interestingly, both resistant cell lines were only able to disseminate to the head region of the embryos, while the MDA-MB-231 cells, known for their highly metastatic abilities, were able to disseminate to both the head as well as the tail region of the embryos. Many speculations can be made to justify this according to the available literature. Paget et al., was the first to delineate the non-random pattern of cancer metastasis (Paget, 1889). In 1889 he published the ‘seed and soil’ hypothesis, which depicted the necessity for the compatibility and affinity between the metastasizing tumour cell (the seed) and the milieu of specific organs (the ‘soil’) (Fidler, 2003). According to this hypothesis, metastasis would only form when the seed and the soil are compatible. James Ewing later defied this hypothesis, claiming that cell dissemination to

Page | 103 particular organs was simply a result of a mechanical arrest of the tumour cells in capillary beds. In accordance, Zeidman et al. hypothesized how only cells which can distort their shape can pass through narrow capillary tubes, whereas cells which are more rigid remain trapped. When quantified, the rate and incidence of cellular rest varied according to cell type. The yielding of metastasis was instead independent on location of cellular arrest (Zeidman et al., 1952). Consistently, Sugarbaker took into account both anatomical and mechanical considerations in the prediction of common regional metastasis, rating factors such as the slower weaker flow of the venous circulation of lymphatic drainage (Sugarbaker, 1979). Mechanistic hypothesis were later defied, where multiple studied argued that for subsequent cellular proliferation and growth into secondary lesions, an influence was necessary from the particular organ cells (Hart and Fidler, 1980), with circulating cancer cells instead relying on specific binding to endothelial cells and/or reactions to growth factors secreted locally (Fidler, 2003). Clinical studies in cancer patients and experimental murine models have since concluded that location of metastasis is completely independent of vascular anatomy, rate of blood flow, and the number of tumour cells reaching particular organs. Cells are able to attain the microvasculature of every organ, even if they were not able to successfully colonise it (Fidler, 2002; Lea et al., 1986; Talmadge and Fidler, 1982).

Studies to determine the influence of mechanistic factors versus organ micro-environment have not yet been performed in zebrafish embryos. However, a speculation can be made to explain the selective metastasis of the injected cell lines when taking into account the injected cell shape and the embryos vasculature at the time of the experiment: all tumour cells were injected into the yolk sac; from the yolk sac, the blood flows to the heart, from which it irrigates the brain, and then travels to the main body until it reaches the embryos tail, from which it doubles back to return to the yolk sac (Figure 1.4). MDA-MB-231 cells presents the characteristic spindle shape, which is thinner and more adaptable, so theoretically more able to travel the intricate capillaries of the embryo. Thus, MDA-MB-231 would be able to travel in both the head and tail regions of the embryo, before encountering the more fallible venous circulation. Instead, both resistant cell lines could be hindered by their inability to complete the morphological changes which are generally consequent of EMT: their more rounded shape and cell-cell interactions could cause these cells to remain trapped in the first capillaries they encounter, as well as in the major arteries. Thus, they would remain imprisoned upon their encountered with the first major blood vessels, which from the yolk sac would be the ones irrigating the embryo’s head. Thus, the dissemination pattern of the tested cells could be justified purely on mechanistic aspects of the embryos vasculature and cell shape. Further studies would need to be performed to determine any influence from the specific zebrafish organs on the circulating cancer cells.

Page | 104

Despite this incongruence, the zebrafish model still presents multiple advantages when compared to the other available in vivo models. For instance, this model would enable to quickly evaluate whether a drug or genetic manipulation could affect the metastatic phenotype of a cell line. Furthermore, this model would be significantly favourable due to its time frame: 5 days versus 6 months using murine alternatives. Economically, zebrafish are cheaper to buy, produce larger progenies and do not require immunosuppression, allowing more experimental replicates, providing statistical backup of the data. Then, in vivo imaging of small metastatic lesions is impossible in murine models, due to the deep tissue embedding, requiring instead the sacrifice of the animal (Teng et al., 2013).

Over the years, numerous studies have attempted to optimise the zebrafish embryo model for the study of metastasis. The technique varies on the location of tumour injection (yolk sac (Beloqui et al., 2011) or the perivitelline cavity (Zhao et al., 2011), the method of fluorescent staining of the cells to inject (intrinsic stable expression of a fluorescent protein (Lee et al., 2005; White et al., 2008) or lipophilic membrane dye (Marques et al., 2009; Vandepitte et al., 2010)), the incubation days subsequent to injection (between 1 and 10 days) (Lee et al., 2005;White et al., 2008), the incubation temperature (28ºC to 35ºC )(Moshal et al., 2010) ;Marques et al., 2009) and the quantification methods. Most of the model optimisation had been performed before the initiation of my PhD, where I determined that both the injected cancer cells and the embryos were able to survive at both 28ºC and 34ºC degrees, without altering the development of the embryo or the metastasis/angiogenesis of the injected cell lines: I therefore opted for keeping the injected embryos at 28ºC, as this would be most favourable for the embryos survival. Injection in the yolk sac proved to be easier and faster to perform, and sufficiently compartmentalised to allow for the selective migration of the cell lines of choice, and was therefore selected as the location of injection. For the method of fluorescent staining, a lot of controversy has arisen in the past years, claiming lipophilic membrane dyes can diffuse upon the death of the injected cells and accidentally stain nearby immune or epithelial cells, impeding the effective detection of disseminated cells. The obvious manner to overcome this problem would be to use intrinsic fluorescent labelling to distinguish the cells following injection into the embryos. However, this method turned out to be very time consuming and costly, as the fluorescence emitted from a single cell labelled intrinsically was very hard to detect following injection, ensuing the need to replace simple fluorescent microscopes with confocal microscopes for the imaging of the embryos. I therefore continued to use fluorescent membrane dyes to label the cells. The validity of this methods of cell-staining rose when injecting the embryos with the drug resistant versus the sensitive cell lines: only the resistant cell lines displayed any sign of cell migration outside of the yolk sac. If the theory that unspecific

Page | 105 staining would ensue following injection of lipophilic membrane dye stained cells was true, then I would’ve detected traces of the dye outside the yolk sac even for the MCF-7 WT injected embryos. Finally, the incubation period was optimised based on an appearance of metastasis/fish survival optimisation: embryos presenting metastasis appeared at 3dpi, following which they generally died within 24 hours. Leaving the embryos until 4dpi would ensue in the loss of valuable input on the percentage of embryos with metastasis. Injected embryos were therefore imaged at 3 dpi.

A study by Teng Y. et al., obtained results consisted with mine when testing the metastatic potential of a range of cancer cell lines in vivo in zebrafish embryos. Unlike mine, their cell injections were performed in the perivitteline space of the embryos, following which the injected cell lines were allowed to metastasize for 48 hours prior to confocal imaging to detect presence of disseminated cells. Like me, they used the lipophilic fluorescent CM-DiI dye to label the cell lines prior to injection. Consistently with my findings, they noted how cells which displayed a more metastatic behaviour in transwell migration assays also showed severe cellular dissemination in the zebrafish embryos head and tail regions. Furthermore, they also noted how non-metastatic breast cancer cells (MCF-7 cells in my case, and T47D in their case) remained confined within the site of injection, namely the yolk sac. Teng Y. et al., went a step further to confirm their findings by employing murine models: in each case, the tested cells displayed a consistent pattern of metastasis which coincided with the in vitro and zebrafish in vivo data. This last finding confirms the validity of the zebrafish model, and indirectly implies that my zebrafish findings could have confirmation should murine models be exploited further (Teng et al., 2013). Further development of the model should encompass the suggestions depicted by this paper, whereby on top of calculating the percentage of embryos presenting cellular metastasis, one should also analyse the number of cells capable of dissemination per injected tumour mass. To do this, confocal continual monitoring should be performed at peak metastatic times. Despite the difficulty and smaller simultaneous replicate potential of this approach, this method could permit the analysis of the metastatic potential of previously unstudied cell lines or primary tumours. Furthermore, location of metastasis should always be noted and quantified (as distance travelled from site of injection), as this seems to be indicative of the level of EMT achieved by the analysed cancer cell lines.

Overall, this chapter presented strong evidence that indicates that breast cancer MCF-7 cells developed strong mesenchymal properties upon their acquisition of resistance to both epirubicin and paclitaxel. Multiple mechanisms have been reported to be capable of rendering a cell line resistant to the effect of the administered drug. These include alterations in the extracellular microenvironment, mutations in the drug target, increased capacity to activate the DNA damage response, or even disturbances of the apoptotic pathway. Alternatively, alterations in the

Page | 106 expression of genes capable of influencing any of these pathways may ultimately result in the loss of the drug effectiveness against that tumour. In the next chapters, I aimed to correlate these physiological modifications to changes at the molecular level, which have previously been attributed to grant drug resistance, to see if these could also influence the ability of a cell line to undergo cancer progression.

Page | 107

Chapter 3.2: FOXO3 and the cancer progression of drug resistant cell lines As stated previously (Introduction Chapter 1.7.1), FOXO3 is a member of the Forkhead/winged helix box class O (FOXO) of transcription factors, which act downstream of the PI3K/PKB pathway. These FOXO proteins are sub-divided into four sub-classes: FOXO1, FOXO3, FOXO4 and FOXO6, and function in multiple cellular processes, such as cell cycle progression, DNA damage repair, cell death, stress detoxification, as well as glucose metabolism (Myatt and Lam, 2007).

Generally, FOXO3 exhibits a tumour suppressor function, with multiple studies having depicted the correlation between FOXO3 and the modulation of drug resistance. In sensitive colon carcinoma cell lines, FOXO3 presented dephosphorylation and nuclear translocation upon cisplatin administration, thus inducing the expression of its target genes. This effect was not mirrored in cisplatin-resistant colon carcinoma cell lines (Fernández de Mattos et al., 2008). Consistently, FOXO3 silencing rescued the sensitive cell lines from cisplatin mediated apoptosis, implying FOXO3 plays an essential role in the cytotoxicity of cisplatin in colon carcinoma (Fernández de Mattos et al., 2008). A similar result was noted with the leukaemic response to doxorubicin administration, whereby doxorubicin administration increased the expression levels of FOXO3 in sensitive but not in drug resistant cell lines. However, in this instance, FOXO3 expression was correlated to the expression of multi-drug efflux ABCB1 transporters, portraying a novel role for FOXO3 as a promoter of drug resistance. This study concluded that despite the initial pro-apoptotic function, continued FOXO3 activation eventually induced drug resistance (Hui et al., 2008a). A separate study on chronic myelogenous leukaemia (CML) confirmed the correlation between FOXO3 and the insurgence of resistance to doxorubicin described in the previous study. In this case, chronic FOXO3 expression was found to promote the expression of p110α, the catalytic subunit of PI3K, thus increasing the activity of the PI3K/Akt axis in a positive feedback loop (Hui et al., 2008b).

A link was also noted between FOXO3 and paclitaxel treatment in breast cancer cell lines. FOXO3 expression was seen to induce the expression of a panel of pro-apoptotic proteins, such as Bim, upon paclitaxel treatment (Sunters et al., 2003). Further analysis on paclitaxel regulation of FOXO3 induction of apoptosis revealed FOXO3 transcriptional regulation of c-Jun NH2-terminal kinase 1/2 (JNK1/2), p38, and extracellular signal-regulated kinase 1/2 (ERK1/2) Mitogen-activated protein kinases (MAPKs), proteins essential for the initiation of apoptosis upon paclitaxel treatment (Sunters et al., 2006). A different study detected FOXO3 mediated induction of

Page | 108 apoptosis upon gefitinib treatment in a panel of gefitinib-sensitive breast cancer cell lines. Again, FOXO3 nuclear translocation was detected upon treatment. Instead, in gefitinib-resistant breast cancer cell lines, FOXO3 remained phosphorylated, and therefore confined to cytoplasmic sub- cellular localisation, causing its inhibition (Krol et al., 2007).

Despite the incongruence over the oncogenic/tumour suppressor function of FOXO3, FOXO3 has overall presented a positive response to the administration of chemotherapeutic drugs in different cancer types, with its expression increasing in sensitive cell lines. This relationship has led to the hypothesis that FOXO3 regulation might be influencing the altered cancer progression capacities of the resistant cell lines noted in Chapter 1. Given the FOXO3 characteristic function as a tumour suppressor, I aimed to determine the role of FOXO3 in drug resistant cell lines, to understand if its FOXO3 could be targeted to revert the mesenchymal phenotype of the drug resistant breast cancer cell lines.

Chapter 3.2.1: FOXO3 mimics E-cadherin expression in sensitive cell lines Numerous papers have been published to demonstrate the anti-cancer role of FOXO3 in response to chemotherapeutic drugs. In general, FOXO3 competes with FOXM1 (a proto-oncogene) for the binding to the Forkhead Response Elements (FHRE) present on the promoter region of genes. FOXO3 will typically repress the transcription of genes that are deleterious to a cell, and instead promote the transcription of genes which lead to tumour suppression and apoptosis. In response to epirubicin treatment, FOXO3 has been shown to increase its expression to activate pro- apoptotic pathways, culminating in cell death. Given the pro-apoptotic and anti-cancer functions of FOXO3, as well as its close antagonistic relationship to the oncogenic FOXM1, I decided to analyse FOXO3 function in the epirubicin and paclitaxel resistant MCF-7 cells, and to compare it to that of the parental sensitive cell lines. Comprehending possible alterations in FOXO3 expression pattern could enable the definition of new strategies to obtain its re-activation, so as to counteract the cancer progression abilities acquired upon the insurgence of drug resistance by the two resistant MCF-7 cell lines.

Initially, MCF-7 WT cell lines were subjected to 1 µM epirubicin treatment, or 10 nM paclitaxel treatment for 0, 4, 8 and 24 hours, or 0, 8, 16, 24, and 48 hours, respectively. The MCF-7 WT response to either treatment was compared to that exhibited by the respective epirubicin or paclitaxel resistant cell line (MCF-7 EpiR or MCF-7 TaxR). Individually treated cells were harvested and processed for either Western blotting or RTq-PCR quantification. Expression of FOXO3, E- cadherin, N-cadherin and Vimentin were quantified, to obtain a panel of epithelial and mesenchymal markers and compare them to FOXO3 expression. -tubulin was used as a loading

Page | 109 control for Western-blots and all quantifications obtained via RTq-PCR were normalised to L19 expression.

Real-time quantitative PCR of MCF-7 WT vs MCF-7 EpiR epirubicin treatment revealed results consistent with what obtained in the previous chapter: MCF-7 WT cells displayed a loss of epithelial markers (E-cadherin) and a consequent acquisition of mesenchymal markers (N-cadherin and Vimentin) (Figure 2.1). Interestingly, E-cadherin expression was found to significantly increase upon epirubicin treatment in MCF-7 WT with increasing incubation times. This was not mirrored in MCF-7 EpiR cells, where E-cadherin expression remained undetectable throughout treatment. FOXO3 displayed a pattern which mirrored that of E-cadherin in MCF-7 WT cells: with pro- longed exposure to epirubicin, FOXO3 increased significantly, reaching its peak at 24 hours. However, unlike with E-cadherin, FOXO3 expression remained relatively unaltered in MCF-7 EpiR cells throughout treatment. Both N-cadherin and Vimentin remained indiscernible in MCF- 7 WT cell lines, irrespective of epirubicin administration. However, in MCF-7 EpiR cells, their expression was maintained without significant alterations throughout treatment.

The same treatment was re-produced to verify these results using Western blots, so as to assess the protein expression pattern (Figure 2.2). Consistent with the RTq-PCR, FOXO3 expression increased gradually in MCF-7 WT cells until 24 hours of epirubicin treatment. In this instance, treatment was prolonged to verify subsequent expression patterns: in sensitive cell lines, treatment continuation caused a decrease in FOXO3 expression, which was attributed to the apoptotic toll of epirubicin treatment. Again, E-cadherin maintained a strong expression throughout drug treatment. Instead, it remained unexpressed in the resistant cell line, which presented a quasi- constant FOXO3 expression.

MCF-7 WT and MCF-7 TaxR cells were then simultaneously subjected to paclitaxel treatment. Consistent with previous results (Chapter 3.1) and patterns exhibited by the MCF-7 EpiR and MCF-7 WT upon epirubicin treatment, MCF-7 WT displayed a lack in Vimentin and N-cadherin expression, indicating their lack of mesenchymal markers (Figure 2.4). These are instead clearly acquired upon drug resistance, as is confirmed by their strong and unwavering expression in the MCF-7 TaxR cells, irrespective of treatment. Again, E-cadherin expression displayed the particularly interesting pattern of significantly increasing RNA levels upon treatment prologation in MCF-7 WT cells. Again, this pattern was not mirrored by the resistant cell lines, which instead lacked E-cadherin expression completely. Consistently, FOXO3 expression pattern paralleled that of E-cadherin expression in MCF-7 WT cells, with a significant increase in expression exhibited upon time length of treatment.

Page | 110

Figure 3.2.1 FOXO3 regulation of E-cadherin in sensitive and resistant cell lines. MCF-7 WT and MCF-7 EpiR cell lines were treated with 1 µM Epirubicin for time-points 0, 4, 8 and 24 hours. Cells were then harvested for analysis by RTq-PCR for FOXM1, FOXO3, N-cadherin, E- cadherin and Vimentin mRNA trends. L19 was used as a loading control. Student t-test was performed to determine statistical significance between untreated and treated time-points, with P<0.05 = *; P<0.01= **; P<0.001=***. Data shown are mean and SD of n=3 independent experiments (3 replicates each).

Page | 111

Figure 3.2.2 FOXO3 and E-cadherin increase in expression during epirubicin drug treatment. MCF-7 WT and MCF-7 EpiR cell lines were treated with 1 µM epirubicin for 0, 4, 8 or 24 and 48 hours. Treated cells were harvested for analysis through Western-Blot to determine potential down-stream target expression. Protein expression was compared between E-cadherin and FOXO3. B-tubulin was used as a loading control. Data shown are representative of n=3 independent experiments.

Page | 112

Figure 3.2.3 FOXO3 regulation of E-cadherin in sensitive and resistant cell lines. MCF-7 WT and MCF-7 TaxR cell lines were treated with x µM paclitaxel for time-points 0, 4, 8 and 24 hours. Cells were then harvested for analysis by RTq-PCR for FOXM1, FOXO3, N-cadherin, E- cadherin and Vimentin mRNA trends. L19 was used as a loading control. Student t-test was performed to determine statistical significance between untreated and treated time-points, with P<0.05 = *; P<0.01= **; P<0.001=***; Data shown are mean and SD of n=4 independent experiments (3 replicates each).

Page | 113

Figure 3.2.4 FOXO3 and E-cadherin increase in expression during paclitaxel drug treatment. MCF-7 WT and MCF-7 TaxR cell lines were treated with x µM paclitaxel for 0, 4, 8 or 24 and 48 hours. Treated cells were harvested for analysis through Western-blot to determine potential down-stream target expression. Protein expression was compared between E-cadherin and FOXO3. B-tubulin was used as a loading control. Data shown representative of n=2 independent experiments.

Page | 114

MCF-7 TaxR instead continued to express FOXO3 though-out treatment, albeit its expression remained unaltered.

When the same assay was repeated, only to obtain protein expression patterns using Western blotting, a similar pattern emerged. E-cadherin expression was found to increase during the time- course in sensitive cell lines, while remaining absent in MCF-7 TaxR cells. Again, this pattern was mirrored by FOXO3, which instead was detected in resistant cells, albeit at a lowed expression. Unfortunately, N-cadherin pattern was not analysed due to the lack of a functioning primary antibody (Figure 2.4).

Overall, it appeared that FOXO3 regulates E-cadherin expression, and that this regulation is lost in resistant cell lines. This loss of function would coincide with FOXO3 loss of response to drug treatments. Proof of this hypothesis would imply FOXO3 malfunction could result in the loss of E-cadherin, and consequent EMT, characterising the resistant cell lines. To verify this, I next used sub-cellular fractionation to analyse FOXO3 activity in both resistant and sensitive cell lines.

Chapter 3.2.2: Sub-cellular fractionation displays a similar FOXO3 expression pattern between sensitive and drug resistant MCF-7 cells. Sub-cellular fractionation is a technique which enables the sequential fragmentation of the nuclear and cytoplasmic envelopes, so as to extract cytoplasmic and nuclear proteins individually. This technique provides information on the sub-cellular expression of analysed proteins. When applied to study a transcription factor, sub-cellular localisation can provide information on the active/inactive state of a protein. In the case of FOXO3, cytoplasmic or nuclear localisation can be mediated through several post-translational modifications; namely phosphorylation, acetylation and ubiquitination. These can also modify FOXO3 stability and activity, as nuclear localisation generally entails the inactivation of its transcriptional activity. Particularly significant amongst the post-translational modifications is phosphorylation by Akt on Threonine 32, Serine 253 and Serine 315. This marks FOXO3 for nuclear exclusion by causing its binding to 14-3-3, a chaperone protein, consequently inactivating it (Myatt and Lam, 2007).

In this case, MCF-7 WT, -EpiR and -TaxR cell lines were subjected to 0, 6 and 24 hours of epirubicin or paclitaxel drug treatment, respectively, prior to pellet individual cytoplasmic and nuclear fractionation. The protein expression patterns of total FOXO3, phospho-FOXO3 were compared between the cytoplasmic and nuclear extracts, and between the resistant and sensitive cell lines. B- tubulin was used as a loading control for the cytoplasmic fraction and lamin B was used as a loading control for the nuclear fraction. Sub-cellular localisation analysis enabled the detection of active FOXO3 in comparison to inactive FOXO3: FOXO3 nuclear translocation is equivalent to

Page | 115

FOXO3 activation as FOXO3 transcriptional activity is performed exclusively in the nucleus. Furthermore, detection of phosphorylated FOXO3 at Thr32 is further indication of FOXO3 inactivation, as phosphorylation by Akt or PI3K results in nuclear export and FOXO3 inhibition.

Total cytoplasmic FOXO3 levels increased when MCF-7 WT were subjected to epirubicin treatment, particularly at 24 hours. Nuclear total FOXO3 levels instead oscillated, with a slight decrease upon 6 hours of treatment, only to increase again at 24 hours. Cytoplasmic phosphorylated FOXO3 levels mirrored the pattern of total FOXO3, indicating that the increase in cytoplasmic FOXO3 was of inactive FOXO3. Instead, phospho-FOXO3 nuclear levels remained undetectable, suggesting FOXO3 maintains a strong transcriptional activity throughout treatment. Interestingly, E-cadherin presented an increasing pattern at both the nuclear and cytoplasmic level, mirroring that of total FOXO3. Instead, MCF-7 EpiR cells presented an unvarying total cytoplasmic FOXO3 expression, and a nuclear expression which instead remained almost undetectable. As in MCF-7 WT cells, phospho-FOXO3 cytoplasmic levels increased upon epirubicin treatment in MCF-7 EpiR cells, indicating gradual FOXO3 nuclear exclusion and consequent inactivation. Again, nuclear levels of phospho-FOXO3 remained elusive in MCF-7 EpiR. Consistent with previous results, E-cadherin levels were not detectable in MCF-7 EpiR cells. All results are shown in Figure 2.5.

A similar overall pattern emerged when MCF-7 WT and MCF-7 TaxR cells were subjected to paclitaxel treatment (Figure 2.6). Sensitive cells presented a 6 hour increase, and subsequent decrease of both cytoplasmic total and phosphorylated FOXO3 levels. Alternatively, nuclear total FOXO3 levels displayed a gradual decrease in expression, which was not mirrored by the phospho- FOXO3. This indicated that in MCF-7 WT, FOXO3 was transcriptionally active until cells succumbed to paclitaxel treatment (around 24 hours later). In the resistant cell line, total FOXO3 levels remained constant throughout treatment in both nuclear and cytoplasmic fractions. Interestingly, treatment induced a gradual increase in phospho-FOXO3 levels in the cytoplasm, while remaining undetected in the nucleus. This implied that paclitaxel treatment caused a gradual and partial inactivation of FOXO3 in the MCF-7 TaxR cells.

Overall, these results indicated that the FOXO3 expression detected through the RTq-PCR in resistant cell lines is mostly FOXO3 which had been sequestered to the cytoplasm, and is therefore inactive. As FOXO3 has been shown to directly regulate E-cadherin expression transcriptionally, loss

Page | 116

Figure 3.2.5 Subcellular fractionation reveals FOXO3 activation in MCF-7 EpiR cells. MCF- 7 WT and MCF-7 EpiR cells were treated with 1 µM epirubicin for time-point 0, 6 and 24, following which their nuclear and cytoplasmic sub-fractions were extracted and analysed through Western- blot. E-cadherin, total FOXO3, Phosphorylated Foxo3, and FOXM1 were all analysed. B-tubulin was used as a cytoplasmic loading control, and lamin-B was used as a nuclear loading control. Data shown are representative of n=2 independent experiments.

Page | 117

Figure 3.2.6 Subcellular fractionation reveals FOXO3 activation in MCF-7 TaxR cells. MCF-7 WT and MCF-7 TaxR cells were treated with x µM paclitaxel for time-point 0, 6 and 24, following which their nuclear and cytoplasmic sub-fractions were extracted and analysed through Western-Blot. E-cadherin, total FOXO3, Phosphorylated Foxo3, and FOXM1 were all analysed. B-tubulin was used as a cytoplasmic loading control, and lamin-B was used as a nuclear loading control. Data shown are representative of n=2 independent experiments.

Page | 118 of nuclear FOXO3 could be one of the primary causes behind the resistant cell lines EMT. To confirm this, I next sought to identify the direct FOXO3/E-cadherin transcriptional interaction in the three cell lines, to determine if FOXO3 had indeed reduced the stimulation of the tight junction.

Chapter 3.2.3: Chip reveals FOXO3 capacity to bind E-cadherin is significantly impaired in resistant cell lines Chromatin Immuno-Precipitation (ChIP) enables the study of interactions between selected proteins and their binding to specific genomic regions. In this case, it was used to assess the binding capacity of FOXO3 to the Forkhead Binding Elements located on the promoter region of E- cadherin gene in both the sensitive and resistant MCF-7 cell lines.

To do this, MCF-7 WT, -EpiR and -TaxR cells were individually harvested and their pellets lysed to obtain DNA-protein cross-linked chromatin. This was then fragmented using sonication, following which chromatin was incubated with the FOXO3 antibody to immune-precipitate fragments of interest. Following fragment purification, enrichment was verified using RTq-PCR and primers designed to encompass the FOXO3 binding site on the E-cadherin promoter (Figure 2.7A). Results were compared to quantification obtained via IgG non-specific pull-down, and no- pulldown samples.

As shown in Figure 2.7B, MCF-7 WT cells displayed a significant 437-fold enrichment between IgG and FOXO3 pull-down. This clearly indicated FOXO3 is active in MCF-7 WT cells, and its transcriptional activity enables E-cadherin expression, which promotes the epithelial phenotype in these cells. Enrichment was significantly smaller in MCF-7 EpiR, with only a 43-fold increase in respect to the IgG pull-down. A similar, albeit even more significantly reduced effect was noted with the MCF-7 TaxR cells, whereby the increase was by only 7-fold.

Although both resistant cell lines exhibited enrichment for FOXO3 binding to E-cadherin promoter, their levels was so small in comparison to those exhibited by the sensitive cells, that it is expected that the E-cadherin transcription would be minimal. This significant reduction could either be attributed to the lower endogenous FOXO3 expression in the resistant cell lines, or to its inability to bind the promoter of E-cadherin due to, for instance, promoter hyper-methylation. Nonetheless, the effect of this reduction in binding is clear when comparing the different cell phenotypes, both resistant cell lines have shed all epithelial aspects and have instead acquired mesenchymal traits.

Page | 119

Figure 3.2.7 Chromatin immuno-precipitation shows less FOXO3-E-cadherin binding in resistant cell lines. MCF-7 WT, EpiR and TaxR cell lines were harvested for chromatin immuno- precipitation analysis, with selective FOXO3 precipitation. Ensuing lysates were examined for binding to E-cadherin promoter sequence through RTq-PCR analysis using special E-cadherin primers able to encompass that area. All results were normalised to IgG. Student t-test was used to determine statistical significance, with P<0.05 = *; P<0.01= **; P<0.001=***; P<0.0001=****. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 120

Chapter 3.2.4: FOXO3 transient overexpression is unable to revert the mesenchymal phenotype of the resistant cell lines. Sub-cellular fractionation analysis of FOXO3 activity during drug treatment in both sensitive and resistant cell lines revealed FOXO3 is expressed at significantly lower levels in the nucleus in both resistant cell lines when compared to the sensitive cell lines, implying its loss of function. Its crucial role as a fundamental regulator of E-cadherin suggested its loss of function through cytoplasmic sequestration could be at the root of the resistant cell lines mesenchymal phenotype. Consistently, ChIP analysis revealed significant loss of FOXO3 binding to E-cadherin in resistant cell lines. I next attempted to restore FOXO3 expression levels in the MCF-7 WT and MCF-7 EpiR resistant cell line through transient transfection, in an attempt to alter their phenotype through indirectly influencing E-cadherin expression. Transfected cell pellets were individually harvested for analysis of relative alterations in E-cadherin expression via RTq-PCR and Western-Blot. Each transfection was compared to that obtained via control transfected cells. In parallel, FOXO3 was silenced using a FOXO3 siRNA, and its effect on E-cadherin expression was compared with cells transfected with control siRNA plasmids.

As shown in Figure 2.8, FOXO3 overexpression and silencing in MCF-7 WT cells caused a mirroring effect on E-cadherin expression, with its increase leading to a corresponding significant rise in E-cadherin expression, and it’s silencing causing a significant reduction in E-cadherin expression. Instead, despite successful FOXO3 overexpression and silencing, MCF-7 EpiR cells maintained unquantifiable E-cadherin expression levels, clearly indicating that transient FOXO3 alteration was insufficient to revert the cell line phenotype (Figure 2.9). Unfortunately, time limitations prevented the repeat of this experiment using MCF-7 TaxR.

Overall, these results suggest FOXO3 transient overexpression is not sufficient to revert the mesenchymal phenotype of the resistant cell lines back to its original epithelial phenotype. This could either be due to the multitude of other proteins, including FOXM1, which are able to regulate the expression of the epithelial/mesenchymal markers. Alternatively, as suggested above, the E-cadherin promoter may have undergone mutational inactivation or inactivation through promoter methylation, which prevent FOXO3s binding and subsequent transcription initiation. Furthermore, DNA methylation can result in chromatin remodelling, further impeding transcriptional initiation.

Page | 121

Figure 3.2.8 Effect of FOXO3 transient alteration in MCF-7 WT cells. FOXO3 was transiently over-expressed or silenced in MCF-7 WT cells. Transfected cells were harvested for RTq-PCR analysis. Following validation of transfection efficiency, the effect on E-cadherin was observed. All results were normalised to L19. Student t-test was made to determine statistical significance, with P<0.05 = *; P<0.01= **; P<0.001=***; P<0.0001=****. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 122

Figure 3.2.9 Effect of FOXO3 transient alteration in MCF-7 EpiR cells. FOXO3 was transiently over-expressed or silenced in MCF-7 EpiR cells. Transfected cells were harvested for RTq-PCR analysis. Following validation of transfection efficiency, the effect on E-cadherin was observed. All results were normalised to L19. Student t-test was made to determine statistical significance, with P<0.05 = *; P<0.01= **; P<0.001=***. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Being a transcriptional regulator of multiple cell processes, FOXO3 could still influence breast cancer cell line behaviour without this being directly correlated to EMT. Next, I analysed an aspect which had, to date, remained relatively undefined: FOXO3 and its control of the cancer stem cell phenotype.

Page | 123

Chapter 3.2.5: FOXO3 can alter the mammosphere formation in both sensitive and epirubicin resistant cell lines Despite its inability to revert the mesenchymal phenotype of the resistant cell lines, alteration in FOXO3 expression could still affect other aspects of the cancer progression of both the resistant and sensitive cell lines. The relationship between FOXO3 and the development of cancer stem cells is a relatively unexplored area. The most relevant publication to date was by C. Ginestier et al., who documented how the IL-8 receptor CXCR1 inhibition could significantly abolish BCSC formation. Further analysis enabled them to identify how the effect of CXCR1 inhibition was mediated through PI3K/Akt/FOXO3 pathway (Ginestier et al., 2010). This initial connection between FOXO3 and cancer stem cells inspired the theory that FOXO3 could be an essential inhibitor of the cancer stemness in breast cancer, and that the re-integration of its nuclear expression could inhibit the increased stem-like properties exhibited by the drug resistant cell lines.

To determine the effect of FOXO3 on the formation of cancer stem cells, two separate assays were used: Flow Cytometry (FACS) sorting of cells for the CD44high CD24low phenotype, which was kindly performed by Dr. Ylenia Lombardo; and a mammosphere formation assays in non- adherent cultures. FOXO3 expression was also altered in multiple manners: standard silencing mediated by FOXO3 siRNA; FOXO3 indirect down-regulation through the overexpression of its up-stream inhibitor SIRT6; overexpression of FOXO3 through PLPC-FOXO3 plasmid; overexpression of FOXO3 using the FOXO3-A3 plasmid, or FOXM1-ΔN, composed of the standard FOXM1 sequence which instead lacks the FOXM1 inhibitory site, rendering it constitutively active. The effect of FOXO3 alteration was tested on both MCF-7 WT cells and its epirubicin resistant derivative, MCF-7 EpiR.

Initially, FOXO3 expression was altered in MCF-7 WT cells to determine if this could indeed affect mammosphere formation (Figure 2.10B). When FOXO3 was over-expressed in MCF-7 WT cells, there was a decrease in the numbers of mammospheres formed, albeit this was not significant. Instead, when FOXO3 was silenced, a significant increase in the numbers of spheroids was detected. Consistently, SIRT6 overexpression, induced a comparable outcome. In each instance, the number of mammospheres was almost doubled. Together, these results indicated that FOXO3 exerts a crucial inhibitory role on the development of the cancer stem cell phenotype. Its inherent down-regulation in the resistant cell lines could therefore be a major component of their increased capacity to form mammospheres.

Next, the effect of FOXO3 alteration on MCF-7 EpiR spheroid formation was analysed. Given the lack of FOXO3 nuclear expression in this cell line (3.2.2), and FOXO3 inhibitory role on

Page | 124 mammosphere formation, it was decided that over-expressing FOXO3 in this cell line would have the most pronounced effect on their spheroid forming capacity. FOXO3 was over-expressed using the standard pLPC-FOXO3 vector, as well as the mutated FOXO3-A3 vector. The overexpression effect was compared to that ensuing from control transfected cells. Both types of FOXO3 overexpression caused a significant reduction in the percentage of mammospheres formed, with FOXO3-WT plasmid inducing the highest reduction (from 2.73% to 1.26%) and the constitutively active plasmid reducing the mammosphere formation from 2.73% to 2.13% (Figure 2.10C). Thus, it appeared that FOXO3 transient overexpression could diminish mammosphere formation for this resistant cell line. To confirm this, MCF-7 EpiR were subsequently made to over-express SIRT6 or to silence FOXO3 through FOXO3 siRNA. Transfected cells were then sorted to select for the CD44high CD24low population, two of the most prominent markers expressed on BCSCs, through Fluorescence-Activated Cell sorting (FACs). As shown in Figure 2.10A, SIRT6 overexpression increased the CD44high CD24low population from 2.1% to 5.1%. Consistently, FOXO3 siRNA reduced increased the stem cell population from 1.7% to 3.2%. This data was kindly provided by Dr. Ylenia Lombardo.

Overall, these results confirm that FOXO3 has a central inhibitory function in the regulation of the cancer stem cell phenotype in breast cancer cells. Furthermore, study outcomes suggest a new therapeutic strategy to limit the progression of the stem cell population for both sensitive and the epirubicin resistant cell lines.

Page | 125

Figure 3.2.10 FOXO3 can regulate mammosphere formation. MCF-7 WT and EpiR cells were made to over-express FOXO3 or SIRT6, or silence FOXO3. Transfected cells were seeded in equal numbers in non-adherent culture plates and left to grow for 5 days. Spheroid formations were deemed representative on mammospheres and were counted under the bright-field microscope. A) Bar-chart comparing the number of mammospheres between the sensitive and resistant cell lines. Relative mammosphere formation was calculated by making all numbers relative to those quantified with the MCF-7 WT cell line, so as to obtain a fold-increase. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=*** B) Dot-plot representing the diameter of each mammosphere (measured via ImageJ). Non-parametric ANOVA was used to test the significance of the result with P<0.05 = *; P<0.01= **; P<0.001=***. C) Representative images of mammospheres formed after 5 days in non-adherent plates. Data shown in A is obtained from a single pilot experiment; Data shown in B and C are mean and SD of n=2 independent experiments (3 replicates each).

Page | 126

Chapter 3.2.6: Discussion Diverging outcomes ensued from the different studies of FOXO3 in the drug resistance of different cancer cell lines. In some instances, FOXO3 adopted an oncogenic function and promoted the insurgence of drug resistance. In others, FOXO3 maintained its tumour suppressor pro-apoptotic function, and was gradual activated with drug administration, promoting cytokinesis. Give FOXO3 pro-apoptotic role in response to epirubicin treatment in breast cancer cell lines, I attempted to determine whether an aberration in FOXO3 function was the cause behind the increased cancer progression capacities acquired by the epirubicin and paclitaxel resistant cell lines. When studying the function of FOXO3 in sensitive and drug resistant breast cancer MCF-7 cell lines, an interesting pattern emerged. Upon both epirubicin and paclitaxel drug treatment, FOXO3 presented a treatment duration dependent increase in RNA expression in the sensitive MCF-7 WT cell lines. This was not mirrored in the epirubicin or paclitaxel resistant cell lines, which instead maintained a constant FOXO3 expression independent of treatment extent.

This initial set of results is consistent with other studies analysing the FOXO3 response to anti- cancer treatment in the sensitive MCF-7 WT cell line. For instance, upon gefitinib (Riesa) treatment, FOXO3 expression increased according to duration of drug exposure (Krol et al., 2007). In this study, FOXO3 expression was shown to be increased by the drug to mediate cell cycle arrest and apoptosis. Consistently, a study by Sunters A et al. (2003), noted an increase in FOXO3 expression in MCF-7 WT cells upon paclitaxel treatment which was comparable to that detected in this project. Again, this was correlated to an increase in both the pro-apoptotic targets Bim and p27Kip1 (Sunters et al., 2003). A few years later, the same group provided more in depth detail of this mechanism, unveiling the concomitant JNK activation, which simultaneously inactivated Akt and FOXO3 de-phosphorylation and consequent activation (Sunters et al., 2006). Finally, a more recent study by Khongkow M et al. (2013) determined that both epirubicin and paclitaxel resistant MCF-7 cell lines mediated drug resistance through SIRT6 inactivation of FOXO3, and correlated pro-apoptotic pathways (Khongkow et al., 2013a). Overall, these studies are consistent with the findings in this section on FOXO3 response to drug treatment in both sensitive and resistant cell lines. Furthermore, these provide a justification for the expression pattern noted in my studies, whereby FOXO3 is activated by the drug to induce pro-apoptotic signalling pathways, eventually causing cell death. Interestingly, my findings provided a novel outlook on FOXO3 function in resistant cell lines: its inability to regulate E-cadherin, a function which remained unaltered in the MCF-7 WT cells.

Page | 127

FOXO3 direct regulation of E-cadherin has been shown in numerous instances(Fuxe et al., 2010; Huber et al., 2005; Kato et al., 2006; Le et al., 2008; Naka et al., 2010; Pruitt et al., 2006). Consistently, my data presented E-cadherin which always mirrored FOXO3 expression patterns closely. Thus, the lack of E-cadherin expression coupled with unaltered FOXO3 expression implied FOXO3 loss of function in the resistant cell lines. Sub-cellular fractionation results unveiled increased nuclear activated FOXO3 upon both epirubicin and paclitaxel drug treatment in sensitive cells, with the rise increasing uniformly with treatment duration. Alternatively, MCF-7 EpiR lacked FOXO3 nuclear expression, regardless of treatment duration. Consistently, MCF-7 TaxR presented very low FOXO3 nuclear localisation, with an increase in nuclear phosphorylated FOXO3, suggesting gradual FOXO3 inactivation. My results are in agreement with previously published reports on FOXO3 response to paclitaxel treatment (Sunters et al., 2003, 2006), whereby treatment induced a gradual increase in FOXO3 expression in sensitive MCF-7 cell lines, but not in drug resistant MDA-MB-231 cells. These reports also confirmed this result through confocal analysis of FOXO3 sub-cellular localization in response to paclitaxel treatment.

Overall, my data confirms the hypothesis presented in the first result section, whereby FOXO3 is recruited to the nucleus in response to drug administration to activate the pro-apoptotic pathways. Instead, in the resistant cell lines, FOXO3 is inactivated through phosphorylation to induce cytoplasmic sequestration, as an evasion mechanism to guarantee cell survival through suppression of pro-apoptotic mechanisms. The FOXO3 expression detected in the resistant cell lines through RTq-PCR would therefore correspond primarily to inactive/cytoplasmic FOXO3. In accordance, FOXO3 inactivation will also induce a consequent loss of E-cadherin expression, which was noted in both resistant cell lines. Thus, FOXO3 cytoplasmic sequestration enables drug resistant cells to protect themselves from drug effects, and consequently undergoing EMT. This was verified when Chromatin Immuno-precipitation was utilised to test for FOXO3 enrichment for the Forkhead Response Elements present on the E-cadherin promoter region. As predicted, MCF-7 WT cells presented the highest enrichment, with both resistant cell lines displaying a respective 10-fold (MCF-7 EpiR) and 100-fold (MCF-7 TaxR) reduction in enrichment for that binding area. This confirmed the lack of FOXO3/E-cadherin regulation in the resistant cell lines, and provided a valid potential drug target to correct this dysregulation and hinder cancer progression.

I next attempted to apply this concept by re-instating FOXO3 expression in the sensitive and epirubicin resistant cell lines and analysing the effect on E-cadherin expression. Previous reports have managed to revert a mesenchymal phenotype by over-expressing FOXO3, and consequently increasing E-cadherin expression (Belguise et al., 2007; Shiota et al., 2010b). Instead, FOXO3 transient overexpression in my project was unable to raise E-cadherin levels in the MCF-7 EpiR

Page | 128 cells, causing them to remain undetected. This may be due to the inefficiency of transient overexpression, which could be unable to raise FOXO3 levels sufficiently to induce an effect. Confirmation studies with the establishment of stable FOXO3 over-expressing cell lines could be able to revert the resistant cell lines to that of the parental MCF-7 WT. Alternatively, as FOXO3 transient alteration in expression in sensitive cell lines had a significant and measurable effect on E-cadherin expression, the inability of the over-expressed FOXO3 to alter the E-cadherin levels may be due to E-cadherin promoter methylation or mutational inactivation. For instance, mutational inactivation of the E-cadherin gene (CDH1) has been found in 56% of lobular breast tumours, with a complete loss of E-cadherin protein expression noted in 84% of cases. Alternatively, E- cadherin promoter methylation has been directly linked to EMT (Lombaerts et al., 2006). All alterations in E-cadherin promoter would prevent FOXO3 activation, thereby rendering it overexpression futile. Methylation-specific PCR could unveil whether the E-cadherin promoter has become inaccessible in the resistant cell lines, and thus provide novel treatment strategies.

Finally, the role of FOXO3 was tested in MCF-7 WT and -EpiR mammosphere formation. This assay provided a novel insight into FOXO3 regulation of breast cancer, displaying how alteration in its expression was able to not only alter MCF-7 WT mammosphere formation, but also that of the resistant cell lines. Furthermore, FOXO3 effect on mammosphere formation was consistent with the hypothesis that E-cadherin may present a form of promoter methylation which would render it inaccessible to FOXO3, as FOXO3 was able to significantly affect other aspects of the cancer progression of both sensitive and resistant cell lines. Thus, targeting of FOXO3 could still be a viable therapeutic option to avert the cancer progression of resistant cell lines, as well as a preventative treatment for people with sensitive breast cancers (such as MCF-7 cells) to hinder the development of macro-metastases.

Taken together, these results showed how FOXO3 dysregulation through cytoplasmic sequestration could be one of the main causes for the increased cancer progression abilities displayed by the resistant cell lines. However, its function could further be hindered by its down- stream antagonist, FOXM1. Given FOXM1 more delineated oncogenic function as a promoter of cancer progression, and simultaneous regulator of resistance to cytotoxic therapy, I next analysed whether this transcription factor could contribute to the increase in cancer progression presented by the resistant cell lines.

Page | 129

Chapter 3.3: The role of FOXM1 in the cancer progression of drug resistant cell lines Forkhead transcription factors have been extensively characterised in previous chapters (see Introduction). In essence, Forkhead Box M1 (FOXM1, formerly known as HFH-11, MPP-2, Win, Trident) is a transcription factor that belongs to the superfamily of Forkhead proteins, characteristic for their shared homology in the winged-helix DNA binding domain (Koo et al., 2012). Extensive investigation has revealed its role in human embryo development, as well as its essential functions in cellular homeostasis. It’s primary roles include the regulation of cellular proliferation, cell-cycle progression, cell differentiation, DNA damage repair, tissue homeostasis, angiogenesis and apoptosis (Koo et al., 2012). In adult tissues, its expression is generally limited to actively proliferating tissues, as it can otherwise result in the initiation of cancer. Unsurprisingly, FOXM1 has recently been characterised as an oncogene.

Multiple studies have correlated the expression of FOXM1 with the insurgence of resistance to chemotherapeutic drugs, primarily due its control of genes regulating DNA damage response. Investigations began when in breast cancer cell lines, FOXM1 was found to be overexpressed in taxanes and anthracycline resistant cell lines, when its expression was compared to that in their sensitive counter-parts. Subsequent analysis of the molecular pathways for FOXM1 regulation of the drug resistant phenotype unveiled several candidates. For instance, higher XIAP and Survivin expression were noted in both resistant cell lines, implying a potential anti-apoptotic regulation by FOXM1 upon treatment with chemotherapy (de Moraes et al., 2015). Alternatively, studies on epirubicin resistant breast cancer cell lines concluded that OTUB1 positively regulated FOXM1 expression by limiting its ubiquitination and consequent degradation, enabling FOXM1 to maintain high levels throughout epirubicin treatment (Karunarathna et al., 2015). A similar study on epirubicin resistant cell lines noted that FOXM1 was involved in the direct transcriptional regulation of NBS1, which conversely was coupled to ATM phosphorylation. In this manner, FOXM1 was shown to prevent epirubicin induced senescence, promoting the maintenance of the drug resistant phenotype (Khongkow et al., 2013b). Consistently, FOXM1 expression was found to be correlated with double-strand break repair, with FOXM1 being associated with DNA repair by homologous recombination. This was found to be through the regulation of BRIP1, a key regulator of DSB repair (Monteiro et al., 2013). E2F1 was also shown to be a crucial FOXM1 up- stream regulator in epirubicin resistance of breast cancer cell lines. E2F1 controls FOXM1 through p38-MAPK and its downstream target MK2 (MAPK-activated protein kinase 2) (de Olano et al., 2012). FOXM1 was found to be a mediator of resistant to HER2 monoclonal antibody Herceptin

Page | 130 and paclitaxel in breast cancer, through the direct transcriptional regulation of Stathmin, a tubulin destabilizing protein (Carr, 2010). Alternatively, in a study on ovarian carcinogenesis, FOXM1 was identified as a crucial mediator of paclitaxel resistance through the direct transcriptional regulation of KIF2C (Zhao et al., 2014). A separate study conducted on ovarian cancer revealed a crucial link between paclitaxel or cisplatin resistance and FOXM1 expression (Chiu et al., 2015).

Overall, these studies depict how both epirubicin and paclitaxel resistant breast cancer cell lines depend upon FOXM1 overexpression to maintain the drug resistance. However, FOXM1 has already been shown to regulate alternative cellular processes which are instead capable of making cells undergo cancer progression. These include the EMT, tumour neoangiogenesis, cell migration, invasion, stem-cell phenotype and even metastasis (for details, see Chapter 1: Introduction). This chapter hypothesises that the drug resistance cell lines dependence on FOXM1 overexpression, could indirectly enable the cell lines to attain the cancer progression abilities noted in Results Chapter 3.1. Following confirmation of this, I aimed to modify FOXM1 expression levels to alter its activity, to determine if FOXM1 modulation could revert the cancer progression of the drug resistant cell lines.

Chapter 3.3.1: FOXM1 is overexpressed in epirubicin and paclitaxel resistant cell lines Previous studies have reported that FOXM1 is key in the insurgence and maintenance of drug resistance for both MCF-7 EpiR and MCF-7 TaxR cell lines (Khongkow et al., 2013c; Monteiro et al., 2013). Upon drug treatment, both cell line displayed an increase in FOXM1 expression, which remained constant throughout the treatment. Instead, parental MCF-7 WT cell lines presented decreased FOXM1 basal levels, which then gradually diminished as epirubicin or paclitaxel treatment continued, eventually causing cell death. These studies displayed the resistant cell lines addiction to FOXM1 for the resistance to the treatment’s effect, which is only maintained until FOXM1 expression is heightened.

To properly gauge the role of FOXM1 in the cancer progression of the drug resistant cell lines, an initially analysis was conducted to measure the FOXM1 protein expression levels in MCF-7 WT, MCF-7 EpiR and MCF-7 TaxR cell lines. To do this, individual pellets were harvested and lysed to obtain protein extracts which could be examined using Western-blotting. As shown in Figure 3.1,

Page | 131

Figure 3.3.1 FOXM1 is over-expressed in the resistant cell lines. MCF-7 WT, EpiR and TaxR cell lines were subjected to Western-Blot (A) and RTq-PCR (B) analysis to detect FOXM1 expression levels. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***. Data shown in A are presentative of n=2 independent experiments. Data shown in B are mean and SD of n=2 independent experiments (2 replicates each).

Page | 132

FOXM1 expression levels are increased in both the resistant cell lines when compared to the MCF- 7 WT parental cell lines. The MCF-7 TaxR display the highest FOXM1 expression.

This result displayed that, as predicted, both resistant cell lines maintain an overexpressed FOXM1 to be able to resist the treatment. However, an increase in FOXM1 expression also implies that the resistant cell lines could present other phenotypical and morphological characteristics which have been previously associated with an increase in FOXM1 expression ((Meng et al., 2015)(Song et al., 2015)(Cai et al., 2013). These include all characteristics I noted when studying the drug resistant cell lines, such as the increased migration, self-renewal, angiogenetic and metastatic potential (Chapter 3.1). To determine if altered FOXM1 expression was behind these phenotypical changes, I first examined whether modulating FOXM1 expression could alter the migration capabilities of a cell line which is known for its metastatic abilities: the MDA-MB-231 (Homey et al., 2001; Kim et al., 2012; Lee et al., 2009).

Chapter 3.3.2: FOXM1 can modulate the directional migration of MDA-MB-231 cell lines The MDA-MB-231 cell line was established from the pleural effusion of a patient with metastatic breast cancer in the 1970. This cell line has been classified as triple-negative breast adenocarcinoma, and has since been used to identify the major molecular pathways involved in breast cancer metastasis. Notably, when injected intraventricularly in mice models, these cells metastasize to the bones, brains and the lungs of mice, sites consistent with their behaviour in humans (Kathryn et al., 2012). Given its established behaviour, initial cancer progression assays were performed using this cell line so as to optimise their conditions, and attain an initial assessment of whether FOXM1 could regulate this behaviour.

Wound-healing/scratch assays are simple in vitro experiments that can yield useful information on the directional migration of an adherent cell line in an inexpensive and relatively fast manner. Cells normally undergo directional migration in response to extracellular triggers. During directional migration, cells present a characteristic highly polarized morphology, with an asymmetrical distribution of cytoskeleton, centrosome, Golgi apparatus and membrane trafficking (Honore et al., 2005). In wound healing assays, cells are cultured to obtain a confluent mono-layer, following which the well is scratched to mimic wound-creation. The wound-healing is then monitored at selected intervals to obtain the relevant information on the cell migration (Liang et al., 2007).

Page | 133

Figure 3.3.2 Inhibition of FOXM1 reduces MDA-MB-231 directional migration. MDA-MB- 231 cells were transfected with FOXM1 or NSC siRNA prior to seeding into 6-well plates. Upon confluency, each well was scratched to produce a wound of similar width. The wound was then monitored for 24 hours using a bright-field microscope. A) Bar chart depicting the scratch area reduction at time-points 0, 4, 8 and 24 hours post-scratch. Scratch area was measured using Prism ImageJ software from images taken at said time-points at the same location. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Transfection efficiency was confirmed using RTq-PCR. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= ** ; P<0.001=***; R2, N3 C) Representative images of scratch width at the same location taken at 0, 4, 8, and 24 hours. Scratch outline has been high-lighted in black. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 134

To study the role of FOXM1 in the directional migration of the MDA-MB-231 cell line, MDA- MB-231 were transiently transfected with FOXM1 siRNA or non-specific (NSC) siRNA, which was used as a transfection control. Transfected cells were incubated for 24 hours and then seeded in triplicate wells and allowed to grow into colonies. Colonies were disrupted the following day by harvesting and manual pipetting, following which the cells were re-seeded in triplicate wells in a manner which would ensure the growth of a confluent mono-layer the subsequent day. At that point, cells were scratched in individual wells using a sterilised pipette tip, and cellular growth medium changed to remove all ensuing cell debris. Images of the wound were then taken at 0, 4, 8 and 24 hours, in three different locations x well, using a bright-field microscope. To ensure images were always taken of the same location on the scratch, a marker pen was used to annotate the region from which the image should be taken. All assays were stopped following 24 hours to limit the influence of cellular proliferation on wound closure. Additionally, cells were kept in media reduced of FCS content following the creation of the scratch, to further inhibit cellular proliferation. Collected images were then analysed using ImageJ to quantify the width of the scratch over time, and obtain a rate of cellular migration.

Scratch/wound-healing assays aim to mimic the cell migration which occurs during wound healing in vivo, by selectively enabling cells on the leading edge of the wound to migrate (Liang et al., 2007). Upon the creation of scratch, cells on the edges of the wound migrate to fill-out the gap and re- establish cell-cell contacts. Upon FOXM1 silencing, the directional migration of the MDA-MB- 231 cells was inhibited by 30% within 24 hours, when compared to control transfected cells (Figure 3.2A and C). To ensure transfection efficiency, a pellet was obtained upon seeding the wells to analyse via RTq-PCR for alterations in FOXM1 RNA expression. Figure 3.2B confirms FOXM1 silencing.

These results indicate that FOXM1 displayed an essential role in the directional migration abilities of the highly-aggressive MDA-MB-231 cell line, as its silencing significantly inhibited wound- healing. To confirm this result, and ensure the lack of proliferative influence the wound-healing, I next repeated the experiment using a Boyden-Chamber migration assay.

Chapter 3.3.3: FOXM1 inhibition can diminish MDA-MB-231 migration in a Boyden- Chamber assay As described previously, the Boyden Chamber migration assay is based on a chemo-attractant principle whereby the seeded cells are instigated to traverse a porous membrane to reach the complete media which contains serum, unlike the starved media that is present on the other side of the membrane,

Page | 135

Figure 3.3.3 Silencing of FOXM1 or KIF20A significantly inhibits MDA-MB-231 cell migration. MDA-MB-231 cells were made to transiently silence FOXM1 or KIF20A. Cells were then harvested and placed in the top of the insert in serum free medium. The bottom of the well was instead filled with culture medium containing the normally administered 10% FCS to act as a chemo-attractant. After 24 hours, cells which had crossed the membrane were stained with DAPI and counted under the fluorescent microscope. A) DAPI stained cells were counted and the percentage of total cells which had migrated was calculated. All values were then normalised to control transfected cells. Depicted values were obtained from 2 independent experiments. Student t-test was performed to determine statistical significance with P<0.05 =*; P<0.01= **; P<0.001=***; B) Representative images of migrated cells. Images were taken under the DAPI fluorescent channel. For visualisation purposes, images were rendered black and white via Photoshop. Black dots in figure are representative of the migrated cells. Data shown are mean and SD of n=4 independent experiments (3 replicates each).

Page | 136 where the cells are seeded. Only cells with migration capacities will be able to reach the complete media: these will be fixed and stained with DAPI for quantification with a fluorescent microscope.

To confirm that FOXM1 inhibition could thwart MDA-MB-231 cell migration, MDA-MB-231 cells were made to transiently silence FOXM1 using a FOXM1 siRNA. As a control, the cells were transfected separately with non-specific siRNA. Following seeding in the transwell assay, cells were allowed to migrate for 24 hours prior to DAPI staining and quantification under the fluorescent microscope. Images were taken and analysed using the ImageJ software. Migration of MDA-MB- 231 siFOXM1 cells was made relative to that of control (NSC siRNA) transfected cells to obtain relative migration. An RTq-PCR assay was used to confirm transfection efficiency (Figure 3.3 B).

FOXM1 silencing caused a significant 5-fold reduction in the migration of the MDA-MB-231 cells when compared to control transfected cells (Figure 3.3. A and C). This not only confirmed the data obtained using the wound-healing assay, but displayed the crucial role FOXM1 portrays in the control of cellular migration of this aggressive cell line. This result was also consistent with previous reports stating the importance of FOXM1 in the migration of cell lines. Given the increased FOXM1 basal levels in resistant cell lines (Figure 3.1), and their respective increased migration capabilities noted in Results chapter 1 (Figure 1.2), I hypothesized that FOXM1 could also be key to the migration of the resistant cell lines. To see FOXM1 overexpression could increase the migratory abilities of a cell line, I first mimicked the FOXM1 overexpression characteristic of the resistant cell lines by transiently overexpressing FOXM1 in the parental MCF- 7 WT cells. I then used the transfected cells in a Boyden Chamber assay to determine if this single alteration could grant them the increased migration capacities noted in the resistant cell line.

Chapter 3.3.4: FOXM1 overexpression enables parental MCF-7 WT cells to display enhanced migration. The shift from sensitive to drug resistant MCF-7 cell lines appears to be centred upon a shift in FOXM1 expression, or even just an ability to increase FOXM1 expression when required. This shift has granted the resistant cell lines the capacity to resist the effect of the chemotherapeutic drugs epirubicin (Monteiro et al., 2013) and paclitaxel (Khongkow et al., 2015b). However, both resistant cell lines have also presented a simultaneous increase in their migratory abilities, a capacity which FOXM1 has been shown to regulate in separate studies (Ahn et al., 2015; Cai et al., 2015). If the alteration in FOXM1 expression is the cause for the morphological and phenotypical changes in the

Page | 137

Figure 3.3.4 FOXM1 overexpression enables MCF-7 WT cells to acquire higher migration abilities. MCF-7 WT cells were transiently transfected with PCDNA3-FOXM1 or PCDNA3-EV plasmids and then seeded in the upper chamber of a Boyden-chamber assay in serum-free media. The bottom chamber was instead made to contain complete media. Cells were allowed to migrate for 24 hours, following which migrated cells were fixed and stained with DAPI, and analysed under the fluorescent microscope. A) Bar-chart comparing the migration of MC7-WT cells made to over- express FOXM1 with control-transfected cells. Individual migration was quantified using ImageJ, and then normalised against that of control transfected cells to obtain relative migration. Student t-test was used to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) RTq-PCR was performed to confirm transfection efficiency; C) Representative images of cells transfected with FOXM1 or Control plasmids. Black dots indicate migrated cells. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 138 resistant cell lines, then FOXM1 overexpression in the sensitive cell line should enable these cell lines to increase their migration abilities.

To see if this was the case, I initially transiently overexpressed FOXM1 using a PCDNA3-FOXM1 plasmid in MCF-7 cells, to compare their migration using a scratch/wound-healing assay. Despite the multiple attempts in optimising this assay, these cells were unable to migrate significantly within 24 hours, and never completely covered the gap (results not shown). As these cell lines are known to have a limited migration ability, there was a concern that all the ‘migration’ noted was in fact due to cell proliferation. To avoid data misinterpretation, I therefore switched to using the Boyden- Chamber migration assay for all subsequent experiments.

MCF-7 WT cells were transiently transfected with PCDNA3-FOXM1 to attain FOXM1 overexpression. As performed in previous assays, transfected cells were seeded in a Boyden- Chamber assay and allowed to migrate for 24 hours, prior to membrane fixation and quantification. Migration of FOXM1 transfected cells was made relative to numbers of migrated cells for PCDNA3-EV transfected MCF-7 cells, to obtain a relative migration. As seen in Figure 3.4 A and C, FOXM1 overexpressing MCF-7 cells displayed a significant 2-fold increase in migration in respect to control transfected cells. Transfection efficiency was confirmed using RTq-PCR on pellets obtained prior to cell seeding in the transwell assay (Figure 3.4.B).

This result indicated that transient FOXM1 overexpression in MCF-7 WT cells was sufficient to grant MCF-7 the increased migration properties. Albeit heightened, this increase could be correlated to that of the resistant cell lines, implying that FOXM1 could be a key factor in the increased migration abilities of the resistant cell lines. I therefore next tested this hypothesis.

Chapter 3.3.5: FOXM1 silencing inhibits the migration of epirubicin resistant MCF-7 cells and of paclitaxel resistant MCF-7 cells To determine how crucial FOXM1 is to the increased migratory abilities displayed by the epirubicin resistant MCF-7 cell line (MCF-7 EpiR), their migration was tested in a Boyden- Chamber migration assay following FOXM1 silencing. As with all other transwell assays performed in this report, media complete with serum was used as a chemo-attractant, and the cells were allowed to migrate for 24 hours prior to quantification.

FOXM1 silencing reduced MCF-7 EpiR migration 60%, when made relative to the migration exhibited by the control transfected cells (Figure 3.5 A and C). Again, transfection efficiency was confirmed

Page | 139

Figure 3.3.5 FOXM1 silencing significantly impairs EpiR cell migration. EpiR cells were transfected with FOXM1 siRNA or control siRNA, prior to seeding in a Boyden Chamber Assay membrane in serum-free media. DMEM with 10% FCS was placed at the bottom of the transwell, to act as a chemoattractant. Cells were allowed to migrate for 24 hours, and then fixed and stained with DAPI. Migrated cells were then quantified with the use of a fluorescent microscope. A) Number of migrated cells was counted and compared to that control siRNA wells. Quantified cells were made to be relative to control transfected cells, to obtain relative migration. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; P<0.0001=****; B) RTq-PCR was performed to determine transfection efficiency; C) Representative images of migrated cells (black dots). Black line delineates 100 µm. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 140

Figure 3.3.6 FOXM1 silencing significantly impairs TaxR cell migration. TaxR cells were transfected with FOXM1 siRNA or control siRNA, prior to seeding in a Boyden Chamber Assay membrane in serum-free media. DMEM with 10% FCS was placed at the bottom of the well, to act as a chemoattractant. Cells were allowed to migrate for 24 hours, and then fixed and stained with DAPI. Migrated cells were then quantified with the use of a fluorescent microscope. A) Number of migrated cells was counted and compared to control siRNA wells; Student t-test was performed to determine statistical significance with P<0.05 = * ; P<0.01= ** ; P<0.001=***; P<0.0001=****; B) RTq-PCR was used to detect success of transfection; C) Representative images of migrated cells (black dots). Black line denotes 100 µm. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 141 using RTq-PCR (Figure 3.5 B). As seen in Figure 3.5 C, cell migration following FOXM1 silencing became scarce, confirming the crucial role of FOXM1 overexpression in the phenotypical increase in migration noted in Result Chapter 3.1.2.

The same assay was repeated with the paclitaxel resistant MCF-7 TaxR cells. Again, FOXM1 silencing induced a significant 70% decrease in the migration MCF-7 TaxR (Figure 3.6 A and C). Quantitative Real-Time PCR analysis confirmed FOXM1 silencing had been induced in a significant manner (Figure 3.6 C).

Both results confirmed the hypothesis that FOXM1 is key to the acquired migration abilities displayed by the resistant cell lines, as FOXM1 silencing is able to significantly impair this capacity. As FOXM1 can also regulate other aspects of cancer progression, I next analysed its role in the cancer stem cell properties of MCF-7 WT and its derivative drug resistant counter-parts.

Chapter 3.3.6: FOXM1 can modulate MCF-7 mammosphere formation As described previously (Results 3.1.3), cancer stem-cells are a sub-population of cells which are believed to be the cause of tumour recurrence and drug resistance. These exhibit multiple stem- like characteristics, including the capacity to self-renewal, and that of survival to anoikis. These unique features enable their study using simple mammosphere assays, whereby cells are seeded in non-adherent plates and allowed to form spheroid structures termed ‘mammospheres’. Cells unable to survive anoikis, or lacking self-renewal capacities, will be unable to survive in these culture conditions.

Previous studies have confirmed the role of FOXM1 in the maintenance and promotion of the stem-cell phenotype (Gong and Huang, 2012; Li et al., 2015b). Given FOXM1 ability to regulate the migration abilities of both epirubicin and paclitaxel resistant cell lines, I hypothesised it could also infer on their stem cell capacities. Initially, I tested whether an increase in FOXM1 expression could grant MCF-7 WT cells with the increased mammosphere formation abilities noted both resistant cell lines.

MCF-7 WT cells were made to transiently overexpress FOXM1 using the PCDNA3-FOXM1 plasmid, and subsequently seeded in non-adherent plates in media specifically designed to support mammosphere formation and survival. Mammospheres were allowed to form for 5 days, following which they were manually counted and measured using the ImageJ software. Obtained count numbers were normalised to those obtained from control transfected cells (PCDNA3-EV) to attain a relative mammosphere formation. Again, a sample of cells was taken following transfection and analysed using RTq-PCR to confirm transfection efficiency (Fig. 3.6 B).

Page | 142

Figure 3.3.7 FOXM1 overexpression promotes mammosphere formation and size increase in MCF-7 WT cells. MCF-7 WT cells were transfected with EV control or FOXM1 PCDNA3 plasmids prior to seeding in non-adherent cultures. Cells were left to grow for 5 days, after which resulting mammospheres were counted and photographed. A) Bar-chart illustrating relative mammosphere formation following transfection. Relative mammosphere formation was calculated by comparing the FOXM1 PCDNA3 cell lines percentage to that of the control transfected cells to obtain a fold-change. B) Dot-plot representing the diameter of each mammosphere (measured via ImageJ). C) Representative images of mammospheres formed after 5 days in non-adherent plates. White line denotes 400 µm. D) Transfection efficiency was verified via RTq-PCR. In each instance, Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 143

Figure 3.3.8 MCF-7 WT FOXM1 silencing can inhibit mammosphere formation. MCF-7 WT cells were transfected with FOXM1 or non-specific siRNA prior to insertion in non-adherent cultures. Mammospheres were left to grow for 5 days and then quantified under the bright-field microscope. A) Percentage of mammosphere formation was made relative to control. B) Transfection efficiency was verified using RTq-PCR. C) Individual mammosphere diameters were measured using ImageJ (pal) and are represented in dot-plot. D) Representative images of mammospheres formed under the different conditions. While line denotes 400 µm. In each instance, Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 144

As shown in Figure 3.6 A, FOXM1 overexpression caused MCF-7 WT cells to present a 2-fold increase in the numbers of mammospheres formed, when compared to control transfected cells. Furthermore, these mammospheres displayed a significantly larger diameter (Figure 3.6 D) when measured individually, causing a significant increase in the average of cell diameters (measured in pixels, Figure 3.6 C). Successful FOXM1 overexpression was confirmed through RTq-PCR (Figure 3.6 B). Thus, it appeared that FOXM1 overexpression in MCF-7 WT enabled them to create a greater number of mammospheres which were also larger in size. This was not only consistent with the hypothesis that FOXM1 overexpression could be the cause for the mammosphere ability displayed by the resistant cell lines, but it also confirmed the crucial functioning of FOXM1 in the development of the cancer stem cell phenotype. FOXM1 silencing could therefore be able to reduce mammosphere formation in the resistant cell lines. As MCF-7 WT cells presented a basal mammosphere formation capacity, I first determined whether FOXM1 silencing could be used to inhibit their cancer stem cell phenotype.

MCF-7 WT cells were made to transiently silence FOXM1 using a FOXM1 siRNA. Cells were then seeded in non-adherent cultures, and allowed to grow for 5 days prior to quantification as described in the previous assay. Again, all count numbers were made to be relative to the control transfected cells, to obtain a relative mammosphere formation. In this case, FOXM1 silencing significantly reduced relative mammosphere counts only by 20% (Figure 3.7 A). Mammosphere size was instead reduced by a significant 30% (Figure 3.7 C and D). Transfection efficiency was confirmed by RTq-PCR (Figure 3.7 B).

Overall, this data not only showed that FOXM1 could cause the increase in mammosphere formation displayed by the drug resistant cell lines, but that FOXM1 silencing was also able to reduce mammosphere formation in the parental cell lines, despite their inherently low FOXM1 expression levels. As both drug resistant cell lines presented increased FOXM1 expression, and a consistently higher mammosphere forming ability, I therefore predicted that FOXM1 silencing could greatly hinder their acquired mammosphere forming ability. To see if this was the case, I next repeated the mammosphere assay using the drug resistant cell lines individually, having previously transiently silenced FOXM1.

Chapter 3.3.7: FOXM1 silencing hinders the stem-like potential of MCF-7 TaxR and EpiR If FOXM1 overexpression was the cause of the increased mammosphere potential exhibited by the drug resistant cell lines, then FOXM1 silencing should induce a significant inhibition in their

Page | 145

Figure 3.3.9 FOXM1 silencing impairs EpiR ability to form mammospheres. EpiR cells were transfected with FOXM1 siRNA or control siRNA and seeded in non-adherent culture plates. After 5 days, mammospheres were analysed under the bright-field microscope. A) Bar-chart comparing the number of mammospheres between the control and FOXM1 siRNA transfected cells. Relative mammosphere formation was calculated by comparing the FOXM1 siRNA cell lines percentage to that of the control transfected cells to obtain a fold-change. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Transfection efficiency was assessed using an RTq-PCR. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; C) Dot-plot representing the diameter of each mammosphere (measured via ImageJ). Non-parametric ANOVA was used to test the significance of the result with P<0.05 = *; P<0.01= **; P<0.001=***; D) Representative images of mammospheres formed after 5 days in non-adherent plates. White line denotes 400 µm. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 146

Figure 3.3.10 FOXM1 silencing reduces mammosphere formation and size in MCF-7 TaxR cells. MCF-7 TaxR cells were transfected with NSC or FOXM1 siRNA prior to seeding in non- adherent plates. Cells were left to grow for 5 days, after which resulting mammospheres were counted and photographed. A) Bar-chart illustrating relative mammosphere formation following siFOXM1. Relative mammosphere formation was calculated by comparing the FOXM1 siRNA cell lines percentage to that of the control transfected cells to obtain a fold-change. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Dot-plot representing the diameter of each mammosphere (measured via ImageJ). Non- parametric ANOVA was used to test the significance of the result with P<0.05 = *; P<0.01= **; P<0.001=***; C) Representative images of mammospheres formed after 5 days in non-adherent plates. White line denotes 400 µm. D) Transfection efficiency was verified via RTq-PCR. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 147

Mammosphere formation ability. To determine if this was the case, a mammosphere assay was performed as described above using the MCF-7 EpiR cells which had been subjected to transient FOXM1 silencing mediated by FOXM1 siRNA. Their mammosphere potential was compared to that of control transfected cells.

FOXM1 silencing caused the relative number of mammospheres formed to be reduced by half (Figure 3.8 A) in MCF-7 EpiR cells. Furthermore, it caused the mammosphere size to be significantly diminished (Figure 3.8 C and D). Transfection success was confirmed via an RTq- PCR, as shown in Figure 3.8B.

Given the success of the assay using the MCF-7 EpiR cells, the role of FOXM1 in mammosphere formation was also tested in MCF-7 TaxR cells: A similar scenario was found whereby mammosphere relative counts were reduced by approximately 40% (Figure 3.9A), and individual diameters were found to be, on average, significantly reduced (Figure 3.9 C-D). Again, an RTq- PCR assay was sufficient to prove transfection effectiveness (Figure 3.9 B).

All together, these results confirm the essential role that FOXM1 plays in the development and maintenance of the cancer stem-cell phenotype. Furthermore, they display how a transient overexpression of this gene is sufficient to cause parental MCF-7 WT cells to initiate to portray increased mammosphere forming abilities, both in number and in size. This implied that the resistant’s cell lines necessity of FOXM1 overexpression for the maintenance of resistance to drug administration can also enable them to attain mammosphere formation abilities. Thus, as predicted, when epirubicin resistant MCF-7 EpiR cells and paclitaxel resistant MCF-7 TaxR cells were transiently deprived of FOXM1, their mammosphere forming ability was significantly impaired. When this data was combined with the crucial role FOXM1 portrayed in the regulation of migration, I next speculated on whether FOXM1 silencing would be sufficient to prevent effective in vivo cancer metastasis.

Chapter 3.3.8: FOXM1 knock-down diminishes MDA-MB-231 metastasis in vivo As mentioned previously (Chapter 3.1.4), effective cancer metastasis demands multiple properties from cell lines: these include the capacity to migrate, invade, survive anoikis in the circulation, and undergo self-renewal upon colonisation of a new organ. These are all properties which were found to be significantly impaired by FOXM1 silencing. I therefore investigated on whether FOXM1 silencing would be sufficient to hinder cancer metastasis.

Page | 148

Figure 3.3.11 FOXM1 silencing can reduce MDA-MB-231 metastasis in vivo in zebrafish embryos. MDA-MB-231 cells were transfected with NSC control or FOXM1 siRNA. Following 24 hours, cells were harvested, stained with red-fluorescent CM-DiI and injected into the yolk-sac of 1 dpf Tg(fli:GFP) embryos. 3 dpi, injected embryos were imaged under the fluorescent microscope to detect eventual disseminated cells. Presence of cells outside of the yolk-sac was taken to be representative of metastasis. A) Percentage of total fish injected with FOXM1 siRNA MDA-MB-231 cells, presenting metastatic cell dissemination was normalised to control transfected MDA-MB-231 injected fish. Statistical analysis was inconclusive due to insufficient number of experimental repeats. B) Representative images of embryos at 3 dpi following injection with either NSC control or FOXM1 siRNA. Implanted cells can be visualised under the red- fluorescent channel. Presence of disseminated cell is delineated by white arrows. Green fluorescent channel allows visualisation of embryos blood vessels. C) FOXM1 silencing was verified through RTq-PCR. Data shown are mean and SD of n=2 independent experiments (25 replicates each).

Page | 149

Initially, the hypothesis was tested on the MDA-MB-231 cell line, selected for its aggressive nature and aptitude to metastasize. This cell line had already been shown its higher propensity to metastasis when dissemination was noted in both the head and tail regions of the injected zebrafish embryos (see Results 3.1.4). Now, its metastatic abilities subsequent to FOXM1 silencing were tested, using the zebrafish embryo in vivo model described in results chapter 3.1. As in previous assays, cells were fluorescently labelled using the lipophilic membrane dye DiI. Injections were performed into the yolk-sac of 1 dpf zebrafish Tg(fli:GFP) embryos (which present intrinsic GFP- labelled blood vessels), with the insertion of approximately 150 cells x embryo. Injected embryos were subsequently incubated for 3 days, following which they were subjected to anaesthesia and imaging under the fluorescent microscope to detect the presence of any disseminated cells present outside of the yolk-sac region. These were taken to be representative of metastasis.

In this instance, prior to injection, MDA-MB-231 cells were made to transiently silence FOXM1 with the aid of FOXM1 siRNA. Their metastatic abilities were compared to those exhibited by control transfected cells (NSC siRNA), to obtain relative migration. As shown in Figure 3.10, three days post-injection, control MDA-MB-231 injected embryos displayed disseminated cells in both the head and tail region of the embryo. This was consistent with results displayed in previous assays (Chapter 3.1.4). Instead, upon FOXM1 silencing, the number of injected embryos presenting any form of dissemination was halved (Figure 3.10 A and B), when compared to control injected embryos. As this experiment was only performed twice, statistical analysis was not performed on the percentage of fish presenting any form of metastasis. Nevertheless, this pilot data suggested FOXM1 silencing could significantly hinder the metastasis of aggressive breast cancers. Further experimental replicates would be required to confirm this data.

Results from the pilot data suggested FOXM1 silencing could be sufficient to deter the metastasis of the highly metastatic MDA-MB-231. I therefore next analysed whether it could also revert the resistant cell lines metastatic abilities to that of the non-metastatic parental MCF-7 WT cells.

Chapter 3.3.9: FOXM1 silencing can inhibit the metastasis of the resistant cell lines in vivo FOXM1 proved to be essential for the migration and mammosphere formation abilities of the epirubicin and paclitaxel resistant cell lines. These are abilities which are crucial for the successful metastasis of a cell lines. I therefore hypothesised that FOXM1 silencing could hinder the metastasis of the resistant cell lines.

To test this hypothesis, MCF-7 EpiR and MCF-7 TaxR cells were injected individually into the yolk- sac of 1dpf wild-type zebrafish embryos. In both cases, each cell line was subjected to FOXM1

Page | 150

Figure 3.3.12 FOXM1 silencing can inhibit MCF-7 EpiR metastasis in vivo in zebrafish embryos. MCF-7 EpiR cells were transfected with NSC control or FOXM1 siRNA 24 prior to harvesting for injection into 1 dpf Tg(TRA/NAC) zebrafish embryos. To allow for detection following injection into the yolk-sac of zebrafish embryos, cells were stained with red-fluorescent lipophilic membrane dye CM-DiI (Sigma). Approx. 150 cells were injected into the yolk-sac. Injected fish were imaged under the fluorescent microscope at 3 dpi to detect cells which had disseminated out-side of the yolk-sac region. Presence of cell dissemination was considered to be sign of cellular metastasis. A) Bar-chart displaying percentage of total injected with disseminated cells. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Transfection efficiency was tested using RTq-PCR. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01=**; P<0.001=***; C) Representative images obtained from the over-lap of bright-field and red fluorescent-channel images of 3dpi TRA/NAC embryos injected with NSC control or FOXM1 siRNA EpiR cells. Presence of disseminated cells was high-lighted by white arrows. Data shown are mean and SD of n=3 independent experiments (25 replicates each).

Page | 151

Figure 3.3.13 FOXM1 silencing can inhibit MCF-7 TaxR metastasis in vivo in zebrafish embryos. MCF-7 TaxR cells were transfected with NSC control or FOXM1 siRNA 24 prior to harvesting for injection into 1 dpf Tg(TRA/NAC) zebrafish embryos. To allow for detection following injection into the yolk-sac of zebrafish embryos, cells were stained with red-fluorescent lipophilic membrane dye CM-DiI (Sigma). Approx. 150 cells were injected into the yolk-sac. Injected fish were imaged under the fluorescent microscope at 3 dpi to detect cells which had disseminated out-side of the yolk-sac region. Presence of cell dissemination was considered to be sign of cellular metastasis. A) Bar-chart displaying percentage of total injected with disseminated cells. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Representative images obtained from the over-lap of bright-field and red fluorescent-channel images of 3dpi TRA/NAC embryos injected with NSC control or FOXM1 siRNA EpiR cells. Presence of disseminated cells was high-lighted by white arrows. Data shown are mean and SD of n=3 independent experiments (25 replicates each).

Page | 152 silencing with the use of a FOXM1 siRNA prior to injection. Injections were performed using the same parameters as in previous instance, so as to obtain a percentage of metastasis for each cell line, and each condition. In each case, transfection efficiency was verified using RTq-PCR (Figure 3.12 C and Fig. 3.13 C).

Control transfected MCF-7 EpiR cells migrated to the head region of the zebrafish embryos at 3dpi, as seen in Results Chapter 3.1.4, with 6% of the embryos presenting any form of cellular dissemination. Instead, injection of FOXM1 silenced MCF-7 EpiR completely and significantly disabled the metastatic abilities of these cell lines, rendering it null (Figure 3.11 A-B). Consistently, when the assay was performed with MCF-7 TaxR cells, the cells migrated in 12% of the cases, reaching the head region of the embryo (Fig. 3.12 A-B). This increase in respect to the epirubicin resistant cell line was consistent with that noted Results Chapter 3.1.4, where MCF-7 TaxR displayed a greater metastatic ability that MCF-7 EpiR. Interestingly, when FOXM1 was silenced in MCF-7 TaxR cells, their metastatic ability was completely disabled (Figure 3.12 A-B).

Overall, these results indicate that the dependence on FOXM1 for the acquisition and maintenance of drug resistance is capable of enabling epirubicin and paclitaxel resistant cell lines to successfully metastasize in vivo. Consistent with its crucial role, FOXM1 silencing is instead capable of reverting the resistant cell lines phenotype to that of the parental MCF-7 WT cell line, to the point of its transient silencing being able to completely abolish their heightened metastatic abilities. Furthermore, the latter results indirectly provides further confirmation of the validity of the zebrafish model, displaying how intrinsic changes in the injected cell line can abolish their metastatic potential: the cellular dissemination is therefore due to effective cellular migration, and not to the influence from the hosts immune system, or cellular debris, which would otherwise be present in all conditions.

Chapter 3.3.10: Discussion Previous research has linked FOXM1 to the insurgence and maintenance of drug resistance for both breast cancer cell lines resistant to anthracyclines and taxanes. Alternatively, separate studies have portrayed FOXM1 as key to the acquisition of qualities which render cells of multiple tumours able to undergo cancer progression and ultimately successfully metastasize. This chapter aimed to characterise FOXM1 expression in the both epirubicin and paclitaxel resistant breast cancer cell lines, and to determine its role in the regulation of the cancer progression of these cell lines. If FOXM1 showed a favourable role in the control of the cancer progression of the resistant cell lines, I then aimed to inhibit its activity to test its suitability as a therapeutic target to prevent the cancer progression of the resistant cell lines.

Page | 153

Initial analysis aimed to confirm FOXM1 presented a heightened expression in both resistant cell lines when these were compared to their sensitive counterparts, initially hypothesized due to its role in the regulation of drug resistance. My data FOXM1 confirmed this hypothesis, with FOXM1 showing an expression pattern that could be correlated to the aggressiveness of the cell line: Lowest in MCF-7 cells and highest in the MCF-7 TaxR cell line. This result was not only consistent with previous studies(Khongkow et al., 2015a), but also quasi predictable given the necessity as FOXM1 is the main mediator of their resistance to the administration of the drugs (Karunarathna et al., 2015; Khongkow et al., 2013b, 2015b; Monteiro et al., 2013; de Moraes et al., 2015; Zhao et al., 2014). Furthermore, the correlation between FOXM1 expression and the aggressiveness of the cell line depicted in Results chapter 3.1 implied a potential role for FOXM1 in the regulation of the cancer progression of these cell lines.

Initially, assays were performed using the MDA-MB-231 cell line instead of the drug resistant cell lines. This was due to the reliability of the cell line due to its extensive previous characterisation available in literature, rendering each outcome more predictable, and thus permitting assay optimisation. Unfortunately, despite the success of the use of the wound-healing assay for this cell line, I was unable to utilise this technique for further analysis of migration patterns. Wound-healing assays, sometimes referred to as ‘scratch-assays’, are used to assess the directional migration of adherent cell lines. This assay is often the technique of choice due to its numerous advantages over other available in vitro techniques. For instance, it is believes to be replicative of migration in vivo: directional wound-healing migration is characteristic of endothelial cells upon damaging of the blood vessel endothelium. Moreover, this assay mimics the migration patterns of both loosely connected populations (such as fibroblasts), or sheets of cells (like in the case of epithelial cells) (Liang et al., 2007). However, despite their beneficial relatively small cost and simple methods, this assays are linked to several disadvantages which hinder reliable data extrapolation. For example, cells need to have reached confluency to permit the creation of a ‘clean’ scratch. This fact alone hinders the study of molecular targets, such as FOXM1, as these are most highly expressed during cellular proliferation, and cells will consequently diminish their endogenous expression levels upon the formation of a confluent monolayer. Furthermore, this assay doesn’t allow the distinction between the effect of cellular proliferation and migration upon wound healing. Ideally, proliferation needs to be inhibited with the use of proliferation inhibitors (such as cytosine b-D- arabinofuranoside (Sigma), actinomycin-C (Santa-Cruz), lovastatin (Sigma)) or partial serum starvation (up to 0.1%). However, proliferation inhibitors could again inadvertently affect FOXM1 expression levels, again disrupting the outcome of the study. Finally, altering FOXM1 expression could also modify the proliferation rates of the selected cell line, rendering the final result a

Page | 154 consequence of inhibited/increased proliferation rather than of actual cellular migration. Due to these multitude of factors, all cell migration subsequent to initial wound-healing assays was performed using Boyden-Chamber assays. Despite their increase in expenses, and their inability to track individual cells, these assays are more straight-forward and eliminate the interference of cell proliferation when quantifying alterations in cellular migration.

Despite the inability to quantify all FOXM1 effects on migration using the wound-healing assay, the Boyden chamber assay revealed FOXM1 inhibition could have a significant inhibitory effect on the migration of MDA-MB-231. To examine if FOXM1 overexpression was sufficient to grant drug resistant cell lines the increased migratory abilities noted in Chapter 3.1, I next overexpressed FOXM1 in MCF-7 cells and analysed their migration pattern. The effect of increased FOXM1 expression has been studied in several cancers. All studies reported the same increase in cancer progression properties, namely in EMT (Kong et al., 2014), migration (Ahn et al., 2015; Jiang et al., 2014a), tumour induced angiogenesis (Zhang et al., 2014), cancer stem cell phenotype (Bergamaschi et al., 2014; Joshi et al., 2013) and metastasis (Meng et al., 2015). Due to previous reports, it was expected that an increase in FOXM1 expression would result in the MCF-7 WT cells displaying increased potential to progress in cancer. However, this result did more than confirm previous reports: it displayed how an alteration in the expression of a single gene could cause a drastic change in a cell lines phenotype, which in this case could render a cell line resistant to chemotherapeutic effect, as well as simultaneously enabling it to acquire all the abilities which would make it able to successfully metastasize.

Having gained confirmation that FOXM1 overexpression, even if transient, could cause the parental MCF-7 WT cells to acquire the increased migration and cancer stem cell qualities exhibited by the drug resistant cell lines in Chapter 3.1, I next tried to use FOXM1 as a target to revert their aggressive phenotype. FOXM1 silencing managed to reduce the migration and mammosphere formation abilities by approximately 50% in both cell lines. Despite the significance of the impairment in each instance, FOXM1 silencing was unable to completely abolish their migration and mammosphere formation capacities. It was speculated that this may in part be due to the transient nature of the silencing of FOXM1 attained in these assays: endogenous FOXM1 will remain, in part, still active, and thus able to allow the cells to migrate. Instead, the transient silencing was able to revert the FOXM1 expression levels to those exhibited by the parental MCF- 7 WT cell line. Consistently, both migration and mammosphere formation abilities (in number and size) became comparable to those of MCF-7 WT cells. This was further confirmation of the crucial role FOXM1 overexpression has on the drug resistant acquired abilities. To completely inhibit the migration of the resistant cell lines, it could be attempted to knock-down FOXM1 utilising a

Page | 155

FOXM1 shRNA. However, this will probably be lethal to the cell lines as they rely on FOXM1 to resist the effect of anti-cancer drugs.

FOXM1 is clearly one of the key factors in the regulation of mammosphere formation, affecting both size and numbers, as its transient overexpression was capable of doubling the numbers of mammospheres formed, and rendering them significantly bigger, thus implying an increase in their proliferation rate. Their size had thus become as big as that displayed by the resistant MCF-7 EpiR and TaxR cell lines, while the numbers ranged in between the 0.5 fold displayed by the MCF-7 EpiR and the 3 fold increase depicted by the MCF-7 TaxR. This clearly indicated that if not for all malignant cell lines, for these resistant MCF-7 cell lines, FOXM1 was key to the shift in mammosphere potential.

FOXM1 silencing instead was able to reduce mammosphere formation in MCF-7 WT cells, but this shift remained, albeit significant, relatively small (only 20%) in terms of mammospheres formed. Alternatively, it was slightly larger decrease in terms of mammosphere size (about 30%), indicating the crucial role of FOXM1 in cellular proliferation, even in mammosphere formation. This relatively small reduction in mammosphere formation was attributed to the low levels of FOXM1 normally expressed by the MCF-7 cell lines (Figure 3.1), which meant that there wasn’t sufficient amounts of endogenous FOXM1 to silence in order to have a drastic effect on mammosphere formation.

A final confirmation of the essential role played by FOXM1 in the cancer progression of the resistant cell lines ensues from the inability of the resistant cell lines to metastasize following FOXM1 silencing. This result indicates that their overall metastatic abilities were reverted to those of the parental MCF-7 WT cell line, which was unable to metastasize in Chapter 3.1, when injected in zebrafish embryos. This result was consistent with previous reports of the ability to reduce cancer metastasis upon FOXM1 inhibition in studies performed, amongst others, in gastric (Cai et al., 2015), ovarian (Fan et al., 2015), liver (Park et al., 2011), pancreatic (Quan et al., 2015), lung (Kong et al., 2014) and breast (Rajamanickam et al., 2016). Furthermore, this result also confirmed the validity of the zebrafish model, as the dissemination patterns of each cell line could be inhibited by the silencing of a gene prior to cell injection: if the dissemination was due to cell debris or interaction with the host’s immune system, FOXM1 silencing should not have affected it.

Overall, this chapter shows how FOXM1 could serve as a therapeutic target to not only revert the drug resistant phenotype, but also to prevent its progression to a metastatic state. Several studies are now attempting to use FOXM1 as a drug target for the treatment of a diverse range of cancers. An interesting study has provided evidence of the use of Imipramine Blue for the selective

Page | 156 inhibition of FOXM1 mediated DNA-damage repair by delivering it through a nano-particle based approach: this was shown to be able to selectively target breast cancer cells, while being non-toxic for neighbouring healthy tissues (Rajamanickam et al., 2016). Alternatively, FOXM1 direct inhibition through microRNA-370 showed potential for the treatment of osteosarcoma (Duan et al., 2015). However, limited approaches have so far been delineated for the effective FOXM1 inhibition without significant systemic toxicity. More common approaches instead aim to indirectly inhibit FOXM1 activity by inhibiting a direct transcriptional FOXM1 target, so as to maintain the therapeutic benefits while causing lower toxicity. In the next Chapter, I aim to identify a FOXM1 downstream target which could be used as a drug target to limit the cancer progression of drug resistant cell lines.

Page | 157

Chapter 3.4: The role of KIF20A in the cancer progression of drug resistant cell lines In the previous chapter, transcription factor FOXM1 was shown to be an essential mediator of the cancer progression capacities of both epirubicin and paclitaxel resistant breast cancer cell line. Consistently, its inhibition was shown to be sufficient to completely abolish the in vivo metastatic abilities of these cell lines. However, its central role in the cellular homeostasis of both healthy and neoplastic cells render direct FOXM1 targeting an unattractive approach, due to the ensuing systemic toxicity. It is therefore important to identify a FOXM1 downstream effector which could instead be targeted to revert the metastasis of drug resistant cell lines. Amongst other potential targets, kinesin 20A emerged in this Chapter as a promising candidate.

Kinesins were first discovered in 1985, and have since been subdivided into 45 murine and human kinesin protein superfamilies, typically named kinesin-1 to kinesin-14 according to their subfamily (Gatzeva-topalova et al., 1985). Yu et al., defined them as a ‘conserved class of microtubule- dependent molecular motor proteins that have adenosine triphosphate (ATPase) activity and motion characteristics’ (Yu and Feng, 2010). Kinesins present the characteristic conserved motor domain which is able to bind microtubules and travel their length by generating mechanical force through ATP hydrolysis (Taniuchi et al., 2005a). There are three main kinesin sub-types, classified according to the position of their motor domain, crucial to their function as it contains both the ATP-binding and microtubule-binding consensus sequences: amino-terminal type, middle-type and carboxy-terminal type. (Nobutaka et al., 1998). Kinesins are known to contribute to numerous cellular functions, namely during mitosis by regulating the formation of mitotic spindles and chromosome separation, or in the intracellular transport of organelles and vesicles (Nobutaka et al., 1998).

Structurally, kinesins present four domains: the motor, neck, stalk and tail. The motor domain is composed of up to 360 amino acids and is attached to the stalk domain, which is instead long with a central coil that is connected to the tail domain. The motor domain presents both an ATP binding site and an adjacent microtubule binding site. Its primary role is to generate energy through ATP hydrolysis to promote the movement of proteins along the microtubule fibres. Alternatively, the neck domain displays sub-type specificity, which is crucial for the determination of movement direction. The stalk domain instead functions for interface with alternate subunits of the holoenzyme, and doubles up to create the kinesin dimer. Finally, the tail domain carries the cargo molecules, which can vary between proteins, lipids or nucleic acids. This is found at the opposite end of the protein (Yu and Feng, 2010).

Page | 158

The 14 kinesin sub-groups can be distinguished into the N-kinesin, M-kinesins, and C-kinesins, according to the area in which they carry the motor domain (amino-, middle- or carboxyl- terminus respectively). This influences their directional movement, with N-kinesins undergoing a plus-end direction, the C-kinesins preferring a minus-end directed transport and the M-kinesins thriving on microtubule depolymerisation (Yu and Feng, 2010). This divergence allows the function of the kinesins to vary from synaptic vesicle transportation in neuronal axons to chromosomal segregation in mitosis (Yu and Feng, 2010).

Of late, kinesins have started to emerge as regulators of cell migration. For instance, mitotic centromere-associated kinesin (MCAK, KIF2C) was found to be up-regulated in gastric cancer patient samples. Its overexpression was able to increase the cell’s ability to migrate, as well as its resistance to anoikis in vitro (Nakamura et al., 2007). Another study on pancreatic cancer identified the mitotic kinesin Eg5 as an essential mediator of migration and invasion (Sun et al., 2011). Alternatively, a study on breast cancer MDA-MB-231 cells concluded that WAVE2, a member of the WASP/WAVE family of actin cytoskeleton regulatory proteins, was carried to the leading edge of the cellular periphery through the kinesin 5B. This would mediate lamellopodia formation, thus mediating cell migration (Takahashi and Suzuki, 2008). A second study performed on breast cancer patients noted that KIF18A expression was correlated with tumour grade, metastasis and poor survival. Furthermore, KIF18A silencing proved sufficient to inhibit breast cancer cell migration and induce anoikis through microtubule stabilization at the leading edge and eventually causing inactivation of the PI3K-Akt signalling pathway(Zhang et al., 2010).

Kinesin family member 20A (KIF20A, a.k.a. RAB6KIFL, Rab6-interacting kinesin-like Protein, Mitotic kinesin-like protein 2) is part of the kinesin protein family. Recent evidence had portrayed the essential role of KIF20A in cytokinesis, noted due to its accumulation in the mid-zone of the spindle during anaphase and cleavage furrow mid-body during telophase, with its silencing resulting in multinuclear cells (Hill et al., 2000). Alternatively, KIF20A novel role as a main regulator of breast cancers resistance to paclitaxel treatment has recently emerged. In this study, KIF20A silencing was shown to have a similar effect as paclitaxel treatment, with the promotion of abnormal spindle morphology and chromosomal alignment, and the inevitable induction of mitotic catastrophe-dependent senescence. KIF20A deregulation was thus able to mediate paclitaxel drug resistance (Khongkow et al., 2015a).

Of particular interest are recent studies focusing on the role of KIF20A in cancer cell migration: for instance, in pancreatic cancer, KIF20A was shown to promote the motility and invasiveness through its transport of the RNA-binding protein IGF2BP3 and IGF2BP3-bound towards cell

Page | 159 protrusions at the leading edge (Taniuchi et al., 2014). KIF20A is currently being used as a target antigen in immunotherapy peptide vaccines for the treatment of advanced pancreatic cancer. Its selection as a target was due to its significant up-regulation in the majority of pancreatic cancers (Taniuchi et al., 2005a). To diminish its expression in patients with advanced pancreatic cancers, a KIF20A-66 epitope peptide was created and administered in a Phase I and Phase II clinical trial. Its use reported the effective induction of peptide-specific response by cytotoxic T-lymphocytes (CTL), with good tolerability, successfully improving patient prognosis (Asahara et al., 2013). This study recently prompted the analysis of KIF20A expression in melanoma cases, so as to use this peptide as a target for treatment against advanced melanoma. Its expression was found to be correlated with disease progression, as well as to be up-regulated in most melanomas compared to control tissues (Yamashita et al., 2012).

Given the correlation with KIF20A and paclitaxel resistance, as well as the few studies reporting a role for KIF20A in cancer migration, I aim to delineate the relationship between FOXM1 and KIF20A, as well as the role of KIF20A in the cancer progression of sensitive and drug resistant cell lines.

Chapter 3.4.1: Selection of FOXM1 downstream targets FOXM1 is a transcription factor which exerts its proto-oncogenic role through the regulation of selected downstream targets. As targeting FOXM1 directly could be fatal to healthy cells, targeting a FOXM1 downstream target could offer the therapeutic benefit of allowing the inhibition of FOXM1 function, without causing toxicity in healthy cells.

Determining a suitable FOXM1 downstream target for this purpose required careful selection. Initially, a sub-set of candidate genes was obtained based on micro-array data previously attained in the lab (data not shown). The microarray enabled to detect gene expression response to a wide array of potential target genes following FOXM1 modulation. From this, several targets were selected for validation of direct FOXM1 regulation due to their high response to FOXM1 alteration. Analysed candidates included Kinesin 20A (KIF20A), Kinesin 2C (KIF2C), Kinesin 23 (KIF23), antibody KI-67 (MKI67), Kinesin 3C KIF3C), Kinesin C3 (KIFC3), PAK4, kinesin 1C (KIF1C), kinesin 4A (KIF4A), kinesin 18B (KIF18B), kinesin 14 (KIF14), kinesin 11 (KIF11), kinesin 15 (KIF15), kinesin 7 (KIF7), Aurora kinase A (AURKA), Aurora kinase B (AURKB), Topoisomerase IIα (TOP2A), pituitary tumour transforming 1 (PTTG1), cyclin A2, B1 and B2 (CCNB1, CCNB2, CCNA2), ribonucleotide reductase M2 (RRM2), protein regulator of cytokinesis 1 (PRC1) and baculoviral IAP repeat-containing 5 (BIRC5). Initially, targets were analysed for the pattern in their expression levels in the epirubicin resistant cell line MCF-7 EpiR

Page | 160 to determine if they responded to treatment in a manner comparable to FOXM1. This would imply a potential correlation with FOXM1. Furthermore, analysis of the expression pattern could reveal possible influence in the insurgence or maintenance of drug resistance for the MCF-7 EpiR cell lines. FOXM1 and FOXO3 levels were also monitored simultaneously to enable comparison between the targets and the transcription factors.

To detect the transcriptional expression patterns of the selected genes, MCF-7 WT and MCF-7 EpiR were treated with 1 µM epirubicin for the time period of 0, 4, 8 or 24 hours. Ensuing cells were then harvested and pellets lysed for RNA extraction and subsequent RTq-PCR was performed. All obtained quantification was normalised to L19, a house-keeping gene, to detect any increase or decrease in transcription. Figure 4.1 shows a subset of analysed targets, namely Kinesin 20A (KIF20A), kinesin 2C (KIF2C), monoclonal antigen Ki67 (MKI67), Kinesin C3 (KIFC3), Kinesin 3C (KIF3C), Kinesin 23 (KIF23) and p21 activated-kinase 4 (PAK4). As seen in Figure 4.1, FOXM1 expression was increased at 8 h hours in sensitive MCF-7 WT cells, following which it was reduced at 24 h. FOXM1 remained relatively constant throughout treatment in the MCF-7 EpiR cells. This pattern was consistent with previous literature depicting the role of FOXM1 in drug resistance to epirubicin treatment through the activation of the DNA damage response (Khongkow et al., 2013c). Alternatively, consistent with what seen in Results Chapter 2, FOXO3 displayed a gradual increase in expression in sensitive cell lines through-out treatment, and a relatively constant pattern in epirubicin resistant cell lines. KIF20A, KIF2C, MKI67 and KIF23 all portrayed a pattern similar to that of FOXM1, whereby their expression was gradually reduced through-out treatment in sensitive cells, and their expression remained constant in resistant cells. Alternatively, KIF3C, KIFC3 and PAK4 all appeared to present a pattern close to that of FOXO3, where the expression increased as the epirubicin treatment was extended in sensitive cell lines, and it remained relatively constant in resistant cell lines.

Page | 161

Figure 3.4.1 Selection of FOXM1 down-stream targets based on behavioural similarities upon epirubicin treatment. MCF-7 WT and MCF-7 EpiR cell lines were treated with 1µM epirubicin for0, 4, 8 or 24 hours. Treated cells were harvested and subjected to analysis through RTq-PCR or Western-Blot to determine potential down-stream target expression. A) RNA expression of FOXM1, KIF20A, KIF2C, MKI67, KIF3C, FOXO3, KIFC3, KIF23 and PAK4 expression was normalised to L19. T-test of each value was performed against untreated control value with P<0.05 = *; P<0.01= **; P<0.001=***; B) Protein expression was compared between FOXM1, KIF2C, PAK4, and KIF20A. B-tubulin was used as a loading control. Data shown in A are mean and SD of n=4 independent experiments (3 replicates each). Data shown in B are representative of n=2 independent experiments.

Page | 162

Due to promising RNA expression patterns, protein expression patterns of KIF20A, KIF2C and PAK4 were also verified via Western-blotting. Cells were treated in the same manner, and pellets harvested for cell lysis. FOXM1 expression was also verified for comparison purposes. Β-Tubulin, a house-keeping gene, was used as a loading control. As shown in Figure 4.1B, FOXM1 displayed a pattern consistent with that detected via RTq-PCR, with a slight increase at 8 hours and an overall decrease in sensitive cell lines, while its levels remained relatively constant in the resistant cells. KIF20A, PAK4 and KIFC presented the same patterns detected during RTq-PCR, with both KIF20A and KIF2C displaying a gradual decrease and PAK4 and increase in sensitive cells.

Targets were selected for further validation if their expression levels were significant in epirubicin resistant cell lines, and did not diminish upon drug treatment, as this implied they may have a role in the maintenance of the resistance to the administered drugs, or in other areas crucial for the phenotype of the cell. Potential FOXM1 regulated targets selected for future studies included KIF2C, KIF20A and MKI67. To determine the nature of their interaction, these were analysed following transient alteration in FOXM1 expression levels.

Chapter 3.4.2: KIF20A pattern follows that of FOXM1 Following an initial analysis of potential target response to epirubicin treatment, promising candidates were examined on their response to transient alteration in FOXM1 expression. Initially, FOXM1 expression was increased in MCF-7 WT cells using transient transfection mediated by pcDNA3-FOXM1. pcDNA3-EV was used as a transfection control. Transfected cells were harvested and the pellets lysed for RNA extraction. Expression levels following FOXM1 overexpression were compared to those of control transfected cells. L19 was used as a transcriptional control. Figure 4.2A displays the effect of FOXM1 overexpression on KIF2C, KIF20A and MKI67 expression: a significant increase in expression was noted in all selected proteins.

Next, the targets were examined for their response to FOXM1 silencing. To do this, the epirubicin resistant MCF-7 EpiR cell line was selected, as it presented increased FOXM1 expression compared to MCF-7 WT cells (Result Chapter 3.3.1): This would permit a more substantial physiological response to FOXM1 silencing. FOXM1 silencing was performed via the use of a FOXM1 siRNA, and the alterations in expression compared to those presented by control transfected cells (NSC siRNA). Again, analyses was performed using RTq-PCR, with all values normalised to L19. As displayed in Figure 4.2B, only KIF20A and MKI67 displayed a significant decrease upon FOXM1 silencing, while KIF2C levels were reduced, albeit not significantly.

Page | 163

Figure 3.4.2 Effect of FOXM1 alteration on potential down-stream target expression. FOXM1 expression levels were altered and the response of potential down-stream targets measured with either RTq-PCR or western-blot. A) MCF-7 WT cells were made to transiently over-express FOXM1. Corresponding response of KIF20A, KIF2C and MKI67 was recorded through RTq-PCR. B) MCF-7 EpiR were made to transiently silence FOXM1. Resulting alteration in expression of KIF20A, KIF2C and MKI67 was detected using RTq-PCR. C) FOXM1 expression was compared between MCF-7 WT cells, and stably FOXM1 over-expressing MCF-7 WT cells (termed MCM-7). Alteration in expression of KIF020A, KIF2C and KIF23 expression was measured in both cell lines. In each instance, Student t-test was performed against the transfection control with P<0.05 = *; P<0.01= **; P<0.001=***; D) Effect of transient FOXM1 overexpression in MCF-7 WT cells on protein expression of KIF20A and KIF2C through Western-blot. B-tubulin was used as a loading control. E) MCF-7 WT cells were subjected to FOXM1 silencing or control siRNA. Expression levels of KIF20A, KIF2C and PAK4 were analysed using western-blot. B-tubulin was used as a loading control. Data shown in A, B, C are mean and SD of n=2 independent experiments (3 replicates each). Data shown in D and E are representative of n=2 independent experiments.

Page | 164

Finally, target validation was performed comparing target expression in a stable overexpressing FOXM1 cell line previously created in the lab (MCM-7), with that in MCF-7 WT cells. A final RTq-PCR was performed using stably FOXM1 overexpressing cells, to verify that upon stable FOXM1 overexpression the potential downstream targets would also present a corresponding increase in their expression. The expression of the targets was compared with that exhibited by parental MCF-7 WT cells. Consistently with previous results, only KIF20A and MKI67 displayed a corresponding significant increase in expression in MCM-7 cells when compared to MCF-7 WT cells, while KIF2C was increased, albeit again not significantly (Figure 4.2C).

Simultaneously, further verification was obtained via the use of Western blotting, to detect if alteration in FOXM1 would provoke changes in potential target protein expression. Initially, the effect of FOXM1 overexpression on KIF20A and KIF2C was verified by transient FOXM1 overexpression in MCF-7 WT cells. Β-tubulin was used as a loading control. Protein expression levels were compared between FOXM1 and control transfected cells. As seen in Figure 4.2D, only KIF20A showed an increase in expression upon FOXM1 overexpression, while KIF2C levels remained unaltered.

FOXM1 was subsequently silenced in the same cell line, and its effect visualised via Western-Blot. Again, β-tubulin was used as a loading control, and alterations were gauged by comparing them with control transfected cells. Consistently with previous results, only KIF20a displayed a decrease equivalent to that of FOXM1, while KIF2C expression remained stable (Figure 4.2E).

Altogether, these results enabled the narrowing of the target selection to KIF20A and MKI67, as these appeared to mimic FOXM1 alterations in expression. Due to inconsistencies, the study of KIF2C was no longer pursued. Furthermore, MKI67 already presented numerous studies depicting its role in cancer progression, rendering any research performed on it lacking in originality(Anastas and Moon, 2013; Fallis, 2013; Iqbal et al., 2013; Lam et al., 2013; Lebeau, 2010; Li et al., 2015a; Lombaerts et al., 2006; Marangoni et al., 2009; Rampazzo et al., 2013). KIF20A was therefore chosen as a potential FOXM1 downstream target, which could be used for the study of the cancer progression of drug resistant cell lines. Next, given the similarity upon variations in FOXM1 expression, I investigated on the nature of the interaction between FOXM1 and KIF20A.

Chapter 3.4.3: FOXM1 controls KIF20A through direct transcriptional regulation The fact that KIF20A response to FOXM1 alteration implied the possibility of direct FOXM1 regulation; however the nature of this interaction remained to be understood. Initially, a Chromatin Immunoprecipitation (ChIP) analysis was kindly performed by Dr. Parasat Khongkow on MCF-7 WT cells, to identify if FOXM1 was able to bind to the putative Forkhead Responsive Element

Page | 165

(FHRE) present at the region -22/+144 mapped downstream of the most 5’-transcription start site, but upstream of the second transcription start site, mapped at (+163; Ensembl KIF20A-002 transcript). Primers were designed to amplify the +80 bp region containing the FHRE during ChIP, so as to determine FOXM1 binding with RTq-PCR. Results showed how FOXM1 overexpression could induce an increase in the binding of FOXM1 to KIF20A promoter region, and FOXM1 silencing could in turn reduce this (results shown in (Khongkow et al., 2015a).

Following validation of FOXM1 regulation of KIF20A through direct binding to the promoter region, I sought to verify whether this regulation was through FOXM1 direct binding to the FHRE present on the KIF20A promoter region. To do this, a luciferase reporter construct was created containing the 0.3Kbp (-134/+202 bp) KIF20A promoter sequence with none, one or both FHRE mutated (Figure 4.3). MCF-7 WT cells were transfected simultaneously with individual luciferase constructs as well as with increasing amounts of pcDNA3-FOXM1 (0, 10, 20, 30, and 100 ng). FOXM1 binding to the FHRE would cause an increase in the production of luciferase, which could then be detected and measured using a luminometer in the presence of the luciferin substrate and ATP. In this instance, renilla was used as a transfection control. All values were normalised to renilla to obtain relative light emission. Statistical analysis was always performed comparing subsequent FOXM1 concentrations to control levels (0 ng).

Figure 4.3 A-C displays the effects of increasing FOXM1 co-transfection with individual plasmids. The KIF20A WT transfection resulted in a significant increase in light emission corresponding to the increase in FOXM1 concentration. This indicated that FOXM1 was able to bind and initiate transcription at one or both of the potential sites. The KIF20A MUT1 plasmid reduced the luciferase emission by 7-fold, with only higher FOXM1 concentrations (30, 50,100) inducing a significant increase, albeit of less than 2-fold. This implied that without ‘Site 1’, FOXM1 was unable to bind to the region of KIF20A proximal to the promoter, and initiate transcription. The KIF20A MUT2 luciferase plasmid, containing both potential transcription binding sites mutated, presented a similar pattern to MUT1, whereby there was a 7-fold reduction in signal transduction, and only selected concentrations (10, 50 and 100 ng) produced a significant alteration from luciferase emission at control levels, albeit all displaying a decrease. Overall, these results indicated that site 1, located at -80bp, is the primary putative FHRE, from which FOXM1 can perform direct transcriptional regulation of

Page | 166

Figure 3.4.3 FOXM1 regulates KIF20A by binding directly to its promoter region. Luciferase reporter assay was performed with PGL3-KIF20A- WT plasmid (above) and PGL3- KIF20-MUT1 or MUT2 (point mutations highlighted below) in MCF-7 WT cells. PGL3 plasmids contained predicted KIF20A FOXM1 binding site, with PGL3-KIF20A-MUT containing a point mutation in the binding site. In each instance, cells were co-transfected with increasing concentrations of PCDNA3-FOXM1 (0, 10, 20, 30 and 100 ng/µl). Cells were also transfected with renilla as a transfection control. To determine significance, luciferase/renilla values were compared to control (0 ng/µl PCDNA3-FOXM1), with P<0.05=*, P<0.01=**, P<0.001=***. Data shown are mean and SD of n=3 independent experiments (6 replicates each).

Page | 167

KIF20A. Had site 2 been the primary site, luciferase emission would not have been disrupted when site 1 had been mutated individually. Instead, both mutations in site 1 alone, or combined with site 2, caused the same significant decrease in luciferase emission, thus confirming the hypothesis. Overall, these results validate that KIF20A is a direct transcriptional FOXM1 target. Having confirmed the nature of the interaction, I next investigated if KIF20A could contribute to the cancer progression of drug resistant cell lines, in a manner comparable to FOXM1.

Chapter 3.4.4: KIF20A is overexpressed in aggressive MDA-MB-231 cells as well as in drug resistant MCF-7 cells Prior to performing any assay on cancer progression by KIF20A, I assessed if KIF20A could contribute to aspects of cancer progression by measuring its expression levels in the different cell lines. If KIF20A expression proved to be higher in more aggressive cell lines, when compared to epithelial MCF-7 WT, this could be an indication that it may play a role in the cancer progression of these cancer cell lines.

To measure KIF20A expression in the different cell lines, these were harvested and lysed for analysis via Western-blotting. MCF-7 WT expression levels were initially compared to MDA-MB- 231 expression levels. Subsequently, MCF-7 WT expression levels were compared to MCF-7 EpiR and TaxR. In each case, β-tubulin was used as a loading control.

Figure 4.4A shows the protein expression levels of MCF-7 WT and MDA-MB-231 cells: KIF20A displayed a clearly higher expression in the aggressive MDA-MB-231 cells. Figure 4.4B instead compared MCF-7 WT, MCF-7 EpiR and MCF-7 TaxR cell lines. Again, KIF20A displayed a higher expression in the two resistant cell lines, with particularly higher expression in the MCF-7 TaxR cell line.

Overall, KIF20A protein expression patterns correlate meaningfully with the level of aggressiveness displayed by the individual cell lines in Results Chapter 3.1. This is consistent with previous immunohistochemistry data reporting KIF20A overexpression in breast cancer patient samples (Khongkow et al., 2015a). KIF20A could therefore have a role in the cancer progression of the drug resistant cell lines, and of the aggressive MDA-MB-231 cells. To see if this was the case, the role of KIF20A was analysed in individual aspects of cancer progression in these cell lines.

Page | 168

Figure 3.4.4 KIF20A expression across different breast cancer cell lines. Western-blot analysis was performed to compare KIF20A protein expression between MCF-7 WT, MCF-7 EpiR, MCF-7 TaxR and MDA-MB-231 cell lines. B-tubulin was used as a loading control. Data shown representative of n=2 independent experiments.

Chapter 3.4.5: KIF20A can control the directional migration of MDA-MB-231 cells KIF20A displayed the highest expression in MDA-MB-231 cells. As this cell line is the most prone to undergo cancer progression amongst all the other ones used in this project, I initially assessed whether KIF20A overexpression could influence the directional migration of the MDA-MB-231 cells. To do this, a wound-healing/scratch assay was employed, as this assay had previously displayed high efficiencies with this cell line (see Results 3.3.2).

MDA-MB-231 cells were made to transiently silence KIF20A through the use of a KIF20A siRNA. As a control, MDA-MB-231 cells were transfected with non-silencing siRNA. These were then seeded to obtain a confluent monolayer, with three well-replicates per cell condition. The centre of each well was scratched with a sterile pipette tip, to obtain a wound. Images of the wound were taken at time points 0, 4, 8 and 24 hours, ensuring these were of the same location. Cells were kept in starved medium conditions for the duration of the wound-healing imaging. Wound-width was then quantified using ImageJ. Migration was compared to that of control transfected cells. Transfection efficiency was verified using RTq-PCR (Figure 4.5B).

Directional migration of KIF20A silenced MDA-MB-231 cells was significantly impaired from 4 hours post-scratch when compared to control transfected cells (Figure 4.5 A and C). However, the most

Page | 169

Figure 3.4.5 Inhibition of FOXM1 reduces MDA-MB-231 directional migration. MDA-MB- 231 cells were transfected with KIF20A or NSC siRNA prior to seeding into 6-well plates. Upon confluency, each well was scratched to produce a wound of similar width. The wound was then monitored for 24 hours. A) Bar chart depicting the scratch area reduction at time-points 0, 4, 8 and 24 hours post-scratch. Scratch area was measured using Prism ImageJ software from images taken at said time-points at the same location. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Transfection efficiency was confirmed using RTq-PCR. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; C) Representative images of scratch width at the same location taken at 0, 4, 8, and 24 hours. Scratch outline has been high-lighted in black. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 170

Figure 3.4.6 Silencing of FOXM1 or KIF20A significantly inhibits MDA-MB-231 cell migration. MDA-MB-231 cells were made to transiently silence FOXM1 or KIF20A. Cells were then harvested and placed in the top of the insert in serum free medium. The bottom of the well was instead filled with media containing usual amounts of FCS to act as a chemoattractant. After 48 hours, cells which had crossed the membrane were stained with DAPI and counted under the fluorescent microscope. A) DAPI stained cells were counted and the percentage of total cells which had migrated was calculated. All values were then normalised to control transfected cells. Depicted values were obtained from 2 independent experiments. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Representative images of migrated cells. Images were taken under the DAPI fluorescent channel. For visualisation purposes, images were rendered black and white via Photoshop. Black line denotes 100 µm. White dots in figure represent migrated cells. Data shown are mean and SD of n=4 independent experiments (3 replicates each).

Page | 171 significant impairment was noted at time point 24 h, where 52.78% control transfected wound remained uncovered, compared to 73.22% of siKIF20A transfected cells. This indicated that KIF20A silencing was able to significantly impair the directional migration of MDA-MB-231 cells, implying an essential role for KIF20A in the migration of this cell line. However, as KIF20A has also previously been shown to be able to regulate cell proliferation(Zou et al., 2014), which could affect the outcome of a wound healing assay, I subsequently used a Boyden-Chamber migration assay to confirm this result.

Chapter 3.4.6: KIF20A silencing significantly inhibits the migration of MDA-MB-231 cells To verify the role of KIF20A in the migration of the MDA-MB-231 cells, a Boyden-chamber transwell assay was utilised. As in the previous assay, MDA-MB-231 cell lines were made to transiently silence KIF20A prior to seeding in starved medium on the transwell porous membrane. Their migration was compared to that of control transfected cells. Media supplemented with serum was used as a chemo-attractant. Cells were allowed to migrate for 24 hours prior to cell fixing and DAPI stain, to enable imaging. Migrated cells were quantified using the ImageJ software. Numbers were made relative to the control transfected cells to obtain a relative migration. Transfection outcome was verified using RTq-PCR.

MDA-MB-231 migration was significantly impaired upon KIF20A silencing, with a 2-fold decrease when compared to the control transfected cells (Figure 4.6 A and C). Successful KIF20A silencing was verified using RT-q-PCR (Figure 4.6B). This result was consistent with the directional- migration analysis, and it indicated that KIF20A had a role in migration which was distinct from its influence on cellular proliferation. To determine whether this function was also valid for the increased migration of the epirubicin and paclitaxel resistant cell lines, the same assay was subsequently repeated with these cell lines.

Page | 172

Figure 3.4.7 KIF20A silencing significantly impairs MCF-7 EpiR migration. MCF-7 EpiR cells were transfected with KIF20A siRNA or control siRNA, prior to seeding in a Boyden Chamber Assay membrane in serum-free media. DMEM with 10% FCS was placed at the bottom of the well, to act as a chemoattractant. Cells were allowed to migrate for 24 hours, and then fixed and stained with DAPI. Migrated cells were then quantified with the use of a fluorescent microscope. A) Number of migrated cells was counted and compared to control siRNA wells; Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Representative images of migrated cells (black dots). Black line denotes 100 µm. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 173

Figure 3.4.8 KIF20A silencing significantly impairs MCF-7 TaxR cell migration. MCF-7 TaxR cells were transfected with KIF20A siRNA or control siRNA, prior to seeding in a Boyden Chamber Assay membrane in serum-free media. DMEM with 10% FCS was placed at the bottom of the well, to act as a chemoattractant. Cells were allowed to migrate for 24 hours, and then fixed and stained with DAPI. Migrated cells were then quantified with the use of a fluorescent microscope. A) Number of migrated cells was counted and compared to control siRNA wells; Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Representative images of migrated cells (black dots). Black line delineates 100 µm. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 174

Chapter 3.4.7: KIF20A influences the migration of both epirubicin and paclitaxel resistant cell lines As stated previously, performing wound-healing assays requires the use of a cell line which is able to easily attain confluency, and simultaneously display clear phenotypical migration capabilities. As the MCF-7 WT cells hindered the completion of the assay due to their propensity to proliferate, rather than migrate, I opted for using the Boyden-Chamber assay directly for the migration assays of the MCF-7 derivative drug resistant cell lines.

As performed with the MDA-MB-231 cell lines, MCF-7 EpiR and MCF-7 TaxR cell lines were made to transiently silence KIF20A via the use of KIF20A siRNA. Their migration was compared and made relative to that of control transfected cells. Again, media complete with serum was used as a chemo-attractant and all transfections were verified via RTq-PCR (Figure 4.7 B and 4.8B).

MCF-7 EpiR cell migration was significantly diminished upon KIF20A silencing, with a significant 50% reduction when compared to that of control transfected cells (Fig. 4.7 A and C). MCF-7 TaxR migration was instead diminished by only 30% when compared to control transfected cells (Fig. 4.8 A and C). Albeit the latter reduction in migration being less imposing as the one displayed by the MCF-7 EpiR cells, this was still significant, and it rendered the migration of the MCF-7 TaxR cells sparse. Altogether, these results indicated that KIF20A played an essential role in the migration of the triple-negative MDA-MB-231 cells, as well as for the drug resistant cell lines. Furthermore, the resulting significant reduction in migration upon KIF20A silencing implied that KIF20A could be used as a drug target to significantly impair the migration of the drug resistant cell lines, instead of FOXM1. Next, given the crucial role played by KIF20A in cell migration, I analysed whether KIF20A could also be used to impair other aspects of the cancer progression of the drug resistant cell lines.

Chapter 3.4.8: KIF20A is essential for the mammosphere formation of MCF-7 WT cells In previous data, I showed how resistant cell lines were able to form more and larger mammospheres when placed in non-adherent cultures, compared to their parental sensitive counterparts. I then showed how both FOXO3 and FOXM1 could influence this capacity, with particular emphasis on how FOXM1 was crucial to the cancer stem-cell phenotype of the resistant cell lines. As KIF20A proved to be a direct transcriptional downstream target of FOXM1, with a significant role in cell migration, I next analysed its role in the development and maintenance of the cancer stem cell phenotype.

Page | 175

Figure 3.4.9 KIF20A overexpression can increase number but not size of mammospheres in MCF-7 WT cells. MCF-7 WT cells were transfected with POBT7-KIF20A and placed in non- adherent cultures. Mammospheres were allowed to form for 5 days prior to quantification. A) Percentage of mammosphere formed under each condition was made relative to that of control transfected cells to obtain a relative mammosphere formation. B) Individual mammosphere diameters were measured using Image J for each condition. C) Representative images of mammospheres formed. D) RTq-PCR was performed to confirm transfection efficiency. In each instance, Student t-test was performed to determine statistical significance, with P<0.05 = *; P<0.01= **; P<0.001=***. Black line delineates 100 µm. Data shown are mean and SD of n=4 independent experiments (3 replicates each).

Page | 176

Figure 3.4.10 KIF20A silencing impairs MCF-7 WT mammosphere formation. MCF-7 WT cells were subjected to KIF20A silencing through KIF20A siRNA, or transfected with control siRNA. Cells were placed in non-adherent conditions and incubated for 5 days. Mammospheres formed were quantified under the fluorescent microscope. A) Percentage of mammospheres formed under each condition was made relative to that of control cells, to obtain relative mammosphere formation. B) Transfection efficiency was verified using RTq-PCR. C) Individual mammosphere diameters were measured using Image J (in pixels). In each of the previous quantification methods, Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; D) Representative images of mammospheres under each condition. White line denotes 400 µm. Data shown are mean and SD of n=3 independent experiments (3 replicates each).

Page | 177

Initially, the effect of KIF20A overexpression and silencing was monitored individually in MCF-7 WT cells, to see if it could mimic the effect of FOXM1 alteration noted previously (Results Chapter 3.2). KIF20A was transiently overexpressed using a pOBT7-KIF20A expression vector, following which cells were seeded in non-adherent cultures and left to form mammospheres for 5 days. Simultaneously, separate MCF-7 WT cells were transfected with POBT7-EV as a transfection control. All quantification was normalised to that obtained from the seeding of control transfected cells, to obtain a relative mammosphere formation. Successful overexpression was confirmed via RTq-PCR (Figure 4.9 D and 4.10D).

KIF20A overexpression induced a significant 0.6 fold increase in the number of mammospheres formed, when compared to control transfected cells (Figure 4.9A). Surprisingly, when the mammosphere diameters were measured, these proved to be unchanged compared to control transfected cells (Figure 4.9 B and C). Given the KIF20A role in cellular proliferation, an increase in mammosphere size was expected. To verify the nature of this aberration, the same assay was repeated with KIF20A silencing instead of overexpression.

KIF20A silencing caused a significant reduction in the mammosphere forming ability of MCF-7 WT cells, namely diminishing the mammosphere numbers by 30% (Figure 4.10 A) and almost halving the mammosphere size (Figure 4.10 B and C). Despite the lack of influence by KIF20A on mammosphere size in MCF-7 WT cells when overexpressed, its silencing was clearly sufficient to significantly impair mammosphere formation of MCF-7 WT cells. This suggested that KIF20A could clearly affect mammosphere formation, and that its silencing could be made to weaken the cancer stem cell phenotype of the resistant cell lines.

Chapter 3.4.9: KIF20A silencing can inhibit the mammosphere formation of both drug resistant cell lines As KIF20A appeared to be essential for the mammosphere abilities of the parental cell lines, and its expression was up-regulated in both resistant cell lines, I next investigated whether KIF20A silencing could impair the resistant cell lines mammosphere formation in a manner equivalent to that of FOXM1 silencing.

Page | 178

Figure 3.4.11 KIF20A silencing impairs MCF-7 EpiR ability to form mammospheres. MCF- 7 EpiR cells were transfected with KIF20A siRNA or control siRNA and seeded in non-adherent culture plates. After 5 days, mammospheres were analysed under the bright-field microscope. A) Bar-chart comparing the number of mammospheres between the control and KIF20A siRNA transfected cells. Relative mammosphere formation was calculated by comparing the KIF20a siRNA cell lines percentage to that of the control transfected cells to obtain a fold-change. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=*** B) Dot-plot representing the diameter of each mammosphere (measured via ImageJ). Non-parametric ANOVA was used to test the significance of the result with P<0.05 = *; P<0.01= **; P<0.001=***. C) Representative images of mammospheres formed after 5 days in non-adherent plates. White line denotes 400 µm. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 179

Figure 3.4.12 KIF20A silencing impairs MCF-7 TaxR ability to form mammospheres. MCF- 7 TaxR cells were transfected with KIF20A siRNA or control siRNA and seeded in non-adherent culture plates. After 5 days, mammospheres were analysed under the bright-field microscope. A) Bar-chart comparing the number of mammospheres between the control and KIF20A siRNA transfected cells. Relative mammosphere formation was calculated by comparing the KIF20a siRNA cell lines percentage to that of the control transfected cells to obtain a fold-change. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=*** B) Dot-plot representing the diameter of each mammosphere (measured via ImageJ). Non-parametric ANOVA was used to test the significance of the result with P<0.05 = *; P<0.01= **; P<0.001=***. C) Representative images of mammospheres formed after 5 days in non-adherent plates. White line denotes 400 µm. Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 180

As performed in other assays, KIF20A siRNA was transfected individually into the MCF-7 EpiR or the MCF-7 TaxR cell lines. Both cells were also subjected to transfection with control NSC siRNA, following which cells were seeded separately to act as controls. Again, mammospheres were allowed to form for 5 days, and overexpression effectiveness measured through RTq-PCR (Figure 4.11D and 4.12D).

KIF20A silencing significantly impaired mammosphere formation for the MCF-7 EpiR cells, with a 60% reduction in the numbers of mammospheres formed (Figure 4.11A) and a 30% reduction in mammosphere size (Figure 4.11 B and C). Alternatively, the effect of KIF20A silencing was not as drastic in MCF-7 TaxR cells, with a significant 40% reduction in mammosphere numbers (Figure 4.12 A) and an important impairment to mammosphere size (Figure 4.12 B and C).

Taken together, these results show that KIF20A is essential for the mammosphere formation of both parental and drug resistant cell lines. This not only displays a novel role for this kinesin, but offers a new therapeutic strategy to counter-act the cancer progression (in terms of both migration and stem-cell population) of the drug resistant cell lines. Since KIF20A portrayed a function in both migration and mammosphere formation, I next analysed whether it could also affect tumour induced angiogenesis in vivo.

Chapter 3.4.10: KIF20A overexpression can increase tumour induced angiogenesis in vivo The role of FOXM1 in the regulation of tumour induced angiogenesis has been studied extensively. Its direct transcriptional regulation of the VEGF through binding to Forkhead Binding Elements present on the VEGF promoter has been described. In previous work (Laura Bella, unpublished data), I have shown how this regulation could allow MCF-7 WT cells overexpressing FOXM1 to display higher tumour induced angiogenesis abilities in vivo in zebrafish embryos. As KIF20A is a direct FOXM1 downstream target, effectively controlling areas such as cellular proliferation, migration and mammosphere formation, I studied whether it could also affect tumour induced angiogenesis.

To do this, I utilised the novel zebrafish embryo model which was developed during the course of this project. As described previously (Results Chapter 3.1.4), selected cells were injected into the yolk sac of 1 dpf Tg(fli:GFP) zebrafish embryos, in the proximity of the SIV structure. Cells were stained with a lipophilic membrane dye prior to injection, and the blood vessels of the embryo were left to be intrinsically labelled with the green-fluorescent protein, thus enabling the

Page | 181

Figure 3.4.13 KIF20A overexpression increases MCF-7 WT neoangiogenesis. Approx. 150 DiI-stained MCF-7 WT cells transfected with POBT7-KIF20A or POBT7-EV were injected into the yolk-sac of 1dpf Tg(fli:GFP) zebrafish embryos. Injected embryos were imaged under the fluorescent microscope 2dpi, to detect presence of sprouting blood vessels from the SIV complex, located in proximity to the injected cell lines. Any sprouting towards the implanted tumour was considered to be representative of tumour induced angiogenesis. A) Dot-plot depicting the number of sprouting blood vessels from individual injected embryos; Student t-test was used to determine statistical significance with P<0.05 = * ; P<0.01= ** ; P<0.001=***; B) Bar-chart displaying the total percentage of injected embryos presenting any form of angiogenesis. Statistical analysis was not performed due to lack of statistical significant repeats; C) Representative SIV structure of a 3dpf non-injected zebrafish embryo (green). Note the lack of protrusions extending from its structure. D) RTq-PCR was performed to confirm transfection efficiency. Data shown are mean and SD of n=2 independent experiments (25 replicates each).

Page | 182

Figure 3.4.14 KIF20A can alter breast cancer proliferation but not VEGF expression. A) MCF-7 EpiR cells were subjected to FOXM1, KIF20A or non-specific siRNA prior to analysis with western-blot. Expression of FOXM1, KIF20A and VEGF was tested. B-tubulin was used as a loading control. B) MCF-7 TaxR cells were subjected to FOXM1, KIF20A or non-specific siRNA prior to analysis with western-blot. Expression of FOXM1, KIF20A and VEGF was tested. B-tubulin was used as a loading control. C) MCF-7 WT cells were made to transiently over-express FOXM1 and then subjected to a sulforhodamine B (SRB) colorimetric assay in order to assess changes in cellular proliferation rates in 24 hours. Cell proliferation was compared to that of control transfected cell. Student t-test was used to compare statistical significance, with P<0.05 = * ; P<0.01= ** ; P<0.001=***; D) MCF-7 WT cells were made to transiently over-express KIF20A and then subjected to an SRB assay, to assess alterations in proliferation in 24 hours. Cell proliferation was compared to that of control transfected cell. Student t-test was used to compare statistical significance, with P<0.05 = *; P<0.01= **; P<0.001=***; Data shown in A and B are independent of n=1 independent experiments. Data shown in C and D are mean and SD of n=2 independent experiments (6 replicates each).

Page | 183 simultaneous monitoring of both the blood vessels and the injected tumour cells. Blood vessels were allowed to grow for 2 days, following which embryos were analysed under the fluorescent microscope to detect alterations in the SIV structure. Blood vessels sprouting from the structure were taken to be representative of tumour induced angiogenesis.

In this case, MCF-7 WT cells were made to transiently overexpress KIF20A prior to injection into the embryos. Control transfected cells were used as a control to gain basal levels of sprouting induced by MCF-7 WT cells. KIF20A overexpression caused the cells to induce a significant doubling of the vessel sprouting when compared to the control transfected cells (Figure 4.13 A and C), and an increase in the percentage of fish displaying sprouting of approx. 15% (Figure 4.13 B). As the assay was only repeated twice, statistical analysis was not performed on the percentage values.

Overall, these results implied KIF20A could increase the angiogenic potential of the MCF-7 WT cells. However, the nature of this alteration remained elusive, as KIF20A is not a transcription factor, any direct regulation of VEGF was improbable. To verify this hypothesis, I silenced KIF20A or FOXM1 in both drug resistant cell lines, and harvested the pellets for Western blot analysis on their individual effect on VEGF expression. The resistant cell lines were chosen as they displayed higher abilities to induce angiogenesis in vivo: silencing the two genes would therefore display a higher effect on their regulation of VEGF. A pellet of control transfected cells was harvested simultaneously for each cell line. In each case, β-tubulin was used as a loading control.

As shown in Figure 4.14 A and B, FOXM1 silencing and KIF20A silencing was effective in MCF- 7 EpiR cells. In MCF-7 TaxR cells, only FOXM1 silencing appeared effective. FOXM1 silencing also caused a reduction in KIF20A expression, further confirming the direct regulation. As expected, FOXM1 silencing caused a reduction in the VEGF expression in both cell lines. However, KIF20A silencing was unable to alter VEGF levels. Despite the nature of the pilot data, these results suggested that KIF20A was unable to alter the levels of VEGF expression, and could therefore not affect tumour induced angiogenesis directly. Instead, it was hypothesized that KIF20A increases in the tumour induced angiogenesis noted in vivo in this assay could be attributed to its regulation of cell proliferation.

To verify the validity of this hypothesis, MCF-7 WT cells were made to transiently overexpress KIF20A or FOXM1. The cells were simultaneously transfected with the respective control plasmids, to act as monitors for the normal proliferation rate of this cell line. Transfected cells were then seeded in a 96 well-plate and allowed to grow for 24 hours, following which cell proliferation was measured using a sulforhodamine B colorimetric (SRB) assay. As shown in Figure

Page | 184

4.14C, FOXM1 overexpression induced a significant increase in cell proliferation compared to control transfected cells, which caused the proliferation to be almost doubled. Similarly, KIF20A overexpression caused approximately an 80% increase in proliferation compared to control transfected cells (Figure 4.14D). This result not only confirms the essential influence both FOXM1 and KIF20A have on cellular proliferation, but also endorses the hypothesis that cells presenting an increase in KIF20A could display an increase in proliferation and a corresponding increase in VEGF secretion, leading to the increase in the angiogenic potential displayed in the zebrafish embryos. Thus, the increase in KIF20A expression noted in Figure 4.4 could also be correlated with the increased neoangiogenic abilities of the resistant cell lines noted in Results Chapter 3.1

Collectively, my data show that KIF20A is essential for cellular migration, mammosphere formation and able to affect tumour induced angiogenesis. As these are all precursors to cancer metastasis, I next analysed whether KIF20A could affect cancer metastasis of cell lines in vivo.

Chapter 3.4.11: KIF20A silencing can inhibit the metastasis of MDA-MB-231 As the MDA-MB-231 cells displayed the most aggressive phenotype in vivo, I first investigated the role of KIF20A on cancer metastasis using this cell line. To study their behaviour effectively, I used the zebrafish embryos metastasis model developed during this project.

MDA-MB-231 cells were made to transiently silence KIF20A, or were transfected with control siRNA, following which they were stained with lipophilic membrane dye DiI. Transfected cells were injected into the yolk-sac of 1 dpf Tg(fli:GFP) embryos, and allowed to migrate for 3 days. Injected embryos were then imaged under the fluorescent microscope to detect the presence of any cells which had disseminated away from the yolk-sac region. Presence of cells in areas which differed from the compartmentalised space of the yolk-sac were taken to be a sign of metastasis. Metastasis was quantified in terms of percentage of total injected embryos presenting any form of cellular dissemination.

As seen previously, control transfected MDA-MB-231 cells migrated to the head and tail region of the embryo (Figure 4.15 B). Conversely, KIF20A silencing reduced MDA-MB-231 metastatic ability by 90%, causing most of the embryos to contain the cluster of injected cells into the yolk- sac (Figure 4.15 A and B). KIF20A silencing was confirmed by RTq-PCR (Figure 4.15C). This result displayed how KIF20A silencing could significantly hinder the metastatic potential of the MDA-MB-231 cells.

Page | 185

Figure 3.4.15 KIF20A can impair MDA-MB-231 metastasis in vivo. MDA-MB-231 cells were made to transiently silence KIF20A and were stained with CM-DiI prior to injection into the yolk- sac of 1 day post-fertilisation WT zebrafish embryos. Injected cells were allowed to metastasize for 3 days. Embryos were then imaged under the fluorescent microscope to detect any presence of disseminated cells. Presence of cells outside of the yolk sac region was defined as metastasis. A) Percentage of injected fish presenting any cell dissemination was calculated and compared between control transfected cells and siKIF20A transfected cells. Statistical analysis was not performed due to lack of experimental replicates. B) Representative images of control or KIF20A siRNA transfected cell injected embryos at 3 days post-injection. Images depict the bright-field, red- and green-fluorescent channels, as well as the red-and green-channels merged. Disseminated cells are high-lighted by white arrows. C) Rtq-PCR was performed to confirm transfection efficiency. Data shown are mean and SD of n=2 independent experiments (25 replicates each).

Page | 186

Success of this experiment implied KIF20A could be able to hinder the metastasis of drug resistant cell lines.

Chapter 3.4.12: KIF20A inhibition can abolish the metastatic potential of both drug resistant cell lines. In previous sections, I showed how KIF20A is essential for the migration and cancer stem cell phenotype of the drug resistant cell lines. Furthermore, increased KIF20A expression caused significant increases in tumour induced angiogenesis in MCF-7 WT cells. This crucial role in cancer progression implied KIF20A silencing could disrupt the cancer metastasis of the MCF-7 EpiR and MCF-7 TaxR cell lines.

To determine the effect of KIF20A silencing on the metastasis of the MCF-7 EpiR and MCF-7 TaxR cell lines, KIF20A was transiently silenced in these cell lines individually. Simultaneously, each cell line was transfected with non-silencing siRNA as a transfection control. Transfected cells were stained fluorescent red and then injected into the yolk-sac of wild-type embryos. Cells were allowed to migrate for 3 days, following which embryos were analysed under the fluorescent microscope for presence of cells which had disseminated out-side of the yolk-sac region.

MCF-7 EpiR control transfected cells disseminated to the head region, consistently with previous assays. Almost 7% of embryos injected with MCF-7 EpiR control cells presented dissemination in the head. Alternatively, the cell metastasis was reduced to nil when the cells were instead transfected with KIF20A siRNA (Figure 4.16 A and B). Consistently with previous studies in this report, MCF-7 TaxR cells caused 12 % of the injected embryos to display any form of cellular dissemination, particularly localised in the head and heart areas (Figure 4.17 B, white arrows display tumour dissemination). Again, KIF20A silencing had a significant and drastic effect, completely abolishing any metastatic behaviour displayed by this cell line.

Overall, KIF20A proved to be an essential FOXM1 downstream target for the regulation of all aspects of cancer progression. Its inhibition was sufficient to revert the drug resistant phenotype to that of the sensitive MCF-7 cells, which are unable to metastasize. Furthermore, its expression has displayed a good correlation with the cellular phenotype in terms of ability to undergo cancer progression, making this a good prognostic marker to predict a tumours aggressiveness. Having determined the importance of KIF20A for the cancer progression of drug resistant cell lines, and its correlation to FOXM1, I next analysed the importance KIF20A played as an effector of FOXM1.

Page | 187

Figure 3.4.16 KIF20A silencing can inhibit MCF-7 EpiR metastasis in vivo in zebrafish embryos. MCF-7 EpiR cells were transfected with NSC control or KIF20A siRNA 24 prior to harvesting for injection into 1 dpf Tg(TRA/NAC) zebrafish embryos. To allow for detection following injection into the yolk-sac of zebrafish embryos, cells were stained with red-fluorescent lipophilic membrane dye CM-DiI (Sigma). Approx. 150 cells were injected into the yolk-sac. Injected fish were imaged under the fluorescent microscope at 3 dpi to detect cells which had disseminated out-side of the yolk-sac region. Presence of cell dissemination was considered to be sign of cellular metastasis. A) Bar-chart displaying percentage of total injected with disseminated cells. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Representative images obtained from the over-lap of bright-field and red fluorescent-channel images of 3dpi TRA/NAC embryos injected with NSC control or KIF20A siRNA EpiR cells. Presence of disseminated cells was high-lighted by white arrows. Data shown are mean and SD of n=3 independent experiments (25 replicates each).

Page | 188

Figure 3.4.17 KIF20A silencing can inhibit MCF-7 TaxR metastasis in vivo in zebrafish embryos. MCF-7 TaxR cells were transfected with NSC control or KIF20A siRNA 24 prior to harvesting for injection into 1 dpf Tg(TRA/NAC) zebrafish embryos. To allow for detection following injection into the yolk-sac of zebrafish embryos, cells were stained with red-fluorescent lipophilic membrane dye CM-DiI (Sigma). Approx. 150 cells were injected into the yolk-sac. Injected fish were imaged under the fluorescent microscope at 3 dpi to detect cells which had disseminated out-side of the yolk-sac region. Presence of cell dissemination was considered to be sign of cellular metastasis. A) Bar-chart displaying percentage of total injected with disseminated cells. Student t-test was performed to determine statistical significance with P<0.05 = *; P<0.01= **; P<0.001=***; B) Representative images obtained from the over-lap of bright-field and red fluorescent-channel images of 3dpi TRA/NAC embryos injected with NSC control or KIF20A siRNA TaxR cells. Presence of disseminated cells was high-lighted by white arrows. Data shown are mean and SD of n=4 independent experiments (25 replicates each).

Page | 189

Chapter 3.4.13: KIF20A inhibition can abolish the metastatic potential of both drug resistant cell lines. Despite having individually depicted how KIF20A is a direct FOXM1 transcriptional target, and how KIF20A modulation can mimic FOXM1 modulation in the regulation of the cancer progression of the drug resistant cell lines, how crucial KIF20A is for FOXM1 modulation of cancer progression remained elusive. To determine this, I used both MCF-7 EpiR and MCF-7 TaxR cell lines, and co-transfected each one individually to obtain simultaneous FOXM1 overexpression coupled to KIF20A silencing, or KIF20A overexpression coupled to FOXM1 silencing. Transfected cells were placed in a Boyden-chamber assay, along-side control transfected cells, to determine whether the overexpression of one target could rescue the effect of the silencing of the other on this aspect of cancer progression.

KIF20A silencing in MCF-7 EpiR cells reduced the cell migration by 40%, despite FOXM1 overexpression (Figure 4.18A and B). This meant that FOXM1 mainly acts through KIF20A, as its silencing prevented it from exerting its effect on cell migration. Alternatively, upon FOXM1 silencing, KIF20A overexpression was able to maintain cellular migration at 80% compared to control levels. This was further confirmation that KIF20A is an essential FOXM1 downstream target, as it is able to almost abolish the effect of its silencing when expressed on its own. In each instance, effect of co-transfection was detected using RTq-PCR (Figure 4.18C).

Very similar results were obtained when the assay was repeated using MCF-7 TaxR cells in a pilot: FOXM1 overexpression was only partially able to rescue the effect of simultaneous KIF20A silencing on cell migration, enabling relative cell migration to reach 0.66. Consistently with MCF- 7 EpiR, KIF20A overexpression almost completely annulled the effect of FOXM1 silencing, maintaining it at 0.87 compared to control transfected cells (Figure 4.19). Unfortunately, time limitations prevented the verification of transfection efficiency from being performed. Further repeats will therefore need to be performed to validate the outcome. Taken together, these results display the essential role that KIF20A portrays in FOXM1 mediation of cancer progression of the resistant cell lines. However, the exact mechanism through which KIF20A silencing impaired the cancer progression of the breast cancer cell lines remained obscure. I therefore next analysed how KIF20A could affect cell structure.

Page | 190

Figure 3.4.18 KIF20A can over-ride FOXM1 control of MCF-7 EpiR migration. MCF-7 EpiR cells were subjected to co-transfection with either PCDNA-3 FOXM1 plasmid and KIF20A siRNA, or POBT7-KIF20A and FOXM1 siRNA. As control, cells were transfected with both empty-vector plasmids and non-silencing RNA. Transfected cells were placed in a serum deprived chamber of a Boyden Chamber assay, with the adjacent chamber containing full media. Cells were allowed to migrate for 24 hours prior to fixing and DAPI staining for quantification. A) Migrated cells were made relative to those of control transfected cells to obtain relative cell migration. B) Representative images of migrated cells under each condition, with the black dots depicting individual cells. Black line denotes 100 µm C) RTq-PCR was performed to confirm transfection efficiency. Student t-test was performed to confirm statistical analysis with P<0.05 = *; P<0.01= **; P<0.001=***; P<0.0001=****; Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 191

Figure 3.4.19 KIF20A and FOXM1 are essential for MCF-7 TaxR migration. MCF-7 TaxR cells were subjected to co-transfection with either PCDNA-3 FOXM1 plasmid and KIF20A siRNA, or POBT7-KIF20A and FOXM1 siRNA. As control, cells were transfected with both empty-vector plasmids and non-silencing RNA. Transfected cells were placed in a serum deprived chamber of a Boyden Chamber assay, with the adjacent chamber containing full media. Cells were allowed to migrate for 24 hours prior to fixing and DAPI staining for quantification. A) Migrated cells were made relative to those of control transfected cells to obtain relative cell migration. B) Representative images of migrated cells under each condition, with the black dots depicting individual cells. Black line denotes 100 µm. Student t-test was performed to confirm statistical analysis with P<0.05 = *; P<0.01= **; P<0.001=***; P<0.0001=****; Data shown are mean and SD of n=2 independent experiments (3 replicates each).

Page | 192

Chapter 3.4.14: KIF20A silencing alters the microtubule dynamics in both sensitive and drug resistant cell lines Overall, my data depicted KIF20A as one of the main effectors of FOXM1, with its silencing impeding the cancer progression of drug resistant cell lines. Individually, KIF20A silencing was able to significantly impair breast cancer cell migration, mammosphere formation, as well as metastasis in vivo. However, its mechanism of action remained unclear. Kinesins are known for their interactions with microtubules. Microtubules (MTs) are dynamic polymers composed of α/β- tubulin to create hollow tubes of 25 nm in diameter. The two MT poles contrast in that the plus- end is more dynamic than the minus-end, with the minus-end crucial for anchoring to the centrosome, and the plus-end remaining more motile in the cytoplasm, to enable it to interact with different targets. Microtubules dynamics are regulated strictly both temporally and spatially, as their structural role is essential for processes such as shape maintenance, cytokinesis, cell signalling, intracellular transport of vesicles or organelles, cell polarity and cell motility. Essential to their regulation are microtubules interacting molecules, such as nucleotides, MT-associated proteins (MAPS), phosphatases and kinases. MT polymerization is generated through a nucleation- elongation mechanism, where the creation of a short MT ‘nucleus’ is tailed by the subsequent elongation of the MT at its terminus by non-covalent addition of an α-/β- tubulin dimer. Repetitive spurts of shortening at the plus ends coupled with periods of polymerization are thus able to regulate microtubule dynamics. To regulate cell migration, microtubules form pseudopodial protrusions, attach and translocate the cell body towards the new adhesion site, only to repeat the whole process periodically. The leading edge usually contains unusually stable MTs. (Honore et al., 2005).

Limited studies have so far reported on how mitotic spindle inhibition could result in impairment of cellular motility (Vasiliev et al., 1970). Instead, KIF20A has been reported for its regulation of the mitotic spindle at the metaphase plate (Khongkow et al., 2015a). This correlation, together with the notion extracted from the data depicting how KIF20A could primarily affect cancer progression when silenced, rather than overexpressed, spurred the hypothesis that KIF20A could regulate cancer progression by affecting the microtubule dynamics of a cell line, thus affecting cell shape. A migrating cell requires morphological elasticity to be able to encompass all the shifts in cell shape necessary to undergo all the different stages in cancer progression, which encompass frequent cytoskeleton re-organisation. Impairment of the structural role normally performed by KIF20A, particularly in the regulation of cytoskeleton organisation, could damage effective cell shape fluctuations, causing the cell to be unable to metastasize (as seen with KIF20A silencing, Figure 4.16 and 4.17).

Page | 193

To determine how KIF20A silencing affects the cellular cytoskeleton, MCF-7 WT, EpiR and TaxR were transfected with KIF20A or non-silencing siRNA and then seeded at low confluency on chamber glass slides. Following fixing and permeabilization, cells were stained with an anti-α- tubulin antibody, to detect one of the main components of the cytoskeleton. DAPI was used to nucleus localization. Cell morphology and microtubule cytoskeleton was analysed using confocal microscopy, to enable comparison between control and KIF20A siRNA transfected cells.

As shown in Figure 4.20, there was an important morphological difference between MCF-7 WT transfected with control or KIF20A siRNA. The tubulin staining of control transfected cells presented a cytoskeleton which was more wide-spread around the nucleous, while cells deprived of KIF20A displayed a membrane infolding with a contracted cytoplasm, and more densely packed filaments. The same effect was noted in both resistant cell lines Figure 4.21 and 4.22. KIF20A silencing prevented monomers from forming filaments, which would then affect overall filament network and consequent cell shape and size. Despite the pilot nature of these studies, the clear differences in cellular morphology and cytoskeleton organisation imply KIF20A portrays a clear structural role. The impairment in cell structure following KIF20A silencing provides a novel insight in the dynamics through which KIF20A could blight cellular migration, mammosphere formation and consequent cellular metastasis.

Page | 194

Figure 3.4.20 KIF20A silencing impairs tubulin cytoskeleton formation in MCF-7 WT cells. MCF-7 WT cells were transfected with control or KIF20A siRNA and then fixed and stained with anti-tubulin antibody and DAPI for analysis under confocal microscopy. The first column displays α-tubulin stain, the second DAPI stain and the third merges the two. Top two rows show groups of adherent cells, while bottom rows focus on individual cells. Data shown are mean and SD of n=1 independent experiments (3 replicates each).

Page | 195

Figure 3.4.21 KIF20A silencing impairs tubulin cytoskeleton formation in the MCF-7 EpiR cells. MCF-7 EpiR cells were transfected with control or KIF20A siRNA and then fixed and stained with anti-α-tubulin antibody and DAPI for analysis under confocal microscopy. The first column displays tubulin stain, the second DAPI stain and the third merges the two. Top two rows show groups of adherent cells, while bottom rows focus on individual cells. Data shown are mean and SD of n=1 independent experiments (3 replicates each).

Page | 196

Figure 3.4.22 KIF20A silencing impairs tubulin cytoskeleton formation in MCF-7 TaxR cells. MCF-7 TaxR cells were transfected with control or KIF20A siRNA and then fixed and stained with anti-tubulin antibody and DAPI for analysis under confocal microscopy. The first column displays α-tubulin stain, the second DAPI stain and the third merges the two. Top two rows show groups of adherent cells, while bottom rows focus on individual cells. Data shown are mean and SD of n=1 independent experiments (3 replicates each).

Page | 197

Chapter 3.4.15: Discussion This chapter aimed to detect and define a FOXM1 downstream effector which could be used to target FOXM1 mediated cancer progression of drug resistant cell lines. A selection of potential downstream targets was initially obtained from microarray data previously acquired in the lab (E. Lam, unpublished data). From this, selected targets were subjected to different epirubicin time exposures in both MCF-7 WT and EpiR to compare similarities between target response to treatment to that of FOXM1, using both RTq-PCR and Western blotting. FOXM1 expression pattern was as expected from previous reports (de Olano et al., 2012): both FOXM1 protein and RNA expression increased at 4 and 8 hours, as the sensitive cells initially try to combat the DNA damage induced by epirubicin administration through FOXM1 medicated regulation of the DNA damage response. Sensitive MCF-7 WT cells eventually succumb to the epirubicin effect and, with a drastic reduction in FOXM1 levels, undergo apoptosis. Instead, resistant cell lines maintain a constant elevated FOXM1 expression, which enables them to counter act the activity of epirubicin, and maintain their resistance to it. Potential FOXM1 downstream targets were pursued if they followed FOXM1 pattern broadly: in some instances, the effect of alterations in FOXM1 was not seen instantly, but in the subsequent time point. A general reduction in expression, and ultimately stable expression in resistant cell lines was deemed sufficient to imply potential FOXM1 transcriptional regulation, as well as a role in resistant cell lines.

Shortlisted targets were then analysed for their response to more direct FOXM1 expression variation, mediated through transient overexpression and silencing, as well as stable FOXM1 overexpression. Target response was verified with both RTq-PCR and Western-Blot to analyse both protein and RNA expression. From this, both KIF20A and MKI67 emerged as the candidates with best response to FOXM1 modification expression. However, due to existing literature defining MKI67 role in cancer progression (Anastas and Moon, 2013; Fallis, 2013; Iqbal et al., 2013; Lam et al., 2013; Lebeau, 2010; Li et al., 2015a; Lombaerts et al., 2006; Marangoni et al., 2009; Rampazzo et al., 2013), KIF20A was chosen instead for further experiments. Validation of the interaction between FOXM1 and KIF20A was performed using both Chromatin immunoprecipitation (ChIP), as well as the luciferase reporter assay. Together, these assays confirmed KIF20A as being a putative FOXM1 downstream target, from which FOXM1 can control by binding to the Forkhead Response Elements (FHRE) present in proximity of the KIF20A promoter region.

Page | 198

Having established the validity of KIF20A as a direct FOXM1 transcriptional target, its value in the regulation of the cancer progression of drug resistant cell lines still needed accurate definition. Initially, its basal protein expression levels were compared between available breast cancer cell lines (MCF-7 WT, MCF-7 EpiR, MCF-7 TaxR, MDA-MB-231). KIF20A presented higher expression in both epirubicin and paclitaxel resistant cell lines when compared with the sensitive MCF-7 WT cell line, with its expression highest in MCF-7 TaxR. Furthermore, KIF20A was also overexpressed in MDA-MB-231 cell lines. This high expression could relate to the role of KIF20A in cellular proliferation, as it portrays an essential function as an effector of mitosis, thus indicating that both resistant and the triple-negative cell lines proliferate more rapidly than the sensitive MCF-7 WT cells. Alternatively, given the correlation between KIF20A expression, and the aggressive nature of the analysed cell line in Results Chapter 3.1, it was speculated that KIF20A expression in the different cell lines could correlate to the cancer progression ability of that cell line. Thus, KIF20A could be used as a predictive marker to gauge the aggressiveness of breast cancer in patients.

KIF20A expression was later shown to be correlated with the regulation of cancer progression of both sensitive and drug resistant cell lines. For instance, it was shown to be essential for the migration of the highly aggressive MDA-MB-231 cells, as well as both resistant cell lines, without which the cell lines displayed significantly impaired migration. This effect was a further confirmation of its direct functional relation to FOXM1, which could induce the same outcome upon silencing. When KIF20A was silenced, the MCF-7 EpiR presented the highest inhibition in migration, whilst the MCF-7 TaxR presented a reduction by only 30%. This was speculated to be caused by the higher endogenous KIF20A expression in this cell line, which would significantly diminish the effect of transient KIF20A silencing, as an important amount of KIF20A would still remain active, and thus able to permit cell movement. In order to appropriately define the effect of KIF20A on cell migration, its expression would have to be abolished using selective KIF20A inhibitors, such as Paprotrain (Santa Cruz Biotechnology) or KIF20A shRNA (available for purchase from Santa Cruz Biotechnology).

Following successful confirmation of the function of KIF20A in migration, its relation to the cancer stem cell phenotype was then verified. KIF20A was shown to increase mammosphere numbers when overexpressed in MCF-7 WT cells, and impair their formation when silenced in the same cell line. Similarly, KIF20A silencing significantly reduced both numbers and size of mammospheres formed in both resistant cell lines. Again, this function could be related to that of FOXM1, further proving KIF20A candidature as a viable FOXM1 downstream effector. However, KIF20A overexpression, unlike that of FOXM1, was only able to increase the numbers of mammospheres formed, while leaving their sizes unaltered. Given KIF20A function in

Page | 199 proliferation, noted both in literature (Khongkow et al., 2015a) and in my report with the SRB assay, I expected KIF20A overexpression to promote the proliferation of individual cancer stem cells, eventually converging in increased mammosphere sizes(with the correlation between cell proliferation and mammosphere formation previously shown by Xu et al., 2015). This result inspired the first hypothesis of KIF20A playing a structural role in the progression of cancer cells.

Again, when looking at the effect of KIF20A on tumour induced angiogenesis, the hypothesis of KIF20A not having a primary role in the final neoangiogenic outcome emerged. Despite the increase in the angiogenic response to KIF20A overexpression, consistent with that noted in previous data upon FOXM1 overexpression (Laura Bella, 2012, unpublished data), KIF20A was shown to be unable to affect the expression of the VEGF directly. Instead, KIF20A overexpression appeared to promote tumour induced angiogenesis by promoting tumour proliferation following injection. An SRB was sufficient to delineate the theoretical validity of this hypothesis which, to be further confirmed, would require analysis of cellular proliferation following injection. This could be done by measuring the fluorescence emitted by the cells stained with the lipophilic membrane dye following injection, as this is known to halve with every cycle of cellular replication. Despite the indirect effect of alterations in angiogenesis following KIF20A injection, this could probably still serve as a drug target to inhibit the tumour induced angiogenesis of the drug resistant cell lines. However, further experiments would need to be performed to confirm this hypothesis.

Given its central role in the individual aspects of cancer progression, KIF20A silencing causing the inhibition of tumour metastasis in vivo was unsurprising. When tested, KIF20A silencing reduced MDA-MB-231 migration by 80%, and completely abolished metastasis for both resistant cell lines. This effect was more drastic than that of FOXM1 silencing, which only reduced MDA- MB-231 metastasis by 50%, despite being able to inhibit the metastasis of the resistant cell lines. As did FOXM1 silencing, it appears that KIF20A silencing was again sufficient to revert the resistant cell lines phenotype to that of the sensitive cell lines. Thus, KIF20A was shown to be not only a potential prognostic marker for the prediction of the behavioural aspects of breast cancer cell lines, but also a useful drug target to ablate or inhibit the cancer progression of metastatic cells. Targeting KIF20A could avert the high toxicity which could be caused by instead inhibiting FOXM1.

Despite KIF20A central role in cancer progression, it still remained important to determine whether KIF20A was one of the primary FOXM1 effectors, or is instead FOXM1 could by-pass its inhibition and continue to promote cancer progression. This was verified using co-transfection

Page | 200 studies whereby either FOXM1 or KIF20A would be overexpressed in turn, coupled to the inhibition of the other. The ability of the transfected cells to migrate was tested, and it revealed that KIF20A overexpression was able to almost completely revert the effect of FOXM1 inhibition, but that FOXM1 overexpression could not over-come the inhibitory effects of KIF20A. Thus, the viability of KIF20A as a drug target to prevent the cancer progression mediated by FOXM1 was further confirmed.

Lastly, the mechanism through which KIF20A could contribute to cancer progression remained elusive. Not being a transcription factor, KIF20A could not regulate cancer progression genes directly. Instead, its interaction with microtubule and actin filaments, and its reported sub-cellular localisation in both the cytoplasm and the nucleus in breast cancer patient samples (Khongkow et al., 2015a), led to the speculation that KIF20A could hold a structural role. I hypothesized that KIF20A may help support the cytoskeleton, during both dormant, replicative, and various migration morphologies necessitated by a cell line. Indeed, singular reports have implied KIF20A interaction with both actin (Nguyen et al., 2014) and tubulin (Taniuchi et al., 2005b). Furthermore, mitotic spindle poisons, which would be equivalent to KIF20A silencing, have previously been shown to inadvertently affect cellular directional movement (Vasiliev et al., 1970). Further analysis revealed that cells lost the capacity to retain the structural stability in the cell edges, without which they were unable to move. Like joints in a skeleton, KIF20A could render cells able to shift to more elongated shapes during invasion and migration, thus facilitating the cancer progression of a cell line. Alternatively, KIF20A silencing would rob the cytoskeleton of essential supportive junctions, without which a cell would not be able to effectively shift shape in order to accommodate its cancer progression, thus impairing it. Pilot confocal data revealed that KIF20A silencing can render the tubulin component of the cytoskeleton more compacted around the nucleus, with membrane retraction and cell rounding, as if unable to properly adhere and form focal adhesions to the plate. To attain validation, this data would then need to be confirmed staining for both α-tubulin and filamentous actin (F-actin), the main filament components of the cytoskeleton. Furthermore, simultaneous staining with the aid of an anti-KIF20A antibody could reveal the precise interaction between the filaments and KIF20A. For instance, like in the case of KIF18A in breast cancer samples, KIF20A could hinder migration by inhibiting microtubule plus- end dynamics at the leading edges of migrating cells (Zhang et al., 2010). Alternatively, KIF20A could affect actin more closely, as the latter is responsible for filopodia and lamellopodia formation, cellular protrusions crucial for cell migration (Hall and Hall, 2013). Ideally, stained cells should be visualised while migrating, for example using a 24-hour confocal filming session of a

Page | 201 wound-healing assay, to see the exact interface of KIF20A and the cytoskeleton during directional locomotion.

As mentioned previously, KIF20A is already part of phase I and II clinical trials as a KIF20A-66 vaccine for the treatment of metastatic pancreatic cancer. Data revealed it was overall well tolerated and able to prolong patients’ lives (Asahara et al., 2013). Alternatively, the same KIF20A targeting immunotherapy principle was shown to be a therapeutic option for the treatment of melanoma, due to its high expression in advanced melanoma tissue samples (Yamashita et al., 2012). Despite only limited information on its precise mechanism of action, the data in this chapter reveals that KIF20A could not only be used as a prognostic factor to predict future breast cancer behaviour, but that it could be used as an immune-therapeutic target to combat both metastatic breast cancer, as well as anthracycline and paclitaxel-resistant breast cancers. Furthermore, this could also be targeted in a preventative manner, to impair the cancer progression of breast cancers.

Page | 202

Chapter 3.5: SOX4 and the regulation of tumour induced angiogenesis SRY-related HMG-box 4 (SOX-4) is an intronless gene which belongs to the SOX family of transcription factors. These are known for their characteristic and highly conserved structural homology in the HMG domain, distinctive for its ability to bind directly to the minor grove of the DNA helix (Zhang et al., 2012a). The SOX4 gene is located on 6p22.3 and encodes a protein that is 474 amino acids long. This can be segregated in three distinct domains: an HMG box, which acts as the DNA binding domain; a glycine rich region; and a serine rich domain, which functions as a transactivation domain. SOX4 influences multiple pathways in healthy tissues, including several developmental processes in virtually all tissues, including T cell differentiation, and development of thymocytes, nervous and embryonic cardiovascular system (Parvani and Schiemann, 2013).

Recently, SOX4 has attracted a lot of attention due to its role in the development and progression of multiple cancers, namely breast, prostate, colorectal, bladder and hepatocellular carcinoma. SOX4 has furthermore been shown to be overexpressed in several cancers, but its prognostic significance appears to be dependent on tumour type. For instance, elevated SOX4 expression is deleterious in colorectal, gastric, prostate and lymphoblastic leukaemia, whilst being beneficial to bladder carcinoma, melanoma and hepatocellular carcinoma (Ju and Wang, 2016).

In breast cancer, SOX4 has been linked to EMT through the stimulation of the tumour necrosis factor β (TGFβ), Snail, Zeb and Twist. With the exception of TGFβ, all were unable to reciprocally control SOX4 expression, suggesting a functional hierarchy. TGFβ was instead shown to stimulate SOX4 expression in a Smad 2/3/4 dependent fashion, or alternatively through Wnt and Notch signalling (Parvani and Schiemann, 2013). Furthermore, SOX4 was shown to regulate the expression of EZH2 directly, a gene responsible for the activation of the Polycomb group histone methyltransferase with the ability to trimethylate (me3) histone 3 lysine 27 (H3K27). H3K27me3 is of primordial importance for EMT, as its ablation can prevent the process (Tiwari et al., 2013). Other studies instead noted the correlation between elevated SOX4 expression in mammary epithelial cells and enhanced cell migration and invasion, essential precursors of cancer metastasis. In particular, SOX4 was shown to co-operate with Ras, a known oncogene, to induce tumourigenesis in vivo. Furthermore, SOX4 was found to be more highly expressed in triple- negative tumours (ERˉ/PRˉ/HER2ˉ), and able to enrich for the CD44high/CD24low phenotype (Zhang et al., 2012a). SOX4 function in the promotion of metastasis in vivo in nude mice was also reported in hepatocellular carcinoma (Liao et al., 2008). Again, SOX4 displayed a critical role in tumour metastasis in non-small cell lung carcinoma (Li et al., 2016b), of which particular activity

Page | 203 could be selectively inhibited through up-regulating miR-338-3p. Alternatively, in uterine carcinosarcoma, SOX4 was associated with β-catenin signal transduction in the upregulation of Slug and p330, genes known for its role in EMT, as well as functional in the enrichment of the stem cell population and spheroid formation abilities (Inoue et al., 2015).

Despite the extensive studies conducted on the afore mentioned aspects of cancer progression, no studies have been performed on SOX4 function in the regulation of tumour neoangiogenesis. In this chapter I therefore aimed to determine if SOX4 was able to contribute to tumour induced angiogenesis to determine if this could be used as a novel target to combat cancer progression of drug resistant cell lines.

Chapter 3.5.1: SOX4 silencing can inhibit tumour induced angiogenesis The role of SOX4 in the EMT, as well as the migration, invasion and metastatic properties of cancer cell lines has been reported in numerous assays. However, its influence on tumour induced angiogenesis has not yet been analysed. Previous assays have reported on early development lethality in mice upon SOX4 silencing, due to circulatory failure, specifically due to impairment of the endocardial ridges into the semilunar valves (Schilham et al., 1996). The same outcome was reported in a similar study, whereby it was concluded that SOX4 inhibition induced a defect equivalent to the common trunk in humans (Ya et al., 1998). Given its essential role in cardiac development during mouse embryogenesis, I first analysed the effect of SOX4 knock-down on breast cancer mediated neoangiogenesis using the novel in vivo zebrafish embryo model developed during this project (for details, view Results Chapter 1.4).

An MDA-MB-231 breast cancer cell line presenting stable SOX4 silencing via SOX4 shRNA, along with its control shRNA cell line, was kindly provided by Prof. Paul Coffer. Specifically, a lentiviral shRNA construct targeting Sox4 (Sigma) was fused to a ribosomal entry site, followed by the gene encoding for puromycin resistance in the pLKO.1 vector, all inserted in the retroviral packaging cell line. The construct was stably transfected into MDA-MB-231 cells, which were kept in puromycin to maintain the transfection viability (Vervoort et al., 2013). Prior to injection, both cell lines were stained with a lipophilic membrane dye to obtain a red fluorescent cell line, which could be detected subsequent to injection into the zebrafish embryo. To effectively detect modifications in the normal development of the SIV structure, Tg(fli:GFP) embryos were utilised, as they present intrinsically GFP-labelled blood vessels. Approximately 150 cells were

Page | 204

Figure 3.5.1 SOX4 silencing impairs MDA-MB-231 angiogenesis. Approx. 150 DiI-stained MD-MB-231 transfected with SOX4 or control shRNA were injected into the yolk-sac of 1dpf Tg(fli:GFP) zebrafish embryos. Injected embryos were imaged under the fluorescent microscope 2dpi, to detect presence of sprouting blood vessels from the SIV complex, located in proximity to the injected cell lines. Any sprouting towards the implanted tumour was considered to be representative of tumour induced angiogenesis. A) Dot-plot depicting the number of sprouting blood vessels from individual injected embryos; Student t-test was used to determine statistical significance with P<0.05 = * ; P<0.01= ** ; P<0.001=***; B) Bar-chart displaying the total percentage of injected embryos presenting any form of angiogenesis. Statistical analysis was not performed due to lack of statistical significant repeats; C) Diagram depicting the physiology of a zebrafish embryo at the time of imaging, with a light blue box high-lighting the area represented in the images. D) Representative pictures of SIV structure (green) following injection of different cell lines (red). Sprouting blood vessels are highlighted in green. Data shown are mean and SD of n=3 independent experiments (25 replicates each).

Page | 205

injected into the yolk-sac of 1 day post-fertilisation embryos (dpf), in proximity to a structure termed the SIV. If the tumour was able to induce angiogenesis, alterations in the normal development of the SIV would present it-self in the form of protruding blood vessels growing towards the tumour. Normally, the SIV does not present any protrusions at any stage of the embryos development. Injected embryos were left to incubate for 2 days, following which embryos were anaesthetised and subjected to individual imaging under the fluorescent-microscope to detect presence of protrusions extending from the SIV. This was quantified, compared to that present in non-injected fish, and taken to be representative of tumour induced angiogenesis. Furthermore, the number of injected embryos presenting any form of angiogenesis was calculated to obtain a percentage.

Injection of SOX4 shRNA MDA-MB-231 cells caused a significant reduction in the number of sprouting blood vessels in individual fish, from an average of two, to an average of less than 1 (Figure 5.1A and D). Furthermore, the percentage of injected embryos displaying any form of angiogenesis dropped dramatically and significantly from 70% of control cells injected embryos to 20% of SOX4 shRNA injected embryos (Figure 5.1B). Figure 5.1C displays the area of the injected embryos which was photographed to obtain representative images (Figure 5.1D). Overall, these results conveyed a novel and important role for SOX4 in the regulation of tumour induced angiogenesis, displaying how its silencing could significantly impair the angiogenic potential of MDA-MB-231 cell lines in vivo. Next, to further define the role of SOX4 in tumour induced angiogenesis, I attempted to determine whether SOX4 overexpression could also result in an increase in tumour induced angiogenesis.

Chapter 3.5.2: SOX4 induction can cause tumour neoangiogenesis SOX4 displayed a completely novel behaviour when the loss of its expression caused a significant reduction in the tumour induced angiogenesis of the MDA-MB-231 cell line. To further analyse its role in tumour induced angiogenesis, a cell line with inducible SOX4 was created and kindly provided by Prof. Paul Coffer. The conditionally regulated (ER:SOX4) cell lines was created from the fusion of the sequence of the mouse SOX4 gene with the hormone-binding domain of the human ER. The construct was inserted into the polylinker region of the pBABE vector, encompassing an internal ribosomal entry site and a gene which enables puromycin resistance. A mutation in the ligand binding domain in the ER ensured it was uniquely responsive to the synthetic ligand 4-hydroxy-tamoxifen (4-OHT). Thus, in the absence of the ligand, ER remained

Page | 206 sequestered in the cytoplasm, where, through its association with heatshock and chaperone proteins, it would

Figure 3.5.2 SOX4 induction triggers HMLE neoangiogenesis. HMLE WT, ER:WT and ER:SOX4 were subjected to 100 nM tamoxifen (4-OHT) treatment 24 hours prior to harvesting for injection. Approx. 150 DiI-stained cells were injected into the yolk-sac of 1dpf Tg(fli:GFP) zebrafish embryos. Injected embryos were imaged under the fluorescent microscope 2dpi, to detect presence of sprouting blood vessels from the SIV complex, located in proximity to the injected cell lines. Any sprouting towards the implanted tumour was considered to be representative of tumour induced angiogenesis. A) Dot-plot depicting the number of sprouting blood vessels from individual injected embryos; Student t-test was used to determine statistical significance with P<0.05 = * ; P<0.01= ** ; P<0.001=***; B) Bar-chart displaying the total percentage of injected embryos presenting any form of angiogenesis. Statistical analysis was not performed due to lack of statistical significant repeats; C) Representative pictures of SIV structure (green) following injection of different cell lines (red). Sprouting blood vessels are highlighted in green. Data shown are mean and SD of n=3 independent experiments (25 replicates each).

Page | 207

swiftly undergo degradation. Ligand binding instead enabled ER release and nuclear translocation, thus enabling SOX4 activation for the duration of the stimulus (Vervoort et al., 2013).

A breast human mammary epithelial cell line (HMLE) was made to present an ER (ER) –fused with SOX4, thus creating an inducible system where tamoxifen administration would activate SOX4 activity. Control HMLE cell lines were made presenting the ER:WT construct or lacking any alteration (HMLE:WT). The three cell lines were treated to 100nM 4-OHT, individually labelled with the lypophilic membrane dye, and injected into the yolk-sac of 1dpf Tg(fli:GFP) embryos as performed in the previous assay. For further control, a subset of the three cell lines was injected separately without tamoxifen administration, to determine the functionality of the inducible model as well as the basal angiogenic levels displayed by each cell line.

All three control cell lines displayed an average blood vessel sprouting of less than 1 blood vessel per embryo (Figure 5.2A and C). The consistency of this expression indicated that the implementation of the reporter construct did not alter the phenotype of the cell line. Tamoxifen treatment of the HMLE:WT cell line induced a significant reduction in the sprouting of the blood vessels (Figure 5.2A and C). This implied that the cell line does not respond to the inhibitory effect of tamoxifen. Alternatively, tamoxifen administration caused the control HMLE ER:WT cell line to display a slight increase in the average of number of sprouting blood vessels per embryo. This was however not significant, as well as not important (Figure 5.2A and C). This showed that the construct was unable to alter the angiogenic potential of a cell line, without the fusion of ER to SOX4. Tamoxifen treatment of the HMLE ER: SOX4 cell line instead induced a significant increase in angiogenesis, almost doubling that displayed by the HMLE ER:SOX4 cells without tamoxifen (Figure 5.2A and C). This increase was also significantly larger when compared to that induced by tamoxifen treated HMLE WT and HMLE ER:WT cells.

When the number of embryos presenting any form of angiogenesis was quantified, a similar picture emerged (Figure 5.2B). To determine the differences effectively, the percentage of each tamoxifen treated cell line was normalised to its respective non-treated cell line, so as to obtain a fold-change. Tamoxifen treatment of HMLE WT resulted in a significant decrease in the percentage of embryos presenting angiogenesis, as was determined whilst analysing sprouting in individual embryos. Consistently, tamoxifen treatment of HMLE ER:WT cells did not result in a significant alteration of the relative angiogenesis when compared to the non-tamoxifen treated control. Finally,

Page | 208 tamoxifen induced a significant increase in the angiogenic potential of the HMLE ER:SOX4 cells when related

Page | 209

Figure 3.5.3 Silencing of endothelin-1 impairs SOX4 neoangiogenesis. HMLE ER:SOX4 were transfected with endothelin-1 siRNA, as well as 4-OHT treatment. As control, cells were transfected with non-silencing siRNA, or mock transfected. A further control was made which lacked 4-OHT induction. Approx. 150 DiI-stained cells were injected into the yolk-sac of 1dpf Tg(fli:GFP) zebrafish embryos. Injected embryos were imaged under the fluorescent microscope 2dpi, to detect presence of sprouting blood vessels from the SIV complex, located in proximity to the injected cell lines. Any sprouting towards the implanted tumour was considered to be representative of tumour induced angiogenesis. A) Dot-plot depicting the number of sprouting blood vessels from individual injected embryos; Student t-test was used to determine statistical significance with P<0.05 = * ; P<0.01= ** ; P<0.001=***; B) Bar-chart displaying the total percentage of injected embryos presenting any form of angiogenesis. Statistical analysis was not performed due to lack of statistical significant repeats; C) Representative pictures of SIV structure (green) following injection of different cell lines (red). Sprouting blood vessels are highlighted in green. Data shown are mean and SD of n=3 independent experiments (25 replicates each).

Page | 210 to the non-treated control cells. Overall, these results not only confirmed the efficiency of the construct, but established the novel control of angiogenesis exhibited by SOX4. According to my results, SOX4 was not only able to significantly induce angiogenesis, but to also repress it upon SOX4 silencing. Next, having established SOX4 does present a role in tumour neoangiogenesis, it was imperial to determine the mechanism of SOX4 action.

Chapter 3.5.3: SOX4 regulates angiogenesis through endothelin-1 Through a collaboration with Prof. Paul Coffer, endothelin-1 (ET-1) was identified as the main down-stream effector of SOX4 function in tumour induced angiogenesis. This was determined through a combination of microarray and chromatin immune-precipitation, as well as a genome wide-analysis research (Stephin Vervoort, 2016, unpublished data). To confirm the role of ET-1 in angiogenesis, the HMLE ER:SOX4 cell lines utilised in the previous assay was subjected to endothelin-1 silencing. This permitted the study of the significance of ET-1 in SOX4 mediated angiogenesis, while simultaneously determining if ET-1 was involved in angiogenesis.

Endothelins are a class of compounds known to influence several cellular processes, such as cell growth, survival, invasion and angiogenesis. ET-1 was first identified in 1988 as a potent vasoconstrictor implicated in physiological and pathological conditions, such as hypertension and cardiac failure. Endothelins are initially encoded as preproendothelin proteins, which is then cleaved by the endothelin converting enzyme to reveal the active secreted peptide endothelin. Endothelins act primarily through two G-protein coupled transmembrane receptors, termed the endothelin-A and -B, present in both non-vascular and vascular tissues. Binding of endothelins to either receptor induces G-protein dissociation and consequent signal transduction to intracellular effectors. ET-1 has recently gained a lot of interest due to its importance for the neoplastic development of several tumours (Lalich et al., 2016), participating in mitogenesis, apoptosis, angiogenesis, tumour invasion and metastasis (Grant et al., 2003).

In this case, the HMLE ER:SOX4 cell line was made to transiently silence ET-1 via a ET-1 siRNA, following which it was subjected to 4-OHT treatment to induce SOX4 activation. The cells were then stained with DiI and injected into 1 dpf zebrafish Tg(fli:GFP) embryos, as performed previously. As controls, HMLE ER:SOX4 cells were injected individually under different conditions: with tamoxifen treatment only, to verify SOX4 induction of neoangiogenesis; with tamoxifen treatment coupled with transfection of control siRNA, to verify effect of transfection; and without treatment or transfection, as a monitor of basal angiogenic levels. Thus, I aimed to obtain confirmation of the functionality of the construct, as well as evidence that transient non- specific transfections would not cause increases in the angiogenic potential of the cell line.

Page | 211

Consistently with the previous experiment, tamoxifen treatment induced a significant increase in the number of sprouting blood vessels when compared to untreated cells (Figure 5.3 A and C), confirming construct effectiveness. Control transfected cells also displayed a significant increase in angiogenesis when compared to the non-treated cells, and a slight increase when compared to non-transfected cells (Figure 5.3A and C), showing that non-specific siRNA transfection was unable to reduce SOX4 mediated increase in the angiogenic response. Instead, cells which had been subjected to ET-1 silencing prior to tamoxifen treatment displayed a significant decrease in the induced sprouting, causing the average sprouting to revert to levels comparable to that of tamoxifen non-treated cells (Figure 5.3.A and C). Finally, untreated cells presented almost non- discernible levels of angiogenic sprouting (Figure 5.3A and C). Taken together, this data indicated the functioning of SOX4 activation, which was able to induce a significant increase in tumour induced angiogenesis, and that ET-1 silencing was able to significantly impair this effect, marking ET-1 as a primary down-stream effector of SOX4 mediated neoangiogenesis.

When the neoangiogenic potential was instead quantified by calculating the percentage of injected embryos presenting an angiogenic response, the pattern remained consistent with the previous data: a significant 50% increase in angiogenesis was portrayed by both tamoxifen non-transfected and control transfected cells (Figure 5.3 B). Endothelin-1 silencing instead caused a significant reduction in the percentage, bringing it back down to 30%, a level quasi-comparable to that of non-transfected non-treated control cells (10%) (Figure 5.3B). Overall, these results revealed a novel role for SOX4, as a crucial mediator of angiogenesis. This activity was shown to be dependent upon endothelin-1, an essential down-stream effector regulating SOX4 angiogenic activity.

To confirm this hypothesis, experiments were planned using the same methods, with the exception of using Bosentan, a selective ET-1 inhibitor, to replace the ET-1 siRNA. Ideally, these experiments would avoid the cellular stress caused by transfections, and induce a more significant inhibition of ET-1. The inhibitor was initially tested on zebrafish embryo to determine tolerability and dosage. However, time limitations of the projects prevented these experiments from being performed. Nevertheless, the clear role of SOX4 in tumour neoangiogenesis spurred the hypothesis that its activity might be related to that of FOXM1, which displayed a similar role on angiogenesis.

Chapter 3.5.4: SOX4 and FOXM1 In this thesis, both FOXM1 and SOX4 have been shown to significantly induce tumour neoangiogenesis. Furthermore, both transcription factors have been reported to play a role in other

Page | 212 aspects of cancer progression, such as EMT, migration and invasion, cancer stem cells, and metastasis. This functional overlap led the hypothesis that both transcription factors may be part of an inter-related signalling pathway, which could converge in the regulation of same target genes. Alternatively, these could, directly or indirectly, regulate each other. For instance, evidence of transcriptional regulation between SOX4 and FOXQ1, a member of the Forkhead Box family of transcription factors, has been shown in hepatocellular carcinoma (Liao et al., 2008). Understanding the nature of their interaction could provide novel insights to impede their functioning, thus providing new therapeutic strategies to combat breast cancer progression.

Initially, the direct reciprocal regulation between the two factors was by altering FOXM1 or SOX4 in different available breast cancer cell lines. The effect was measured using RTq-PCR. When FOXM1 was significantly overexpressed in MCF-7 WT cells, SOX4 remained unaltered (Figure 5.4A). FOXM1 silencing instead caused a significant 70% reduction in SOX4 expression (Figure 5.4B). SOX4 overexpression in MDA-MB-231 cells instead caused a significant reduction in FOXM1 expression, reducing it by more than half its initial value (Figure 5.4C). Then, activation of SOX4 through tamoxifen administration in HMLE ER:SOX4 cells was accompanied by a significant increase in FOXM1 expression, with a 6-fold increase when compared to that of the non-treated cells (Figure 5.4E). Finally, SOX4 response to epirubicin treatment was compared to that of FOXM1 in both MCF-7 WT and -EpiR cell lines. As shown in Figure 5.4D, SOX4 remains relatively low in MCF-7 WT cells throughout treatment, with what appears to be the highest expression at 48 hours. This is in neat contrast with the FOXM1 trend, which gradually diminishes as treatment exposure progresses. Instead, both transcription factors remain high throughout treatment in MCF-7 EpiR cells.

Pilot data was also kindly provided by Prof. Paul Coffer to analyse the functional interactions between the two transcription factors. Tested genes included N-cadherin, TEA Domain Transcription Factor 2 (TEAD2) and cyclin B1. Experiments were performed in the human embryonic kidney cell line HEK293. A luciferase reporter assay was utilised to assess the individual and combined transcriptional induction for the selected target genes by co-transfecting the two transcription factors individually or in combination, at the same time as the reporter construct of the tested genes. Unfortunately, despite the individual binding of the transcription factors to the target genes, selected for their reported interaction in literature, the combined transfection did not yield a significant increase or decrease in the induction of the potential target in any of the cases (data not shown).

Page | 213

Figure 3.5.4 SOX4 interaction with FOXM1 varies according to cell line. A) FOXM1 was over-expressed in MCF-7 WT cells, and following verification of transfection efficiency, alterations in SOX4 expression levels were analysed through Rtq-PCR; B) FOXM1 was silenced in MCF-7 WT cells, and following verification of transfection efficiency, alterations in SOX4 expression levels were analysed through Rtq-PCR; SOX4 was over-expressed in MDA-MB-231 cells and following verification of transfection efficiency, alterations in FOXM1 expression levels were analysed through Rtq-PCR; In each of the previous instances, L19 was used as a control and a student t-test was performed to verify statistical significance with P<0.05 = * ; P<0.01= ** ; P<0.001=***;D) MCF-7 WT and MCF-7 EpiR were treated with 1uM epirubicin for time-points 0,4,8,16, 24 and 48 hours. Protein expression levels of FOXM1 and SOX4 were measured, using B-tubulin as a loading control. Data shown in A, B, C are mean and SD of n=1 independent experiments (3 replicates each). Data shown in D is a representative of a pilot study.

Page | 214

Chapter 3.5.5: Discussion SRY-related HMG-box 4 (SOX-4) is a transcription factor which has been extensively studied for its role in the cancer progression of several tumours. Reported functions include the induction of migration, invasion, EMT, cancer stem cell enrichment and metastasis. However, its role in tumour neoangiogenesis had so far been unreported. In this chapter, I aimed to determine if SOX4 could affect tumour induced angiogenesis in breast cancer, using the zebrafish in vivo model, in collaboration with Prof. Paul Coffer, who provided all the in vitro and murine model analysis.

The data in this chapter revealed a novel role for SOX4, with its upregulation significantly increasing a tumour ability to induce angiogenesis, and its inhibition able to impair this function. Furthermore, its functioning through its main angiogenic effector, endothelin-1, was revealed. Consistently, endothelin-1 inhibition was sufficient to completely abolish SOX4 function. Despite the relatively low characterisation of the zebrafish angiogenesis model, my results were consistent with the collaborative work performed in the University of Utrecht by Prof. Paul Coffer, which provided further in vitro validation on the angiogenic findings detected in the zebrafish embryos. For instance, conditioned media of the HMLE ER:SOX4 increased the relative network length of the meshed network formed in a matrigel angiogenesis assay when using the human microvasculature endothelial cells (HMEC-1). This was shown to be both diminished by Bosentan treatment, as well as increase by prolonged incubation with the ET-1 peptide. These results were further confirmed by an in vitro angiogenic sprouting assay whereby collagen coated sephadex beads were made to attach to the HMEC-1 prior to insertion in matrigel. Again, when exposed to the conditioned media, these cells produced sprouting which mirrored closely that detected in the zebrafish in vivo assays. As a final validation of both the hypothesis and the validity of the novel zebrafish embryo model, SOX4 shRNA MDA-MB-231 cells were inserted into the mammary fat- pad of an immune-deficient mouse. Consequent vascularisation was determined through CD31 staining and endothelial surface marker expression. SOX4 depletion resulted in a significant reduction in blood vessel area, count and size.

Overall, these results appeared to be in accordance with information available in the published literature. Despite the lack of studies directly studying the role of SOX4 in tumour angiogenesis, SOX4 had been reported, in two instances, to have a role in cardiovascular development during mouse embryogenesis, with its loss causing early embryo mortality (Hong et al., 2007; Ya et al., 1998). More extensive validation had instead been detected for the functioning of endothelin-1. For instance, S.J. Hsu et al. reported how endothelin-1 inhibitors could revert cirrhosis-related

Page | 215 angiogenesis (Hsu et al., 2016). Treatment with selective ET-1 inhibitors was also shown to be correlated with significant less tumour angiogenesis when breast cancers were implanted into murine models. Furthermore, this was associated with smaller tumour mass and inhibited bone metastasis (Dre et al., 2006). Clinical trials are undergoing for the oral administration of bioavailable endothelin agonists for the treatment of prostate cancer, with initial data revealing an extension of patient survival (Lalich et al., 2016). In particular, ET-1 agonist atrasentan, has displayed good tolerability with mild adverse effects, and a statistically significant improvement in pain measures and insurgence of metastasis to the bones (Doganci et al., 2015). In human pancreatic adenocarcinoma, ET-1 and its two receptors, endothelin A and B receptors (ETAR and ETBR) were detected in high doses when immunohistochemical analysis was performed on surgically resected tumour samples (Danø et al., 2005). ET-1 inhibitors, such as Bosentan, are also being used for the treatment of other diseases, such as pulmonary artery hypertension, a disease deriving from dysregulated angiogenesis (Cook et al., 2015).

Several studies have been performed to delineate the mechanism through which ET-1 can mediate angiogenesis. As a potent mitogen, ET-1 can influence proliferation of both endothelial and vascular smooth muscle cells (Komuro et al., 1988). Alternatively, ET-1 can promote angiogenesis indirectly, by stimulating cells to release VEGF. In other instances, VEGF has been shown to promote ET-1 expression (Matsuura et al., 1998). This was validated in vivo, whereby ET-1 was shown to be as potent angiogenic inducer as VEGF (Bek et al., 2000).

Given the extensive functional homology between SOX4 and FOXM1, it was speculated that the two transcription factors might share or interact in a signalling pathway. However, when simple pilot assays were performed to determine how alteration of one could affect the expression of the other in different breast cancer cell lines, the results were inconclusive. Furthermore, pilot analysis of functional overlap also yielded inclusive data. Overall, the pilot data indicates that, in MCF-7 WT cells, FOXM1 overexpression does not affect SOX4, whilst it’s silencing causes SOX4 to increase significantly. Consistently, in MDA-MB-231 cells, SOX4 overexpression induces a significant decrease in FOXM1 expression. Also, in response to epirubicin treatment in MCF-7 WT cells, SOX4 appears to increase as FOXM1 decreases. Together, these results suggest SOX4 may act up-stream of FOXM1, with its expression inhibiting that of FOXM1, and a decrease in FOXM1 expression inducing a further increase in SOX4 expression. However, when SOX4 activation was induced in the HMLE cell line, it was accompanied by a significant increase in FOXM1 expression. Similarly, in MCF-7 EpiR cells, both SOX4 and FOXM1 expression is maintained high throughout treatment. In these two instances, it appears as if SOX4 exerts a positive influence on FOXM1, leading it to increase its expression. The inconsistency between

Page | 216 their interactions in the different cell lines implies SOX4 maintains the residual activity which changes according to tissue type. In this case, subtle variations in breast cancer cell lines appear to be sufficient to completely alter SOX4 function, from that of a tumour suppressor, to that of an oncogene. However, despite SOX4 repressing FOXM1, it still is capable of promoting aggressive cancer progression behaviours. Thus, SOX4 maintains its tumour suppressor role while simultaneously promoting cancer progression. Furthermore, its high expression in MCF-7 EpiR cells throughout treatment provides a novel potential function for SOX4 in the mediation of drug resistance.

Important differences in SOX4 expression between tumour types, as well as breast cancer types, has already been reported in literature. For instance, the MCF-10A cell line lacks endogenous SOX4 expression, while a selection of triple-negative breast cancer samples displayed SOX4 overexpression (Zhang et al., 2012a). Overall, their study concluded SOX4 correlated positively with tumour grade and unfavourable outcome.

Pilot studies on the functional overlap in target regulation unfortunately yielded inconclusive results. Potential experimental failure remains an option, without replicative evidence to support its findings. Alternative, lack of functional overlap could be explained by the two transcription factors not sharing the same downstream effectors. Albeit this not being decisive for target such as N-cadherin, essential for EMT, it appears that it is true for the regulation of tumour neoangiogenesis, whereby FOXM1 mainly acts through VEGF, and SOX4 through ET-1. No direct link has been detected between SOX4 and VEGF, as well as between ET-1 and FOXM1. However, FOXM1 is can regulate VEGF through direct transcriptional binding, and this could in turn affect ET-1 secretion. Thus, FOXM1 could regulate ET-1 indirectly. To further establish the presence of a functional overlap, more experiments will have to be performed using a wider selection of downstream targets shared between the two transcription factors.

The pilot nature of this data infers that a lot of verifying experiments will need to be performed to obtain conclusive evidence of the nature of the interaction between the two transcription factors. However, further studies could reveal important information which could provide new insights on how to target either protein. Given their crucial role in cancer progression, and the essential role of SOX4 in angiogenesis discovered in this project, impeding the functioning of these targets could be beneficial for the treatment of breast cancer.

Page | 217

Chapter 4: Conclusions and Future Work

Tumour metastasis is the process whereby tumour cells migrate away from the primary site to colonize secondary sites in the body. Its understanding is crucial, as metastases are solely responsible for 90% of cancer mortality. To date, tumour metastasis is primarily treated with combinational therapy due to the difficulty in the detection of individual migrated cells, rendering surgical excision impossible. However, even following initial successful chemotherapy, most tumours eventually recur, due to the presence of single dormant resistant cancer cells present within the patient. These have the potential to replicate and create new tumours, which could be resistant to therapy. Novel strategies are necessary to identify and target metastatic cells. To do this, an in depth understanding of the metastatic process needs to be attained, so as to identify the triggers of cancer progression and prevent its occurrence.

This study aimed to characterise the phenotypical, physiological and mechanical alterations which are adopted by breast cancer cells upon the acquisition of resistance to anthracycline- and taxane- based cytotoxic chemotherapy. Then, it intended to identify the influence of the Forkhead Box (FOX) transcription factors on the regulation of these modifications, particularly of FOXO- FOXM1 axis, downstream effectors of the PI3K-Akt pathway, already shown to influence the insurgence of drug resistance. Finally, it planned to uncover novel therapeutic targets functioning downstream of the FOXO-FOXM1 axis, which could be used to modulate the activity of the resistant cell lines.

Initial comparative analysis of the behavioural and physical alterations of the epirubicin or paclitaxel resistant cell lines with the sensitive parental MCF-7 breast cancer revealed that both cell lines had undergone partial EMT, having lost the expression of E-cadherin and acquired that of N-cadherin and Vimentin. However, both resistant cell lines had not developed the characteristic elongated shape associated with a mesenchymal phenotype. Subsequent behavioural studies revealed that both resistant cell lines had completely changed their abilities to undergo different aspects of cancer progression. Acquired capabilities included increased migration, induction of angiogenesis, mammosphere forming capacity as well as the completely novel ability to metastasize in vivo, which was not seen with the parental MCF-7 cells.

Overall, the initial data revealed that breast cancer MCF-7 cells had undergone significant physiological and behavioural changes upon the acquisition of the drug resistance capacities. This novel insight correlated cancer progression with tumour resistance to chemotherapy, unveiling crucial information which, if validated further, could contribute substantially to the development

Page | 218 of therapeutic strategies to treat patients with breast cancer. For instance, therapeutic strategies will need to ensure that the tumour does not present a phenotype which would be more likely to become resistant to the therapies selected. To do this, patient tumour biopsies should be screened to detect the expression of markers which have to date been associated with the regulation of aspects like DNA damage response and cellular proliferation. Then, at regular intervals during treatment, patients should be monitored closely for the development of metastases. Unfortunately, the detection of individual metastasizing cells is, to date, virtually impossible to do. However, following the identification of cellular markers typically expressed in metastasizing cells, these could be targeted through the use of mono-clonal antibodies specifically selecting for their expression. Furthermore, patients showing signs of resistance to therapy should, according to the data obtained in this project, be monitored for the development of metastases. As a prevention, patients should be treated with combinational therapy, so as to target several different pathways simultaneously and limit the likelihood of tumour survival.

As part of the project, I sought to identify transcriptional targets which could cause the altered cellular behaviour which made resistant cell lines able to undergo cancer progression. Given the crucial role of the FOXO-FOXM1 axis in the mediation of drug resistance mechanisms, such as DNA damage response and mitosis, I next investigated on whether these transcription factors could contribute to the behaviour of the resistant cell lines. Characterisation of the FOXO3 expression and activity in sensitive and resistant cell lines uncovered a malfunction in the FOXO3 regulation of E-cadherin. In contrast to the sensitive cell lines, both resistant cell lines lacked E- cadherin mRNA expression despite presence of FOXO3. Further analysis unveiled that resistant cell lines exhibited significantly lower nuclear FOXO3 localization, as well as increasing levels of FOXO3 phosphorylation, indicating cytoplasmic sequestration and continual FOXO3 inactivation. This is in disparity with the subcellular localisation pattern in sensitive cell lines, where consistent with previous studies, drug treatment induced FOXO3 activation and nuclear translocation. It was then revealed that FOXO3 has an E-cadherin binding capacity consistent with its nuclear localisation in the different cell lines, with the wild-type cell line exhibiting the highest binding capacity and the resistant cell lines. Loss of E-cadherin expression coupled with FOXO3 inactivation prompted the attempt to transiently restore FOXO3 expression in the epirubicin sensitive and resistant cell line to indirectly affect E-cadherin expression, and potentially reverting the cell lines phenotype. However, despite the effectiveness of this strategy in sensitive cells, modifications in FOXO3 expression in the epirubicin resistant cell line did not result in quantifiable changes in E-cadherin expression. Alternatively, FOXO3 transient alteration was able

Page | 219 to significantly impact the mammosphere forming capacity of both epirubicin resistant and sensitive MCF-7 cell lines, unveiling a novel function for this tumour suppressor.

Overall, this data suggests that FOXO3 contributes substantially to the altered phenotype of the resistant cell lines. So far, the obtained data demonstrated that the drug resistant cell lines are in part able to alter their phenotype by inhibiting FOXO3 activity, thus preventing it from re-instating E-cadherin expression. Indeed, loss of E-cadherin expression is one of the initial steps which trigger the metastatic cascade: by losing the expression of this tight junction, cancer cells loosen the inter-cellular adherence and shed their polarised morphology, thus becoming more adapted for the loosened physical characteristics which allow a cell to accommodate migratory behaviours. Repression of FOXO3 in the resistant cell lines could therefore be one of the cellular strategies to promote cancer progression, particularly through the repression of FOXO3 promotion of E- cadherin expression.

Despite this important consequence of FOXO3 inhibition, I speculated that the FOXO3 inhibition, characteristic of the resistant cell lines, would primarily be a response to the chemotherapy: Indeed, as an attempt to evade apoptosis, inhibition of FOXO3 could prevent it from activating p53 through ATM signalling in response to DNA damage. Tumour cell evasion of apoptosis through its inhibition of pro-apoptotic signalling pathways, such as FOXO3, could, like in this case, inadvertently inhibit the inhibition of other tumour suppressive pathways. Thus, inhibition of FOXO3 activity also caused the direct inhibition of E-cadherin expression, rendering the drug resistant cell lines not only able to survive the damaging effects of chemotherapy, but also able to disrupt their cell-cell interactions which prevented them from attaining a pro-metastatic morphology.

To contribute to this data further, future work should encompass extensive characterisation of the loss of FOXO3/E-cadherin regulation, primarily by identifying mutations/methylation of the E- cadherin promoter. Only a detailed understanding of the disruption preventing FOXO3 from regulating E-cadherin expression will enable us to construct targeted therapies to reinstate FOXO3 functional role, potentially inhibiting the metastasis of the drug resistant cell lines by causing them to revert back to the parental MCF-7 behaviour. Furthermore, stable FOXO3 overexpression should be attempted to determine if this is sufficient to revert the mesenchymal phenotype of the resistant cell lines. Despite the available evidence of FOXO3 contribution to other aspects of cancer progression, the elucidation of its role in the progression of the resistant cell lines is still inconclusive: future work should analyse each area individually to determine in which instances FOXO3 re-activation could prevent their progression. Definition of FOXO3 expression should

Page | 220 then be defined in patient samples to serve as prognostic factors to predict cancer progression in patients. Taken together, this data will determine whether reverting the inhibition of FOXO3 could be a viable therapeutic strategy to prevent the cancer progression of the drug resistant cell lines. Due to FOXO3 tumour suppressive role, re-instating its expression may be more beneficial than directly inhibiting other tumour promoting genes, as these may still be necessary during selected homeostatic pathways, such as during cell proliferation or tissue repair. However, this process would have to be monitored closely, as it could cause healthy cells to undergo apoptosis. The effects of FOXO3 expression should therefore be studied extensively in cell lines before attempting to be translated into targeted drug therapies.

Alternatively, loss of FOXO3 expression should be used as a prognostic factor which could enable clinicians to predict the development of possible resistance to the current chemotherapy/radiotherapy treatment. Furthermore, a reduction in FOXO3 expression in the tumour biopsy could also warn that the tumour has the potential to transform into a malignant lesion. If used correctly, monitoring for FOXO3 expression could allow clinicians to alter the treatment course according to the tumour response more accurately than would be possible with the current available techniques.

Given the notable oncogenic function of the FOXO3 downstream factor FOXM1, I next investigated on its influence on the drug resistant cell lines acquired capacities. FOXM1 has not only been reported to influence every aspect of cancer progression, but to also be a crucial mediator of repair mechanisms which are capable of circumventing the damage induced by cytotoxic drugs. Analysis of FOXM1 influence of individual aspects of the cancer progression of the sensitive and drug resistant cell lines revealed that this transcription factor has a central enhancing role in all analysed areas, including cell migration, mammosphere formation, and tumour metastasis in vivo. Importantly, FOXM1 inhibition was sufficient to revert the acquired cancer progression capacities of the two resistant cell lines back to basal levels presented by the parental cell line. Furthermore, FOXM1 overexpression in the sensitive cell line was able to induce the increase in cancer progression abilities presented by the resistant cell lines. Overall, the data indicated that FOXM1, initially over-expressed to overcome the drug effect, is central to the behavioural alterations presented by the resistant cell lines.

FOXM1 oncogenic function has been characterised extensively in several cancer types. In this instance, its central role was unveiled in the regulation of the cancer progression of resistant cell line. However, its essential role in cellular homeostasis renders it an unattractive drug target, promoting the identification of a novel down-stream effector which could be targeted to induce

Page | 221 an equivalent effect. Future continuation of these studies should therefore focus on the indirect inhibition of FOXM1 function, instead of focusing on defining its role. Nevertheless, like FOXO3, FOXM1 overexpression should be measured in breast cancer patients prior to and in response to during cytotoxic chemotherapy, to predict for future loss of response to the therapy, as well as to identify to which chemotherapeutic treatment is more likely to induce the initiation of the cancer progression cascade.

According to the data obtained in this project, FOXM1 may have a greater impact on the behavioural changes exhibited by the drug resistant cell lines, than FOXO3. This may be in part due to the fact that FOXM1 promotes tumour development and growth, while FOXO3 is primarily a tumour suppressor: actively promoting the progression of a process can often have a greater impact than inhibiting it. However, in this case, the two regulators are directly linked, often fighting for the same binding site on the same target genes. Thus, basal expression levels can determine if a gene is expressed or repressed. To avert the need to target FOXM1 directly, a therapeutic strategy could be to regulate FOXO3 and resume its expression in the resistant cell lines. Suggested future experiments should aim to define the influence of FOXO3 on different aspects of cancer progression, thus determining the effectiveness of utilising FOXO3 to inhibit the cancer progression of the resistant cell lines. This information could later also be used to reveal whether reinstating FOXO3 expression would be sufficient to repress FOXM1 expression.

Alternatively, studies have shown that FOXM1 can be targeted directly to revert the metastatic phenotype of selected cell lines. For instance, in studies on nasopharyngeal carcinoma, the aberrant function of FOXM1 has been reverted through thiostrepton treatment. Thiostrepton is a natural cyclic oligopeptide antibiotic which has been shown to be a direct FOXM1 inhibitor. When applied to nasopharyngeal carcinoma cells, thiostrepton inhibition of FOXM1 impeded the migration and invasion of these cells. It was later determined that this was through the inhibition of FOXM1 directed downstream targets MMP-1 and -9 and fascin-1.

Despite the essential homeostatic role played by FOXM1 in cellular homeostasis, inhibiting FOXM1 activity in cancer cells could be a viable strategy due to FOXM1’s regulation of multiple oncogenic signalling pathway, which, when activated, are able to promote the transformation of a benign primary tumour to a metastatic lesion. To date, several FOXM1 direct effectors have been identified. These include VEGF and uPA, essential promoters of angiogenesis, the phosphorylation of Akt, which results in the promotion of several EMT pathways, ZEB1, ZEB2, Snail 2, contributing to the formation of mammospheres and the cancer stem cell phenotype, and β-catenin, MMP-2 and MMP-9, essential mediators of cellular metastasis. Therefore, targeting

Page | 222

FOXM1 directly by using inhibitors such as thiostrepton could simultaneously inhibit several aberrant strategies. It would however be essential to limit FOXM1 inhibition selectively to tumour cells. Indeed, despite the fact that FOXM1 expression is minimal in the majority of adult tissues, its expression is re-instated in actively proliferating cells. Systemic inhibition of FOXM1 could hence result in catastrophic toxic side effects for the body. To date, several studies have praised the effectiveness of thiostrepton in the selective inhibition of FOXM1 in neoplastic mesenchymal cell lines, resulting in the cancer cell lines reverting to an epithelial phenotype, and becoming unable to migrate and invade both in vivo and in vitro. The success of this preliminary data has led scientists to speculate that thiostrepton treatment would be an effective treatment when coupled to standard chemotherapy. However, substantial in vivo evidence is still lacking, and the systemic effect of thiostrepton administration in humans is still to be determined. Ideally, therefore, a method should be devised to administer FOXM1 selectively to the tumour cells, thus averting the risk of toxic side-effects which could damage healthy tissues. Only then will thiostrepton become an effective anti-tumour strategy which could simultaneously prevent cell lines from becoming resistant to chemotherapy and initiate cancer progression.

An alternative therapeutic strategy which averts the need to impede FOXM1 directly, is to target its aberrant function through the inhibition of its down-stream effectors. Following the identification of targets which participate in the FOXM1 directed cancer progression cascade, including tumour induced angiogenesis or metastasis, novel therapeutic strategies can be developed to directly inhibit their function, so as to indirectly prevent FOXM1 from exerting its harmful action, without preventing it from contributing to healthy cellular homeostasis. Targeting the down-stream effectors directly can furthermore enable the selective inhibition of the functionality of cancer cells, leaving healthy cells unaffected. This strategy could provide the therapeutic benefits of chemotherapy, without causing the side-effects induced by its lack of selectivity. Furthermore, it could identify and target individual cells which have already metastasized and are lying dormant to prevent their growth and development into the creation of micrometastases. This would be a unique advantage, as most available anticancer therapies only target cells which are actively proliferating, leaving the other cells unharmed: thus, single dormant tumour cells, which cannot be located with the available technology, could be left unharmed, eventually re-instating tumour recurrence. Ideally, targeting FOXM1 downstream targets upon the first detection of the presence of breast cancer in patients, could be used to prevent tumours from becoming malignant and spreading in other organs.

Targeting FOXM1 downstream targets could also facilitate tumour prognosis, with the expression levels of the target genes used to predict the likelihood of the initiation of cancer progression. Due

Page | 223 to FOXM1 regulation of the insurgence of resistance to anthracyclines and taxanes, the targets could also be used to predict tumour response to their treatment, to prevent the likelihood of the development of resistance to the drugs. Thus, by finding the right FOXM1 downstream target, as was attempted to be done in this project, one could simultaneously predict the tumour’s response to the therapeutic options, as well as determine its progression. This would enable the development of more personalised and targeted therapeutic approaches, coupled with more frequent screening for patients more at risk of developing metastases.

In the next section, KIF20A was identified as a FOXM1 down-stream effector. Like FOXM1, KIF20A contributes to the development of drug resistance in breast cancer cell lines, particularly mediating the circumvention of paclitaxel, during the late phases of the cell cycle. Conversely, this study unveiled a novel and poorly defined function for KIF20A as a mediator of cell migration, mammosphere formation and tumour metastasis in vivo. The effective inhibition of these processes in response to its transient silencing implies that KIF20A could be considered as a drug target for patients not responding to available chemotherapy, or as an adjuvant therapy to combat both drug resistance and risk of cancer progression for patients under epirubicin or paclitaxel therapy. In addition, KIF20A expression could be tested in tumour biopsies as a prognostic factor. Future work should however first define the exact mechanism through which this kinesin can inhibit migration, mammosphere formation and metastasis of cancer cells, as only basic speculations based on pilot studies were performed in this project.

Despite the validation of KIF20A function in cancer progression, the exact mechanism of its action remained unclear. To date, several studies had documented KIF20A involvement in the metastasis of different tumour types, and yet no study had unveiled its mechanism of action. In this project, I attempted to define its involvement by hypothesizing that KIF20A could impact on cancer progression by having a structural role. In general, KIF20A is known for its characteristic motor domain, as well as its plus-end microtubule-dependent motion ability. Its essential function during mitosis, particularly during anaphase and telophase, has been described extensively. Furthermore, individual reports have demonstrated that KIF20A can participate in other normal cellular biologic activities by transporting molecules contained within vesicles. These could, for instance, contain proteins which function in the extension of phylopodia during cellular migration.

In this project, I instead hypothesized that KIF20A may portray a more structural role, which may be related to its close interaction with cellular microtubules. Indeed, other reports have depicted the crucial function of microtubules in the maintenance of cellular structure during cellular

Page | 224 migration: the cytoskeleton needs to adapt to specific conformations to enable the cell to traverse through interstitial spaces during the intra- and extravasation of the metastatic process.

KIF20A has previously been reported to interact with microtubule and actin filaments in sub- cellular localisation experiments in breast cancer. Based on this information, I hypothesized that KIF20A may portray a structural role which would be essential for the cytoskeleton of a cell to accommodate the dormant, replicative and migratory phases of a cell’s life. Assuming this hypothesis to be true, KIF20A silencing would have the equivalent effect of a mitotic spindle poison, which could halt mitosis midway and cause cell death. Mitotic spindle poisons have also been shown to significantly impair cell migration, by causing the cells to be unable to retain the structural stability at the cell edges, thereby forcing the cells to be unable to support the cytoskeletal structural modifications essential for migration. Hence, the effect of KIF20A silencing on the resistant cell lines migration could be related to the indirect impairment of the cytoskeleton. In accordance, my pilot data showed that cells lacking KIF20A presented tubulin filaments which were more compacted towards the cell nuclei, whilst the unaltered breast cancer cells displayed a more relaxed and expansive tubulin, extending to the cellular protrusions. Despite the nature of the data, and the lack of experimental replicates, this initial information suggests that KIF20A silencing could be sufficient to impair cell motility by preventing it from altering its structure. As would joints, KIF20A could support the cytoskeleton when migrating cells would shift to a more elongated structure, or when the cell would extend protrusions to its structure to facilitate cell migration. Pilot confocal imagery supports this hypothesis, with the cells with silenced KIF20A appearing to be unable to form focal adhesions to the plate.

Overall, the data in this project supports the use of KIF20A targeted therapy to indirectly inhibit FOXM1 oncogenic regulation and preventing breast cancer cells from both becoming resistant to paclitaxel therapy, but also from progressing to a malignant state. However, this project failed to completely unveil the mechanism through which KIF20A regulates migration. Future work should therefore incorporate a more thorough investigation on the interaction between KIF20A and the cytoskeleton.

For instance, experiments could simultaneously stain for α-tubulin and filamentous acting (F-actin) one of the primary components of the cytoskeleton. Imaging should be performed under these conditions with cells both with silenced and unaltered KIF20A expression. Thus, the effect of KIF20A silencing will be assessed on individual components of the cytoskeleton, and, simultaneously, the direct interaction of KIF20A with the cytoskeleton will be visualised. Then, components of the cytoskeleton should be analysed and compared between different cell lines

Page | 225 presenting varying levels of KIF20A expression. This would further validate the presence of an interaction between KIF20A and the cytoskeleton, and determine whether cytoskeletal alterations are part of the cellular modifications which allow cells to attain a metastatic phenotype. Simultaneously, experiments should be performed to assess KIF20A interaction with the leading edges of migrating cells. Instead of impairing the whole cytoskeleton, KIF20A silencing could simply affect microtubule plus-end dynamics at the leading edge of migrating cells. Alternatively, KIF20A could interact with the actin component of the cytoskeleton. Actin also contributes to the creation of filopodia and lamellipodia, essential cellular protrusions which facilitate migration. Assessing migrating cells will however be more complicated than visualising adherent fixed cells. Subcellular fluorescent imagery should therefore be combined with continuous visualisation of migrating cells, to examine, for example, the formation of cellular protrusions in response to different levels of KIF20A expression.

This project also unveiled a completely novel function for the transcription factor SOX4 as a primary regulator of tumour induced angiogenesis. The SRY-related HMG-box 4 (SOX4) is an intronless gene which is part of the SOX family of transcription factors. This had recently attracted attention due to its essential role in several aspects of cancer progression. Like FOXM1, SOX4 was found to regulate EMT, cell migration, invasion and metastasis. Examples of genes which have been shown to be direct transcriptional targets of SOX4 include the transforming growth factor-β (TGF-β), Snail, ZEB, Twist, Wnt and Notch. However, no analysis had been performed to date to investigate the role of SOX4 in tumour induced angiogenesis. SOX4 functional similarity to FOXM1, as an oncogene contributing to several aspects of cancer progression through the regulation of more than one target, led to the speculation that SOX4 could, as FOXM1, also contribute to the rate-limiting process of tumour induced angiogenesis.

In this project, using the novel in vivo zebrafish embryo angiogenesis model, SOX4 was shown to be essential for the development of tumour induced angiogenesis in breast cancer cell lines. Indeed, SOX4 depletion from mesenchymal cells prevented these from inducing the protrusion of blood vessel from the proximal vessel structure. In accordance, SOX4 overexpression was correlated with a significant increase in the angiogenic response. This project thus unveiled a completely novel function for SOX4 as one of the primary modulators of neoangiogenesis. However, unlike FOXM1, SOX4 was found to regulate angiogenesis through a different pathway. Indeed, subsequent research showed that SOX4 directly regulated endothelin-1 (ET-1), which could, in turn, positively regulate neoangiogenesis by binding to the ET-1 receptors present on the zebrafish embryos blood vessels.

Page | 226

Overall, this project unveiled both functional similarities and substantial differences between the two transcription factors SOX4 and FOXM1. The functional similarities in the regulation of all aspects of cancer progression led to the hypothesis that there may be a connection between SOX4 and FOXM1. However, time limitations in the project prevented its relationship with the FOXO- FOXM1 axis from being elucidated. Pilot data instead suggested that SOX4 may act up-stream of FOXM1, and that this relationship may be dependent on the cell line. These results were consistent with reports in the literature which showed that SOX4 expression and mechanism of action was not only tissue dependent, but also dependent on the cell line within the tissue. Interestingly, SOX4 can act as both an oncogene and a tumour suppressor, and this is completely dependent upon which tissue is analysed. In my project, pilot data suggested that SOX4 acted as a tumour suppressor by inhibiting the activity of FOXM1. Simultaneously, data in this project, coupled with studies published to date, demonstrated that SOX4 can also clearly act as an oncogene, promoting all steps of cancer progression. I therefore hypothesized that SOX4 inhibition of FOXM1 may be due to residual tumour suppressive functions of SOX4 in healthy tissues. However, potential alterations in SOX4 signalling pathway have made this transcription factor a powerful oncogene, which can drive tumour progression alone.

Unfortunately, time limitations in the project also prevented the analysis of SOX4 role in the cancer progression of the drug resistant cell lines. Interestingly, SOX4 was shown to be more highly expressed in MCF-7 cell lines resistant to epirubicin than in their parental cell line. This pilot data suggests that SOX4 could contribute to the regulation of the DNA damage response, facilitating the cell lines overcoming of the DNA damage induced by the drug, thus rending the cells more resistant to therapy. Alternatively, SOX4 overexpression could contribute to driving the cancer progression of the drug resistant cell lines. It is interesting to note that in these cell lines, SOX4 does not appear to inhibit the expression of FOXM1, which is significantly over-expressed when compared to the parental cell lines. If SOX4 inhibited FOXM1, this may actually revert their phenotype to a more epithelial non-aggressive state. Also, it could cause the cells to become sensitised to the effect of epirubicin. SOX4 should therefore act as an oncogene. It would be important to elucidate the nature of the interaction between the two transcription factors, as well as unveiling whether SOX4 effectively aids the cancer progression or drug resistance of the drug resistant cell lines, as confirmation of this role would imply that it would not be sufficient to inhibit FOXM1 to combat the cancer progression of drug resistant cell lines. Instead, inhibiting FOXM1 would just enable the cell line to eventually overcome this inhibition by utilising SOX4 to undergo cancer progression, putting the patients at risk of becoming resistant to FOXM1 inhibition.

Page | 227

Given its promise as a major regulator of tumour induced angiogenesis, and previous studies reporting its oncogenic regulation of migration and EMT, SOX4 function should be studied extensively in both sensitive and drug resistant breast cancer cell lines. SOX4 could provide a novel target to inhibit the increased angiogenesis of the resistant cell lines, or an alternative way to inhibit their metastasis or cancer stem cell population if patients fail to respond to KIF20A or FOXM1 targeting. Furthermore, if SOX4 proves to be able to overcome the inhibition of FOXM1, understanding the role of this transcription factor in the cancer progression of the drug resistant cell lines will provide an additional potential prognostic factors in view, selecting the patients which are more likely not to benefit by selective FOXM1 inhibition, as well as a potential drug target to be targeted in combination with FOXM1.

Finally, this project helped the development of both a tumour angiogenesis and a cancer metastasis zebrafish in vivo model, two viable cost- and time-effective in vivo alternatives to provide reliable information on the tumour-host interactions which could, if characterised sufficiently, surpass the use of murine alternatives. Both models were developed to enable the injection of a cell line of choice, which could have been previously manipulated to present a particular phenotype. Furthermore, to facilitate its use, the model was developed to enable any type of fluorescent staining to be sufficient for the scientist to monitor the behaviour of the injected cell line following its insertion into the embryo. Indeed, to avoid the time-consuming protocol to attain stably fluorescent cell lines, transient fluorescent staining methods, such as the commercially available lipophilic membrane dyes (which can be applied to most live cell lines), are suitable and easily applicable for the use in this in vivo model. In addition, visualisation of the injected tumour is rendered possible by the possibility of removing the zebrafish embryo skin pigmentation through the addition of the chemical 1-phenyl 2-thiourea to the embryo’s water, enabling the use of any desired transgenic zebrafish line. Thus, the zebrafish model can present an infinite array of possibilities which could allow the study of several tumour-host interaction processes. Furthermore, unlike other with other existing in vivo models, any of the desired processes could be monitored live when using the zebrafish embryos. To do this, the injected embryos simply need to be placed in a solution containing a very low concentration of agarose to prevent movement, and can then be visualised continuously using any fluorescent microscope. Individual injected cancer cells can thus be tracked as they migrate within the embryo when using a confocal microscope, or the gradual sprouting of blood vessels can be visualised to detect its precise development to contour the injected tumour. In this way, this model could provide a unique platform to detect the triggers which initiate all cancer progression steps, providing information on the involvement of all host and tumour components, potentially revealing processes which had

Page | 228 previously been concealed by the lack of availability of an in vivo model which could maintain the host alive while visualising the tumour.

However, their novelty entails the validation of all zebrafish findings in murine models as confirmation of both the result, as well as the validity of the model. Lack of practical murine angiogenesis models could be surpassed by a combination of zebrafish tumour induced angiogenesis data with in vitro angiogenesis tools, such as tube formation assays. Alternatively, multiple aspects of the use of this model still necessitate elucidation: for instance, the cause of the different metastatic localisation of cells needs to be defined through, for example, the continuous monitoring of cell migration to determine if the cells follow the blood stream. Otherwise, influence of biomarkers present in the head or tail of the fish should be analysed, by harvesting individual sections and searching for the expression of characteristic biomarkers known to attract tumour cell lines in humans or murine models. Alternatively, novel methods need to be developed to exploit the full potential of the zebrafish embryo model: for instance, this model could be used to study the interactions of the tumour with the immune system. By exploiting the numerous zebrafish lines, each presenting a different fluorescently-labelled immune cell, this model could provide original insights on the role of either the innate or adaptive the immune system in the promotion/inhibition of cancer metastasis. Instead, zebrafish could be used as a high-throughput screening method select for novel compounds by defining their effect on tumour neoangiogenesis or metastasis. To do this, the compound would just have to be added to the water of recently tumour injected embryos in pre-defined concentrations.

In conclusion, this project has not only identified that breast cancer cells lines resistant to chemotherapy are more prone to undergo cancer progression, but that the FOXO-FOXM1 axis is key to this regulation. Furthermore, it has identified two novel and potential drug targets, KIF20A and SOX4, which could, following future studies, provide a therapeutic option for patients not responding to chemotherapy. Finally, it has developed a new fast and cost-effective model to characterise cancer cell lines in vivo, providing a platform with endless possibilities.

Page | 229

References

Adams, J.C. (2004). Roles of fascin in cell adhesion and motility. Curr. Opin. Cell Biol. 16, 590–596. Ahn, H., Sim, J., Abdul, R., Chung, M.S., Paik, S.S., Oh, Y.-H., Park, C.K., and Jang, K. (2015). Increased expression of forkhead box M1 is associated with aggressive phenotype and poor prognosis in estrogen receptor-positive breast cancer. J. Korean Med. Sci. 30, 390–397. Alberts B (2002). Molecular biology of the cell, 4th ed / Bruce Alberts [et al.] edn. Garland Science: New York Al-hajj, M., Wicha, M.S., Benito-hernandez, A., Morrison, S.J., and Clarke, M.F. (2003). Prospective identification of tumorigenic breast cancer cells. PNAS 100, 3983–3988. Ali, S., and Coombes, R.C. (2002). ENDOCRINE-RESPONSIVE BREAST CANCER AND STRATEGIES FOR COMBATING RESISTANCE. Nat. Rev. 2, 101–115. Alitalo, K., Tammela, T., and Petrova, T. V (2005). Lymphangiogenesis in development and human disease. Nature 438, 946–953. Allan, A.L., Vantyghem, S.A., Tuck, A.B., and Chambers, A.F. (2007). Tumor Dormancy and Cancer Stem Cells : Implications for the Biology and Treatment of Breast Cancer Metastasis. 26, 87–98. Anastas, J.N., and Moon, R.T. (2013). WNT signalling pathways as therapeutic targets in cancer. Nat. Rev. Cancer 13, 11–26. Anderson, M.J., Viars, C.S., Czekay, S., Cavenee, W.K., Arden, K.C., and Al, A.E.T. (1998). Cloning and Characterization of Three Human Forkhead Genes That Comprise an FKHR-like Gene Subfamily. 199, 187–199. Arvatz, G., Shafat, I., Levy-Adam, F., Ilan, N., and Vlodavsky, I. (2011). The heparanase system and tumor metastasis: Is heparanase the seed and soil? Cancer Metastasis Rev. 30, 253–268. Asahara, S., Takeda, K., Yamao, K., Maguchi, H., and Yamaue, H. (2013). Phase I/II clinical trial using HLA-A24-restricted peptide vaccine derived from KIF20A for patients with advanced pancreatic cancer. J. Transl. Med. 11, 291. Augustin, H.G., Koh, G.Y., Thurston, G., and Alitalo, K. (2009). Control of vascular morphogenesis and homeostasis through the angiopoietin-Tie system. Nat. Rev. Mol. Cell Biol. 10, 165–177. Bakin, a V, Tomlinson, a K., Bhowmick, N. a, Moses, H.L., and Arteaga, C.L. (2000). Phosphatidylinositol 3-kinase function is required for transforming growth factor beta-mediated epithelial to mesenchymal transition and cell migration. J. Biol. Chem. 275, 36803–36810. Baluk, P., Hashizume, H., and M, D.M. (2005). Cellular abnormalities of blood vessels as targets in cancer. Curr. Opin. Genet. Dev. 15, 102–111. Bao, B., Wang, Z., Ali, S., Kong, D., Banerjee, S., Ahmad, A., Li, Y., Azmi, A.S., Miele, L., and Sarkar, F.H. (2011). Over-expression of FoxM1 leads to epithelial-mesenchymal transition and cancer stem cell phenotype in pancreatic cancer cells. J. Cell. Biochem. 112, 2296–2306. Barrallo-Gimeno, A., and Nieto, M.A. (2005). The Snail genes as inducers of cell movement and survival: implications in development and cancer. Development 132, 3151–3161. Bartlett, J.M.S., Going, J.J., Mallon, E.A., Watters, A.D., Reeves, J.R., Stanton, P., Richmond, J., Donald, B., Ferrier, R., and Cooke, T.G. (2001). Evaluating HER2 amplification and overexpression in breast cancer. J. Pathol. 195, 422–428.

Page | 230

Belguise, K., Guo, S., and Sonenshein, G.E. (2007). Activation of FOXO3a by the green tea polyphenol epigallocatechin-3-gallate induces estrogen receptor alpha expression reversing invasive phenotype of breast cancer cells. Cancer Res. 67, 5763–5770. Beloqui, I., Abalde, L., Sanchez, Y., Callol, C., and Martin, A.G. (2011). Xenografts in zebrafish embryos as a rapid functional assay for breast cancer stem-like cell identification a n d e s i o s c i e n c e o n o t d i s t r i b u t e. Cell Cycle 3751–3757. Bergamaschi, A., Madak-Erdogan, Z., Kim, Y., Choi, Y.-L., Lu, H., and Katzenellenbogen, B.S. (2014). The forkhead transcription factor FOXM1 promotes endocrine resistance and invasiveness in estrogen receptor–positive breast cancer by expansion of stem-like cancer cells. Breast Cancer Res. 16, 436. Bergers, G., and Benjamin, L.E. (2003). Tumorigenesis and the angiogenic switch. Nat. Rev. Cancer 3, 401–410. Bergers, G., and Song, S. (2005). The role of pericytes in blood-vessel formation and maintenance. Neuro. Oncol. 452–464. Berx, G., and Van Roy, F. (2001). The E-cadherin/catenin complex: an important gatekeeper in breast cancer tumorigenesis and malignant progression. Breast Cancer Res. 3, 289–293. Berx, G., Cleton-Jansen, A.M., Strumane, K., de Leeuw, W.J., Nollet, F., van Roy, F., and Cornelisse, C. (1996). E-cadherin is inactivated in a majority of invasive human lobular breast cancers by truncation mutations throughout its extracellular domain. Oncogene 13, 1919–1925. Berx, G., Becker, K., Höfler, H., and Roy, F. Van (1998). Mutations of the Human E-Cadherin ( CDH1 ) Gene. 237, 226–237. Besson, A., Dowdy, S.F., and Roberts, J.M. (2008). Review CDK Inhibitors : Cell Cycle Regulators and Beyond. Dev. Cell 159–169. Boire, A., Covic, L., Agarwal, A., Jacques, S., Sherifi, S., and Kuliopulos, A. (2005). PAR1 is a matrix metalloprotease-1 receptor that promotes invasion and tumorigenesis of breast cancer cells. Cell 120, 303–313. Bonneterre, J., Dieras, V., Tubiana-Hulin, M., Bougnoux, P., Bonneterre, M.-E., Delozier, T., Mayer, F., Culine, S., Dohoulou, N., and Bendahmane, B. (2004). Phase II multicentre randomised study of docetaxel plus epirubicin vs 5-fluorouracil plus epirubicin and cyclophosphamide in metastatic breast cancer. Br. J. Cancer 91, 1466–1471. Borgstrom P, Gold DP, Hillan KJ, Ferrara N. (1999). Importance of VEGF for breast cancer angiogenesis in vivo: implications from intravital microscopy of combination treatments with an anti-VEGF neutralizing monoclonal antibody and doxorubicin. Anticancer Research 19, 4203-4214. Bos, P.D., Zhang, X.H.-F., Nadal, C., Shu, W., Gomis, R.R., Nguyen, D.X., Minn, A.J., van de Vijver, M.J., Gerald, W.L., Foekens, J. a, et al. (2009). Genes that mediate breast cancer metastasis to the brain. Nature 459, 1005–1009. Boulay, J.L., Dennefeld, C., and Alberga, a. (1987). The Drosophila developmental gene snail encodes a protein with nucleic acid binding fingers. Nature 330, 395–398. Brabletz, T., Jung, A., Reu, S., Porzner, M., Hlubek, F., Kunz-Schughart, L. a, Knuechel, R., and Kirchner, T. (2001). Variable beta-catenin expression in colorectal cancers indicates tumor progression driven by the tumor environment. PNAS 98, 10356–10361. Brooks, P.C., Strömblad, S., Klemke, R., Visscher, D., Sarkar, F.H., and Cheresh, D. a (1995). Antiintegrin alpha v beta 3 blocks human breast cancer growth and angiogenesis in human skin. J.

Page | 231

Clin. Invest. 96, 1815–1822. Brownawell, A.M.Y.M., Kops, G.J.P.L., and Macara, I.A.N.G. (2001). Inhibition of Nuclear Import by Protein Kinase B ( Akt ) Regulates the Subcellular Distribution and Activity of the Forkhead Transcription Factor AFX. Mol. Cell. Biol. 21, 3534–3546. Browne, B.C., O’Brien, N., Duffy, M.J., Crown, J., and O’Donovan, N. (2009). HER-2 signaling and inhibition in breast cancer. Curr. Cancer Drug Targets 9, 419–438. Brunet, A., Bonni, A., Zigmond, M.J., Lin, M.Z., Juo, P., Hu, L.S., Anderson, M.J., Arden, K.C., Blenis, J., and Greenberg, M.E. (1999). Akt Promotes Cell Survival by Phosphorylating and Inhibiting a Forkhead Transcription Factor. Cell 96, 857–868. Bugge, T.H., Lund, L.R., Kombrinck, K.K., Nielsen, B.S., Holmba, K., Drew, A.F., Flick, M.J., Witte, D.P., Danù, K., and Degen, J.L. (1998). Reduced metastasis of Polyoma virus middle T antigen-induced mammary cancer in plasminogen-deficient mice. Oncogene 16, 3097–3104. Burcombe, R.J., Makris, A., Richman, P.I., Daley, F.M., Noble, S., Pittam, M., Wright, D., Allen, S.A., and Dove, J. (2005). Evaluation of ER , PgR , HER-2 and Ki-67 as predictors of response to neoadjuvant anthracycline chemotherapy for operable breast cancer. Br. J. Cancer 92, 147–155. Burgering, B. (2008). A brief introduction to FOXOlogy. Oncogene 27, 2258–2262. Burgering, B.M.T. (2016). Decisions on life and death : FOXO Forkhead transcription factors are in command when PKB / Akt is off duty. J. Leukoc. Biol. 73, 689–701. Cai, H., Chen, J., He, B., Li, Q., Li, Y., and Gao, Y. (2015). A FOXM1 related long non-coding RNA contributes to gastric cancer cell migration. Mol. Cell. Biochem. 31–41. Cai, Y., Balli, D., Ustiyan, V., Fulford, L., Hiller, a., Misetic, V., Zhang, Y., Paluch, a. M., Waltz, S.E., Kasper, S., et al. (2013). Foxm1 Expression in Prostate Epithelial Cells Is Essential for Prostate Carcinogenesis. J. Biol. Chem. 288, 22527–22541. Calnan, DR; Brunet, A. (2008). The FoxO code. Oncogene 27, 2276–2288. Cantley, L.C. (2002). The Phosphoinositide 3-Kinase Pathway. 296, 1655–1658. Carpten, J.D., Faber, A.L., Horn, C., Donoho, G.P., Briggs, S.L., Robbins, C.M., Hostetter, G., Boguslawski, S., Moses, T.Y., Savage, S., et al. (2007). A transforming mutation in the pleckstrin homology domain of AKT1 in cancer. Nature 448, 439–445. Carr, J. (2010). FoxM1 Mediates Resistance to Herceptin and Paclitaxel. Cancer Res. 70, 1–18. Cavallaro, U., and Christofori, G. (2004). Cell adhesion and signalling by cadherins and Ig-CAMs in cancer. Nat. Rev. Cancer 4, 118–132. Chambers, A.F., Groom, A.C., and MacDonald, I.C. (2002). Dissemination and growth of cancer cells in metastatic sites. Nat. Rev. Cancer 2, 563–572. Chávez, M.N., Aedo, G., Fierro, F.A., Allende, M.L., and Egaña, J.T. (2016). Zebrafish as an Emerging Model Organism to Study Angiogenesis in Development and Regeneration. Front. Physiol. 7, 1–15. Chen, B., Dodge, M.E., Tang, W., Lu, J., Ma, Z., Fan, C., Wei, S., Hao, W., Kilgore, J., Williams, N.S., et al. (2009). Small molecule – mediated disruption of Wnt-dependent signaling in tissue regeneration and cancer. Nat. Chem. Biol. 5, 100–107. Chen, J., Gomes, A.R., Monteiro, L.J., Wong, S.Y., Wu, L.H., Ng, T.T., Karadedou, C.T., Millour, J., Ip, Y.C., Cheung, Y.N., et al. (2010). Constitutively nuclear FOXO3a localization predicts poor survival and promotes Akt phosphorylation in breast cancer. PLoS One 5.

Page | 232

Chen, S., Han, Q., Wang, X., Yang, M., Zhang, Z., Li, P., Chen, a, Hu, C., and Li, S. (2013). IBP-mediated suppression of autophagy promotes growth and metastasis of breast cancer cells via activating mTORC2/Akt/FOXO3a signaling pathway. Cell Death Dis. 4, e842. Cheng, G.Z., Chan, J., Wang, Q., Zhang, W., Sun, C.D., and Wang, L.H. (2007). Twist transcriptionally up-regulates AKT2 in breast cancer cells leading to increased migration, invasion, and resistance to paclitaxel. Cancer Res. 67, 1979–1987. Cheng, S., Tu, Y., and Zhang, S. (2013). FoxM1 Promotes Glioma Cells Progression by Up- Regulating Anxa1 Expression. PLoS One 8, e72376–e72376. Childs, S., Chen, J.-N., Garrity, D.M., and Fishman, M.C. (2002). Patterning of angiogenesis in the zebrafish embryo. Development 129, 973–982. Chiu, W.-T., Huang, Y.-F., Tsai, H.-Y., Chen, C.-C., Chang, C.-H., Huang, S.-C., Hsu, K.-F., and Chou, C.-Y. (2015). FOXM1 confers to epithelial-mesenchymal transition, stemness and chemoresistance in epithelial ovarian carcinoma cells. Oncotarget 6, 2349–2365. Cho, H.J., Baek, K.E., Saika, S., Jeong, M.-J., and Yoo, J. (2007). Snail is required for transforming growth factor-β-induced epithelial–mesenchymal transition by activating PI3 kinase/Akt signal pathway. Biochem. Biophys. Res. Commun. 353, 337–343. Choi, W.W.L., Lewis, M.M., Lawson, D., Yin-Goen, Q., Birdsong, G.G., Cotsonis, G. a, Cohen, C., and Young, A.N. (2005). Angiogenic and lymphangiogenic microvessel density in breast carcinoma: correlation with clinicopathologic parameters and VEGF-family gene expression. Mod Pathol 18, 143–152. Chou, C.C., Lee, K.H., Lai, I.L., Wang, D., Mo, X., Kulp, S.K., Shapiro, C.L., and Chen, C.S. (2014). AMPK reverses the mesenchymal phenotype of cancer cells by targeting the Akt-MDM2-Foxo3a signaling axis. Cancer Res. 74, 4783–4795. Clementi, M.E., Giardina, B., Di Stasio, E., Mordente, A., and Misiti, F. (2003). Doxorubicin-derived metabolites induce release of cytochrome C and inhibition of respiration on cardiac isolated mitochondria. Anticancer Res. 23, 2445–2450. Cobaleda, C., Cruz, J.J., González-Sarmiento, R., Sánchez-García, I., and Pérez-Losada, J. (2008). The Emerging Picture of Human Breast Cancer as a Stem Cell-based Disease. Stem Cell Rev. 4, 67–79. Cobleigh, M.A., Langmuir, V.K., Sledge, G.W., Miller, K.D., Haney, L., Novotny, W.F., Reimann, J.D., and Vassel, A. (2003). A Phase I / II Dose-Escalation Trial of Bevacizumab in Previously Treated Metastatic Breast Cancer. Semin. Oncol. 7754, 117–124. Cock-Rada, A.M., Medjkane, S., Janski, N., Yousfi, N., Perichon, M., Chaussepied, M., Chluba, J., Langsley, G., and Weitzman, J.B. (2012). SMYD3 Promotes Cancer Invasion by Epigenetic Upregulation of the Metalloproteinase MMP-9. Cancer Res. 72, 810–820. Coley, H.M. (2008). Mechanisms and strategies to overcome chemotherapy resistance in metastatic breast cancer. Cancer Treat. Rev. 34, 378–390. Cook, N., Brais, R., Qian, W., Hak, C.C.W., and Corrie, P.G. (2015). Endothelin-1 and endothelin B receptor expression in pancreatic adenocarcinoma. Br. Med. J. 68, 309–313. Costa, C., Soares, R., Reis-Filho, J.S., Leitão, D., Amendoeira, I., and Schmitt, F.C. (2002). Cyclo- oxygenase 2 expression is associated with angiogenesis and lymph node metastasis in human breast cancer. J. Clin. Pathol. 55, 429–434. Danø, K., Behrendt, N., Høyer-hansen, G., Johnsen, M., Lund, L.R., Ploug, M., and Rømer, J. (2005). Plasminogen activation and cancer. Thromb. Haemost. 93, 676–681.

Page | 233

Datta, S.R., Dudek, H., Tao, X., Masters, S., Fu, H., Gotoh, Y., and Greenberg, M.E. (1997). Akt Phosphorylation of BAD Couples Survival Signals to the Cell-Intrinsic Death Machinery. Cell 91, 231– 241. Dean, M., Fojo, T., and Bates, S. (2005). Tumour stem cells and drug resistance. Nat. Rev. Cancer 5, 275–284. Derksen, P.W.B., Liu, X., Saridin, F., van der Gulden, H., Zevenhoven, J., Evers, B., van Beijnum, J.R., Griffioen, A.W., Vink, J., Krimpenfort, P., et al. (2006). Somatic inactivation of E-cadherin and p53 in mice leads to metastatic lobular mammary carcinoma through induction of anoikis resistance and angiogenesis. Cancer Cell 10, 437–449. Deroo, B.J., and Korach, K.S. (2006). Estrogen receptors and human disease. J. Clin. Invest. 116, 561– 570. Dias, S., Hattori, K., Heissig, B., Zhu, Z., Wu, Y., Witte, L., Hicklin, D.J., Tateno, M., Bohlen, P., Moore, M.A.S., et al. (2001). Inhibition of both paracrine and autocrine VEGF/ VEGFR-2 signaling pathways is essential to induce long-term remission of xenotransplanted human leukemias. Proc. Natl. Acad. Sci. 98, 10857–10862. Dillon, R.L., Marcotte, R., Hennessy, B.T., Woodgett, J.R., Mills, G.B., and Muller, W.J. (2009). Akt1 and Akt2 Play Distinct Roles in the Initiation and Metastatic Phases of Mammary Tumor Progression. Cancer Res. 69, 5057–5064. Doganci, S., Yildirim, V., Erol, G., Kadan, M., Ozkan, G., and Ozgurtas, T. (2015). Comparison of angiogenic and proliferative effects of three commonly used agents for pulmonary artery hypertension ( sildenafil , iloprost , bosentan ): is angiogenesis always beneficial ? Eur. Rev. Med. Pharmacol. Sci. 19, 1900–1906. Dorman, J.B., Albinder, B., Shroyer, T., and Kenyon, C. (1995). The age-1 and daf-2 genes function in a common pathway to control the lifespan of C. elegans. Genetics 141, 1399–1405. Dre, D., Wyan, H., Mckillop, Æ.I.H., and Clemens, Æ.M.G. (2006). Bosentan inhibits tumor vascularization and bone metastasis in an immunocompetent skin-fold chamber model of breast carcinoma cell metastasis. Clin Exp Metastasis 23, 41–53. Duan, N., Hu, X., Yang, X., Cheng, H., and Zhang, W. (2015). MicroRNA-370 directly targets FOXM1 to inhibit cell growth and metastasis in osteosarcoma cells. Int. J. Clin. Exp. Pathol. 8, 10250–10260. Dubrovska, A., Kim, S., Salamone, R.J., Walker, J.R., Maira, S.-M., García-Echeverría, C., Schultz, P.G., and Reddy, V. a (2008). The role of PTEN / Akt / PI3K signaling in the maintenance and viability of prostate cancer stem-like cell populations. Proc. Natl. Acad. Sci. U. S. A. 106, 268–273. Dylla, S.J., Beviglia, L., Park, I.-K., Chartier, C., Raval, J., Ngan, L., Pickell, K., Aguilar, J., Lazetic, S., Smith-Berdan, S., et al. (2008). Colorectal cancer stem cells are enriched in xenogeneic tumors following chemotherapy. PLoS One 3, e2428. Egeblad, M., and Werb, Z. (2002). NEW FUNCTIONS FOR THE MATRIX METALLOPROTEINASES IN CANCER PROGRESSION. Nat. Rev. 2, 161–174. Eklund, L., Bry, M., and Alitalo, K. (2013). Mouse models for studying angiogenesis and lymphangiogenesis in cancer. Mol. Oncol. 7, 259–282. El-rehim, D.M.A., Ball, G., Pinder, S.E., Rakha, E., Paish, C., Robertson, J.F.R., Macmillan, D., Blamey, R.W., and Ellis, I.O. (2005). High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses. Int. J. Cancer 350, 340–350.

Page | 234

Engelman, J.A. (2009). Targeting PI3K signalling in cancer : opportunities , challenges and limitations. Nat. Rev. Cancer 9, 551–562. Engelman, J.A., Luo, J., and Cantley, L.C. (2006). The evolution of phosphatidylinositol 3-kinases as regulators of growth and metabolism. Nat. Rev. 7, 606–619. Fallis, A.. (2013). Mouse Models To Study Angiogenesis, Vasculogenesis and Arteriogenesis In The Context of Cardiovascular Diseases. J. Chem. Inf. Model. 53, 1689–1699. Fan, Q., Cai, Q., and Xu, Y. (2015). FOXM1 is a downstream target of LPA and YAP oncogenic signaling pathways in high grade serous ovarian cancer. Oncotarget 6, 27688–27699. Faneyte, I.F., Kristel, P.M.P., Maliepaard, M., Scheffer, G.L., Scheper, R.J., Schellens, J.H.M., and Vijver, M.J. Van De (2002). Expression of the Breast Cancer Resistance Protein in Breast Cancer. Clin. Cancer Res. 8, 1068–1074. Fernández de Mattos, S., Villalonga, P., Clardy, J., and Lam, E.W.-F. (2008). FOXO3a mediates the cytotoxic effects of cisplatin in colon cancer cells. Mol. Cancer Ther. 7, 3237–3246. Ferrara, N., Gerber, H.-P., and LeCouter, J. (2003). The biology of VEGF and its receptors. Nat. Med. 9, 669–676. Fidler, I.J. (2002). The organ microenvironment and cancer metastasis. Differentiation 70, 498–505. Fidler, I.J. (2003). The pathogenesis of cancer metastasis: the “seed and soil” hypothesis revisited. Nat. Rev. Cancer 3, 453–458. Fidler, I.J., and Talmadge, J.E. (1986). Evidence That Intravenously Derived Murine Pulmonary Melanoma MÃ © tastases Can Originate from the Expansion of a Single Tumor Cell. 5167–5171. Fojo, T., and Menefee, M. (2007). Mechanisms of multidrug resistance : the potential role of microtubule-stabilizing agents. Ann. Oncol. 18, 3–8. Friedl, P., and Alexander, S. (2011). Cancer invasion and the microenvironment: Plasticity and reciprocity. Cell 147, 992–1009. Friedl, P., and Gilmour, D. (2009). Collective cell migration in morphogenesis, regeneration and cancer. Nat. Rev. Mol. Cell Biol. 10, 445–457. Froelich-ammon, S.J., and Osheroff, N. (1995). Topoisomerase Poisons : Harnessing the Dark Side of Enzyme Mechanism. J. Biol. Chem. 953, 21429–21433. Fruman, D.A., and Cantley, L.C. (2002). Phosphoinositide 3-kinase in immunological systems. Immunology 14, 7–18. Funan, H., Wang, R.-Y., and Hsu, T. (1987). Clonal Origin of Metastasis in B16 Murine Melanoma : A cytogenetic Study. JNCI 78, 155–163. Furuyama, T., Nakazawa, T., Nakano, I., and Mori, N. (2000). consensus binding sequences for mouse DAF-16 homologues. 634, 629–634. Fuxe, J., Vincent, T., and De Herreros, A.G. (2010). Transcriptional crosstalk between TGFβ and stem cell pathways in tumor cell invasion: Role of EMT promoting Smad complexes. Cell Cycle 9, 2363– 2374. Gangopadhyay, S., Nandy, A., Hor, P., and Mukhopadhyay, A. (2013). Breast cancer stem cells: a novel therapeutic target. Clin. Breast Cancer 13, 7–15. Garber, B.K. (2007). Notch emerges as a new cancer drug target. JNCI 99, 1284–1285.

Page | 235

Gatzeva-topalova, P.Z., Warner, L.R., Pardi, A., and Carlos, M. (1985). Identification of a novel force- generating protein, kinesin, involved in microtubule-based motility. Cell 42, 39–50. Giaccone, G., and Pinedo, H.M. (1996). Drug Resistance. Oncologist 1, 82–87. Ginestier, C., Liu, S., and Diebel, M. (2010). CXCR1 blockade selectively targets human breast cancer stem cells in vitro and in xenografts. J. Clin. Invest. 120, 485–497. Giordano, F.J., Pink, P., McKirnana, M.D., Nozaki, S., DeMaria, A.N., Dillman, W.H., Mathieu-Costello, O., and Hammond, K.H. (1996). Intracoronary gene transfer of fibroblast growth factor-5 increases blood flow and contractile function in an ischemic region of the heart. Nat. Med. 2, 534–539. GLOBOCAN (2017) Globocan Fact sheets by cancer. Available at: http://globocan.iarc.fr/Pages/fact_sheets_cancer.aspx (Accessed: 13 February 2017). Goldhirsch, A., Glick, J.H., and Gelber, R.D. (1998). Meeting Highlights : International Consensus Panel on the Treatment of Primary Breast Cancer. J. Natl. Cancer Inst. 90, 1601–1608. Gomes, A.R., Zhao, F., and Lam, E.W.F. (2013). Role and regulation of the forkhead transcription factors FOXO3a and FOXM1 in carcinogenesis and drug resistance. Chin. J. Cancer 32, 365–370. Gong, A., and Huang, S. (2012). FoxM1 and Wnt/β-catenin signaling in glioma stem cells. Cancer Res. 72, 5658–5662. Good, D.J., Polverini, P.J., Rastinejad, F., Le Beau, M.M., Lemons, R.S., Frazier, W. a, and Bouck, N.P. (1990). A tumor suppressor-dependent inhibitor of angiogenesis is immunologically and functionally indistinguishable from a fragment of thrombospondin. Proc. Natl. Acad. Sci. U. S. A. 87, 6624–6628. Goswami, S., Sahai, E., Wyckoff, J.B., Cammer, M., Cox, D., Pixley, F.J., Stanley, E.R., Segall, J.E., and Condeelis, J.S. (2005). Macrophages Promote the Invasion of Breast Carcinoma Cells via a Colony- Stimulating Factor-1 / Epidermal Growth Factor Paracrine Loop. Cancer Res. 65, 5278–5283. Gottesman, M.M., Fojo, T., and Bates, S.E. (2002). MULTIDRUG RESISTANCE IN CANCER : ROLE OF ATP-DEPENDENT TRANSPORTERS. Nat. Rev. 2, 48–58. Gould Rothberg, B.E., and Bracken, M.B. (2006). E-cadherin immunohistochemical expression as a prognostic factor in infiltrating ductal carcinoma of the breast: A systematic review and meta- analysis. Breast Cancer Res. Treat. 100, 139–148. Grady, W.M., Willis, J., Guilford, P.J., Dunbier, a K., Toro, T.T., Lynch, H., Wiesner, G., Ferguson, K., Eng, C., Park, J.G., et al. (2000). Methylation of the CDH1 promoter as the second genetic hit in hereditary diffuse gastric cancer. Nat. Genet. 26, 16–17. Gralow, J.R. (2005). Optimizing the treatment of metastatic breast cancer. Breast Cancer Res. Treat. 89. Grant, C.M., and Kyprianou, N. (2013). Epithelial mesenchymal transition (EMT) in prostate growth and tumor progression. Transl. Androl. Urol. 2, 202–211. Grant, K., Loizidou, M., and Taylor, I. (2003). Endothelin-1: a multifunctional molecule in cancer. Br. J. Cancer 88, 163–166. Greer, E.L., and Brunet, A. (2005). FOXO transcription factors at the interface between longevity and tumor suppression. Oncogene 24, 7410–7425. Guchelaar, H., Nortier, J.W.R., Dezentje, V.O., Van, C.J.H., and Gelderblom, H. (2009). Clinical Implications of CYP2D6 Genotyping inT amoxifen reatment for Breast Cancer. Clin. Cancer Res. 15, 15–21.

Page | 236

Guo, W., Lasky, J.L., and Wu, H. (2006). Cancer stem cells. Pediatr. Res. 59, 59R–64R. Gupta, G.P., and Massagué, J. (2006). Cancer metastasis: building a framework. Cell 127, 679–695. Gupta, G.P., Nguyen, D.X., Chiang, A.C., Bos, P.D., Kim, J.Y., Nadal, C., Gomis, R.R., Manova-todorova, K., and Massague, J. (2007). Mediators of vascular remodelling co-opted for sequential steps in lung metastasis. Nature 446, 766–771. Gutierrez, M.C., Detre, S., Johnston, S., Mohsin, S.K., Shou, J., Allred, D.C., Schiff, R., Osborne, C.K., and Dowsett, M. (2016). Molecular Changes in Tamoxifen-Resistant Breast Cancer : Relationship Between Estrogen Receptor , HER-2 , and p38 Mitogen-Activated Protein Kinase. J. Clin. Oncol. 23, 2469–2476. Habashy, H.O., Rakha, E.A., Aleskandarany, M., Ahmed, M.A., Green, A.R., Ellis, I.O., and Powe, D.G. (2011). FOXO3a nuclear localisation is associated with good prognosis in luminal-like breast cancer. Breast Cancer Res. Treat. 129, 11–21. Hall, A., and Hall, A. (2013). Rho GTPases and the Actin Cytoskeleton. Front. Cell Biol. 509, 509–514. Hanahan, D., and Folkman, J. (1996). Patterns and emerging mechanisms of the angiogenic switch during tumorigenesis. Cell 86, 353–364. Hanahan, D., and Weinberg, R. a (2008). Retrospective: Judah Folkman (1933-2008). Science 319, 1055. Hanahan, D., and Weinberg, R. a. (2011). Hallmarks of cancer: The next generation. Cell 144, 646– 674. Hankinson, S.E., Colditz, G.A., and Willett, W.C. (2004). Review Towards an integrated model for breast cancer etiology The lifelong interplay of genes , lifestyle , and hormones. Breast Cancer Res. 6, 213–218. Harbeck, N., Kates, R.E., Schmitt, M., Gauger, K., Kiechle, M., Jänicke, F., Thomssen, C., Maxime, P., and Foekens, J.A. (2004). Urokinase-type plasminogen activator and its inhibitor type 1 predict disease outcome and therapy response in primary breast cancer. Clin. Breast Cancer 5, 348–352. Hart, I.R., and Fidler, I.J. (1980). Role of organ selectivity in the determination of metastatic patterns of B16 melanoma. Cancer Res. 40, 2281–2287. Hashizume, H., Baluk, P., Morikawa, S., McLean, J.W., Thurston, G., Roberge, S., Jain, R.K., and McDonald, D.M. (2000). Openings between defective endothelial cells explain tumor vessel leakiness. Am. J. Pathol. 156, 1363–1380. Hayashi, S., Eguchi, H., Tanimoto, K., Yoshida, T., Omoto, Y., and Inoue, A. (2003). The expression and function of estrogen receptor alpha and beta in human breast cancer and its clinical application. Endocr. Relat. Cancer 10, 193–202. Henderson, B.E., and Feigelson, H.S. (2000). Hormonal carcinogenesis. Carcinogenesis 21, 427–433. Heppner, K.J., Matrisian, L.M., Jensen, R.A., and Rodgerst, W.H. (1996). Expression of Most Matrix Metalloproteinase Family Members in Breast Cancer Represents a Tumor-Induced Host Response. Am. J. Pathol. 149, 273–282. Herschkowitz, J.I., Komurov, K., Zhou, A.Y., Gupta, S., Yang, J., Hartwell, K., Onder, T.T., Gupta, P.B., Evans, K.W., Hollier, B.G., et al. (2010). Correction for Taube et al., Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes. Proc. Natl. Acad. Sci. U. S. A. 107, 19132.

Page | 237

Herynk, M.H., and Fuqua, S.A.W. (2016). Estrogen Receptor Mutations in Human Disease. 25, 869– 898. Heuberger, J., and Birchmeier, W. (2010). Interplay of cadherin-mediated cell adhesion and canonical Wnt Signalling. Cold Spring Hard Perspect Biol. 2, a002915. Hill, R., and Wu, H. (2009). PTEN, stem cells, and cancer stem cells. J. Biol. Chem. 284, 11755–11759. Hill, E., Clarke, M., and Barr, F. a (2000). The Rab6-binding kinesin, Rab6-KIFL, is required for cytokinesis. EMBO J. 19, 5711–5719. Holland, J.D., Klaus, A., Garratt, A.N., and Birchmeier, W. (2013). Wnt signaling in stem and cancer stem cells. Curr. Opin. Cell Biol. 25, 254–264. Homey, B., Soto, H., Ge, N., Catron, D., Buchanan, M.E., Mcclanahan, T., Mu, A., Zlotnik, A., Murphy, E., Yuan, W., et al. (2001). Involvement of chemokine receptors in breast cancer metastasis. Nature 410, 51–56. Hong, T.M., Chen, Y.L., Wu, Y.Y., Yuan, A., Chao, Y.C., Chung, Y.C., Wu, M.H., Yang, S.C., Pan, S.H., Shih, J.Y., et al. (2007). Targeting neuropilin 1 as an antitumor strategy in lung cancer. Clin. Cancer Res. 13, 4759–4768. Honore, S., Pasquier, E., and Braguer, D. (2005). Understanding microtubule dynamics for improved cancer therapy. Cell. Mol. Life Sci. 62, 3039–3056. Horst, A. Van Der, Vries-smits, A.M.M. De, Brenkman, A.B., Triest, M.H. Van, Broek, N. Van Den, Colland, F., Maurice, M.M., and Burgering, B.M.T. (2006). FOXO4 transcriptional activity is regulated by monoubiquitination and USP7 / HAUSP. Nat. Cell Biol. 8, 1064–1076. Hsu, S., Lin, T., Wang, S., Chuang, C., Lee, F., and Huang, H. (2016). Endothelin receptor blockers reduce shunting and angiogenesis in cirrhotic rats. Eur. J. Clin. Invest. 46, 572–580. Huber, M. a., Kraut, N., and Beug, H. (2005). Molecular requirements for epithelial-mesenchymal transition during tumor progression. Curr. Opin. Cell Biol. 17, 548–558. Hui, R.C.-Y., Francis, R.E., Guest, S.K., Costa, J.R., Gomes, A.R., Myatt, S.S., Brosens, J.J., and Lam, E.W.-F. (2008a). Doxorubicin activates FOXO3a to induce the expression of multidrug resistance gene ABCB1 (MDR1) in K562 leukemic cells. Mol. Cancer Ther. 7, 670–678. Hui, R.C.-Y., Gomes, A.R., Constantinidou, D., Costa, J.R., Karadedou, C.T., Fernandez de Mattos, S., Wymann, M.P., Brosens, J.J., Schulze, A., and Lam, E.W.-F. (2008b). The forkhead transcription factor FOXO3a increases phosphoinositide-3 kinase/Akt activity in drug-resistant leukemic cells through induction of PIK3CA expression. Mol. Cell. Biol. 28, 5886–5898. Huntly, B.J.P., Shigematsu, H., Deguchi, K., Lee, B.H., Mizuno, S., Duclos, N., Rowan, R., Amaral, S., Curley, D., Williams, I.R., et al. (2004). MOZ-TIF2 , but not BCR-ABL , confers properties of leukemic stem cells to committed murine hematopoietic progenitors. Cancer Cell 6, 587–596. Hyder, S.M., Murthy, L., and Stance, G.M. (1998). Progestin Regulation of Vascular Endothelial Growth Factor in Human Breast Cancer Cell. Cancer Res. 58, 18–21. IARC (2017) INTERNATIONAL AGENCY FOR RESEARCH ON CANCER. Available at: https://www.iarc.fr/ (Accessed: 13 February 2017). Inoue, H., Takahashi, H., Hashimura, M., Eshima, K., Akiya, M., Matsumoto, T., and Saegusa, M. (2015). Cooperation of Sox4 with β-catenin/p300 complex in transcriptional regulation of the Slug gene during divergent sarcomatous differentiation in uterine carcinosarcoma. BMC Cancer 16, 53.

Page | 238

Iqbal, J., Chong, P.Y., and Tan, P.H. (2013). Breast cancer stem cells: an update. J. Clin. Pathol. 1–6. Jacobs, F.M.J., Heide, L.P. Van Der, Wijchers, P.J.E.C., Burbach, J.P.H., Hoekman, M.F.M., and Smidt, M.P. (2003). FoxO6 , a Novel Member of the FoxO Class of Transcription Factors with Distinct Shuttling Dynamics. J. Biol. Chem. 278, 35959–35967. Jeong, H., Kim, M., Hyun, S., Ho, B., Bae, S., Hee, J., Chul, W., and Gong, G. (2011). Different prognostic signi fi cance of CD24 and CD44 expression in breast cancer according to hormone receptor status q. The Breast 20, 78–85. Jiang, L., Wang, P., and Chen, H. (2014a). Overexpression of FOXM1 is associated with metastases of nasopharyngeal carcinoma. Ups. J. Med. Sci. 1–9. Jiang, L., Wang, P., Chen, L., and Chen, H. (2014b). Down-regulation of FoxM1 by thiostrepton or small interfering RNA inhibits proliferation , transformation ability and angiogenesis , and induces apoptosis of nasopharyngeal carcinoma cells. Int J Clin Exp Pathol 7, 5450–5460. Johnsen, M., Lund, L.R., Rømer, J., Almholt, K., and Danø, K. (1998). Cancer invasion and tissue remodeling: Common themes in proteolytic matrix degradation. Curr. Opin. Cell Biol. 10, 667–671. Jordan, N.J., Gee, J.M.W., Barrow, D., Wakeling, A.E., and Nicholson, I. (2004). Increased constitutive activity of PKB / Akt in tamoxifen resistant breast cancer MCF-7 cells. Breast Cancer Res. Treat. 87, 167–180. Joshi, K., Banasavadi-Siddegowda, Y., Mo, X., Kim, S.-H., Mao, P., Kig, C., Nardini, D., Sobol, R.W., Chow, L.M.L., Kornblum, H.I., et al. (2013). MELK-dependent FOXM1 phosphorylation is essential for proliferation of glioma stem cells. Stem Cells 31, 1051–1063. Ju, J.C.H.L., and Wang, X.Y.Y.T.J. (2016). SOX4 is a potential prognostic factor in human cancers : a systematic review and meta-analysis. Clin Transl Oncol 18, 65–72. Ju, S.-Y., Huang, C.-Y., Huang, W.-C., and Su, Y. (2015). Identification of thiostrepton as a novel therapeutic agent that targets human colon cancer stem cells. Cell Death Dis. 6, e1801. Kaestner, K.H., Kno, W., and Martı, D.E. (2000). Unified nomenclature for the winged helix / forkhead transcription factors. Genes Dev. 14, 142–146. Kang, Y., Siegel, P.M., Shu, W., Drobnjak, M., Kakonen, S.M., Cord??n-Cardo, C., Guise, T. a., and Massagu??, J. (2003). A multigenic program mediating breast cancer metastasis to bone. Cancer Cell 3, 537–549. Karadedou, C.T., Gomes, a R., Chen, J., Petkovic, M., Ho, K.-K., Zwolinska, a K., Feltes, a, Wong, S.Y., Chan, K.Y.K., Cheung, Y.-N., et al. (2012). FOXO3a represses VEGF expression through FOXM1- dependent and -independent mechanisms in breast cancer. Oncogene 31, 1845–1858. Karnoub, A.E., Dash, A.B., Vo, A.P., Sullivan, A., Brooks, M.W., Bell, G.W., Richardson, A.L., Polyak, K., Tubo, R., and Weinberg, R. a (2007). Mesenchymal stem cells within tumour stroma promote breast cancer metastasis. Nature 449, 557–563. Karunarathna, U., Kongsema, M., Zona, S., Gong, C., Cabrera, E., Gomes, a R., Man, E.P.S., Khongkow, P., Tsang, J.W.-H., Khoo, U.-S., et al. (2015). OTUB1 inhibits the ubiquitination and degradation of FOXM1 in breast cancer and epirubicin resistance. Oncogene 35, 1–12. Kathryn, J.C., Sireesha V, G., and Stanley, L. (2012). Triple Negative Breast Cancer Cell Lines: One Tool in the Search for Better Treatment of Triple Negative Breast Cancer. Breast Dis 32, 35–48. Kato, M., Yuan, H., Xu, Z.-G., Lanting, L., Li, S.-L., Wang, M., Hu, M.C.-T., Reddy, M. a, and Natarajan, R. (2006). Role of the Akt/FoxO3a pathway in TGF-beta1-mediated mesangial cell dysfunction: a

Page | 239 novel mechanism related to diabetic kidney disease. J. Am. Soc. Nephrol. 17, 3325–3335. Katoh, M. (2011). Network of WNT and other regulatory signaling cascades in pluripotent stem cells and cancer stem cells. Curr Pharm Biotechnol 12, 160–170. Katoh, M., and Katoh, M. (2004). Human FOX gene family (Review). Int. J. Oncol. 25, 1495–1500. Kaufmann, E., Muller, D., and Knochel, W. (1995). DNA Recognition Site Analysis of Xenopus Winged. J Mol Biol 248, 239–254. Kaurah, P., MacMillan, A., Boyd, N., Senz, J., De Luca, A., Chun, N., Suriano, G., Zaor, S., Van Manen, L., Gilpin, C., et al. (2007). Founder and recurrent CDH1 mutations in families with hereditary diffuse gastric cancer. Jama 297, 2360–2372. Kawai, H., Li, H., Chun, P., Avraham, S., and Avraham, H.K. (2002). Direct interaction between BRCA1 and the estrogen receptor regulates vascular endothelial growth factor (VEGF) transcription and secretion in breast cancer cells. Oncogene 21, 7730–7739. Khongkow, M., Olmos, Y., Gong, C., Gomes, A.R., Monteiro, L.J., Yagüe, E., Cavaco, T.B., Khongkow, P., Man, E.P.S., Laohasinnarong, S., et al. (2013a). SIRT6 modulates paclitaxel and epirubicin resistance and survival in breast cancer. Carginogenesis 34, 1476–1486. Khongkow, P., Karunarathna, U., Khongkow, M., Gong, C., Gomes, a R., Yagüe, E., Monteiro, L.J., Kongsema, M., Zona, S., Man, E.P.S., et al. (2013b). FOXM1 targets NBS1 to regulate DNA damage- induced senescence and epirubicin resistance. Oncogene 33, 1–12. Khongkow, P., Karunarathna, U., Khongkow, M., Gong, C., Gomes, a R., Yagüe, E., Monteiro, L.J., Kongsema, M., Zona, S., Man, E.P.S., et al. (2013c). FOXM1 targets NBS1 to regulate DNA damage- induced senescence and epirubicin resistance. Oncogene 1–12. Khongkow, P., Gomes, a R., Gong, C., Man, E.P.S., Tsang, J.W.-H., Zhao, F., Monteiro, L.J., Coombes, R.C., Medema, R.H., Khoo, U.S., et al. (2015a). Paclitaxel targets FOXM1 to regulate KIF20A in mitotic catastrophe and breast cancer paclitaxel resistance. Oncogene 1–13. Khongkow, P., Gomes, a R., Gong, C., Man, E.P.S., Tsang, J.W.-H., Zhao, F., Monteiro, L.J., Coombes, R.C., Medema, R.H., Khoo, U.S., et al. (2015b). Paclitaxel targets FOXM1 to regulate KIF20A in mitotic catastrophe and breast cancer paclitaxel resistance. Oncogene 35, 1–13. Kikuno, N., Shiina, H., Urakami, S., Kawamoto, K., Hirata, H., Tanaka, Y., Place, R.F., Pookot, D., Majid, S., Igawa, M., et al. (2007). Knockdown of astrocyte-elevated gene-1 inhibits prostate cancer progression through upregulation of FOXO3a activity. Oncogene 26, 7647–7655. Kim, I., Ramakrishna, S., Gusarova, G.A., Yoder, H.M., Costa, R.H., and Kalinichenko, V. V (2005). The Forkhead Box M1 Transcription Factor Is Essential for Embryonic Development of Pulmonary Vasculature *. J. Biol. Chem. 280, 22278–22286. Kim, S.-J., Shin, J.-Y., Lee, K.-D., Bae, Y.-K., Sung, K.W., Nam, S.J., and Chun, K.-H. (2012). MicroRNA let-7a suppresses breast cancer cell migration and invasion through downregulation of C-C chemokine receptor type 7. Breast Cancer Res. 14, R14. Kirschmann, D. a, Seftor, E. a, Fong, S.F.T., Nieva, D.R.C., Sullivan, C.M., Edwards, E.M., Sommer, P., Csiszar, K., and Hendrix, M.J.C. (2002). A Molecular Role for Lysyl Oxidase in Breast Cancer Invasion A Molecular Role for Lysyl Oxidase in Breast Cancer Invasion. Cancer Res. 62, 4478–4483. Klauber N (1997). Inhibition of Angiogenesis and Breast Cancer in Mice by the Microtubule Inhibitors 2-Methoxyestradiol and Taxol. Cancer Res. 57, 81_86. Klymkowsky, M.W., and Savagner, P. (2009). Epithelial-mesenchymal transition: a cancer

Page | 240 researcher’s conceptual friend and foe. Am. J. Pathol. 174, 1588–1593. Komuro, I., Kurihara, H., Sugiyama, T., Takaku, F., and Yazaki, Y. (1988). Endothelin stimulates c-fos and c-myc expression and proliferation of vascular smooth muscle cells. FEBS Lett. 238, 249–252. Konecny, G.E., Meng, Y.G., Untch, M., Wang, H.-J., Bauerfeind, I., Epstein, M., Stieber, P., Vernes, J.- M., Gutierrez, J., Hong, K., et al. (2004). Association between HER-2/neu and vascular endothelial growth factor expression predicts clinical outcome in primary breast cancer patients. Clin. Cancer Res. 10, 1706–1716. Kong, F.-F., Qu, Z.-Q., Yuan, H.-H., Wang, J.-Y., Zhao, M., Guo, Y.-H., Shi, J., Gong, X.-D., Zhu, Y.-L., Liu, F., et al. (2014). Overexpression of FOXM1 is associated with EMT and is a predictor of poor prognosis in non-small cell lung cancer. Oncol. Rep. 31, 2660–2668. Koo, C.-Y., Muir, K.W., and Lam, E.W.-F. (2012). FOXM1: From cancer initiation to progression and treatment. Biochim. Biophys. Acta - Gene Regul. Mech. 1819, 28–37. Kops, G.J., and Burgering, B.M. (1999). Forkhead transcription factors: new insights into protein kinase B (c-akt) signaling. J Mol Med 77, 656–665. Korkola, J.E., Devries, S., Fridlyand, J., Hwang, E.S., Estep, A.L.H., Chen, Y., Chew, K.L., Dairkee, S.H., Jensen, R.M., and Waldman, F.M. (2003). Differentiation of Lobular versus Ductal Breast Carcinomas by Expression Microarray Analysis Differentiation of Lobular versus Ductal Breast Carcinomas by Expression. Cancer Res. 7167–7175. Kotb, A.M., Hierholzer, A., and Kemler, R. (2011). Replacement of E-cadherin by N-cadherin in the mammary gland leads to fibrocystic changes and tumor formation. Breast Cancer Res. 13, 1–16. Krol, J., Francis, R.E., Albergaria, A., Sunters, A., Polychronis, A., Coombes, R.C., and Lam, E.W.-F. (2007). The transcription factor FOXO3a is a crucial cellular target of gefitinib (Iressa) in breast cancer cells. Mol. Cancer Ther. 6, 3169–3179. Küchler, A.M., Gjini, E., Peterson-Maduro, J., Cancilla, B., Wolburg, H., and Schulte-Merker, S. (2006). Development of the zebrafish lymphatic system requires VEGFC signaling. Curr. Biol. 16, 1244–1248. Labrousse, A.M., Zappaterra, M.D., Rube, D.A., Bliek, V. Der, Cell, M., Sesaki, H., Jensen, R.E., Biol, J.C., Arimura, S., Tsutsumi, N., et al. (2003). Cell Migration : Integrating Signals from Front to Back. Science (80-. ). 302, 1704–1710. Lalich, M., Mcneel, D.G., Wilding, G., Liu, G., Lalich, M., Mcneel, D.G., Wilding, G., Liu, G., Lalich, M., Mcneel, D.G., et al. (2016). Endothelin Receptor Antagonists in Cancer Therapy. Cancer Invest. 7907, 785–794. Lam, E.W.-F., Brosens, J.J., Gomes, A.R., and Koo, C.-Y. (2013). Forkhead box proteins: tuning forks for transcriptional harmony. Nat. Rev. Cancer 13, 482–495. Lapidot, T., Sirard, C., Vormoor, J., Murdoch, B., Hoang, T., Caceres-Cortes, J., Minden, M., Peterson, B., Caligiuri, M.A., and Dick, J. (1994). A cell initiating human acute myeloid leukaemia after transplantation into SCID mice. Nature 367, 645–648. Lara, R., Mauri, F.A., Taylor, H., Derua, R., Shia, A., Gray, C., Nicols, A., Shiner, R.J., Schofield, E., Bates, P.A., et al. (2011). An siRNA screen identifies RSK1 as a key modulator of lung cancer metastasis. Oncogene 30, 3513–3521. Laurent, G., and Jaffre, J. (2016). Signaling pathways activated by daunorubicin. Blood 98, 913–925. Laurentiis, M. De, Arpino, G., Massarelli, E., Ruggiero, A., Carlomagno, C., Ciardiello, F., Diego, D., Caputo, F., Cancello, G., Montagna, E., et al. (2005). A Meta-Analysis on the Interaction between

Page | 241

HER-2 Expression and Response to EndocrineTreatment in Advanced Breast Cancer. Clin. Cancer Res. 11, 4741–4748. Le, N.H., Franken, P., and Fodde, R. (2008). Tumour-stroma interactions in colorectal cancer: converging on beta-catenin activation and cancer stemness. Br. J. Cancer 98, 1886–1893. Lea, S., Price, J.E., and Fidler, I.J. (1986). Different Deficiencies in the Prevention of Tumorigenic-Low- Metastatic Murine K-1735b Melanoma Cells from Producing Metastases. JCNI 77, 915–924. Lebeau, A. (2010). Precancerous lesions of the breast. Breast Care 5, 204–206. Lebok, P., Huber, J., Burandt, E.C., Lebeau, A., Marx, A.H., Terracciano, L., Heilenkötter, U.W.E., Jänicke, F., Müller, V., Paluchowski, P., et al. (2016). Loss of membranous VEGFR1 expression is associated with an adverse phenotype and shortened survival in breast cancer. Mol. Med. Rep. 14, 1443–1450. Lee, L.M.J., Seftor, E. a, Bonde, G., Cornell, R. a, and Hendrix, M.J.C. (2005). The fate of human malignant melanoma cells transplanted into zebrafish embryos: assessment of migration and cell division in the absence of tumor formation. Dev. Dyn. 233, 1560–1570. Lee, S.L.C., Rouhi, P., Dahl Jensen, L., Zhang, D., Ji, H., Hauptmann, G., Ingham, P., and Cao, Y. (2009). Hypoxia-induced pathological angiogenesis mediates tumor cell dissemination, invasion, and metastasis in a zebrafish tumor model. Proc. Natl. Acad. Sci. U. S. A. 106, 19485–19490. De Leeuw, W.J.F., Berx, G., Vos, C.B.J., Peterse, J.L., Van De Vijver, M.J., Litvinov, S., Van Roy, F., Cornelisse, C.J., and Cleton-Jansen, A.M. (1997). Simultaneous loss of E-cadherin and catenins in invasive lobular breast cancer and lobular carcinoma in situ. J. Pathol. 183, 404–411. Lehr, H. a., Folpe, a., Yaziji, H., Kommoss, F., and Gown, a. M. (2000). Cytokeratin 8 immunostaining pattern and E-cadherin expression distinguish lobular from ductal breast carcinoma. Am. J. Clin. Pathol. 114, 190–196. Li, F., Li, F., Tiede, B., Massagué, J., and Kang, Y. (2007). Beyond tumorigenesis : cancer stem cells in metastasis. Cancer Res. 17, 3–14. Li, J., Wang, Y., Luo, J., Fu, Z., Ying, J., Yu, Y., and Yu, W. (2012). miR-134 inhibits epithelial to mesenchymal transition by targeting FOXM1 in non-small cell lung cancer cells. FEBS Lett. 586, 3761–3765. Li, L., Li, Z., Kong, X., Xie, D., Jia, Z., Jiang, W., Cui, J., Du, Y., Wei, D., Huang, S., et al. (2014). Down- regulation of microRNA-494 via loss of SMAD4 increases FOXM1 and β-catenin signaling in pancreatic ductal adenocarcinoma cells. Gastroenterology 147, 485–97.e18. Li, M., Brooks, C.L., Kon, N., and Gu, W. (2004). A Dynamic Role of HAUSP in the p53-Mdm2 Pathway. Mol. Cell 13, 879–886. Li, Q., Zhang, N., Jia, Z., Le, X., Dai, B., Wei, D., Huang, S., Tan, D., and Xie, K. (2009a). Critical role and regulation of transcription factor FoxM1 in human gastric cancer angiogenesis and progression. Cancer Res. 69, 3501–3509. Li, Q., Zhang, N., Jia, Z., Le, X., Dai, B., Wei, D., Huang, S., Tan, D., and Xie, K. (2009b). Critical Role and Regulation of Transcription Factor FoxM1 in Human Gastric Cancer Angiogenesis and Progression. 3501–3509. Li, Q., Ma, Z., Liu, Y., Kan, X., Wang, C., Su, B., Li, Y., Zhang, Y., Wang, P., Luo, Y., et al. (2016a). Low doses of paclitaxel enhance liver metastasis of breast cancer cells in the mouse model. FEBS J. 283, 2836–2852.

Page | 242

Li, X., Lewis, M.T., Huang, J., Gutierrez, C., Osborne, C.K., Wu, M., Hilsenbeck, S.G., Pavlick, A., Zhang, X., Chamness, G.C., et al. (2008). Intrinsic Resistance of Tumorigenic Breast Cancer Cells to Chemotherapy. JNCI 100, 672–679. Li, Y., Drabsch, Y., Pujuguet, P., Ren, J., van Laar, T., Zhang, L., van Dam, H., Clément-Lacroix, P., and ten Dijke, P. (2015a). Genetic depletion and pharmacological targeting of αv integrin in breast cancer cells impairs metastasis in zebrafish and mouse xenograft models. Breast Cancer Res. 17, 1–16. Li, Y., Chen, P., Zu, L., Liu, B., Wang, M., and Zhou, Q. (2016b). MicroRNA-338-3p suppresses metastasis of lung cancer cells by targeting the EMT regulator Sox4. Am J Cancer Res 6, 127–140. Li, Z., Jia, Z., Gao, Y., Xie, D., Wei, D., Cui, J., Mishra, L., Huang, S., Zhang, Y., and Xie, K. (2015b). Activation of Vitamin D Receptor Signaling Downregulates the Expression of Nuclear FOXM1 Protein and Suppresses Pancreatic Cancer Cell Stemness. Clin. Cancer Res. 21, 844–853. Liang, C.-C.C., Park, A.Y., and Guan, J.-L.L. (2007). In vitro scratch assay: a convenient and inexpensive method for analysis of cell migration in vitro. Nat. Protoc. 2, 329–333. Liao, Y.-L., Sun, Y.-M., Chau, G.-Y., Chau, Y.-P., Lai, T.-C., Wang, J.-L., Horng, J.-T., Hsiao, M., and Tsou, a-P. (2008). Identification of SOX4 target genes using phylogenetic footprinting-based prediction from expression microarrays suggests that overexpression of SOX4 potentiates metastasis in hepatocellular carcinoma. Oncogene 27, 5578–5589. Lieschke, G.J., and Currie, P.D. (2007). Animal models of human disease: zebrafish swim into view. Nat. Rev. Genet. 8, 353–367. Lister-Sharp, D., McDonagh, M.S., Khan, K.S., and Kleijnen, J. (2000). A rapid and systematic review of the effectiveness and cost-effectiveness of the taxanes used in the treatment of advanced breast and ovarian cancer. Health Technol. Assess. 4, 1–113. Liu, H., Yin, J., Wang, H., Jiang, G., Deng, M., Zhang, G., Bu, X., Cai, S., Du, J., and He, Z. (2015). FOXO3a modulates WNT/β-catenin signaling and suppresses epithelial-to-mesenchymal transition in prostate cancer cells. Cell. Signal. 27, 510–518. Liu, Y., Su, C., Shan, Y., Yang, S., and Ma, G. (2016). Targeting Notch1 inhibits invasion and angiogenesis of human breast cancer cells via inhibition Nuclear Factor-κB signaling. Am J Transl Res 8, 2681–2692. Lombaerts, M., van Wezel, T., Philippo, K., Dierssen, J.W.F., Zimmerman, R.M.E., Oosting, J., van Eijk, R., Eilers, P.H., van de Water, B., Cornelisse, C.J., et al. (2006). E-cadherin transcriptional downregulation by promoter methylation but not mutation is related to epithelial-to-mesenchymal transition in breast cancer cell lines. Br. J. Cancer 94, 661–671. Longley, D.B., and Johnston, P.G. (2005). Molecular mechanisms of drug resistance. J. Pathol. 275– 292. Lopez-girona, A., Furnari, B., Mondesert, O., and Early, P.R. (1999). Nuclear localization of Cdc25 is regulated by DNA damage and a 14-3-3 protein. Lett. to Nat. 397, 172–175. De Luca, A., Fiorillo, M., Peiris-Pagès, M., Ozsvari, B., Smith, D.L., Sanchez-Alvarez, R., Martinez- Outschoorn, U.E., Cappello, A.R., Pezzi, V., Lisanti, M.P., et al. (2015). Mitochondrial biogenesis is required for the anchorage-independent survival and propagation of stem-like cancer cells. Oncotarget 6. Lund, L.R., Rømer, J., Thomasset, N., Solberg, H., Pyke, C., Bissell, M.J., Danø, K., and Werb, Z. (1996). Two distinct phases of apoptosis in mammary gland involution : proteinase- independent and - dependent pathways. Development 193, 181–193.

Page | 243

Ma, L., Teruya-Feldstein, J., and Weinberg, R. a (2007). Tumour invasion and metastasis initiated by microRNA-10b in breast cancer. Nature 449, 682–688. Maehama, T., and Dixon, J.E. (1998). The Tumor Suppressor , PTEN /MMAC1, Dephosphorylates the Lipid Second Messenger, Phosphatidylinositol 3,4,5-Triphosphate. J. Biol. Chem. 278, 13375–13379. Maeshima, Y., Sudhakar, A., Lively, J.C., Ueki, K., Kharbanda, S., Kahn, C.R., Sonenberg, N., Hynes, R.O., and Kalluri, R. (2002). Tumstatin, an endothelial cell-specific inhibitor of protein synthesis. Science 295, 140–143. Mani, S.A., Guo, W., Liao, M., Eaton, E.N., Ayyanan, A., Zhou, A.Y., Brooks, M., Reinhard, F., Zhang, C.C., Shipitsin, M., et al. (2008). The Epithelial-Mesenchymal Transition Generates Cells with Properties of Stem Cells. Cell 113, 704–715. Marangoni, E., Lecomte, N., Durand, L., de Pinieux, G., Decaudin, D., Chomienne, C., Smadja-Joffe, F., and Poupon, M.-F. (2009). CD44 targeting reduces tumour growth and prevents post-chemotherapy relapse of human breast cancers xenografts. Br. J. Cancer 100, 918–922. Marques, I.J., Weiss, F.U., Vlecken, D.H., Nitsche, C., Bakkers, J., Lagendijk, A.K., Partecke, L.I., Heidecke, C.-D., Lerch, M.M., and Bagowski, C.P. (2009). Metastatic behaviour of primary human tumours in a zebrafish xenotransplantation model. BMC Cancer 9, 128. Massagué, J. (2008). TGF β in Cancer. Cell 134, 215–230. Matsuda, K., Maruyama, H., Guo, F., Itakura, J., Matsumoto, Y., Lander, A.D., and Korc, M. (2001). Glypican-1 Is Overexpressed in Human Breast Cancer and Modulates the Mitogenic Effects of Multiple Heparin-binding Growth Factors in Breast Cancer Cells. Cancer Res. 61, 5562–5569. Matsuura, a, Yamochi, W., Hirata, K., Kawashima, S., and Yokoyama, M. (1998). Stimulatory interaction between vascular endothelial growth factor and endothelin-1 on each gene expression. Hypertension 32, 89–95. Mauri, D., Pavlidis, N., Polyzos, N.P., and Ioannidis, J.P.A. (2006). Survival With Aromatase Inhibitors and Inactivators Versus. J. Natl. Cancer Inst. 98, 1285–1291. Maxhimer, J.B., Quiros, R.M., Stewart, R., Dowlatshahi, K., Gattuso, P., Fan, M., Prinz, R.A., and Xu, X. (132AD). Heparanase-1 expression is associated with the metastatic potential of breast cancer. Surgery 2, 326–333. Mayo, L.D., and Donner, D.B. (2001). A phosphatidylinositol 3-kinase ͞ Akt pathway promotes translocation of Mdm2 from the cytoplasm to the nucleus. PNAS 98, 11598–11603. Meng, F.-D., Wei, J.-C., Qu, K., Wang, Z.-X., Wu, Q.-F., Tai, M.-H., Liu, H.-C., Zhang, R.-Y., and Liu, C. (2015). FoxM1 overexpression promotes epithelial-mesenchymal transition and metastasis of hepatocellular carcinoma. World J. Gastroenterol. 21, 196–213. Miki, Y., Swensen, J., Shattuck-eidens, D., Futreal, P.A., Harshman, K., Tavtigian, S., Liu, Q., Cochran, C., Bennett, L.M., Ding, W., et al. (1994). Strong Candidate for the Breast and Ovarian Cancer. Science (80-. ). 266, 66–71. Miller, S.J., Lavker, R.M., and Sun, T. (2005). Interpreting epithelial cancer biology in the context of stem cells : Tumor properties and therapeutic implications. Biochim. Biophys. Acta 1756, 25–52. Minn, A.J., Gupta, G.P., Siegel, P.M., Bos, P.D., Shu, W., Giri, D.D., Viale, A., Olshen, A.B., Gerald, W.L., and Massague, J. (2005). Genes that mediate breast cancer metastasis to lung. Nature 436, 518–524. Minotti, G., Menna, P., Salvatorelli, E., Cairo, G., and Gianni, L. (2004). Anthracyclines : Molecular Advances and Pharmacologic Developments in Antitumor Activity and Cardiotoxicity. Pharmacol.

Page | 244

Rev. 56, 185–229. Mitchell, K., Svenson, K.B., Longmate, W.M., Gkirtzimanaki, K., Sadej, R., and Wang, X. (2010). Suppression of Integrin α 3 β 1 in Breast Cancer Cells Reduces Cyclooxygenase-2 Gene Expression and Inhibits Tumorigenesis , Invasion , and Cross-Talk to Endothelial Cells. Cancer Res. 70, 6359– 6367. Miyamoto, K., Araki, K.Y., Naka, K., Arai, F., Takubo, K., Yamazaki, S., Matsuoka, S., Miyamoto, T., Ito, K., Ohmura, M., et al. (2007). Foxo3a Is Essential for Maintenance of the Hematopoietic Stem Cell Pool. Cancer Stem Cell 1, 101–112. Monteiro, L.J., Khongkow, P., Kongsema, M., Morris, J.R., Man, C., Weekes, D., Koo, C.-Y., Gomes, a R., Pinto, P.H., Varghese, V., et al. (2013). The Forkhead Box M1 protein regulates BRIP1 expression and DNA damage repair in epirubicin treatment. Oncogene 32, 4634–4645. de Moraes, G.N., Delbue, D., Silva, K.L., Robaina, M.C., Khongkow, P., Gomes, A.R., Zona, S., Crocamo, S., Mencalha, A.L., Magalh??es, L.M., et al. (2015). FOXM1 targets XIAP and Survivin to modulate breast cancer survival and chemoresistance. Cell. Signal. 27, 2496–2505. Morel, A.-P., Lièvre, M., Thomas, C., Hinkal, G., Ansieau, S., and Puisieux, A. (2008). Generation of breast cancer stem cells through epithelial-mesenchymal transition. PLoS One 3, e2888. Moshal, K.S., Ferri-Lagneau, K.F., and Leung, T. (2010). Zebrafish model: worth considering in defining tumor angiogenesis. Trends Cardiovasc. Med. 20, 114–119. Moy, B., and Goss, P.E. (2006). Lapatinib : Current Status and Future Directions in Breast Cancer. Oncologist 11, 1047–1057. Mueller, M.D., Vigne, J.L., Minchenko, a, Lebovic, D.I., Leitman, D.C., and Taylor, R.N. (2000). Regulation of vascular endothelial growth factor (VEGF) gene transcription by estrogen receptors alpha and beta. Proc. Natl. Acad. Sci. U. S. A. 97, 10972–10977. Murdoch, C., Muthana, M., Coffelt, S.B., and Lewis, C.E. (2008). The role of myeloid cells in the promotion of tumour angiogenesis. Nat. Rev. Cancer 8, 618–631. Muss, H.B., Thor, A.D., Berry, D.A., Kute, T., Liu, E.T., and Koerner, F. (1994). c-erb-2 expression and response to adjuvant therapy in women with node-positive early breast cancer. N. Engl. J. Med. 330, 1260–1265. Myatt, S.S., and Lam, E.W.-F. (2007). The emerging roles of forkhead box (Fox) proteins in cancer. Nat. Rev. Cancer 7, 847–859. Nagy, J. a., Chang, S.H., Shih, S.C., Dvorak, A.M., and Dvorak, H.F. (2010). Heterogeneity of the tumor vasculature. Semin. Thromb. Hemost. 36, 321–331. Nahta, R., and Esteva, F.J. (2006). HER2 therapy Molecular mechanisms of trastuzumab resistance Trastuzumab : mechanisms of antitumor effects. Breast Cancer Res. 8, 1–8. Naka, K., Hoshii, T., Muraguchi, T., Tadokoro, Y., Ooshio, T., Kondo, Y., Nakao, S., Motoyama, N., and Hirao, A. (2010). TGF-beta-FOXO signalling maintains leukaemia-initiating cells in chronic myeloid leukaemia. Nature 463, 676–680. Nakamura, Y., Tanaka, F., Haraguchi, N., Mimori, K., Matsumoto, T., Inoue, H., Yanaga, K., and Mori, M. (2007). Clinicopathological and biological significance of mitotic centromere-associated kinesin overexpression in human gastric cancer. Br. J. Cancer 97, 543–549. Nakshatri, H. (2010). Radiation resistance in breast cancer : cells to blame ? Breast 12, 2–3.

Page | 245

Nakshatri, H. (2011). Biomarkers for breast cancer stem cells : the challenges ahead R eview. Biomarkers Med 5, 661–671. Nawrocki-Raby, B., Gilles, C., Polette, M., Bruyneel, E., Laronze, J.Y., Bonnet, N., Foidart, J.M., Mareel, M., and Birembaut, P. (2003). Upregulation of MMPS by soluble E-cadherin in human lung tumor cells. Int. J. Cancer 105, 790–795. Nestal de Moraes, G., Delbue, D., Silva, K.L., Cristina Robaina, M., Khongkow, P., Gomes, A.R., Zona, S., Crocamo, S., Luiz Mencalha, A., Magalhães, L.M., et al. (2015). FOXM1 targets XIAP and Survivin to modulate breast cancer survival and chemoresistance. Cell. Signal. 27, 2496–2505. Nguyen, P. a, Groen, A.C., Loose, M., Ishihara, K., Wühr, M., Field, C.M., and Mitchison, T.J. (2014). Spatial organization of cytokinesis signaling reconstituted in a cell-free system. Science 346, 244– 247. Nicholson-Dykstra, S., Higgs, H.N., and Harris, E.S. (2005). Actin Dynamics : Growth from Dendritic Branches The dendritic nucleation model was devised to. Curr. Biol. 15, 346–357. Nicoli, S., and Presta, M. (2007). The zebrafish/tumor xenograft angiogenesis assay. Nat. Protoc. 2, 2918–2923. Nieman, M.T., Prudoff, R.S., Johnson, K.R., and Wheelock, M.J. (1999). N-cadherin Promotes Motility in Human Breast Cancer Cells Regradless of of their E-Cadherin Expression. J. Cell Biol. 147, 631–643. Nieto, M. a, Sargent, M.G., Wilkinson, D.G., and Cooke, J. (1994). Control of cell behavior during vertebrate development by Slug, a zinc finger gene. Science (80-. ). 264, 835–839. Nisato, R.E., Tille, J., Jonczyk, A., Goodman, S.L., and Pepper, M.S. (2003). Canastatin acts on endothelial and tumor cells via mitochondrial damage initiated through interaction with integrins. Cancer Res. 65, 105–119. Nobutaka, H., Yasuko, N., and Yasushi, O. (1998). Kinesin and dynein superfamily proteins in organelle transport and cell division. Curr. Opin. Cell Biol. 10, 60–73. Noguchi, S. (2006). Predictive factors for response to docetaxel in human breast cancers. Cancer Sci 97, 813–820. Nyberg, P., Xie, L., and Kalluri, R. (2005). Endogenous Inhibitors of Angiogenesis. Cancer Res. 65, 3967–3979. O’Reilly, M.S., Holmgren, L., Shing, Y., Chen, C., Rosenthal, R. a., Moses, M., Lane, W.S., Cao, Y., Helene Sage, E., and Folkman, J. (1994). Angiostatin: A novel angiogenesis inhibitor that mediates the suppression of metastases by a Lewis lung carcinoma. Cell 79, 315–328. O’Reilly, M.S., Boehm, T., Shing, Y., Fukai, N., Vasios, G., Lane, W.S., Flynn, E., Birkhead, J.R., Olsen, B.R., and Folkman, J. (1997). Endostatin: an endogenous inhibitor of angiogenesis and tumor growth. Cell 88, 277–285. Okkenhaug, K., and Vanhaesebroeck, B. (2001). New Responsibilities for the PI3K Regulatory Subunit p85 α. Sci. STKE 1–6. Okkenhaug, K., and Vanhaesebroeck, B. (2003). PI3K IN LYMPHOCYTE DEVELOPMENT , DIFFERENTIATION AND ACTIVATION. Nat. Rev. 3, 317–330. de Olano, N., Koo, C.-Y., Monteiro, L.J., Pinto, P.H., Gomes, A.R., Aligue, R., and Lam, E.W.-F. (2012). The p38 MAPK-MK2 axis regulates E2F1 and FOXM1 expression after epirubicin treatment. Mol. Cancer Res. 10, 1189–1202.

Page | 246

Onder, T.T., Gupta, P.B., Mani, S.A., Yang, J., Lander, E.S., and Weinberg, R.A. (2008). Loss of E- Cadherin Promotes Metastasis via Multiple Downstream Transcriptional Pathways. Cancer Res 68, 3645–3655. Padua, D., Zhang, X.H., Wang, Q., Nadal, C., Gerald, W.L., Gomis, R.R., and Massague, J. (2008). TGF b Primes Breast Tumors for Lung Metastasis Seeding through Angiopoietin-like 4. Cell 133, 66–77. Palma, M. De, Murdoch, C., Venneri, M.A., Naldini, L., and Lewis, C.E. (2007). Tie2-expressing monocytes : regulation of tumor angiogenesis and therapeutic implications. Trends Immunol. 28, 519–524. Pardal, R., Clarke, M.F., Morrison, S.J., Medical, H.H., and Arbor, A. (2003). Applying the principles of stem-cell biology to cancer. Nat. Rev. 3, 895–902. Park, H.J., Gusarova, G., Wang, Z., Carr, J.R., Li, J., Kim, K.-H., Qiu, J., Park, Y.-D., Williamson, P.R., Hay, N., et al. (2011). Deregulation of FoxM1b leads to tumour metastasis. EMBO Mol. Med. 3, 21–34. Parvani, J.G., and Schiemann, W.P. (2013). Sox4, EMT programs, and the metastatic progression of breast cancers: mastering the masters of EMT. Breast Cancer Res. 15, R72. Patanaphan, V., Salazar, O., and Rafael, R. (1988). Breast cancer: metastatic patterns and their prognosis. South. Med. J. 81, 1109–1112. Pece, S., Tosoni, D., Confalonieri, S., Mazzarol, G., Vecchi, M., Ronzoni, S., Bernard, L., Viale, G., Pelicci, P.G., Paolo, P., et al. (2010). Biological and Molecular Heterogeneity of Breast Cancers Correlates with Their Cancer Stem Cell Content. Cell 140, 62–73. Perez-Moreno, M., Jamora, C., and Fuchs, E. (2003). Sticky business: Orchestrating cellular signals at adherens junctions. Cell 112, 535–548. Polgar, O., and Bates, S.E. (2005). ABC transporters in the balance : is there a role in multidrug resistance ? 1. Biochem. Soc. Trans. 33, 241–245. Pollard, T.D., Borisy, G.G., and Haven, N. (2003). Cellular Motility Driven by Assembly and Disassembly of Actin Filaments. Cell 112, 453–465. Polyak, K., and Weinberg, R. a (2009). Transitions between epithelial and mesenchymal states: acquisition of malignant and stem cell traits. Nat. Rev. Cancer 9, 265–273. Ponti, D., Costa, A., Zaffaroni, N., Pratesi, G., Petrangolini, G., Coradini, D., Pilotti, S., Pierotti, M.A., and Daidone, M.G. (2005). Isolation and In vitro Propagation of Tumorigenic Breast Cancer Cells with Stem / Progenitor Cell Properties. Cancer Res 65, 5506–5511. Potente, M., Urbich, C., Sasaki, K.I., Hofmann, W.K., Heeschen, C., Aicher, A., Kollipara, R., DePinho, R. a., Zeiher, A.M., and Dimmeler, S. (2005). Involvement of Foxo transcription factors in angiogenesis and postnatal neovascularization. J. Clin. Invest. 115, 2382–2392. Presta, M., Maier, J.A., Rusnati, M., and Ragnotti, G. (1989). Basic fibroblast growth factor is released from endothelial extracellular matrix in a biologically active form. J. Cell. Physiol. 140, 68–74. Pruitt, K., Zinn, R.L., Ohm, J.E., McGarvey, K.M., Kang, S.-H.L., Watkins, D.N., Herman, J.G., and Baylin, S.B. (2006). Inhibition of SIRT1 reactivates silenced cancer genes without loss of promoter DNA hypermethylation. PLoS Genet. 2, e40. Pyke, C., Grsem, N., Ralfkiaer, E., Brunner, N., and Dane, K. (1993). Receptor for Urokinase Is Present in T \ imor-associated Breast Carcinoma1 Macrophages in Ductal. Cancer Res. 53, 1911–1915. Qian, B., and Pollard, J.W. (2016). Macrophage Diversity Enhances Tumor Progression and

Page | 247

Metastasis. Cell 141, 39–51. Quan, M., Cui, J., Xia, T., Jia, Z., Xie, D., Wei, D., Huang, S., Huang, Q., Zheng, S., and Xie, K. (2015). Merlin/NF2 Suppresses Pancreatic Tumor Growth and Metastasis by Attenuating the FOXM1- Mediated Wnt/beta-catenin Signaling. Raguz, S., and Yagu, E. (2008). Resistance to chemotherapy : new treatments and novel insights into an old problem. Britis 387–391. Raica, M., Cimpean, A.M., and Ribatti, D. (2009). Angiogenesis in pre-malignant conditions. Eur. J. Cancer 45, 1924–1934. Rajamanickam, S., Panneerdoss, S., Gorthi, A., Timilsina, S., Onyeagucha, B., Kovalsky, D., Ivanov, D., Hanes, M. a, Vadlamudi, R.K., and Chen, Y. (2016). Inhibition of FOXM1-Mediated DNA repair by Imipramine Blue Suppresses Breast Cancer Growth and Metastasis. Clin. Cancer Res. clincanres. 2535.2015. Rampazzo, E., Persano, L., Pistollato, F., Moro, E., Frasson, C., Porazzi, P., Della Puppa, a, Bresolin, S., Battilana, G., Indraccolo, S., et al. (2013). Wnt activation promotes neuronal differentiation of Glioblastoma. Cell Death Dis. 4, e500. Raza, A., Franklin, M.J., and Dudek, A.Z. (2010). Critical Review Pericytes and vessel maturation during tumor angiogenesis and metastasis. Am. J. Hematol. 85, 593–598. Relf, M., LeJeune, S., Scott, P. a. E., Fox, S., Smith, K., Leek, R., Moghaddam, A., Whitehouse, R., Bicknell, R., and Harris, A.L. (1997). Expression of the Angiogenic Factors Vascular Endothelial Cell Growth Factor, Acidic and Basic Fibroblast Growth Factor, Tumor Growth Factor β-1, Platelet-derived Endothelial Cell Growth Factor, Placenta Growth Factor, and Pleiotrophin in Human Primary Br. Cancer Res. 57, 963–969. Rena, G., Guo, S., Cichy, S.C., Unterman, T.G., Cohen, P., and Thr, A.-S. (1999). Phosphorylation of the Transcription Factor Forkhead Family Member FKHR by Protein Kinase B. J. Biol. Chem. 274, 17179– 17183. Reya, T., Morrison, S.J., Clarke, M.F., and Weissman, I.L. (2001). Stem cells, cancer, and cancer stem cells. Nature 414, 105–111. Reya, T., Duncan, A.W., Ailles, L., Domen, J., Scherer, D.C., Willert, K., Hintz, L., Nusse, R., and Weissman, I.L. (2003). A role for Wnt signalling in self-renewal of haematopoietic stem cells. Nature 423, 409–414. Ridley, A.J., Schwartz, M. a, Burridge, K., Firtel, R. a, Ginsberg, M.H., Borisy, G., Parsons, J.T., and Horwitz, A.R. (2003). Cell migration: integrating signals from front to back. Science 302, 1704–1709. Robert, J. (1994). Clinical Pharmacokinetics of Epirubicin. Clin. Pharmacokinet. 26, 428–438. Saadin, K., and White, I.M. (2013). Breast cancer stem cell enrichment and isolation by mammosphere culture and its potential diagnostic applications. Expert Rev. Mol. Diagn. 13, 49–60. Sabbah, M., Emami, S., Redeuilh, G., Julien, S., Prévost, G., Zimber, A., Ouelaa, R., Bracke, M., De Wever, O., and Gespach, C. (2008). Molecular signature and therapeutic perspective of the epithelial-to-mesenchymal transitions in epithelial cancers. Drug Resist. Updat. 11, 123–151. Saharinen, J., Hyytia, M., Taipale, J., and Keski-oja, J. (1999). Latent transforming growth factor- b binding proteins ( LTBPs ) structural extracellular matrix proteins for targeting TGF- b action. Cytokine Growth Factor Rev. 10, 99–117. Salhia, B., Kiefer, J., Ross, J.T.D., Metapally, R., Martinez, R.A., Johnson, K.N., DiPerna, D.M.,

Page | 248

Paquette, K.M., Jung, S., Nasser, S., et al. (2014). Integrated genomic and epigenomic analysis of breast cancer brain metastasis. PLoS One 9, e85448. Sambasivarao, S. V (2013). FOXM1 and its oncogenic signaling in pancreatic cancer pathogenesis. Santos, S.C.R., and Dias, S. (2004). Internal and external autocrine VEGF/KDR loops regulate survival of subsets of acute leukemia through distinct signaling pathways. Blood 103, 3883–3889. Sanz-moreno, V., Gadea, G., Ahn, J., Paterson, H., Marra, P., Pinner, S., Sahai, E., and Marshall, C.J. (2008). Rac Activation and Inactivation Control Plasticity of Tumor Cell Movement. Cell 135, 510– 523. Saxe C. (2013). Unlocking the Mysteries of Metastasis. American Cancer Society. Available at: http://blogs.cancer.org/expertvoices/2013/01/23/unlocking-the-mysteries-of-metastasis/ [Last accessed: 14/02/17] Schilham, M.W., Oosterwegel, M., Moerer, P., Ya, J., de Boer, P.A., and de Wetering, M. (1996). Defects in cardiac outflow tract formation and pro-B-lymphocyte expansion in mice lacking SOX-4. 711–714. Schrader, K. a., Masciari, S., Boyd, N., Wiyrick, S., Kaurah, P., Senz, J., Burke, W., Lynch, H.T., Garber, J.E., and Huntsman, D.G. (2008). Hereditary diffuse gastric cancer: Association with lobular breast cancer. Fam. Cancer 7, 73–82. Scully, O.J., Bay, B.-H., Yip, G., and Yu, Y. (2012). Breast cancer metastasis. Cancer Genomics Proteomics 9, 311–320. Serpa, J., Caiado, F., Carvalho, T., Torre, C., Gon??alves, L.G., Casalou, C., Lamosa, P., Rodrigues, M., Zhu, Z., Lam, E.W.F., et al. (2010). Butyrate-rich colonic microenvironment is a relevant selection factor for metabolically adapted tumor cells. J. Biol. Chem. 285, 39211–39223. Serrano-Gomez, S.J., Maziveyi, M., and Alahari, S.K. (2016). Regulation of epithelial-mesenchymal transition through epigenetic and post-translational modifications. Mol. Cancer 15, 18. Sher, I., Adham, S.A., Petrik, J., and Coomber, B.L. (2009). Autocrine VEGF-A/KDR loop protects epithelial ovarian carcinoma cells from anoikis. Int. J. Cancer 124, 553–561. Shiota, M., Song, Y., Yokomizo, A., Kiyoshima, K., Tada, Y., Uchino, H., Uchiumi, T., Inokuchi, J., Oda, Y., Kuroiwa, K., et al. (2010a). Foxo3a suppression of urothelial cancer invasiveness through twist1, Y-box-binding protein 1, and E-cadherin regulation. Clin. Cancer Res. 16, 5654–5663. Shiota, M., Song, Y., Yokomizo, A., Kiyoshima, K., Tada, Y., Uchino, H., Uchiumi, T., Inokuchi, J., Oda, Y., Kuroiwa, K., et al. (2010b). Foxo3a suppression of urothelial cancer invasiveness through Twist1, Y-box-binding protein 1, and E-cadherin regulation. Clin. Cancer Res. 16, 5654–5663. Sidky, Y. a, and Borden, E.C. (1987). Inhibition of angiogenesis by interferons: effects on tumor- and lymphocyte-induced vascular responses. Cancer Res. 47, 5155–5161. Sisci, D., Maris, P., Cesario, M.G., Anselmo, W., Coroniti, R., Trombino, G.E., Romeo, F., Ferraro, A., Lanzino, M., Aquila, S., et al. (2013). The estrogen receptor α is the key regulator of the bifunctional role of FoxO3a transcription factor in breast cancer motility and invasiveness. Cell Cycle 12, 3405– 3420. Siu, M.K.Y., Wong, E.S.Y., Kong, D.S.H., Chan, H.Y., Jiang, L., Wong, O.G.W., Lam, E.W.-F., Chan, K.K.L., Ngan, H.Y.S., Le, X.-F., et al. (2013). Stem cell transcription factor NANOG controls cell migration and invasion via dysregulation of E-cadherin and FoxJ1 and contributes to adverse clinical outcome in ovarian cancers. Oncogene 32, 3500–3509.

Page | 249

Sommers, C.L., Gelmann, E.P., Kemler, R., Cowin, P., and Byers, S.W. (1994). Alterations in beta- catenin phosphorylation and plakoglobin expression in human breast cancer cells. Cancer Res. 54, 3544–3552. Song, B., Wang, C., Liu, J., Wang, X., Lv, L., Wei, L., Xie, L., Zheng, Y., and Song, X. (2010). MicroRNA- 21 regulates breast cancer invasion partly by targeting tissue inhibitor of metalloproteinase 3 expression. J. Exp. Clin. Cancer Res. 29, 29. Song, I.-S., Jeong, Y.J., Jeong, S.H., Heo, H.J., Kim, H.K., Bae, K.B., Park, Y.-H., Kim, S.U., Kim, J.-M., Kim, N., et al. (2015). FOXM1-induced PRX3 Regulates Stemness and Survival of Colon Cancer Cells via Maintenance of Mitochondrial Function. Gastroenterology 149, 1006–1016.e9. Sørlie, T., Perou, C.M., Tibshirani, R., Aas, T., Geisler, S., Johnsen, H., Hastie, T., Eisen, M.B., Rijn, M. Van De, Jeffrey, S.S., et al. (2001). Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. PNAS 98, 10869–10874. Stavrovskaya, A., Turkina, A., Sedyakhina, N., Stromskaya, T., Zabottna, T., Khoroshko, N., and Baryshnikov, A. (2016). Prognostic Value of P-Glycoprotein and Leukocyte Differentiation Antigens in Chronic Myeloid Leukemia Prognostic Value of P-Glycoprotein and Leukocyte Differentiation Antigens in Chronic Myeloid Leukemia. Leuk. Lymphoma 28, 469–482. Storz, P., Döppler, H., Copland, J. a, Simpson, K.J., and Toker, A. (2009). FOXO3a promotes tumor cell invasion through the induction of matrix metalloproteinases. Mol. Cell. Biol. 29, 4906–4917. Sugarbaker, E. V. (1979). Cancer metastasis: A product of tumor-host interactions. Curr. Probl. Cancer 3, 1–59. Sun, X., Shi, X., Sun, X., Luo, Y., Wu, X., Yao, C., Yu, H., Li, D., Liu, M., and Zhou, J. (2011). Dimethylenastron suppresses human pancreatic cancer cell migration and invasion in vitro via allosteric inhibition of mitotic kinesin Eg5. Acta Pharmacol. Sin. 32, 1543–1548. Sunters, A., Fernández De Mattos, S., Stahl, M., Brosens, J.J., Zoumpoulidou, G., Saunders, C. a., Coffer, P.J., Medema, R.H., Coombes, R.C., and Lam, E.W.F. (2003). FoxO3a Transcriptional Regulation of Bim Controls Apoptosis in Paclitaxel-treated Breast Cancer Cell Lines. J. Biol. Chem. 278, 49795–49805. Sunters, A., Madureira, P. a., Pomeranz, K.M., Aubert, M., Brosens, J.J., Cook, S.J., Burgering, B.M.T., Coombes, R.C., and Lam, E.W.F. (2006). Paclitaxel-induced nuclear translocation of FOXO3a in breast cancer cells is mediated by c-Jun NH2-terminal kinase and Akt. Cancer Res. 66, 212–220. Takahashi, K., and Suzuki, K. (2008). Requirement of kinesin-mediated membrane transport of WAVE2 along microtubules for lamellipodia formation promoted by hepatocyte growth factor. Exp. Cell Res. 314, 2313–2322. Takaishi, H., Konishi, H., Matsuzaki, H., Ono, Y., Shirai, Y., Saito, N., and Kitamura, T. (1999). Regulation of nuclear translocation of Forkhead transcription factor AFX by protein kinase B. PNAS 96, 11836–11841. Talmadge, J.E., and Fidler, I.J. (1982). Cancer metastasis is selective or random depending on the parent tumour population. 593–984. Taniuchi, K., Nakagawa, H., Nakamura, T., Eguchi, H., and Ohigashi, H. (2005a). Down-regulation of RAB6KIFL / KIF20A , a Kinesin Involved with Membrane Trafficking of Discs Large Homologue 5 , Can Attenuate Growth of Pancreatic Cancer Cell Membrane Trafficking of Discs Large Homologue 5 , Can Attenuate Growth of Pancreatic Cancer Cel. Cancer Res. 105–112. Taniuchi, K., Nakagawa, H., Nakamura, T., Eguchi, H., Ohigashi, H., Ishikawa, O., Katagiri, T., and

Page | 250

Nakamura, Y. (2005b). Down-regulation of RAB6KIFL/KIF20A, a kinesin involved with membrane trafficking of discs large homologue 5, can attenuate growth of pancreatic cancer cell. Cancer Res. 65, 105–112. Taniuchi, K., Furihata, M., and Saibara, T. (2014). KIF20A-Mediated RNA Granule Transport System Promotes the Invasiveness of Pancreatic Cancer Cells. Neoplasia 16, 1082–1093. Tenbaum, S.P., Ordóñez-Morán, P., Puig, I., Chicote, I., Arqués, O., Landolfi, S., Fernández, Y., Herance, J.R., Gispert, J.D., Mendizabal, L., et al. (2012). β-catenin confers resistance to PI3K and AKT inhibitors and subverts FOXO3a to promote metastasis in colon cancer. Nat. Med. 18, 892–901. Teng, Y., Xie, X., Walker, S., White, D.T., Mumm, J.S., and Cowell, J.K. (2013). Evaluating human cancer cell metastasis in zebrafish. BMC Cancer 13, 453. Thiery, J.P., Acloque, H., Huang, R.Y.J., and Nieto, M.A. (2009). Epithelial-Mesenchymal Transitions in Development and Disease. Cell 139, 871–890. Timar, J., Lapis, K., Dudas, J., Sebestyen, A., Kopper, L., and Kovalszky, I. (2002). Proteoglycans and tumor progression : Janus-faced molecules with contradictory functions in cancer. Cancer Biol. 12, 173–186. Tiwari, N., Tiwari, V., Waldmeier, L., Balwierz, P., Arnold, P., Pachkov, M., Meyer-Schaller, N., Schübeler, D., vanNimwegen, E., and Christofori, G. (2013). Sox4 Is a Master Regulator of Epithelial- Mesenchymal Transition by Controlling Ezh2 Expression and Epigenetic Reprogramming. Cancer Cell 23, 768–783. Toi, M., Hoshina, S., Takayanagi, T., and Tominaga, T. (1994). Association of vascular endothelial growth factor expression with tumor angiogenesis and with early relapse in primary breast cancer. Jpn. J. Cancer Res. 85, 1045–1049. Toker, A., and Yoeli-lerner, M. (2006). Akt Signaling and Cancer : Surviving but not Moving On. Cancer Res. 66, 3963–3966. Tothova, Z., and Gilliland, D.G. (2007). FoxO Transcription Factors and Stem Cell Homeostasis: Insights from the Hematopoietic System. Cell Stem Cell 1, 140–152. Tothova, Z., Kollipara, R., Huntly, B.J., Lee, B.H., Castrillon, D.H., Cullen, D.E., Mcdowell, E.P., Lazo- kallanian, S., Williams, I.R., Sears, C., et al. (2007). FoxOs Are Critical Mediators of Hematopoietic Stem Cell Resistance to Physiologic Oxidative Stress. Cell 128, 325–339. Vandepitte, J., Maes, J., Van Cleynenbreugel, B., Van Poppel, H., Lerut, E., Agostinis, P., and de Witte, P. (2010). An improved orthotopic rat bladder tumor model using DiI-loaded fluorescent AY-27 cells. Cancer Biol. Ther. 9, 986–993. Vasiliev, J.M., Gelfand, I.M., Domnina, L. V, Ivanova, O.Y., Komm, S.G., and Olshevskaja, L. V (1970). Effect of colcemid on the locomotory behaviour of fibroblasts. J. Embryol. Exp. Morphol. 24, 625– 640. Vassilomanolakis, M., Koumakis, G., Barbounis, V., Demiri, M., Panopoulos, C., Chrissohoou, M., Apostolikas, N., and Efremidis, A.P. (2005). First-line chemotherapy with docetaxel and cisplatin in metastatic breast cancer. Breast 14, 136–141. Vaswani, K., Hum, M.W., Chan, H., Ryan, J., Wood-, R.J., Nitert, M.D., Mitchell, M.D., Armitage, J.A., and Rice, G.E. (2013). The Effect of Gestational Age on Angiogenic Gene Expression in the Rat Placenta. PLoS One 8, 1–11. Vervoort, S.J., Lourenço, A.R., van Boxtel, R., and Coffer, P.J. (2013). SOX4 Mediates TGF-β-Induced Expression of Mesenchymal Markers during Mammary Cell Epithelial to Mesenchymal Transition.

Page | 251

PLoS One 8, 1–11. Wang, R., Lv, Q., Meng, W., Tan, Q., Zhang, S., Mo, X., and Yang, X. (2014). Comparison of mammosphere formation from breast cancer cell lines and primary breast tumors. J. Thorac. Dis. 6, 829–837. Wang, W., Goswami, S., Lapidus, K., Wells, A.L., Wyckoff, J.B., Sahai, E., Singer, R.H., Segall, J.E., and Condeelis, J.S. (2004). Identification and testing of a gene expression signature of invasive carcinoma cells within primary mammary tumors. Cancer Res. 64, 8585–8594. Wang, W., Eddy, R., and Condeelis, J. (2007). The cofilin pathway in breast cancer invasion and metastasis. Nat. Rev. Cancer 7, 429–440. Wang, Z., Banerjee, S., Li, Y., Rahman, K.M.W., Zhang, Y., and Sarkar, F.H. (2006). Down-regulation of Notch-1 Inhibits Invasion by Inactivation of Nuclear Factor- K B , Vascular Endothelial Growth Factor , and Matrix Metalloproteinase-9 in Pancreatic Cancer Cells. Cancer Res. 3, 2778–2784. Warr, M.R., Binnewies, M., Flach, J., Reynaud, D., Garg, T., Malhotra, R., and Debnath, J. (2013). FOXO3A directs a protective autophagy program in haematopoietic stem cells. Nature 494, 323–324. Wei, P., Zhang, N., Wang, Y., Li, D., Wang, L., Sun, X., Shen, C., Yang, Y., Zhou, X., and Du, X. (2015). FOXM1 Promotes Lung Adenocarcinoma Invasion and Metastasis by Upregulating SNAIL. Int. J. Biol. Sci. 11, 186–198. Weigand, M., Hantel, P., Kreienberg, R., and Waltenberger, J. (2005). Autocrine vascular endothelial growth factor signalling in breast cancer. Evidence from cell lines and primary breast cancer cultures in vitro. Angiogenesis 8, 197–204. Weigelt, B., Peterse, J.L., and van ’t Veer, L.J. (2005). Breast cancer metastasis: markers and models. Nat. Rev. Cancer 5, 591–602. Weil, R.J., Palmieri, D.C., Bronder, J.L., Stark, A.M., and Steeg, P.S. (2005). Breast Cancer Metastasis to the Central Nervous System. Am. J. Pathol. 167, 913–920. Weiss, R.B. (1992). The anthracyclines: will we ever find a better doxorubicin? Semin. Oncol. 19, 670–686. Wen, N., Wang, Y., Wen, L., Zhao, S.-H., Ai, Z.-H., Wang, Y., Wu, B., Lu, H.-X., Yang, H., Liu, W.-C., et al. (2014). Overexpression of FOXM1 predicts poor prognosis and promotes cancer cell proliferation, migration and invasion in epithelial ovarian cancer. J. Transl. Med. 12, 134. Wendt, M.K., Taylor, M.A., Schiemann, B.J., and Schiemann, W.P. (2011). Down-regulation of epithelial cadherin is required to initiate metastatic outgrowth of breast cancer. Mol. Biol. Cell 22, 2423–2435. Wenzel, U.O., Thaiss, F., Helmchen, U., Stahl, R.A.K., and Wolf, G. (2002). Angiotensin II infusion ameliorates the early phase of a mesangioproliferative glomerulonephritis. Kidney Int. 61, 1020– 1029. White, R.M., Sessa, A., Burke, C., Bowman, T., Ceol, C., Bourque, C., Dovey, M., Goessling, W., Burns, E., and Zon, L.I. (2008). Transparent adult zebrafish as a tool for in vivo transplantation analysis. Cell Stem Cell 2, 183–189. Wicki, A., and Christofori, G. (2008). The angiogenic switch in tumorigenesis. Tumor Angiogenes. Basic Mech. Cancer Ther. 19, 67–88. Winter, J.P. De, Dijkeb, P., Vries, C.J.M. De, Achterberg, T.A.E. Van, Sugino, H., Waelee, P. De, Huylebroeckb, D., Verschuerenb, K., and Raaij, A.J.M.V.D.E. (1996). Follistatins neutralize activin

Page | 252 bioactivity by inhibition of activin binding to its type II receptors. Mol. Cell Endocrinol. 116, 105–114. Wolf, K., Wu, Y.I., Liu, Y., Geiger, J., Tam, E., Overall, C., Stack, M.S., and Friedl, P. (2007). Multi-step pericellular proteolysis controls the transition from individual to collective cancer cell invasion. Nat. Cell Biol. 9, 893–900. Wooster, R., Bignell, G., Lancaster, J., Swift, S., and Seal, S. (1995). Identification of the breast cancer susceptibility gene BRCA2. Nature 378, 789–792. Xia, L., Huang, W., Tian, D., Chen, Z., Zhang, L., Li, Y., Hu, H., Liu, J., Tang, G., Dou, J., et al. (2014). ACP5, a direct transcriptional target of FoxM1, promotes tumor metastasis and indicates poor prognosis in hepatocellular carcinoma. Oncogene 33, 1395–1406. Xie, Z., Tan, G., Ding, M., Dong, D., Chen, T., Meng, X., Huang, X., and Tan, Y. (2010). Foxm1 transcription factor is required for maintenance of pluripotency of P19 embryonal carcinoma cells. Nucle 38, 8027–8038. Xu, C., Sun, X., Qin, S., Wang, H., Zheng, Z., Xu, S., Luo, G., Liu, P., Liu, J., Du, N., et al. (2015). Let-7a regulates mammosphere formation capacity through Ras/NF-κB and Ras/MAPK/ERK pathway in breast cancer stem cells. Cell Cycle 14, 1686–1697. Xu, N., Jia, D., Chen, W., Wang, H., Liu, F., Ge, H., Zhu, X., Song, Y., Zhang, X., Zhang, D., et al. (2013). FoxM1 is associated with poor prognosis of non-small cell lung cancer patients through promoting tumor metastasis. PLoS One 8, e59412. Xue, C., Wyckoff, J., Liang, F., Sidani, M., Violini, S., Tsai, K., Zhang, Z., Sahai, E., Condeelis, J., and Segall, J.E. (2006). Epidermal Growth Factor Receptor Overexpression Results in Increased Tumor Cell Motility In vivo Coordinately with Enhanced Intravasation and Metastasis. Cancer Res. 66, 192– 197. Xue, J., Lin, X., Chiu, W., Chen, Y., Yu, G., Liu, M., Feng, X., Sawaya, R., Medema, R.H.H., Hung, M., et al. (2014). Sustained activation of SMAD3 / SMAD4 by FOXM1 promotes TGF- β – dependent cancer metastasis. J. Clin. Invest. 124, 564–579. Ya, J., Schilham, M.W., de Boer, P. a, Moorman, a F., Clevers, H., and Lamers, W.H. (1998). Sox4- deficiency syndrome in mice is an animal model for common trunk. Circ. Res. 83, 986–994. Yamaguchi, H., and Condeelis, J. (2007). Regulation of the actin cytoskeleton in cancer cell migration and invasion. Biochim. Biophys. Acta - Mol. Cell Res. 1773, 642–652. Yamaguchi, H., Wyckoff, J., and Condeelis, J. (2005). Cell migration in tumors. Curr. Opin. Cell Biol. 17, 559–564. Yamashita, J., Fukushima, S., Jinnin, M., Honda, N., Makino, K., Sakai, K., Masuguchi, S., Inoue, Y., and Ihn, H. (2012). Kinesin Family Member 20A is a Novel Melanoma-associated Antigen. Acta Derm. Venereol. 92, 593–597. Yang, A.D., Fan, F., Camp, E.R., Buren, G. Van, Liu, W., Somcio, R., Gray, M.J., Cheng, H., Hoff, P.M., and Ellis, L.M. (2006). Chronic Oxaliplatin Resistance Induces Epithelial-to-Mesenchymal Transition in Colorectal Cancer Cell Lines ransition in Colorectal Cancer Cell Lines. Clin. Cancer Res. 12, 4147– 4153. Yang, C., Chen, H., Tan, G., Gao, W., Cheng, L., Jiang, X., Yu, L., and Tan, Y. (2013). FOXM1 promotes the epithelial to mesenchymal transition by stimulating the transcription of Slug in human breast cancer. Cancer Lett. 340, 104–112. Yang, K., Jiang, L., Hu, Y., Yu, J., Chen, H., Yao, Y., and Zhu, X. (2015). Short hairpin RNA- mediated gene knockdown of FOXM1 inhibits the proliferation and metastasis of human colon cancer cells

Page | 253 through reversal of epithelial-to-mesenchymal transformation. J. Exp. Clin. Cancer Res. 34, 40. Yaniv, K., Isogai, S., Castranova, D., Dye, L., Hitomi, J., and Weinstein, B.M. (2006). Live imaging of lymphatic development in the zebrafish. Nat. Med. 12, 711–716. Yarden, Y., and Sliwkowski, M.X. (2001). UNTANGLING THE ErbB SIGNALLING NETWORK. Mol. Cell Biol. 2, 127–137. Ye, H., Kelly, T.F., Samadani, U., Lim, L., Rubio, S., Overdier, D.G., Roebuck, K. a, and Costa, R.H. (1997). Hepatocyte Nuclear Factor 3 / fork head Homolog 11 Is Expressed in Proliferating Epithelial and Mesenchymal Cells of Embryonic and Adult Tissues. Mol. Cell. Biol. 17, 1626–1641. Yoeli-Lerner, M., Yiu, G.K., Rabinovitz, I., Erhardt, P., Jauliac, S., and Toker, A. (2005). Akt blocks breast cancer cell motility and invasion through the transcription factor NFAT. Mol. Cell 20, 539–550. Yu, Y., and Feng, Y.M. (2010). The role of kinesin family proteins in tumorigenesis and progression. Cancer 116, 5150–5160. Yu, F., Yao, H., Zhu, P., Zhang, X., Pan, Q., Gong, C., Huang, Y., Hu, X., Su, F., Lieberman, J., et al. (2007). let-7 Regulates Self Renewal and Tumorigenicity of Breast Cancer Cells. Cell 131, 1109–1123. Zhang, C., Zhu, C., Chen, H., Li, L., Guo, L., Jiang, W., and Lu, S.H. (2010). Kif18A is involved in human breast carcinogenesis. Carcinogenesis 31, 1676–1684. Zhang, H.G., Xu, X.W., Shi, X.P., Han, B.W., Li, Z.H., Ren, W.H., Chen, P.J., Lou, Y.F., Li, B., and Luo, X.Y. (2015a). Overexpression of forkhead box protein M1 (FOXM1) plays a critical role in colorectal cancer. Clin. Transl. Oncol. 1, 1–6. Zhang, J., Liang, Q., Lei, Y., Yao, M., Li, L., Gao, X., Feng, J., Zhang, Y., Gao, H., Liu, D.X., et al. (2012a). SOX4 induces epithelial-mesenchymal transition and contributes to breast cancer progression. Cancer Res. 72, 4597–4608. Zhang, J., Lu, F., Lu, T., Dong, W., Li, P., Liu, N., Ma, D., and Ji, C. (2014). Inactivation of FoxM1 transcription factor contributes to curcumin-induced inhibition of survival, angiogenesis, and chemosensitivity in acute myeloid leukemia cells. J. Mol. Med. 92, 1319–1330. Zhang, N., Wei, P., Gong, A., Chiu, W., Lee, H., Colman, H., Huang, H., Xue, J., Medema, H., He, X., et al. (2011). FoxM1 Promotes b -Catenin Nuclear Localization and Controls Wnt Target-Gene Expression and Glioma Tumorigenesis. Cancer Cell 20, 427–442. Zhang, N., Xie, Y., Li, B., Ning, Z., Wang, A., and Cui, X. (2015b). FoxM1 influences mouse hepatocellular carcinoma metastasis in vitro. Int J Clin Exp Pathol 8, 2771–2778. Zhang, Y., Zhang, H., Wang, X., Wang, J., Zhang, X., and Zhang, Q. (2012b). The eradication of breast cancer and cancer stem cells using octreotide modified paclitaxel active targeting micelles and salinomycin passive targeting micelles. Biomaterials 33, 679–691. Zhao, Y.D. (2015). Endothelial FOXM1 mediates bone marrow progenitor cell-induced vascular repair and resolution of inflammation following inflammatory lung injury. Stem Cells 32, 1855–1864. Zhao, C., Wang, X., Zhao, Y., Li, Z., Lin, S., Wei, Y., and Yang, H. (2011). A novel xenograft model in zebrafish for high-resolution investigating dynamics of neovascularization in tumors. PLoS One 6, e21768. Zhao, F., Siu, M.K.Y., Jiang, L., Tam, K.F., Ngan, H.Y.S., Le, X.F., Wong, O.G.W., Wong, E.S.Y., Gomes, A.R., Bella, L., et al. (2014). Overexpression of Forkhead Box Protein M1 (FOXM1) in Ovarian Cancer Correlates with Poor Patient Survival and Contributes to Paclitaxel Resistance. PLoS One 9, e113478.

Page | 254

Zheng, Y., Guo, J., Zhou, J., Lu, J., Chen, Q., Zhang, C., Qing, C., Koeffler, H.P., and Tong, Y. (2015). FoxM1 transactivates PTTG1 and promotes colorectal cancer cell migration and invasion. BMC Med. Genomics 8, 49. Zhou, B.S., and Elledge, S.J. (2000). The DNA damage response: putting checkpoints in perspective. Nature 408, 433–439. Zielske, S.P., Spalding, A.C., Wicha, M.S., and Lawrence, T.S. (2011). Ablation of Breast Cancer Stem Cells with Radiation. Transl. Oncol. 4, 227–233. Zou, J.X., Duan, Z., Wang, J., Sokolov, A., Xu, J., Chen, C.Z., Li, J.J., and Chen, H.-W. (2014). Kinesin family deregulation coordinated by bromodomain protein ANCCA and histone methyltransferase MLL for breast cancer cell growth, survival, and tamoxifen resistance. Mol. Cancer Res. 12, 539–549.

Page | 255

Appendix 1: List and sequence of all primer utilised in this project. GENE Forward (5’-3’) Reverse (5’-3’) NAME FOXM1 TGCAGCTAGGGATGTGAATCTTC GGAGCCCAGTCCATCAGAACT BIRC5 AGGCTGGGAGCCAGATGAC AAGCGCAACCGGACGAA MKI67 CGACGGTCCCCACTTTCC GCTGGATACGGATGTCACATTC RRM2 TCCCCATCGAGTACCATGATATC TTCCCAGTGCTGAATGTCCTT CCNA2 GCAGCAGAGGCCGAAGAC GACATGCTCATCATTTACAGGAAGA CCNB1 CAGTTATGCAGCACCTGGCTAAG TGTGGTAGAGTGCTGATCTTAGCAT CCNB2 GTTACAACCAGAGCAGCACAAGTAG TTGGTGGGTTGAACTGGAACT AURKB CAGTGGGACACCCGACATC GCCCAATCTCAAAGTCATCAATT TOP2A GAAGTCACTTTTGTTCCTGGTTTGT TGGGTCCCTTTGTTTGTTGTC AURKA GCATCAAAACAGAAAAATGAAGAATC GGGCGACCAATTTCAAAGTC PTTG1 CACCCGTGTGGTTGCTAAGG TGAGATCTCCCATCTAAGGCTTTG L19 GCGGAAGGGTACAGCCAAT GCAGCCGGCGCAAA PRC1 CTGGGTCAAAGGCCAAGGT GTTCTTCCAACCGATCCACTTCTA KIF23 CGGAAACCTACCGTGAAAAA CTTGATCAGGAAAGCCCAGT KIF3C CTGAAGAGGCAGGAGATTGC TTGGTTTTGACCTCCACCTC KIF1C CCCAAAAGCTTCACCTTTGA TTGCTGCTGAGATGCAAACT KIFC3 GAGCCCTTAGCGTGGACTG AGGAGGAGTTCCGAGACCTG KIF2C CATGATTGCCACGATCTCAC CGTTAGAGCAGGCTTCCATC KIF20A GCCAACTTCATAACACCT GTGGACAGCTCCTCCTCCTG E-cad CCTGGGACTCCACCTACAGA GGAAATGGGCCTTTTTCATT N-cad GCGTCTGTAGAGGCTTCTGG AAATCTGCAGGCTCACTGCT Vim GGGACCTCTACGAGGAGGAG AAGATTGCAGGGTGTTTTCG SOX4 GGCCTCGAGCTGGGAATCGC GCCACTCGGGGTCTTGCAC

Page | 256