Effect of RB1 Loss on Breast Cancer Cell Invasion and Response to Experimental Therapy

Effect of RB1 loss on Breast Cancer Cell Invasion and response to experimental therapy

Ioulia Vorobieva

A thesis submitted in conformity with the requirements for the degree of Master of Science Graduate Department of Laboratory Medicine and Pathobiology University of Toronto

Effect of RB1 loss on Breast Cancer Cell Invasion and Response to Experimental Therapy

Ioulia Vorobieva

Master of Science

Graduate Department of Laboratory Medicine and Pathobiology University of Toronto

2019 Abstract

Breast cancer is a heterogeneous disease with triple negative breast cancer (TNBC) exhibiting the worst prognosis. Novel therapies are urgently needed. RB1 and TP53 tumor suppressors are known drivers of metastasis and are disrupted together in ~30% of TNBCs. RB1-loss is not directly druggable, and the mechanism by which it promotes TNBC metastasis is largely unknown. I found that RB knockdown enhanced migration of TNBC cells through a process potentially involving an

E2F1-induced increase in mitochondrial protein translation. The CDC25 phosphatase inhibitor

BN82008 killed RB1+ TNBC cells and their derivatives with RB1-knockdown, equally well, and without inhibiting cell cycle progression. I also found that RB1 knockdown modulated the expression of glycosylated PD-L1, suggesting RB1-deficient TNBC may benefit from anti-PD-L1 immunotherapy. These studies directly demonstrate that RB1-deficiency promotes migration and suggests downstream pathways that can be targeted to combat aggressive RB1-deficient TNBC and other cancers.

Acknowledgments

Firstly I would like to thank Dr. Eldad Zacksenhaus for his guidance and support, I have learned valuable skills and lessons these past 2 years. I would like to thank my M.Sc. committee members Dr. Sean Egan, and Dr. Vathany Kulasingam for their advice and support throughout my thesis.

I would like to thank all of the members past and present of the Zacksenhaus Lab, I wish all the best success to each of you in your future endeavors.

Lastly I would like to thank my friends and family who have supported me throughout this thesis, without whom this would not have been possible.

Attributions

I would like to thank Dr. Subrata Chowdhury and Mariusz Shreztha for generating the MCF7 CRISPR cell lines. I thank Jeff C. Liu for his guidance in teaching me how to use Flow cytometry.

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Table of Contents

Acknowledgments...... iii

Table of Contents ...... iv

List of Tables ...... vi

List of Figures ...... vi

List of Appendices ...... vii

List of Abbreviations ...... viii

Chapter 1 ...... 1

Introduction ...... 1

1.1 Breast Cancer ...... 1

1.1.1 Breast Cancer and Metastasis ...... 2

1.2 Retinoblastoma protein 1 ...... 2

1.3 TP53 ...... 5

1.4 RB and p53 in Breast Cancer ...... 6

1.5 Experimental Therapeutics Targeting RB1-deficiency ...... 8

1.5.1 Targeting Metabolic Reprogramming: Tigecycline ...... 8

1.5.2 Targeting Immune Evasion ...... 9

1.5.3 Targeting Cell Cycle dysregulation: CDC25 phosphatases ...... 10

1.5.4 Targeting migration: CDC42BPA ...... 11

1.6 Rational ...... 12

1.6.1 Hypothesis...... 13

1.6.2 Objective ...... 13

Chapter 2 ...... 14

Materials and Methods ...... 14

2.1 Cell Culture ...... 14

2.2 Transfection with Small Interfering RNA (siRNA)...... 14

2.3 Scratch Test Migration Assay ...... 15

2.4 Chromatin Immunoprecipitation (ChIP) ...... 15

2.5 Cell Cycle Analysis by Flow Cytometry ...... 15

2.6 MTT Viability Assay ...... 16

2.7 Western Blot Analysis ...... 16

2.8 RNA isolation and Quantitative Real-time PCR ...... 17

2.9 ATP Assay ...... 17

2.10 Cell Proliferation Assay ...... 18

2.11 Stable Cell Line Generation ...... 18

Chapter 3 ...... 19

Results ...... 19

3.1 RB-deficiency induces MPT possibly mediated by E2F transcription factors ...... 19

3.2 RB Knockdown promotes cell migration in most but not all cell lines, but has no obvious effect on cell proliferation ...... 21

3.3 Increased MRPL37 expression at mRNA and protein level in RB-deficient highly migratory cells...... 25

3.4 RB1-deficient Cell line response to Experimental Therapy ...... 28

3.4.1 Cell Sensitivity to MPT inhibitor, Tigecycline, is not altered in response to RB1 knockdown...... 28

3.4.2 CDC42BPA does not cooperate with RB knockdown to further promote migration...... 28

3.4.3 CDC25 Inhibition has cytotoxic effect on RB-Deficient TNBC cells...... 31

3.4.4 RB knockdown induces PD-L1 expression in TNBC cell lines...... 33

Chapter 4 ...... 34

Discussion ...... 34 v

4.1 Summary ...... 38

References ...... 40

Appendix ...... 53

List of Tables

Table 1. Cell lines used in this study…………………………………………………………….14 Table 2. qPCR primers used in this study…………………………………………………….....17 List of Figures

Figure 1. ChIP analysis suggests that E2F1 is directly recruited to the MRPL37 promoter…...20

Figure 2. Effective RB knockdown in HER2+ and TNBC cell lines .………………………….22

Figure 3. RB Knockdown does not significantly impact cell proliferation in most HER2+ and TNBC cell lines……………….………………………………..………………………………...23

Figure 4. RB knockdown promotes cell migration in most but not all cancer cell lines ……….24

Figure 5. Rb knockdown promotes expression of MPT-related genes but does not significantly affect cellular ATP levels….………..…………………………………………………………...26

Figure 6. Cell Sensitivity to MPT inhibitor, Tigecycline is not altered in response to RB1 knockdown……………………………………………………………………………………….27

Figure 7. Migration of RBKD Cell lines is decreased in the presence of MPT inhibitor (Tigecycline) and Mitochondrial ETC inhibitor (Rotenone)…………………………………….29

Figure 8. CDC42BPA KD promotes migration but does not cooperate with RB knockdown in MDA MB231 cell line…………………………………………………………………………...30

Figure 9. RB1-deficient TNBC cells are sensitive to CDC25 inhibition………………………..32

Figure 10. RB knockdown induces PD-L1 expression in TNBC cell lines……………………...33

List of Appendices

Figure A1. Aphidicolin does not affect the ability of the cells to migrate……………………...53

Figure A2. RBKO p130KD MCF7(kshp130) are more sensitive to tigecycline than RBKO MCF7(kSCRAM) cells…………………………………………………………………………..54

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List of Abbreviations

ARF/p14- Alternative Reading Frame ATM- ataxia telangiectasia mutated ATP- Adenosine Triphosphate ATR- ataxia telangiectasia and Rad3 related Bax- BCL2 associated X BC- Breast Cancer Bcl-2- B-cell Lymphoma 2 Bid- BH3 Interacting Domain Death Agonist BRCA1- Breast Cancer Susceptibility gene 1 CBP/p300- \cAMP response element-binding protein-binding protein/p300 CDC25- Cell Division Cycle 25 CDC42- Cell division control protein 42 CDK- Cyclin- Dependent Kinases CDKN- Cyclin Dependent Kinase Inhibitor CHK- Checkpoint kinase Drp1- dynamin-related protein 1 dsDNA- double stranded Deoxyribonucleic Acid ECAR- Extracellular Acidification Rate Ef-Tu- Elongation Factor- Thermo Unstable EMT- Epithelial to Mesenchymal Transition ER- Estrogen Receptor GSH- Glutathione HDAC- Histone deacetylases HER2- Human Epidermal Growth Factor Receptor 2 IFN-ϒ- Interferon gamma IL6- Interleukin-6 INK4a/p16- Inhibitor of CDK4a KD- knockdown MEF- Mouse Embryonic Fibroblasts

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MELK- Maternal Embryonic Leucine Zipper Kinase Mfns- Mitofusins MHC- Major Histocompatibility Complex MMPs- Matrix Metalloproteases MOMP- mitochondrial outer membrane perforation MPT- Mitochondrial Protein Translation MRCK/CDC42BPA- Myotonic Dystrophy Kinase-Related CDC42-Binding Kinase/ CDC42 Binding protein A MRPL37- mitochondrial ribosomal protein L37 MTT- (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide) MUC1- Mucin1 NF-κB- Nuclear Factor Kappa-Light-Chain-Enhancer of Activated B Cells NK- Natural Killer Noxa- Phorbol-12-Myristate-13-Acetate-Induced Protein 1 OCAR- Oxygen Consumption Rate OXPHOS- Oxidative Phosphorylation PARP- Poly (ADP-ribose) polymerase pCAF- CBP/p300-associated factor PD- Programmed Death PD-L1- Programmed Cell Death Ligand PGC1-α- Peroxisome proliferator-activated receptor gamma coactivator 1-alpha PR- Progesterone Receptor Puma- BCL2 Binding Component 3 qRT-PCR- Quantitative Reverse Transcriptase Polymerase Chain Reaction RB1- Retinoblastoma gene RNA- Ribonucleic Acid RHAMM- Receptor for Hyaluronan Mediated Motility RhoA- Ras Homolog Family Member A RhoC- Ras Homolog Family Member C MDM2/HDM2- murine double minute 2/human double minute 2 ROS- Reactive Oxygen Species shRNA- short hairpin Ribonucleic Acid

SPOP-CUL1- Speckle Type BTB/POZ Protein-Cullin1 SV40- Simian Virus 40 TILs- tumor infiltrating lymphocytes TNBC- Triple Negative Breast Cancer TP53-tumor protein 53 TRAIL- TNF-related apoptosis-inducing ligand TSG- Tumor Suppressor Gene

Chapter 1

Introduction

1.1 Breast Cancer

Breast Cancer (BC) is the leading cause of female mortality, an estimated 5,000 Canadian women succumbed to the disease in 2017, and according to 2019 estimates, 1 in 8 women will develop BC within their lifetime (Shah et al., 2014; Siegel et al., 2019). This heterogeneous disease is the most common cause of death in less developed countries and second to lung cancer in developed countries (Harbeck and Gnant, 2017). There are three major types of breast cancer characterized by receptor expression: ER+, HER2/NEU/ERBB2+, and triple negative breast cancer (TNBC) which does not express these receptors or the Progesterone Receptor (PR) (The Cancer Genome Atlas and The Cancer Genome Atlas Network, 2012). Gene expression has also allowed profiling of BC tumors to be further subdivided into 5 molecular subtypes: HER2-enriched, Luminal A, Luminal B, Normal-like and Basal-like (The Cancer Genome Atlas and The Cancer Genome Atlas Network, 2012). TNBCs, which are 90% basal-like, were further subdivided by gene expression by Lehmann et al., into 7 subtypes: Basal-like1, Basal-like2, Immunomodulatory, Mesenchymal- like, Mesenchymal Stem-like, Luminal Androgen Receptor and Unstable/Unspecified (Lehmann et al., 2011). ER+ positive breast cancer is the most common amounting to 70% of patients. Estrogen Receptor (ER) is a steroid hormone receptor, which when activated by estrogen acts as a transcription factor to activate oncogenic pathways in BC cells (reviewed in (Spears and Bartlett, 2009)). This subtype can also express PR which is a marker of ER signaling. HER2/NEU/ERBB2+ breast cancer amounts to 15-20% of breast cancer. Human epidermal growth factor receptor 2 (HER2) is a transmembrane receptor tyrosine kinase in the epidermal growth factor receptor family and is overexpressed in this subtype. TNBC amounts to 15% percent of all BCs diagnosed however it is the most aggressive and has the worst prognosis. TNBC also has the highest likelihood of recurrence within 5 years following diagnosis with 85% 5 year survival compared to 93-99% 5 year survival of receptor positive subtypes (Waks and Winer, 2019).

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1.1.1 Breast Cancer and Metastasis

Mortality from BC is caused by dissemination of cancer cells that leave the primary tumor and spread, forming metastases in other tissues where they disrupt organ function. Metastasis is a complex multistep process where cells must first separate from the primary tumor, migrate through surrounding tissue, enter the circulation and then exit to a target organ where they proliferate (Yates et al., 2017). In BC the most common site of metastasis is the bone, lung and liver, but BC can metastasize to other organs including the brain (Bos et al., 2009; Minn et al., 2005).

Metastatic TNBC has a median survival of only 10-13 months, compared to the 4-5 year median in the hormone receptor positive subtypes (Waks and Winer, 2019). While there are targeted therapies available for HER2+ (Herceptin) (Nahta, 2012), and ER+ (Tamoxifen) (Jordan, 2008) or Aromatase inhibitors for postmenopausal women (Campos, 2004), there is currently no effective targeted therapy for TNBC. Poly (ADP-ribose) polymerase (PARP) inhibitors are effective in a subset of TNBC (Anders et al., 2010). Only 10% of TNBC have a breast cancer susceptibility 1 (BRCA1) mutation and PARP inhibitors were shown to be effective in some tumors with a “BRCA-ness” phenotype such as methylated BRCA1 promoter which is found at high frequencies in basal like-1 TNBC (Geenen et al., 2018). However TNBC tumors without this phenotype show a poor response to the therapy and many patients gain resistance to treatment. Thus, further investigation is needed to improve current patient prognosis. One strategy is to find other common mutations in TNBC that could be exploited as therapeutic targets.

1.2 Retinoblastoma protein 1

Retinoblastoma 1 (RB1) was the first tumor suppressor ever identified, in an epidemiological study for its role in a specific type of eye cancer called retinoblastoma (Knudson and Jr., 1971; Strong et al., 1981). RB1 gene is located on chromosome 13 and encodes a 928 amino acid protein with 3 domains: N-terminal domain, central “pocket” domain which contains domains A and B, composed of 11 helices and 8 helices with a beta sheet respectively, separated by a flexible linker which forms the small pocket domain, and the C-terminal domain (Xiao et al., 2003). Domain B within the central pocket domain contains an “LXCXE” binding domain which acts as a binding site for multiple proteins including chromatin remodeling complexes such as histone deacetylases (HDACs). pRb is part of the pocket protein family along with p107 and p130, which can also bind

E2F transcription factors to regulate expression of target genes. p130 and p107 bind E2F4-5 whereas pRb binds E2F1-3 although some compensation between these complexes has been noted (Hurford et al., 1997). There is some evidence that other pocket protein family members can compensate for RB1 loss, however the p107 and p130 genes are rarely mutated in human cancers (Burkhart and Sage, 2008).

In addition to Retinoblastoma, Rb is dysregulated in almost all solid tumors and an RB1-loss transcriptomic signature is associated with poor clinical outcomes across almost all cancer types (Chen et al., 2019). RB1 function can be either disrupted through mutation, deletion, and promoter methylation, or functionally inactivated by posttranslational modifications such as phosphorylation by cyclin-dependent kinases CDK4/6 and CDK2 (Burkhart and Sage, 2008).

Rb’s canonical function is to control cell proliferation through regulation of the G1 checkpoint (Weinberg, 1995). pRB can act as a transcriptional co-repressor by blocking the trans-activation domains of activating transcription factors E2F1-3, and by recruiting chromatin modifying enzymes to silence gene expression, thereby suppressing genes involved in G1 to S phase progression and apoptosis. During G0, RB is in its hypophosphorylated state, and is bound to the transactivation domain of E2F complexes. When RB’s is hyperphosphorylated first by Cyclin D- CDK4/6 in early G1 at S249, T356, S807, S811 and T826 and then by Cyclin E-CDK2 at S612 and T821 in late G1 it no longer binds to E2F transcription factors and cell cycle is allowed to progress (Buchkovich et al., 1989; Hinds et al., 1992; Lees et al., 1993; Zarkowska and Mittnacht, 1997). This is because when the RB is phosphorylated by these G1-dependent cyclins, a conformational change occurs resulting in intramolecular interactions within the central pocket region which excludes binding of HDACs blocking chromatin remodeling and active transcriptional repression, these conformational changes lead to pRb being phosphorylated by cyclin E/Cdk2 at S567 which is in the core pocket region and blocks binding to transactivation domain of E2F, allowing E2F-dependent transcriptional activation and transition to S phase (Munro et al., 2012).

Apart from its canonical role in controlling cell cycle, RB has over a hundred binding partners that are thought to mediate transcription of target genes involved not only in cell cycle regulation but also in cell differentiation, genomic instability, apoptosis, migration, and senescence (Burkhart and Sage, 2008). This diversity of function is in part dictated by the diverse post translational

4 modifications of RB including phosphorylation, acetylation, sumoylation, and caspase-cleavage. In addition to phosphorylation by CDKs, pRb acts as a substrate for multiple protein kinases. For instance p38 responds to DNA damage by phosphorylating pRb at S567, resulting in it being targeted for degradation by Mdm2 (Delston et al., 2011). Acetylation and methylation of Rb or its sumoylation, serve opposite roles: the former suppressing phosphorylation by CDKs, while the later enhancing CDK binding (Carr et al., 2011; Chan et al., 2001; Meng et al., 2016). The CDK4/6 kinases can be inhibited by CDKN1/2 (p16/p21) (Sherr and Roberts, 1999).

Cellular senescence is a stable form of cell cycle arrest regulated by RB1. Sustained expression of unphosphorylated RB results in decreased heterochromatin formation and silencing of E2F1 target genes and consequently in cellular senescence (Narita et al., 2003). Genome-wide analyses revealed that RB binds to and represses E2F target genes involved in DNA replication in senescent cells (Chicas et al., 2010).

Indeed, RB regulates expression of dihydrofolate reductase, ribonucleotide reductase, and thymidylate synthase involved in dNTP synthesis. In drosophila, the RB homolog Rbf can regulate nucleotide synthesis and glutathione (GSH) metabolism, though this effect was not consistently seen in RB1-negative mammalian cancer cells. Deletion of all 3 members of the RB gene family (Rb, p107, and p130) in mouse embryonic fibroblasts (MEFs) induces GSH metabolism. Thus, RB may function to suppress cancer-associated metabolic reprogramming. Indeed, the Zacksenhaus lab has demonstrated that Rb loss in a mouse model of TNBC induces MPT genes (see section 1.4 below).

RB is also important for genome integrity, in which RB inactivation results in decreased genomic integrity (Manning et al., 2010). Additionally, RB assists in nucleotide excision repair, through regulating E2F1 interaction with damaged DNA binding gene (DDB2) (Lin et al., 2009). RB1 has also been shown to impact immune response to the tumor. This will be discussed in detail in sections below, as it serves as a potential therapeutic target.

Apart from RB1 loss causing dysregulation of the cell cycle it has also been shown to increase invasiveness of cells by regulating expression of matrix metalloproteases (MMPs), in particular MMP9, MMP14 and MMP15 promoters were found to be bound by E2F transcription factors (Curran and Murray, 1999; Johnson et al., 2012). Metastasis is a complex multistep process often linked to epithelial to mesenchymal transition (EMT). Rb-deficiency enhances EMT, invasiveness

5 and lung metastasis in mice, through regulation of a cell-surface receptor and adhesion molecule: CD44 (Kim et al., 2013). Additionally it has been implicated in promoting metastasis of luminal breast cancer cell lines and cytoskeletal reorganization (Kim et al. 2013), as well as promoting metastasis in prostate cancer (Thangavel et al., 2017). RB-E2F pathway has also been implicated in angiogenesis through activating transcription of vascular endothelial growth factor (Gabellini et al., 2006).

Interestingly, the effect of RB1 loss is context specific. Indeed RB1 loss can promote aberrant cell cycle progression and cell death through E2F-mediated transcription of pro-apoptotic genes (Zacksenhaus et al., 1996). Thus, in cancer, RB1 is lost together with functional disruption of p53 or with activation of other survival pathways, that overcome pro-apoptotic signaling.

1.3 TP53

Tumor protein 53(p53), was identified through the study of SV40, a virus which can induce tumor formation in mice (Lane and Crawford, 1979; Linzer and Levine, 1979). A 53-54kDa was found to bind to SV40 large T antigen. This protein in mutant form was initially characterized as an oncogene. In contrast, wildtype p53 suppresses tumor formation. Since its discovery it has been found that p53 regulates multiple pathways within the cell, both within the nucleus, in the cytoplasm, and even within the mitochondria.

The crystallography structure of p53 was resolved in 1994 that p53 consists of 393 amino acids and 5 regions: (1) N-terminal domain that contains a transactivation domain, and phosphorylation sites (2) proline-rich region, (3) central DNA-binding domain that binds to dsDNA, (4) tetramerization domain, (5) C-terminal domain that contains acetylation sites(Joerger and Fersht, 2008).

TP53 functions as a nuclear transcription factor which in response to cellular stresses such as DNA damage, helps maintain genomic instability by inducing cell cycle arrest through activation of cyclin-dependent kinase inhibitor p21. P53 is negatively regulated by E3 ligase MDM2(mouse)/HDM2(human) which when bound to p53 activates ubiquitin mediated degradation of p53. During p53 activation the amino-terminus of p53 can be phosphorylated by protein kinases ATR and ATM at serine 15 preventing MDM2/HDM2 from binding, resulting in stabilization of p53. P53 then undergoes “antirepression” where it is acetylated by activated

CBP/p300/pCAF and released by mdm2 (Zilfou and Lowe, 2009). P53 can then bind DNA as a tetramer in a sequence specific manner to activate or repress transcription of target genes through interaction with cofactors (El-Deiry et al., 1992).

Continued accumulation of p53 leads to cell apoptosis, necrosis or senescence (Sherr and McCormick, 2002), this is because of the relative affinity of p53 to promoter regions. When p53 begins to accumulate it binds to high affinity promoter regions which promote cell cycle arrest and DNA repair, however if the DNA damage is not fixed p53 accumulates to the point where it begins to bind to lower affinity promoter regions, which are involved in apoptosis. For example p53 can induce transcription of Bax, Puma, Noxa and Bid, which are Bcl-2 family members with proapoptotic functions, these proteins translocate to the mitochondria in the cell to induce MOMP (mitochondrial outer membrane perforation) and thus the leaking of proapoptotic mitochondrial genes such as cytochrome C , which can join other proteins in the cytosol to form the apoptosome, eventually resulting in death this is known as the intrinsic apoptotic pathway. P53 can also induce extrinsic apoptosis through transcriptional activation of cell surface receptors Fas, DR5, and PERP. In addition to p53’s role in DNA repair and apoptosis, it can also regulate autophagy, metabolism, ROS control, inflammation, pluripotency, EMT, invasion and epigenetics (Bensaad et al., 2006; Puzio-Kuter, 2011; Santhanam et al., 1991; Zhang et al., 2011).

The diversity of p53 functional roles is very much in line with its high mutation rate in cancer (mutations in 50% of all cancers, and 80% of BCs). The type of p53 mutations are important and can impact tumor aggressiveness and response to treatment.

1.4 RB and p53 in Breast Cancer

Major hallmarks of cancer include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, activating invasion and metastasis, reprogramming of energy metabolism and evading immune destruction (Hanahan and Weinberg, 2011). As described above the tumor suppressors RB1 and TP53, influence all eight of these hallmarks, and their combined inactivation is found across aggressive forms of many tumor types. A major clue to the importance of RB1/TP53 cooperation in cancer progression come from their collective inactivation by viral oncoproteins including SV40 large T, Adenovirus E1A/E1B, and HPV E6 and E7 (Rathi et al., 2009; Yim and Park, 2005). Additionally both these

7 tumor suppressors are regulated by a locus which encodes 2 proteins in different reading frames: p16 INK4a, and p14 ARF(p19 in mouse) (Sherr, 2001). p16 INK4a inhibits CDK4/6, thus maintaining Rb in its hypophosphorylated/activated state (Riaz et al., 2013; Serrano et al., 1993). p14 ARF inhibits MDM2 by sequestering it in the nucleus as well as by blocking its E3 ligase activity, thus stabilizing p53 (Honda and Yasuda, 1999; Weber et al., 1999). P53 can then induce expression of p21 which inhibits CyclinE-CDK2 which results in hyperphosphorylation of RB, arresting the cell cycle, and allowing DNA repair. In response to extensive DNA damage, p53 further accumulates and transcriptionally activates pro-apoptotic genes such as BAX, leading to cell demise. MDM2 can bind directly to the c-terminus of RB blocking its interactions with E2F; overexpression of MDM2 leads to RB degradation (Uchida et al. 2005; X.P. Zhang, Liu, and Wang 2010). P53 and RB may also cooperate to modulate the immune response; wildtype p53 and RB decrease expression of IL-6 and MHC complex in Hela cells (Santhanam et al., 1991).

When Rb is deleted in mouse mammary progenitors combined with p53 deletion it induces basal- like/EMT tumor subtypes (Jiang et al., 2010). In TNBC TSGs RB and p53 are interrupted in 28- 40% of samples and are main drivers of metastasis (Jones et al., 2016). Using mouse models of RB+/p53-, and RB-/p53- loss, the Zacksenhaus lab has shown that RB loss was accompanied by an E2F1/3-dependent transcriptional stimulation of MPT compared to p53 loss alone (Jones et al., 2016). This suggests a possible change in the balance of glycolysis and oxidative phosphorylation (OXPHOS), a metabolic pathway known to promote metastasis. MPT refers to mitochondrial protein synthesis of 13 polypeptides, which are involved in OXPHOS (D’souza and Minczuk, 2018). Many genes encoded in the nucleus also participate in MPT for example mitochondrial ribosomal protein L37 (MRPL37). Interestingly, overexpression of E2F1/3 results in increased expression of MRPL37, and E2F1 consensus binding sequences were found in the MRPL37 promoter suggesting that increases in MPT in response to Rb deficiency are mediated by E2F1. MRPL37 was also identified as a potential binding target for p130-E2F4 complexes, providing additional evidence of pocket proteins and E2Fs regulating metabolism (Cam et al., 2004).

1.5 Experimental Therapeutics Targeting RB1-deficiency

RB1 is among the 9 most commonly altered genes in BC, making it a very attractive therapeutic target (E. Zacksenhaus et al., 2017). Unfortunately, RB loss is not directly druggable, however it is conceivable that pathways downstream of its loss could be (Witkiewicz et al., 2018). Additionally, it has been shown previously that TNBC response to therapy can be dependent on RB1 status (Robinson et al., 2013).

1.5.1 Targeting Metabolic Reprogramming: Tigecycline

The Zacksenhaus lab performed a re-purposing screen with FDA-approved drugs for growth inhibitors of the RB/p53-deficient TNBC-like mouse tumors and identified the MPT antagonist tigecycline, an antibiotic, as a potent drug (Jones et al., 2016). RB1-deficient human TNBC cell lines were on average more sensitive to tigecycline than RB1+ TNBC lines both in vitro and in xenograft assays in mice suggesting RB1-deficiency in TNBC increases MPT and sensitizes cells to inhibitors of this pathway (Jones et al., 2016). Interestingly tigecycline was found to be successful in inducing mitochondrial oxidative stress and tumor cell death, both in vitro and in vivo as well as inhibiting angiogenesis (Xiong et al., 2018). Tigecycline has also been shown to have efficacy in killing renal, colon and liver cells, both in vitro and in vivo (Stein and Craig, 2006; Tan et al., 2017; Wang et al., 2017). Importantly it was shown to synergize with paclitaxel, a chemotherapy drugs used to treat TNBC, in cervical squamous cell cancer xenografts, and renal cell carcinoma cell lines (Li et al., 2015; Wang et al., 2017; Yim and Park, 2005). Additionally shRNA-mediated knockdown of EF-Tu mitochondrial translation factor in leukemic cells reproduced the antileukemia activity of tigecycline, supporting its role in inhibiting MPT as the mechanism for cell growth suppression (Škrtić et al., 2011).

Given RB1 deficiency’s roles in promoting OXPHOS and driving metastasis, it is interesting whether RB1 promotes migration and sensitizes TNBC cells to tigecycline, and whether tigecycline could block migration.

1.5.2 Targeting Immune Evasion

The tumor microenvironment is a major regulator of tumor progression. It consists of extracellular matrix, myoepithelial cells, endothelial cells, fibroblasts, adipocytes as well as immune cells (Place et al., 2011; Schaer et al., 2018). The immune system can have both anit-tumor and pro-tumor effects. The leukocyte population includes natural killer cells (NK), CD8 and CD4+ T cells. NK can promote inflammation through secreting cytokines; short term inflammation has anti-tumor effects however chronic inflammation promotes tumor progression and metastasis. CD4+ T cells or regulatory T cells, are associated with poor prognosis whereas CD8+ cytotoxic T cells are associated with better prognosis. Additionally, high levels of tumor infiltrating lymphocytes (TILs) is associated with more-favorable prognosis in TNBC and HER2+ BC. The increased prognostic value of TILs in TNBC in comparison to the other BC subtypes is due to the high rates of mutation (mutation load) in this subtype which supplies antigenicity to stimulate an immune response (Savas et al., 2016; Wang et al., 2014).

Cancer evades the immune system through a process called immune-editing which consists of three phases: elimination, equilibrium and escape (Gavin P. Dunn,1 Lloyd J. Old and and Robert D. Schreibe, 2004). During elimination, both the innate and adaptive immunity, NK and T-cells respectively, are able to detect neoantigens presented by cancerous cells and eliminate them. IFN- ϒ, perforin and TRAIL are important pathways for elimination of cancerous cells. The equilibrium phase involves a battle between the immune system and a population of genomically unstable heterogenous cancer cells; yet, through clonal evolution eventually some cells persist, thus leading to the next stage of immune-editing: escape. The cancerous cells that have escaped destruction by the immune system and ultimately proliferate to form the tumor bulk. One way to escape the immune system is to evade an immune checkpoint. One such checkpoint investigated for its potential as a therapeutic target in breast and other cancers is the PD1:PD-L1 receptor/ligand pair (Dua and Tan, 2017).

Programmed death ligand-1 (PD-L1) which is often expressed by aggressive cancer cells, binds to programmed death-1 (PD-1) on activated T cells to suppress immune response. PD-L1 expression

10 was evaluated in 45 breast cancer lines, and it was found that basal and mesenchymal cell lines showed significantly higher PD-L1 expression in comparison to luminal cell lines (Sabatier et al., 2015). Analysis of PD-L1 in 5,454 breast cancer samples, it was found that 20% showed overexpression in comparison to normal breast (Sabatier et al., 2015). Interestingly, loss of hyperphosphorylated pRb in prostate cancer cell model, was shown to increase PD-L1 expression and promote tumor immune evasion (Jin et al., 2019). RBKD in these cells increases PD-L1 expression through interaction with NF-κB (Jin et al., 2019). However it is unknown whether RB plays a similar role in TNBC.

1.5.3 Targeting Cell Cycle dysregulation: CDC25 phosphatases

In some tumors RB is present but hyperphosphorylated and therefore inactive. CDK4/6-inhibitors such as PD0332991, are highly effective against cancer cells expressing RB, but not against RB- deficient cells. Kinome/phosphatase inhibitor screens performed in the Zacksenhaus lab on multiple mouse RB/p53-, PTEN/p53-, and human RB/PTEN/TP53-deficient TNBC cells identified CDC25 phosphatase as a common target (Perry and Kornbluth, 2007). CDC25 phosphatases are found in all eukaryotic organisms except plants, and act as dual phosphatases meaning that they can dephosphorylate tyrosine, threonine or serine residues (Boutros et al., 2007). Humans have CDC25A, CDC25B and CDC25C isoforms all which phosphorylate CDK-cyclin complexes to regulate the cell cycle. CDK1 complexes are regulated by phosphorylation at Thr14, Thr161 and Tyr15. Thr14 and Tyr 15 residues are phosphorylated by WEE1 and MYT kinases, to activate CDK1. CDC25 phosphatases remove these two phosphate groups, then CDK-activating kinase (CAK) is required to phosphorylate Thr161 for complete activation. All three CDC25 isoforms are involved in regulating the cell cycle G1-S and G2-M transitions (Boutros et al., 2007; Lammer et al., 1998; Perry and Kornbluth, 2007). CDC25 phosphatases themselves can be inactivated through phosphorylation by CDK-cyclin complexes and other kinases such as Aurora A (CDC25B) and polo-like kinase (CDC25C) (Dutertre et al., 2004; Qian et al., 1998). Additionally CDC25B and C can be phosphorylated by CHK1 kinases creating a binding site for 14-3-3 family of proteins preventing the CDC25B and C interaction with CDK1, thus inhibiting mitosis (Schmitt et al., 2006). CDC25B can also be phosphorylated at the site of the centrosome by CHK1 and MELK, thereby inhibiting mitotic progression (Lammer et al., 1998). CDC25

11 phosphatases play a role in arresting the cell cycle in response to DNA damage. Single stranded DNA regions or double-stranded DNA breaks induce, ATR and ATM, respectively, which then phosphorylate checkpoint kinases CHK1 and 2 (Löffler et al., 2006). CHK1 and CHK2 control CDC25 phosphatases’ activity directly through phosphorylation and/or its degradation. Furthermore, CHK1 activates WEE1 activity, which antagonizes CDC25, to further inhibit CDK- cyclin complexes and progression to mitosis (Perry and Kornbluth, 2007).

Interestingly CDC25B is overexpressed in 32% of primary breast cancers and this expression correlates with more aggressive disease (Galaktionov et al., 1995). CDC25A/B can not only respond do DNA damage signals such as those mediated by p53, CDC25A is also a transcriptional target of RB-E2F, making it a therapeutic target of interest.

1.5.4 Targeting migration: CDC42BPA

The Zacksenhaus lab showed that knockdown of CDC42BPA in MDA-MB-231 promoted migration in comparison to controls. CDC42 (cell division cycle 42) itself is a member of the p21 Rho family of small GTPases that regulates actin cytoskeletal reorganization, assisting in actin localization, nuclear displacement, protein trafficking and directed cell movement (Nobes and Hall, 1995). CDC42 (BPA)binding protein A, also known as MRCK, Myotonic Dystrophy Kinase-Related CDC42-Binding Kinase is a member of the serine/threonine protein kinase family, and was originally identified as PK428 (Zhao et al., 1997). The MRCKs are a family of 190kDa serine threonine kinases highly related (68%) to the myotonic dystrophy kinase, and bind to GTP- bound form of CDC42 (Leung et al., 1998). MRCKα and MRCKβ both have the following domains: kinase, cysteine rich, PH, p21 and GTPase binding domain. MRCKα localizes to punctate structures in the cytoplasm, but mostly on cell periphery especially at the leading edge and along the cell-cell junction, colocalizing with CDC42 (Leung et al., 1998). Over expression of MRCKα with low levels of CDC42 led to the formation of microspikes and filipodia in Hela cells, whereas CDC42 alone did not. This suggests that CDC42BPA plays a crucial role in cytoskeletal reorganization (Leung et al., 1998).

CDC42BPA was also identified in a proteomic screen and then validated in vitro as promoting migration and invasion in colon cancer cells. Also its expression was correlated with poor prognosis in colon cancer patients (H.F. Hu et al. 2017). CDC42BPA is also involved in epithelial extrusion (Gagliardi et al., 2018). It is not fully clear however if it promotes or suppresses metastasis of BC cells.

1.6 Rational

BC is the 2nd leading cause of female cancer mortality in Canadian women; according to a 2017 study, 14 women died from BC every day. Of the three major pathological subtypes, TNBC has the worse prognosis and urgently needs targeted therapy. In the absence of known targetable receptors, other mutations common across the subtype can be explored as possible therapeutic targets. RB1 and TP53 are two commonly mutated tumor suppressors in TNBC, and they have also been identified as drivers of metastasis which is the main cause of mortality in BC. RB1 is among the 9 most commonly altered genes in Breast Cancer, and is associated with recurrent disease making it a very attractive therapeutic target (E. Zacksenhaus et al., 2017). Unfortunately, RB1 loss is not directly targetable, and therefore pathways downstream of RB deficiency must be examined.

To that end using mouse models of RB+/p53-, and RB-/p53- loss, the Zacksenhaus lab has shown that RB loss was accompanied by an E2F1/3-dependent stimulation of MPT compared to p53 loss alone (Jones et al., 2016), exposing increased MPT as a possible therapeutic target as well as a possible mechanism for RB1-deficiency-driven metastasis. CDC25 phosphatase was identified in kinome/phosphatase inhibitor screens for RB-/p53- tumors, and as potential therapeutic target for all BCs missing RB. CDC42BPA was found to be altered in combination with RB loss in an in vivo mutagenesis screen and given its effect on cell migration it was imperative to determine whether loss of these two proteins cooperate to promote metastasis.

1.6.1 Hypothesis

I hypothesize that RB-deficiency will result in increased cell migration, which corresponds to an increase to MPT, and that this increased migration can be blocked using an MPT inhibitor: Tigecycline. Given the E2F1/3-dependent transcriptional increase in MPT I predict that the E2F1 will bind promoter regions of MPT-related genes. I hypothesize that given CDC42BPA’s role in actin reorganization that its knockdown will synergize with RB knockdown to further promote migration. Finally, I hypothesize that RB’s downstream effect on cell cycle dysregulation and immunomodulation can be explored as therapeutic avenues by targeting CDC25 phosphatases and PD-L1 expression respectively. To asses these hypotheses I carried out the following objectives.

1.6.2 Objective

1) Interrogate the role of RB1 loss in cancer cell migration. 2) Investigate the role of RB1 loss in breast cancer cell response to experimental therapy.

Chapter 2

Materials and Methods 2.1 Cell Culture

MDA-MB-157, Hs578T, MDA-MB-231, MCF7 MDA-MB-436, BT549 and JIMT1 human breast cancer cell lines were maintained in DMEM containing 6%FBS and 1%PEST, at 37⁰C with 5%

CO2. HCC38, HCC1937 and HCC1954 cell lines were maintained in RPMI media containing 6% FBS and 1% PEST. Cell line Breast Cancer Subtype RB1 P53 MCF7 ER+ + wildtype MDA-MB-231 TNBC + mutant MDA-MB-157 TNBC + wildtype Hs578T TNBC + mutant HCC38 TNBC + mutant HCC1954 HER2+ + mutant JIMT1 HER2+ + mutant BT549 TNBC - mutant HCC1937 TNBC - mutant MDA-MB-436 TNBC - mutant ****RB1 and p53 status according to COSMIC cell database

Table 1. Cell lines used in this study

2.2 Transfection with Small Interfering RNA (siRNA) siRNAs for RB and scrambled negative control, siRNA transfection reagent, and Opti-MEM reduced serum transfection medium were purchased from Dharmacon. A day before transfection, 2x105 cells were seeded in 6-well plates with regular medium and incubated for 24hr. Transfection complexes were prepared with RB or scrambled siRNA, and Lipofectamine RNAiMAX Reagent, diluted in Opti-MEM. Cells were washed with pre-warmed PBS. After 20min of incubation at room temperature, 500µl of siRNA-lipofectamine complexes were added directly to adherent cells. The next day cells were split into 96-well plates for MTT analysis 3 days later.

2.3 Scratch Test Migration Assay

Cells were plated at confluency in a 12 well plate and the next day treated with aphidicolin at a concentration of 500nM for 12h prior to scratch. A scratch was made using a 10µl pipette tip, plates were washed and media replaced with 500nM aphidicolin media. Images where then taken at 0, 12, and 14 hours. Area of scratch was calculated for each image using ImageJ. Data from independent experiments with normalized time 0, were pooled together to calculate significance using nonparametric t-test in GraphPad Prism. To test migration in the presence of tigecycline or rotenone, cells were plated, then on the next day treated with 500nM aphidicolin overnight. The following day the scratch was performed. Cells were washed and media replaced with either aphidicolin (control), tigecycline, or rotenone. Images were taken at 0, 12, 18 or 24h post scratch, and areas calculated using ImageJ software.

2.4 Chromatin Immunoprecipitation (ChIP)

Cells were crosslinked in 1%PFA for 15min at room temperature. Crosslinking was quenched by addition of glycine to a final concentration of 0.125M for 5min at room temperature. Cells were then washed and collect in PBS with protease inhibitor cocktail. Cells were centrifuged at 1400rpm in 4⁰C. Cells were lysed for 1 hour on ice. Cells were sonicated on ice for 15sON30sOFF for 35cycles. Samples were centrifuged to remove debris. Supernatant was then transferred to a new Eppendorf tube and incubated overnight at 4⁰C with either control Rabbit IgG (CST2729), or Rabbit IgGs against H3K4me3 (CST9751S), or E2F1(sc-193)/E2F1(EMD 05-379). Samples where then incubated with Repligen A beads for 4h at 4⁰C. Beads were then washed with Low Salt Buffer, High Salt Buffer, LiCl Buffer and finally resuspended in ChIP Elution Buffer. Samples where incubated with RNAase at 37⁰C for 1h, with ProK at 42⁰C for 1h, and then overnight at 65⁰C. DNA was purified using Qiagen PCR purification kit (Qiagen28104). PCR was performed using POLA1 fwd5’GAAAGCAAGGGGAAGGTTTG3’ rev5’ACCGTGACAGGAGGTGACT3’, MRPL37 fwd5’CACGTGAGGATTTTCCAGGT3’ and TK1 fwd5’AGGAACCTTGCTTGGGAAAC3’ rev5’ACGAACCCGAGTACTCTCCA3’.

2.5 Cell Cycle Analysis by Flow Cytometry

Cell cycle analysis was performed using PI/RNAse Staining Buffer (BD Sciences). Cells were treated with DMSO (vehicle control), WEE1 inhibitor (MK-1775), or CDC25 inhibitors

(BN82002 and NSC663284). Due to different kinetics of cell killing, MK-1775 and NSC663284 treated cells were collected after 24 hours, whereas DMSO and BN82002 treated cells were collected after 48 hours. Prior to trypsinization, cell supernatants were collected. Supernatants were later combined with their respective trypsinized cell suspensions, pelleted, washed with PBS, and fixed in 66% Ethanol. Fixed cells were washed with PBS, resuspended in PI/RNAse staining buffer and incubated in the dark at 37¹C for 1 hour. Next cells were strained into a 5mL polysterene round-bottom FACS tubes (BD Falcon) and placed on ice. Samples were processed on LSRII (BD Sciences) at the SickKids-UHN Flow and Mass Cytometry facility, and results were analyzed using FlowJo Software.

2.6 MTT Viability Assay

Cells were seeded in 96-well plates at 1000-1500cells/well and treated the following day. Three days (72 h) later 30 µL of 2 mg/mL MTT (3-[4,5-dimethylthiazol-2-yl]- 2, 5-diphenyl tetrazolium bromide, Sigma) was added to each well and incubated for 3 hours. MTT/media solution was aspirated and replaced with 100 µL DMSO and left at R.T. for 15–20 min to dissolve the formazan dye. After gentle agitation to ensure even mixture of the dye, a 96-well microplate reader (Molecular Devices) was used to determine the optical density (OD) of each well at 570 nm. Each assay was performed with 6 replicates and repeated at least 3 times.

2.7 Western Blot Analysis

Cells were washed with PBS and lysed using RIPA lysis buffer (0.15 M NaCl, 1% Nonidet P-40, 0.5% Sodium deoxycholate, 0.1% SDS, 25mM Tris 7.4, 5 mM NaF, 0.5 mM Na3VO4, and 1:100 protease inhibitor cocktail [1 mg/mL leupeptin, 2 µg/mL aprotinin, and 100 mM PMSF]). Protein concentration was determined by Pierce Reagent (Thermo Scientific). PD-L1 immunoblot lysates were collected using SDS lysis buffer (1%SDS, 11%glycerol, 0.1M Tris ph6.8). About 20 µg of protein was fractionated by SDS-PAGE and transferred onto PVDF membranes. The membranes were blocked with 5% nonfat dried milk in phosphate-buffered saline containing 0.05% Tween 20 (PBST) at R.T. for 1 h, washed 3 × 5 min with PBST, and incubated at 4 °C overnight with following antibodies: MRPL37 (abcam 224467), RB (Santa Cruz C-15), CDC42BPA (sc-374568), PD-L1 (CST E1L3N), E2F1(sc-193)/E2F1(EMD 05-379) and GAPDH (sc-47724). Membranes were washed with PBST buffer 3 × 5 min each and incubated with HRP-conjugated anti-rabbit IgG secondary antibody (Cell Signaling) for 2 h. Primary antibodies were diluted 1:1000 in PBS

(GAPDH 1:2000) with 5% BSA; secondary antibody was diluted 1:2000. Blots were imaged using thermofisherPicoPlus ECl.

2.8 RNA isolation and Quantitative Real-time PCR

RNA was isolated from cell lines using Trizol (Sigma), and ethanol precipitation. A NanoDrop 2000 spectrophotometer (Thermo Scientific) was used to measure RNA concentration. RT PCR was performed using SensiFAST cDNA Synthesis Kit (BIO-65053 from Bioline). qPCR was performed using SYBR Green PCR Master mix (4309155) on a 7900HT Fast Real-Time PCR system (Applied Biosystems). Results were analyzed using the comparative threshold cycle method. All experiments were performed in triplicate and relative gene expression was normalized to GAPDH and calibrated to control (scrambled shRNA infected cells). Detailed primer information in Table 2. hTOMM40 Mitochondrial forward GAGTTTGAGGCCAGCACAAG Translation reverse ACCCACGATCCAGTTGCTAT hCISD1 Mitochondrial forward TACTGCCGTTGTTGGAGGTC Translation reverse ATCAGAGGGCCCACATTGTC NDUFAB1 Mitochondrial forward CAGCCGGCCTTAGTGCTC Translation reverse GGTCCTGGATGCCCTCTAAC hMRPL37 Mitochondrial forward TGGACTGTAACGAGGGTGTC Translation reverse TGTCTCTGGCTTGAAACCAAC hTK1 Cell cycle forward ATGCCAAAGACACTCGCTAC reverse TCGTCGATGCCTATGACAGC hPOLalppha1 Cell cycle forward GAAGTTCAAGTCTAAGCCAGTGG reverse AGGCTAGATGTGTTGGTCCC hCCNE1 Cell cycle forward CAAAATCGACAGGACGGCG reverse CTTGCACGTTGAGTTTGGGT hGAPDH Housekeeping forward TGGAAGGACTCATGACCACAG control gene reverse ATGATGTTCTGGAGAGCCCC

Table 2. qPCR Primers used in this study.

2.9 ATP Assay

Cellular ATP levels were determined using the CellTiter-Glo Luminescent Cell Viability Assay (Promega) according to manufacturer instructions.

2.10 Cell Proliferation Assay

Cells were plated in a 24 well plate, and each day an equivalent well was trypsinized and cells counted using a hemocytometer over 4 days, and cell doubling time was calculated. Three independent experiments were performed, and significance calculated using students t-test, using GraphPad Prism. For IncuCyte analysis, cells were seeded at 1000 cells per well, and placed in the IncuCyte incubator. Images were taken every hour for 96 hours (3 days). IncuCyte software was used to analyze the occupied area of cells over time to calculate % confluence of cells.

2.11 Stable Cell Line Generation

Lentiviral plasmids: scrambled and shRB pLKO vector, and scrambled and shRNA RB vector (from Dharmacon), were expanded in E.coli, and extracted using miniprep (Qiagen). For lentivirus production, packaging plasmids psPAX2 and PMD2, and with target vector, were co-transfected into HEK293T or Phx cells using PEI. 48h post transfection media supernatant was harvested, filtered through a 0.45µm filter and then used to infect target cell line. After 24 h infection, medium was changed, and cells either sorted for GFP positive cells and/or were grown in presence of puromycin to obtain resistant cells.

Chapter 3

Results Note: Figure 9 was published in “Identification of CDC25 as a common therapeutic target for triple-negative breast cancer” in Cell Reports 2018 (Liu et al., 2018). Other Results presented in this thesis will be published elsewhere.

3.1 RB-deficiency induces MPT possibly mediated by E2F transcription factors

RB1 loss is not targetable. One approach to target RB1-deficient tumors is to block downstream pathways such as those induced by E2F1-3, one of the major binding partners of pRb (Johnson and Schneider-Broussard, 1998). Our laboratory established that RB and E2F1/3 regulate MPT genes such as MRPL37 in TNBC (Jones et al., 2016; Eldad Zacksenhaus et al., 2017). I therefore set out to determine whether E2F1 binds to the promotor of MRPL37. For this purpose, I used MCF7 luminal cell line with CRISPR knockout (CRISPR-KO) of RB, and stable knockdown of p130 (Figure 1A). MCF7 CRISPR RBKO p130KD MCF7 cells were used in order to avoid possible compensation for RB by p130, a distinct pocket protein family member. ChIP analysis revealed that E2F1 is bound at the MRPL37 promoter, and at TK1 (thymidine kinase 1) and at POLa1 (DNA Polymerase Alpha 1) the later two are known E2F target genes (Figure 1B). The level of E2F1 binding was not visibly different in control versus RBKO/p130KD cell lines. E2F1 binding to the MRPL37 promoter provides direct evidence of Rb-E2F1 mediated metabolic reprogramming. Migration is an energy-demanding process and this increase in MPT, may be a potential mechanism by which RB-loss promotes metastasis. To further explore this idea, I created several human RB-knockdown (RBKD) BC cell lines.

Figure 1. ChIP analysis suggests that E2F1 is directly recruited to the MRPL37 promoter. (A) Western Blot measuring RB and p130 expression in CRISPR control MCF7(ccMCF7) and CRISPR-RBKO MCF7 and CRISPR-RBKO shRNA p130KD (B) Representative ChIP-PCR gel from CRISPR control MCF7 cells and CRISPR-RBKO p130KD MCF7 cells. Lane controls: genomic DNA (gDNA), unsonicated sample (UNS), Input DNA after sonication (5% Input), negative control rabbit IgG immunoprecipitated sample (IgG), and positive control anti-histone 3 lysine 4 trimethylation immunoprecipitated sample (H3K4me3). TK1 and POLa1 were used as positive control for E2F1 regulated cell cycle genes (n=2).

3.2 RB Knockdown promotes cell migration in most but not all cell lines, but has no obvious effect on cell proliferation

Using lentiviral shRNA, I generated RB knockdown and scrambled control TNBC cell lines: MDA-MB-231 (M231), Hs578T, HCC38, MDA-MB-157 (M157), and HER2+: JIMT1 and HCC1954 cell lines (Dai et al., 2017). Knockdown was confirmed by western blot (Figure 2). RB Knockdown (RBKD) did not significantly affect proliferation in HCC1954, JIMT1, M231 and HCC38 cell lines. Cell proliferation was assessed by both population doubling time and IncuCyte analysis (Figure 3). The exception was Hs578T which showed significant increase in cell proliferation. Interestingly RBKD in this line was most efficient suggesting that perhaps complete KD of RB1 is necessary to observe effect on cell division. In contrast, nearly all these tumors lines including those with no increase in cell proliferation. M231, Hs578T, HCC38, HCC1954 and JIMT1 RBKD, migrated faster than control in Scratch Assay (Figure 4). Note that all cells were pretreated with aphidicolin before the assay to block cell proliferation, aphidicolin treatment did not affect cell migration (Figure A1). MDA-MB-157 RBKD cell line did not migrate faster than scrambled control. This may be due to the difference in mutational background and source of the cell line. Indeed, all other cell lines exhibited tumorgenicity and metastasis in tumor mouse xenograft models whereas M157 cells only induce primary tumors (Smith et al., 2017). All other cell lines also have mutated p53 whereas M157 is p53 WT. TP53 is a major driver of metastasis, suggesting p53 mutation may be required to cooperate with RBKD to promote cell migration in TNBC (Robinson et al., 2017). This possibility is testable by knocking down TP53 in M157.

Increases in migration led us to look at the ATP levels in cells. Trends towards (but insignificant) increased total ATP levels was seen in M231, Hs578T, and HCC1954 RBKD cell lines in comparison to scrambled controls as assessed by CellTiterGlo (Figure 5A). Notably, mitochondrial fission (fragmentation) allows for accumulation of monomeric mitochondria at the site off lamellipodia, leading to high, localized ATP concentrations required for cell migration (Zhao et al., 2013). Thus, it may not be the total level of ATP within the cell that promotes increased migration in RB-deficient cell lines but its localization.

Figure 2. Effective RB knockdown in HER2+ and TNBC cell lines. (A) Representative Western Blot showing (B) significant knockdown of RB in comparison to scrambled controls as assessed using ImageJ. Significance calculated using t-test in Prism (n=3).

Figure 3. RB Knockdown does not significantly impact cell proliferation in most HER2+ and TNBC cell lines. (A) Population doublings of human breast cancer lines, as assessed using Trypan blue cell counts (n=3). Significance calculated using GraphPad Prism, unpaired t-test (*p<0.05). (B) IncuCyte data for M231 scrambled and RB knockdown cell line growth curves over 100 hours (n=1).

Figure 4. RB knockdown promotes cell migration in most but not all cancer cell lines. Scratch assays showing the migration of HER2+ (A-B) and TNBC (C-F) RBKD cells in comparison to control SCRAM cells at time 0, 12, 18 or 24 hours post scratch (n=3). Scratch areas were calculated using Image J and normalized to time zero across independent experiments. Significance calculated using GraphPad Prism, unpaired t-test (*p<0.05).

3.3 Increased MRPL37 expression at mRNA and protein level in RB-deficient highly migratory cells.

To determine the mechanism for increased migration of RB-deficient cell lines, expression of MPT at both the protein and mRNA levels was explored. Protein levels of MRPL37, an MPT protein, increased in RB-deficient M231 and HCC1954 cells compared with control RB-proficient parental cells (Figure 5B). TK1 is a cell cycle associated gene known to be regulated by RB-E2F1. TK1 transcript level was found to significantly increase following RBKD in all cell lines tested (Figure 5C). MPT-associated genes MRPL37 and CISD1 (CDGSH Iron Sulfur Domain 1) significantly increased in M231 and HCC1954 RB KD cell lines in comparison to controls (Figure 5D). Interestingly RBKD M231 and HCC1954 cell lines were the only ones to migrate faster than controls at both the 12h and 24h time points and were also the two cell lines to show significant increase in protein and mRNA expression of MPT genes. This suggests that increased MPT is a possible mechanism for increased migration in response to RB1-defficiency.

Figure 5. RB knockdown promotes expression of MPT-related genes but does not significantly affect cellular ATP levels. (A) ATP levels show a trend towards significant increased levels in Hs578T, M231 and HCC1954 cell lines. Cellular ATP levels were determined using the CellTiter-Glo Luminescent Cell Viability Assay (Promega). (B) Representative Western Blot of 3 biological replicates. (C) MRPL37 expression was elevated in M231 and HCC1954 RBKD cell lines. (D) Relative mRNA expression of cell cycle (green) and MPT(yellow) associated transcripts in TNBC(Hs578T, M231, HCC38) and HER2+(HCC1954) cell lines normalized to GAPDH and scrambled control. Significance was assessed using students’ t-test in GraphPad Prism (*p<0.05) (n=3).

Figure 6. Cell Sensitivity to MPT inhibitor, Tigecycline is not altered in response to RB1 knockdown. (A) Cell survival after 3 days of treatment with Tigecycline as assessed by MTT assay (n=3).

3.4 RB1-deficient Cell line response to Experimental Therapy

BC cell lines show differential response to therapy based on RB1-status (Knudsen and Knudsen, 2008; Eldad Zacksenhaus et al., 2017). Using the RB knockdown cell lines I developed, different possible therapeutic targets were explored.

3.4.1 Cell Sensitivity to MPT inhibitor, Tigecycline, is not altered in response to RB1 knockdown.

Tigecycline is an FDA-approved antibiotic, that targets mitochondrial protein translation, and was identified by the Zacksenhaus lab as a potential drug for RB/p53-deficient TNBC in mice (Jones et al., 2016). Given the increase in MPT seen in the RB knockdown cell line, cell sensitivity to tigecycline was tested using the MTT assay. I found that the cells showed variable sensitivity to tigecycline that was not dependent on RB status (Figure 6). Although Tigecycline did not show RB-status specific sensitivity it is possible that it can block the increased migration seen in RBKD cell lines. To test this I treated HCC1954 and M231 RB knockdown cell lines with either aphidicolin, tigecycline or rotenone, an ETC inhibitor, and compared migration using the scratch assay (Figure 7). Migration of cell lines was attenuated by both tigecycline and rotenone.

3.4.2 CDC42BPA does not cooperate with RB knockdown to further promote migration.

The Zacksenhaus lab identified CDC42BPA as a gene which is targeted by transposon mutagenesis in a Sleeping Beauty mutagenesis screen for genes that cooperate with RB loss to promote metastasis. They further found that knockdown of CDC42BPA in M231 cells promoted migration in comparison to parental control cells (unpublished). To investigate whether combined loss of RB and CDC42BPA may synergize to further promote migrations, I created shRNA double knockdown RB/CDC42BPA GFP+ cell lines. Efficient knockdown was confirmed by western blot (Figure 8A). Migration of the double knockdown cell line was not significantly faster than the CDC42BPA single knockdown cell line (Figure 8C). The nearly antagonist effect of combined RB plus CDC42BPA loss may suggest that the two genes operate on the same pathway. However, further analysis including using less migratory cells than M231 is needed to elucidate the interaction between these genes.

Figure 7. Migration of RBKD Cell lines is decreased in the presence of MPT inhibitor (Tigecycline) and Mitochondrial ETC inhibitor (Rotenone). Cell Migration as assayed by scratch test at 0h, 12h, and 18h or 24h timepoints is decreased across all cell lines tested but this decrease is not affected by the RB status in the cell. (A)M231 (n=5) (B) HCC1954 (n=3) Scratch areas were calculated using Image J and normalized to time zero across independent experiments. Significance calculated using GraphPad Prism, unpaired t-test (*p<0.05).

% % Scratch Area

Figure 8. CDC42BPA KD promotes migration but does not cooperate with RB knockdown in M231 cell line. (A) Western Blot showing knockdown of CDC42BPA and RB. (B) Images of GFP cell lines. (C) Cell Migration assayed using Scratch assay at 0h, 12h, and 24h timepoints, areas calculated using ImageJ software, significance calculated in prism using non-parametric paired t-test (n=6) (*p<0.05).

3.4.3 CDC25 Inhibition has cytotoxic effect on RB-Deficient TNBC cells.

CDC25 phosphatase activates, whereas WEE1 kinase inhibits CDK2-cyclinB complexes required for G1/S and G2/M transitions. The Zacksenhaus lab identified CDC25 as potential target for diverse TNBC including highly aggressive RB1/PTEN/TP53-deficient TNBC cells. Using a small molecule inhibitor of CDC25, BN82002, I assessed sensitivity in MCF7, HCC3153, M231, HCC1937, Hs578T and M157 using MTT assays (Figure 9A). To assess the effect of RB1 status on sensitivity to CDC25 inhibitors, I transiently knocked-down RB in M231 using siRNA. I found that RB knocked-down did not affect sensitivity to BN82008 (Figure 9B). To further decipher the mechanism by which CDC25 inhibits cancer cell growth, I performed cell cycle analysis by flow cytometry. BT549 and M231 cells were pretreated with either CDC25 (BN82008 and NSC663284) or WEE1 (MK-1775) inhibitors, fixed, stained with propidium iodide and analyzed by flow cytometry (BD FACS Calibur).

WEE1 inhibition resulted in accumulation of cells in S phase, whereas CDC25 inhibitors induced cell death without apparent accumulation of cells in any particular phase of the cell cycle (Figure 9C). This suggests that CDC25 and WEE1 inhibitors induce cell death through independent mechanisms.

Figure 9. RB-deficient TNBC cells are sensitive to CDC25 inhibition (A) IC50s of BN82002 in indicated luminal (CAMA1; MCF7; MDA-MB-361), basal A (basal-like; HCC3153, MDA- MB-468, HCC1937) and basal B (claudin-low; BT549, Hs578T, MDA-MB-157, MDA-MB-231, MDA-MB-436) breast cancer lines. P value denotes one-way Anova with Tukey posthoc. (B) Efficient RB knockdown in MDA-MB-231 cells. Cells were transfected with RB-specific or scrambled RNAi and analyzed for RB expression 3 days later. Knock-down of RB via RNAi does not reduce sensitivity of MDA-MB-231 cells to BN82002. (C) Cell cycle profiles of BT549 (RB1- ) and MDAMB231 (RB1+) cells treated with DMSO (vehicle control), or indicated concentrations of WEE1 inhibitor (MK-1775), or CDC25 inhibitors (BN82002 or NSC663284) using PI staining and Flow Cytometry analysis. % of cells in each phase is indicated, excluding cells with <2N or >4N DNA.

3.4.4 RB knockdown induces PD-L1 expression in TNBC cell lines.

RB-knockdown in other cancer models has recently been shown to increase expression of PD-L1, an important target for immunotherapy (Dua and Tan, 2017). Using the RBKD cell lines I assessed whether a similar trend could be seen in TNBC. Increased expression of PD-L1 in Hs578T and M231 RBKD cell lines in comparison to scrambled controls was observed by Western Blot (Figure 10). These results expose PD-L1 as a possible target for RB-deficient TNBC, although further interrogation into mechanism of increase is warranted and underway in the Zacksenhaus lab.

Figure 10. RB knockdown induces PD-L1 expression in TNBC cell lines. Increased expression of PD-L1 in Hs578T and M231 RB KD cell lines in comparison to scrambled controls as assessed by Western Blot.

Chapter 4 Discussion

In the US alone there will be an estimated 271,270 new cases of BC , and despite significant efforts in the field 42,260 women and men are estimated to succumb to the disease this year (2019) (Siegel et al., 2019). RB1 loss signature is associated with aggressive disease, increased metastasis and is a marker of breast cancer recurrence, however the mechanism by which RB1 exerts these effects are largely unknown (Chen et al., 2019; Robinson et al., 2017; Thangavel et al., 2017; Weigelt et al., 2005). One of the important initial steps of tumor metastasis is the migration of cells away from the primary tumor site. In this thesis I show that in most human TNBC and HER2+ cell lines tested, RBKD promotes migration which correlates with increased MRPL37 expression in highly migratory RBKD cell lines. ChIP analysis revealed that pRB’s binding partner E2F1 bound to the promoter region of MRPL37, suggesting direct regulation of this gene by pRB-E2F. Cell sensitivity and cell migration inhibition, by tigecycline (MPT inhibitor) and rotenone (ETC inhibitor) were not dependent on RB status. Given that RB1 is disrupted in 30% of TNBCs, experimental therapies targeting downstream alterations of this loss, have potential for great impact. In this study I have explored mitochondrial protein translation, cytoskeletal reorganization pathway (CDC42BPA), CDC25 phosphatases and the PD-L1 immune checkpoint as possible therapeutic targets downstream of RB1 loss.

Migration is only a small component of the complex process of metastasis, therefore further investigation of RB1-loss as a driver of other steps in the metastatic cascade is warranted. It is possible that RB1-deficiency drives metastasis through multiple mechanisms such as actin polymerization, EMT, angiogenesis, DNA instability, and metabolic reprogramming. RB suppression has been shown to increase cell migration in multiple other models of cancer including prostate, non-small cell lung cancer and glioblastoma (Thangavel et al., 2017). For instance, in a mouse prostate cancer model RB depletion was shown to increase migration and metastasis through E2F regulated transcription of receptor for hyaluronan-mediated motility (RHAMM) (Thangavel et al., 2017). RBKD in a luminal BC cell line induced cancer cell migration and CD44 expression; a hyaluronic acid receptor that is essential for maintenance of cancer stem cell phenotype (Kim et al., 2013). Additionally, in an in vitro model it was found that RBKD epithelial cells upregulated expression of Rho A and C, snail and increased expression of basal markers:

35 cytokeratin 5/6 (Kim et al., 2013). RB1 is also implicated in activating epithelial to mesenchymal transition in BC (Jiang et al., 2011). RB1 loss allows E2F1-mediated transcription of VEGF and other proangiogenic factors, promoting not only primary tumor growth, but also more opportunities for dissemination of cancer cells (Lehmann and Pietenpol, 2014). Thus the increased migration observed in the M231, HCC1954, and Hs578T cell lines in this study could be a result of increased EMT or CD44/RHAMM pathway activation, and may translate to increased metastasis in vivo.

In M231 cells, CDC42BPA KD also led to a significant increase in migration in comparison to controls. In contrast CDC42BPA KD in colon cancer cell lines led to a decrease in cell invasion and vimentin expression, a marker for mesenchymal cells (H. Hu et al., 2017). Chemical inhibition of CDC42BPA in a squamous carcinoma cell model resulted in reduced myosin light chain phosphorylation, cell motility and tumor cell invasion (Unbekandt et al., 2014). This suggests a context-specific role for CDC42BPA, and further investigation into its functions in BC is warranted. I found that combined RB plus CDC42BPA KD in M231 cells had no additive effect on migration. M231 is a highly migratory cell line and as such testing the double knockdown in a less motile cell line may reveal cooperation between CDC42BPA and RB KD. Alternatively, RB and CDC42BPA may act on the same pathway and may therefore be even antagonists, as I found at the 24hrs time point. Additional assays to monitor migration could be done to confirm these results; for example by testing invasion using Cornwell trans-well assay. IncuCyte could also be used to monitor cells moving through a 3D matrix towards a stimulus, whereby images can be taken at specific timepoints without removing the cells from the incubator, thereby decreasing variability between experiments. In addition movement of cells through a 3D matrix may be more representative of cancer cell dissemination in vivo.

I hypothesize that given the increased migration of RBKD cell lines in vitro, mice transplanted with RBKD BC cell lines will have more metastasis. To monitor whether increased cell migration in vitro translates to increased metastasis in vivo, RB1KD and scrambled control cell lines could be transplanted into the mammary fat pad of recipient mice, and primary tumor growth and metastasis analyzed by histology. Alternatively, RB1KD cell lines tagged with luciferase could be created so that tumor dissemination can be monitored at several time points in the same mouse using bioluminescent imaging.

In HCC1954 and M231 RBKD cell lines, a significant increase in expression of MPT genes was seen both at the mRNA and protein level. These lines also had the greatest difference in migration suggesting a role for MPT in this process, downstream of RB. Tigecycline and rotenone, two drugs that target mitochondrial function were able to effectively inhibit cell migration. These results are consistent with previous observations that mitochondrial function, OXPHOS, as well as PGC1-α which induces mitochondrial biogenesis all increase cell migration (Sancho et al., 2016; Eldad Zacksenhaus et al., 2017). In MCF7 cells, another member of the Zacksenhaus lab found that while RB1KO showed some increased sensitivity to tigecycline, there was a great increase in sensitivity when p130 was knocked down concurrently with RBKO. This suggests that p130 may compensate for RB1-deficiency and thus decrease cell sensitivity to tigecycline (Figure A2. Mariusz Shrestha, unpublished). To test this hypothesis M231RBKD p130KD cell lines could be generated and tigecycline sensitivity compared to the single knockdown cell lines. Given the increase in MPT seen in the RBKD cell lines, I hypothesize that there could also be an increase in OXPHOS, which is a metabolic program known to promote metastasis (Sancho et al., 2016). To test this, Seahorse analysis can be performed comparing RBKD and scrambled control cell lines. Seahorse analysis measures extracellular acidification (ECAR) and oxygen consumption rates (OCAR), which are representative of the level of glycolysis and OXPHOS respectively. I expect RB1 deficient cells to exhibit increased levels of ECAR/OXPHOS. Mass spectrometry analysis can reveal differences in metabolite breakdown and trafficking within these cell lines. Together, this analysis will uncover metabolic reprogramming in response to RB loss, including OXPHOS vs glycolysis, the levels of key metabolites, and metabolic flux in TNBC cells.

Interestingly, no significant increase in ATP levels was observed in RBKD cell lines. However there is evidence that it is not the level of ATP but its localization within the cell that is important in promoting cell migration. Mitochondria can undergo fission and fusion which is regulated by dynamin-related protein 1 (Drp1) and mitofusins (Mfns)(Chan, 2006). In highly migratory cells fragmented mitochondria at the leading edge of lamellipodia are required for efficient migration (Zhao et al., 2013). Thus, I hypothesize that ATP in RBKD cell lines is localized to migratory structures, through fragmented mitochondria at lamellipodia although the total level of ATP would be the same as seen in controls in this context. This could be confirmed using fluorescence microscopy staining both polymerizing actin and mitochondria to compare both actin polymerization and mitochondrial structure in RBKD and scrambled cell lines.

Inhibition of CDC25 phosphatases induced apoptosis in TNBC cells independent of RB status and without obvious perturbation of the cell cycle. Interestingly, CDC25 inhibition also showed synergy with inhibitors of the WEE1 kinase, which antagonized CDC25. Further investigation into this pathway may lend itself to application of this therapeutic approach to other cancers with RB1 and p53 deletions.

Current research suggests multiple mechanisms for regulation of PD-L1. There is evidence that RBKD increases PD-L1 expression through interaction with NF-κB in prostate cancer (Jin et al., 2019). Cdk4/6 inhibitors have been shown to increase PD-L1 expression though inhibition of the SPOP-CUL1 E3 ligase, and thereby preventing ubiquitination-mediated PD-L1 degradation (Nihira et al., 2017). Interestingly a recent paper shows that in TNBC, transmembrane protein Mucin 1 is able to promote MYC and NF-κB binding to PD-L1 promoter to increase PD-L1 expression (X. Hu et al., 2017). Furthermore, MYC was shown to directly regulate PD-L1 and CD47, the latter acting as a “don’t eat me” signal to macrophages (Walz et al., 2016). It would thus be important to test whether CD47 is induced in response to RB knock-down. Future experiments can determine the effects of MYC, NF-κB, MUC1 and SPOP downstream of RB by, for example, knocking down MYC, NF-κB, MUC1 and testing whether this would block PD-L1 induction in RBKD cells. Notably, another Zacksenhaus lab member has found opposite results, where RBKD in BC cell lines led to a decrease in PD-L1, and there is some evidence that PD-L1 expression may increase with cell confluence. This line of research is ongoing in the Zacksenhaus Lab.

4.1 Summary

Breast Cancer (BC) is a leading cause of female mortality, with 5,000 Canadian women estimated to succumb to this disease in 2017. There are three main subtypes of breast cancer characterized by receptor expression; ER+, HER2/NEU/ERBB2+ and TNBC the latter of which does not express these receptors or the Progesterone Receptor. Mortality from BC is caused by dissemination of cancer cells, which leave the primary tumor and spread, forming metastases in other tissues and disrupting normal organ function. Starkly, metastatic TNBC has a median survival of only 10-13 months, compared to the 4-5-year median in the hormone receptor positive subtypes. While there are targeted therapies available for HER2+ and ER+ breast cancer, only chemotherapy is currently effective for TNBC. Therefore, further investigation is needed to improve current patient prognosis and therapy. In the absence of targetable hormone receptors, one strategy for developing targeted therapy involves identification of common mutations in TNBC. The RB1 pathway and TP53 have been identified as two major drivers of metastatic progression and are interrupted in 28-40% of samples. Unfortunately, RB1 loss is not directly targetable. Also it is not fully understood how RB1-loss promotes tumor invasion and metastasis.

Here I investigated how RB1-loss impacts invasion and metastasis, and whether RB1-deficient TNBC can be targeted for therapy. Previous results from our laboratory found that RB loss was accompanied by an E2F1/3-dependent transcriptional stimulation of mitochondrial protein translation (MPT) and Oxidative phosphorylation (OXPHOS), which is implicated in enhanced motility and metastasis. In preliminary results I have found that E2F1 binds the promoter of the MPT gene, MRPL37, to regulate its expression in control and MCF7 CRISPR-RBKO/p130 KD cells. I showed that knockdown of RB in several independent TNBC cells enhanced migration relative to isogenic control cells. This was accompanied by increased MRPL37 gene expression, in HCC1954 and MDA-MB-231 cells. Cell migration was inhibited by MPT inhibitor (Tigecycline) and mitochondrial electron transport chain inhibitor (Rotenone). My data suggest that RB loss may induce changes in cell metabolism, promoting cell migration, and this effect may be mediated by E2F1. In addition to RB-deficiency leading to downstream changes in migration, other possible downstream vulnerabilities were also investigated. PD-L1 is expressed by aggressive tumors to evade cytotoxic T-cell-mediated cell death and can be targeted using anti- PD-L1 inhibitors. I found that RB knockdown induces PD-L1 expression in TNBC cell lines,

39 suggesting that RB1 loss in breast cancer cells may promote evasion of immune surveillance. I also found that inhibition of CDC25 phosphatase has cytotoxic effect on RB-deficient TNBC cells without cell cycle perturbation. In contrast, inhibition of WEE1 resulted in accumulation of cells at S phase. CDC42BPA knockdown, although correlated with RB-deficiency, did not further promote migration of RB depleted MDA-MB-231 cells.

My results suggest that RB1 deficiency promotes metastasis by increasing cell motility in part through enhanced MPT. Downstream vulnerabilities such as increased PD-L1 expression and CDC25 sensitivity are also possible therapeutic targets. In conclusion the results of my study helped decipher the role of RB1 loss in regulating cancer metabolic reprogramming that promotes recurrent disease, exposing pathways downstream of RB1 loss as potential therapeutic targets.

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Appendix

Figure A1. Aphidicolin does not affect the ability of the cells to migrate. (A) JIMT1 and (B) HCC1954 were plated in 12 well plates and pretreated with media either without aphidicolin, 500nM aphidicolin or 1µM aphidicolin, then scratch migration assay was performed. Three separate experiments were used to calculate mean of areas measured using ImageJ. Statistics calculated in GraphPad prism using students unpaired t-test.

Figure A2. RBKO p130KD MCF7(kshp130) are more sensitive to tigecycline than RBKO MCF7(kSCRAM) cells. IC40(uM) shown on graph. Sensitivity assessed using MTT assay and significance calculated in Graph Pad prism using unpaired t-test (n=3). Data provided by Mariusz Shrestha, PhD. candidate in the Zacksenhaus Lab.