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5-2018

SPHINGOSINE 1 REGULATES FASCIN EXPRESSION TO PROMOTE METASTASIS IN TRIPLE NEGATIVE BREAST CANCER

Sunil Acharya

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METASTASIS IN TRIPLE NEGATIVE BREAST CANCER

by

Sunil Acharya, M.S.

APPROVED:

______Dihua Yu, M.D., Ph.D. Advisory Professor

______Anil K. Sood, M.D.

______Boyi Gan, Ph.D.

______Dos D. Sarbassov, Ph.D.

______Swathi Arur, Ph.D.

______

APPROVED:

______Dean, The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences

SPHINGOSINE KINASE 1 REGULATES FASCIN EXPRESSION TO PROMOTE

METASTASIS IN TRIPLE NEGATIVE BREAST CANCER

A

DISSERTATION

Presented to the Faculty of

The University of Texas

MD Anderson Cancer Center UTHealth

Graduate School of Biomedical Sciences

in Partial Fulfillment

of the Requirements

for the Degree of

DOCTOR OF PHILOSOPHY

by

Sunil Acharya, M.S.

Houston, Texas

May, 2018

Dedication

This dissertation is dedicated to my parents Mathura Acharya and Dilleshwor Acharya, my wife Deepa Bhattarai, and my loving daughter Sanvi Acharya.

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Acknowledgments

First and foremost, I would like to thank Dr. Dihua Yu, for accepting me into her scientific family and allowing me to perform my dissertation research under her mentorship. I am thankful for her continuous guidance and support over the years for my scientific development. There was not a single day where I was not inspired by her passion towards science and amount of effort she puts into mentoring her trainees.

I would like to thank my present and previous committee members, Dr. Swathi Arur, Dr.

Anil K. Sood, Dr. Boyi Gan, Dr. Dos D. Sarbassov, Dr. Jessica Tyler and Dr. Xin Lin for their valuable suggestions and guidance in order keep my research project on track and improve the quality of my dissertation. I would also like to thank my collaborators, Dr. Jun Yao for helping me with bioinformatics analysis, Dr. Hua Guo for immunohistochemical slides analysis, Dr.

Helen Piwnica-Worms for providing patient derived xenograft model, Dr. Jean J. Zhao for providing SPHK1 overexpression plasmid and MDACC Breast Tumor Bank for providing tissue microarray slides.

Next, I would like to thank all the past and present members of Yu Lab, for being my second family. I am thankful for their scientific inputs and technical guidance and I really enjoyed working will all of them. Specifically, I would like to thank previous and current graduate students of Yu lab, Dr. Jia Xu, Dr. Frank J. Lowery, Dr. Tina Chang, Dr. Sumaiyah K.

Rehman, Dr. Brain Pickering, Dr. Lin Zhang, Yingda Jiang and Dr. Samuel Brady. Special thanks to Drs. Jia Xu and Frank J. Lowery, for taking me under their wings when I just joined theYu lab and teaching me everything. Also, my sincere gratitude goes towards Dr. Patrick

Zhang for not only teaching and sharing his ideas about science, but also just about anything in life. I also want to take this opportunity to thank Mrs. Ping Li and Mrs. Irene Shih for their unconditional help and support.

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I would like to thank my graduate school classmates and friends, Houston friends, Blue

Gurkha teammates, Dead Runners teammates and UTHealth StudentIntercouncil colleagues for making my graduate school life wonderful and enjoyable. Although, I didn’t mention any names here, you know who you are and I will always cherish the fun moments we shared together. I would also like to thank GSBS, GSBS staffs, Cancer Biology Program and Department of

Molecular and Cellular Oncology at MDACC for their support.

Finally, I would like to thank all of my family members, who are currently residing in the USA, Nepal, India, Australia and Germany. Without their help and support this journey would not have been possible.

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Abstract

SPHINGOSINE KINASE 1 REGULATES FASCIN EXPRESSION TO PROMOTE

METASTASIS IN TRIPLE NEGATIVE BREAST CANCER

Sunil Acharya, M.S.

Advisory Professor: Dihua Yu, M.D., Ph.D.

Distant metastasis is the primary cause of breast cancer–related mortality. To date, effective therapeutic drugs that target metastasis are still lacking. Triple negative breast cancer (TNBC) occurs in high frequency in young women and are more likely to recur and metastasize than are other breast cancer subtypes. Also, TNBC patients cannot benefit from currently available hormonal or targeted therapies, as they lack estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2. Thus, understanding the signaling pathways that promote TNBC metastasis and developing novel therapeutic approaches to target them are critical, in order to prolong the survival and improve the quality of life for these patients.

Aiming for fast clinical-translation, I performed bioinformatic analysis of patient- derived TCGA dataset to identify targets whose expressions are elevated in TNBC and which also have FDA-approved or in-pipeline pharmaceutical agents for repurposed intervention. Here, I found that sphingosine kinase 1 (SPHK1) was expressed at higher levels in TNBCs patients samples than in other breast cancer subtypes and high SPHK1 expression is associated with poor survival in TNBC patients. Also, TNBC cell lines have relatively higher expression of SPHK1 at both and mRNA levels compared to cell lines of other subtypes

vi of breast cancer. Overexpression of SPHK1 in MDA-MB-231 cells, increased the metastatic related properties in vitro and spontaneous metastasis in vivo. Genetic knockdown of SPHK1 in TNBC cell lines decreased invasion and migration potential in vitro and significantly reduced spontaneous lung metastasis in vivo, indicating that SPHK1 may promotes spontaneous metastasis. Further, SPHK1 expression is positively correlated with FSCN1 expression in TNBC tissue specimens and overexpression of FSCN1 in the SPHK1 knockdown background restores spontaneous metastasis in mice. Molecularly, SPHK1 upregulates FSCN1 expression at the transcriptional level via NFκB transcription factor in order to promote metastasis in a FSCN1-dependent manner. In an orthotopic syngeneic mouse model, pharmaceutical inhibition of SPHK1 and/or NFκB was sufficient to reduce spontaneous metastasis to the lungs. Overall, our study identifies the SPHK1/NFκB/FSCN1 axis as an important regulator of TNBC metastasis and provides an opportunity for fast repositioning of available therapeutics for treatment of TNBC metastasis.

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Table of Contents

Approval Sheet…………………………..………………………………………………………..i

Title Page…………………………………………………………………………………………ii

Dedication ...... iii

Acknowledgments...... iv

Abstract ...... vi

Table of Contents ...... viii

List of Illustrations ...... xi

List of Tables ...... xiii

Abbreviations ...... xiv

Chapter 1: Introduction ...... 1

1.1 Breast cancer ...... 1

1.1.1 Epidemiology of breast cancer ...... 3

1.1.2 Molecular subtypes of breast cancer ...... 4

1.1.3 Breast cancer treatments ...... 9

1.1.4 Breast cancer metastasis ...... 15

1.2 and its classification...... 21

1.2.1 signaling pathway ...... 22

1.2.2 Sphingosine Kinase ...... 24

1.2.3 SPHK1/S1P axis and its role in cancer ...... 28

1.3 Fascin and its role in cancer ...... 34

1.4 Hypothesis, specific aims, and significance ...... 39

Chapter 2: Materials and methods ...... 42

2.1 Cell culture ...... 42

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2.2 Antibodies and reagents ...... 42

2.3 Generation of stable cell lines ...... 43

2.4 Western blotting ...... 43

2.5 RNA extraction, – chain reaction (RT-PCR), and

quantitative real-time PCR (qPCR) ...... 44

2.6 Cell proliferation assay...... 45

2.7 Migration assay and invasion assay ...... 45

2.8 Animal experiments ...... 46

2.9 cDNA microarray and analysis ...... 47

2.10 Plasmids construction ...... 48

2.11 Site-directed mutagenesis ...... 48

2.12 Transient transfection and luciferase reporter assay ...... 49

2.13 ChIP assay ...... 49

2.14 SPHK1 kinase activity ...... 49

2.15 Three-dimensional (3D) cell culture ...... 50

2.16 Quantification of 3D invasiveness ...... 50

2.17 mRNA stability assay ...... 50

2.18 Immunohistochemical analysis ...... 51

2.19 Case selection, tissue microarray (TMA) construction and analysis ...... 51

2.20 Bioinformatics, statistics, and survival analysis ...... 53

Chapter 3: Expression of SPHK1 in TNBC tumors and cell lines ...... 54

3.1 SPHK1 is overexpressed in TNBC tumors ...... 54

3.2 SPHK1 is overexpressed in TNBC cell lines ...... 54

Chapter 4: Role of SPHK1 in TNBC progression and metastasis ...... 57

4.1 SPHK1 overexpression increases metastatic related properties in vitro ...... 57 ix

4.2 SPHK1 overexpression promotes spontaneous metastasis to lungs in mice ...... 57

4.3 SPHK1 knockdown decreased metastatic related properties in vitro ...... 60

4.4 SPHK1 knockdown decreased spontaneous metastatic spread to the lungs in mice ...... 60

Chapter 5: Molecular mechanism of SPHK1-mediated TNBC metastasis ...... 66

5.1 Identification and validation of the FSCN1 as a SPHK1 regulated gene ...... 66

5.2 Correlation between SPHK1 and FSCN1 in breast cancer patients’

samples ...... 66

5.3 SPHK1 metastasis function is mediated by FSCN1...... 69

5.4 SPHK1 regulates FSCN1 expression in 3D culture but not in 2D culture ...... 69

5.5 SPHK1 regulates FSCN1 by increasing the transcriptional rate via NFκB transcription

factor...... 75

Chapter 6: Potential of SPHK1 as therapeutic target of breast cancer metastasis ...... 80

6.1 Combined expression of SPHK1, pNFκB and FSCN1 in TNBC patients correlates with

poor survival ...... 80

6.2 Targeting SPHK1 and the NFκB signaling pathway decreased tumor progression and

spontaneous metastasis to the lungs ...... 83

Chapter 7: Discussion and future directions ...... 88

Chapter 8: References ...... 97

Vita ...... 139

x

List of Illustrations

Figure 1: Cartoon showing the normal and abnormal mammary ducts and lobules...... 2

Figure 2: Four major molecular subtypes of breast cancer and its characteristics...... 6

Figure 3: Sphingolipids metabolism pathway showing the interconnection between various bioactive sphingolipids...... 23

Figure 4: Schematics showing the various roles of Sphingosine-1-phosphate...... 25

Figure 5: Schematic diagram of two isoenzymes of sphingosine kinase i.e. SPHK1 and SPHK2.

...... 26

Figure 6: Protein sequence of human SPHK1 showing various putative posttranslational modification sites...... 28

Figure 7: Schematic diagram (top) and ribbon structure (bottom) of human fascin-1...... 35

Figure 8: SPHK1 is overexpressed in TNBC tumors...... 55

Figure 9: SPHK1 is overexpressed in TNBC cell lines...... 56

Figure 10: SPHK1 overexpression increases metastatic related properties in vitro...... 58

Figure 11: SPHK1 overexpression promotes spontaneous metastasis to lungs in mice...... 59

Figure 12: SPHK1 knockdown decreased metastatic related properties in vitro...... 61

Figure 13: SPHK1 knockdown decreased spontaneous metastatic spread to the lungs in mice. 63

Figure 14: IHC staining of xenograft primary tumor formed in nude mice...... 64

Figure 15: Identification and validation of the FSCN1 as a SPHK1 regulated gene...... 67

Figure 16: Correlation between SPHK1 and FSCN1 gene expression in breast cancer patients’ samples...... 68

Figure 17: Ectopic expression of FSCN1 in SPHK1 knockdown cells...... 70

Figure 18: SPHK1 metastasis function is mediated by FSCN1...... 71

Figure 19: SPHK1 regulates FSCN1 expression in 3D culture but not in 2D culture...... 73

xi

Figure 20: SPHK1 regulation of FSCN1 requires extracellular matrix, and control 3D invasiveness...... 74

Figure 21: SPHK1 plays role in increasing the transcriptional rate of FSCN1 gene transcription but not the mRNA stability...... 76

Figure 22: SPHK1 upregulates FSCN1 gene expression at transcriptional level through NFκB transcription factor...... 78

Figure 23: Combined Expression of SPHK1, pNFκB and FSCN1 in TNBC patients correlates with poor survival...... 82

Figure 24: Targeting SPHK1 and the NFκB signaling pathway decreased tumor progression and spontaneous metastasis to the lungs...... 874

Figure 25: Immunohistochemistry staining of various markers in primary tumor samples excised from mice under time-matched experiment, as mentioned in 24(D)……………………………87

Figure 26: Graphical abstract...... 89

xii

List of Tables

Table 1: Estimated new female breast cancer cases and deaths in US by age in 2017...... 3

Table 2: The most frequently mutated in each molecular subtypes of breast cancer...... 7

Table 3: List of inhibitors developed against sphingosine kinase...... 33

Table 4: Primers used for qRTPCR...... 45

Table 5: Clinical and pathological features of triple negative patient cohort used for TMA...... 81

xiii

Abbreviations

µl: Microliter µm: Micrometer 2D: two dimensional 3D: three dimensional aa: Amino acid AIs: Aromatase inhibitors AKT: B ATP: Adenosine tri-phosphate BCS: Breast-conserving surgery BOR: Bortezomib bp: Ca2+: Calcium cation CDK: Cyclin dependent kinases cDNA: Complementary deoxyribonucleic acid ChIP: Chromatin immunoprecipitation cm: Centimeter CNS: Central nervous system CRC: Colorectal cancer CTCs: Circulating tumor cells Cu2+: Cupric cation CXCR4: C-X-C motif chemokine receptor 4 DAG: Diacylglycerol DCIS: Ductal carcinoma in situ DFS: Disease free survival DMEM: Dulbecco modified eagle medium DMFS: Distance metastasis free survival ECM: Extracellular matrix EDTA: Ethylenediaminetetraacetic acid xiv

EFG: Epithelial growth factor EGFR: Epidermal growth factor receptor EMT: Epithelial to mesenchymal transition ER: Endoplasmic reticulum ER: Estrogen receptor ERK1, ERK2: Extracellular signal–regulated kinases1, Extracellular signal–regulated kinases2 FBS: Fetal bovine serum FDA: Food and drug administration Fe2+: Ferrous FFPE: Formalin-fixed and paraffin-embedded FSCN1, FSCN2, FSCN3: Fascin 1, Fascin 2, Fascin 3 GBM: Glioblastoma multiforme GEO: Gene expression omnibus GPCRs: G-protein coupled receptors GSEA: Gene set enrichment analysis HDAC: Histone deacetylases HER2: Human epidermal growth factor receptor 2 HNSCC: Head and neck squamous cell cancer HR: Hormone receptor i.p.: Intraperitoneally IGF-I: Insulin-like growth factor I IgG: Immunoglobulin G IHC: Immunohistochemistry IPA: Ingenuity pathway analysis KCl: Potassium chloride kDa: Kilo dalton LCIS: Lobular carcinoma in situ LPS: Lipopolysaccharide MAPKs: Mitogen-activated protein kinases

xv

MFP: Mammary fat pad mg/kg: Milligram per kilogram Mg2+: Magnesium cation ml: Milliliter mM: Millimolar MMP: Matrix metalloproteinase Mn2+: Manganese cation mRNA: Messenger ribonucleic acid MS: Multiple sclerosis mTOR: Mechanistic target of rapamycin MTT: 3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide NaCl: Sodium chloride NFκB: Nuclear factor kappa-light-chain-enhancer of activated B cells NGF: Nerve growth factor NGS: Next generation sequencing nm: Nanometer NSCLC: Non-small cell lung cancer ORF: Open reading frame OS: Overall survival PAI: Plasminogen activator inhibitor PanIN: Pancreatic intraepithelial neoplasia PARP: Poly (adenosine diphosphate ribose) polymerase PD1: Programmed cell death-1 PDGF: Platelets derived growth factor PDL1: Programmed death- 1 PDX: Patient derived xenograft PI3K: Phosphatidylinositol 3-kinase PKC: Protein kinase C PMA: para-Methoxyamphetamine

xvi pNFκB: phospho-Nuclear factor kappa-light-chain-enhancer of activated B cells PR: Progesterone receptor qRTPCR: Quantitative real-time polymerase chain reaction RNA: Ribonucleic acid S1P: Sphingosine-1-phosphate S1PR: Spingosine-1-phosphate receptor SAF: SAM: sequence analysis of microarray SERM: Selective estrogen receptor modulator Sp1: Specificity protein 1 SPHK1, SPHK2: Sphingosine kinase 1, Sphingosine kinase 2 TCGA: The cancer genome atlas TDM-1: Ado-trastuzumab emtansine TILs: Tumor infiltrating lymphocytes TMA: Tissue microarray TN: Triple negative TNBC: Triple negative breast cancer TNFα: Tumor factor alpha TRAF-2: Tumor necrosis factor receptor-associated factor 2 TSP-1: Thrombospondin-1 TUNEL: Terminal deoxynucleotidyl dUTP nick end labeling U.S.: United States uPA: Urokinase-type plasminogen activator VEGF: Vascular endothelial growth factor VSMC: Vascular smooth muscle cells Zn2+: Zinc cation μCi: Microcurie

xvii

Chapter 1: Introduction

Human body consists of trillions of cells, which in normal condition grow and divide to form news cells as required by the body. When, these cells gets damaged which cannot be fixed or ages, these cells undergo natural programmed cell death mechanism, and are replaced by a new cells. But, when cells don’t follow this orderly process and begin to divide without stopping, even if they are damaged or old, than these cells give rise to excessive growth, often resulting in cancer [1]. Cancer can start in any cells within the body and in many cases they can spread into or invade surrounding tissue. Cancer is very complex and deadly disease, because of which lots of effort has been made towards finding a cure for it, mainly by understanding the molecular mechanism by which cancer progress and spread. So far, more than 100 types of cancer has been identified, usually categorized by the organ or tissue where they arise from [1].

This dissertation is mainly focused on breast cancer.

1.1 Breast Cancer

Breast cancer is cancer which arises mainly from the cells of the lobules (milk producing glands) or the mammary ducts (the passage which connects lobules to the nipple) (Figure 1) [2].

Mostly, breast cancer is caused by the genetic abnormalities in cells, which is either inherited

(5-10%) or acquired (85-90%) [3]. At early stages, the cancer cells will replace the normal cells either in ducts or in lobules and grow in situ, and called ductal carcinoma in situ (DCIS) or lobular carcinoma in situ (LCIS) (Figure 1). Only 20% of the breast cancer patients are diagnosed with in situ cancer, of which about 83% are DCIS and 10-13% are LCIS. Remaining

80% of patients are mostly diagnosed with invasive breast cancer, which is considered as later stages of breast cancer (Table 1) [2]. Although, DCIS may progress and become invasive tumor,

LCIS seldom progress to invasive cancer. However, both DCIS and LCIS patients are almost

1

Figure 1: Cartoon showing the normal and abnormal mammary ducts and lobules.

(Top) Abnormal cells grow inside the lining of normal mammary duct to give rise to ductal carcinoma in situ (DCIS). (Bottom) Uncontrolled growth of the cells of the lobule give rise to lobular carcinoma in situ (LCIS). Reprinted with permission from the National Cancer

Institute © (2012) Terese Winslow LLC, U.S. Govt. has certain rights.

2

Table 1: Estimated New Female Breast Cancer Cases and deaths in US by age in 2017.

Reprinted with permission from American Cancer Society. Breast Cancer Facts & Figures 2017-

2018. Atlanta: American cancer Society, Inc.2017 [2]. ten times more likely to develop new invasive breast cancer compared to patients without in situ cancer [4, 5]. Invasive cancers cells usually invade into nearby tissue or spread to lymph node and other organs of the body.

1.1.1 Epidemiology of Breast Cancer

Breast cancer accounts for almost 25% of newly diagnosed cancers in women globally

[6]. In U.S. women, breast cancer is the second most commonly diagnosed cancer. In 2017, about 30% of newly diagnosed cancers in U.S. women were estimated to be breast cancer [2]. In

2018, it is estimated that approximately 63, 960 cases of in situ breast cancer and approximately

266,120 cases of invasive breast cancer will be diagnosed in U.S. women. It is also estimated that, in 2018 about 40,920 women will die from breast cancer in U.S, which is the second leading cause of cancer-related death in U.S. women behind lung cancer [2]. Compared to women, whose lifetime risk of developing breast cancer is about 1 in 8, lifetime risk of

3 developing breast cancer for men is very low which is about 1 in 1000. In 2018, about 2,550 new cases of invasive breast cancer are expected to be diagnosed in U.S. men with 480 expected fatalities [7]. The mortality trend of breast cancer patients have shown remarkable improvement in past three decade with decrease in death rate by 40% [2]. This is mainly due to early detection of breast cancer, because of awareness of screening and better screening techniques, and development of various effective treatment options [2].

Gender is the most significant risk factor for developing breast cancer, as mentioned earlier women are far more likely to have breast cancer compared to men. The next most significant risk factor is age, as the incident and mortality rate of breast cancer increases with age (Table 1) [2]. During 2010-2014, the median age at which breast cancer was diagnosed for

U.S. women was 62 years [8]. Race and ethnicity of women is also considered a risk factor for breast cancer incidence and mortality. Non-Hispanic white women have the highest rate of breast cancer incidence and mortality followed by African American women, Hispanic women and Asian women respectively [2]. Other risk factor include obesity, family history, physically inactivity, early menstrual period, late or no pregnancy, postmenopausal hormone use and alcohol consumption [9-18].

1.1.2 Molecular subtypes of breast cancer

Breast cancer, like many other cancers, is highly heterogeneous with diverse natural history and responsiveness to treatment. Therefore, many efforts have been undergoing on how to classify breast cancer into various subtypes, so that it can be helpful for planning treatments and developing new therapies. Breast cancer has been divided into various subtypes based on histology, molecular status (hormone receptor status) and gene expression profiling. There are almost 21 different histological subtypes which have some prognostic value, but lack a molecular basis because of which these have less potential for prognostic prediction and

4 therapeutic response [19, 20]. Although, gene expression profiling is recently getting attention and have potential for the better understanding of the breast cancer, it is complicated and expensive and is not a standard practice yet [21]. Currently, for the clinical point of view breast cancers are divided into four major intrinsic molecular subtypes based on the presence of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor

2 (HER2). The four molecular subtypes are: Luminal A, Luminal B, HER2 type and triple negative (TN) (Figure 2) [22-25].

1.1.2.1 Luminal A

About 30-70% of breast cancer patients are classified as luminal A subtype [2]. The cancer cells with this subtypes mainly arise from the inner cell lining of the mammary ducts and are ER and PR positive but lack HER2. The patients with this subtype have most favorable prognosis as these cancers tend to be slow growing (low ki67 staining, < 14%) and are less aggressive [26]. These tumors are also very responsive to hormonal therapy, because of which these patients have high survival and low recurrence rates [27, 28]. The genes which are commonly mutated in this subtypes are PIK3CA (45%), MAP3K1 (13%), GATA3 (13%) and

TP53 (12%). The most comprehensive list of mutated genes are shown in Table 2 [21, 26].

1.1.2.2 Luminal B

About 10-20% of breast cancer patients are classified as luminal B subtype [2]. The cancer cells with this subtypes mainly arise from the inner cell lining the mammary ducts and are ER and PR positive, similar to liminal A. Luminal B tumors may or may not be HER2 positive. However, HER2 negative tumors tends to be highly proliferative with high ki67 staining (≥14 %) [26]. Unlike luminal A, patients with luminal B are often diagnosed at a younger age and have poor prognosis (large tumor size with poor tumor grade and often lymph node

5

Figure 2: Four major molecular subtypes of breast cancer and its characteristics. Reprinted with the permission form: Wong E, Rebelo J and Chaudhry S (2012): Breast Cancer, McMaster

Pathophysiology Review. (http://www.pathophys.org/breast-cancer/).

positive). Compared to other subtypes, patients with this subtype have higher survival rate but not as high as those of luminal A [28]. The genes which are most commonly mutated in this subtypes are PIK3CA (29%), TP53 (29%), GATA3 (13%) and TTN (12%) (Table 2) [21, 29].

1.1.2.3 Her2 type

Most of the HER2 type tumors are HER2 positive but ER and PR negative, with HER2 protein overexpression mainly due to the HER2 DNA amplification. Almost 5-15% of breast cancer patients are classified as HER2 type and tumors tend to grow faster and are diagnosed at younger age than those with Lumina A and B subtypes [30]. Although, patients with HER2 type

6 have worse prognosis, the overall outcome of these patients have been significantly improved because of the recent development of targeted therapies against HER2 positive breast cancer

[28, 31]. The genes which are most commonly mutated in this subtypes are TP53 (72%),

PIK3CA (39%) and MUC16 (14%) (Table 2) [21]. This tumor subtype also has significantly higher expression of receptor tyrosine kinases, like FGFR4 and EGFR [26].

Table 2: The most frequently mutated genes in each molecular subtypes of breast cancer.

Luminal A Luminal B HER2-enriched Basal-like

PIK3CA 45% PIK3CA 29% TP53 72% TP53 80%

MAP3K1 13% TP53 29% PIK3CA 39% TTN 19%

GATA3 13% GATA3 13% MUC16 14% USH2A 11%

TP53 12% TTN 12% LRP1 8% FLG 7%

CDH1 9% RYR2 7% ERBB3 8% MUC16 7%

TTN 9% RELN 5% DNAH11 8% PIK3CA 7%

MLL3 7% FAT3 5% LRP2 8% MUC17 6%

MAP2K4 6% MLL3 5% TTN 8% DNAH7 5%

NCOR1 5% MUC16 5% ATP1A4 7% FAT3 5%

AKT1 4% KCNB2 4% KIAA1109 7% SYNE1 5%

PTEN 4% MAP3K1 4% CACNA1E 7% DST 5%

Reprinted with the permission form: Toss A and Cristofanilli M (2015): Molecular characterization and targeted therapeutic approaches in breast cancer, Breast Cancer Res,

17(1):60

7

1.1.2.4 Triple negative

Approximately 15-20% of breast cancers are triple-negative, i.e., they lack ER, PR, and

HER2 [25]. Triple-negative breast cancer (TNBC) tends to occur at high frequency in young women (under 40 years of age) and is particularly aggressive, with a high recurrence rate [32].

Compared to other subtypes, TNBC patients have poor overall prognosis (the 5-year survival rate for patients with stage IV TNBC is about 22%), mainly due to early-onset of metastasis

[32]. TNBC is diagnosed more frequently in African-American women followed by Hispanic and White women [2, 33, 34]. Since TNBC tumors lack hormone receptors, patients cannot benefit from currently available targeted therapies, so identifying the targetable alteration in

TNBC is one of the promising research area [35]. Most TNBC tumors are basal like, as these tumors have cells that look similar to those of the outer basal cells surrounding the mammary duct. The TP53 is the most frequent (80%) aberration in TNBC followed by the mutations in

TTN (19%) and USH2A (11%) (Table 2) [21, 26].

More recently with the help of microarray based gene expression analysis, a new subtype of breast cancer has been identified and classified as “claudin-low” [36]. This subtype is characterized as ER/PR/HER2 negative and have a high expression of genes involved in epithelial to mesenchymal transition (EMT), immune cell infiltration and exhibit a cancer stem cell like properties [37]. Patients with this subtype have better overall survival as well as disease free survival compared to TN subtype.

At present, this molecular classification of breast cancer has tremendously benefited patients as it was very helpful in predicting a response to targeted therapies [26, 38]. This molecular subtyping can be further supplemented with molecular profiling, with the recent advancement of next generation sequencing (NGS), into a more comprehensive classification that can be useful to clinicians in predicting the most effective treatment for the benefit of the patients. 8

1.1.3 Breast Cancer Treatments

There are various treatment options available for breast cancer patients today. Physicians together with patients decide on which treatment to use based on the stage of the disease, molecular subtype of the disease and patients status. Surgery, is the most commonly used treatment option as almost all patients undergo this process, provided tumors are amenable to surgical resection. Two types of surgical procedure that are currently in use are breast- conserving surgery (BCS) and mastectomy. BCS, also known as partial mastectomy or lumpectomy is a procedure where only the cancerous tissue and small portion of normal tissue surrounding the cancerous tissue are removed surgically. Patients undergoing this type of surgery also receive radiation therapy to breast afterwards [39]. Mastectomy is the procedure where entire breast is removed. It has been reported that, patients undergoing mastectomy usually choose to do bilateral mastectomy, i.e. to remove both breasts, even if only one breast in diagnosed with cancer [40]. Recently, more patients undergoing mastectomy are preferring to have breast reconstruction surgery afterwards [41]. Usually, some regional lymph nodes are also removed during both BCS and mastectomy surgical procedure to help determine the stage of the breast cancer. Depending on the stage and subtype of breast cancer, surgery is mostly accompanied by radiation therapy or systemic therapy (, hormonal therapy or targeted therapy).

Radiation therapy is also commonly used option to treat breast cancer patients, usually to kill residual cells after surgery. This therapy is given three to four weeks after surgery for the breast cancer patients based on their clinical and pathological conditions, whereas patients undergone BCS almost always receive this therapy [39]. Radiation therapy involves the use of high-energy beams (like X-rays, gamma rays) or charged particles to kill cancer cells. Radiation therapy kills cancer cells either by directly damaging DNA or by creating charged particles inside the cell which can than damage the DNA. There are two main ways by which radiation 9 therapy is administered to patients, which are external beam radiation and internal radiation.

Based on stage, type, location of tumor and patients characteristics, patients can either receive one type of treatment or sometimes combination of both. External beam radiation is most traditional and commonly used, where photon beams are generated by machines, which is outside the body, and these beams are highly focused on the area affected by cancer. This kind of treatment needs multiple appointments, as they are usually given in outpatient radiation clinics for 5 days a week for five to seven weeks. Recently, few studies shows that for some patients even 3 weeks treatment was effective [42, 43]. Internal radiation therapy, also called brachytherapy, has been developed more recently where radiation sources are placed in catheters or other devices and are implanted on or inside the body where the cancer grew [44].

This method is shown to be as effective as external beam radiation and have much less delivery time and fewer side effects, because of which more patients are opting towards this therapy even though long-term efficacy of this therapy has not been established [45, 46].

The most commonly used systemic therapy is chemotherapy, where cytotoxic chemical agents are used in order to kill cancer cells. Chemotherapy, usually works by targeting and inhibiting mitosis of rapidly dividing cells, which means, it’s not specific against cancer cells and may target normal cells that divide rapidly. Even with this drawback, it is one of the widely used therapeutic option in cancer treatment, usually in combination with other treatment options like surgery. Chemotherapy given after surgery is usually called adjuvant chemotherapy and is used to kill any residual cancer cells after surgery or to lower the risk of recurrence at same site or at different organ [47]. In some cases, chemotherapy is also given before the surgery, which is called neoadjuvant chemotherapy, and is given to shrink the tumor to facilitate the process of surgical resection [47]. Chemotherapy is given either intravenously (injected into veins) or orally. Doxorubicin, paclitaxel, docetaxel, 5-fluorouracil, cyclophosphamide and carboplatin are

10 commonly used chemotherapy drugs in adjuvant and neoadjuvant setting in order to treat early or locally advanced breast cancer. These drugs are usually used in combination of two or three.

More often in advanced or metastatic breast cancer single drug is used for treatment. There are reports that patients with HER2 type and TNBC tumors are more sensitive to chemotherapy treatment compared to patients with luminal A or B subtype [48, 49]. In some cases, it is hard for clinicians to decide if chemotherapy is beneficial for patients or not after surgery. In order to help clinicians and patients to determine if chemotherapy is good option for them after surgery, there are various gene expression testing kits available (like Mammoprint, Oncotype DX and

PAM50), to predict those who could benefit from chemotherapy or those who should avoid it

[50, 51]. Currently, many clinical trials are undergoing to evaluate the predictive value of such tests, so in future they can be used as a standard test.

Hormone therapy is a form of systemic therapy which is only given to patients with hormone receptor (HR) positive (ER positive and/or PR positive) breast cancer. Estrogen and

Progesterone, are produced by ovaries in women and by fat and skin in both women and men.

They bind to ER and PR respectively in breast cancer cells and promote the growth of the cancer cells and spread to other organ. Hormone therapy in this setting will either stop or slow tumor growth by blocking the production of hormones or by interfering with the binding of hormone to breast cancer cells. There are various types of hormonal therapy available for HR positive breast cancer patients, and one of a criteria to choose between them is the menopausal status as hormone therapy can be different between premenopausal and postmenopausal women

[2]. Tamoxifen, most commonly used hormone therapy, works by blocking the estrogen receptors only on breast cancer cells but have estrogenic effects in other tissues like uterus, liver and bones, thus called selective estrogen receptor modulator (SERM). Tamoxifen is FDA approved to treat as an adjuvant therapy for premenopausal women, postmenopausal women

11 and men with early stage ER positive breast cancer [52-54]. Reports have shown that, treating early stage HR positive patients with tamoxifen as adjuvant therapy for 5 years has reduced the recurrence rate by approximately 40-50% throughout the first 10 years, and reduced mortality by approximately 30% in first 15 years [55]. More recently, tamoxifen therapy has been recommended to use for 10 years, instead of 5 years as extended use of tamoxifen has been shown to further reduce the risk of cancer recurrence and mortality [56]. There are some clinical trials using the combination of tamoxifen with ovarian suppression drugs (luteinizing hormone- releasing hormone analogs, to suppress estrogen production) in premenopausal women with advanced HR positive breast cancer patients that show improved survival [57]. Not only as a treatment drug, tamoxifen has also been approved by FDA as a prevention drug for both premenopausal and postmenopausal women as it has been shown to reduce the risk of developing breast cancer in women with high risk of the disease [58, 59]. Fulvestrant, unlike tamoxifen is a selective estrogen receptor degrader that blocks and damage estrogen receptors throughout the body [60]. It is FDA approved to treat HR positive advanced or metastatic breast cancer patients [61]. Aromatase inhibitors (AIs), are a class of drugs which work by lowering or blocking the production of estrogen, and includes drugs like letrozole, anastrozole and exemestane [60]. AIs are usually not effective to block estrogen produced by ovaries, and can only blocks the production of estrogen by fat tissue which use aromatase to produce estrogen. Because of this reason, AI therapy is mostly given to postmenopausal women, and used in combination with drugs that can suppress ovarian function in premenopausal women. AI is also commonly used as an adjuvant therapy. Postmenopausal women have been shown to have benefite by including AIs somewhere along their treatment plan with tamoxifen, rather than just using tamoxifen alone for 5 years [62]. Current treatment guidelines for HR positive postmenopausal women usually include AIs, as an alternate with tamoxifen for a total of at least

5 years, or to take in sequence with tamoxifen for at least 3 years [60, 63]. 12

As more and more research is revealing more genes, or molecular pathways that are involved in cancer progression and spread, new drugs are designed to attack specifically those molecules and are defined under the term targeted therapy. It is called targeted therapy because, unlike chemotherapy which attack all fast growing cells, it only targets certain changes which is supposed to be present only in cancer cells. For example, about 20% of all breast cancer patients have cancer cells that have high amount of HER2 protein on their surface [2].

So, these patients are treated with HER2 targeting drug, Herceptin (Trastuzumab) which is specially made monoclonal antibody that targets HER2 positive cancer cells [64]. This drug is

FDA approved and studies have shown that when HER2 positive early stage breast cancer patients are treated with Trastuzumab in combination with chemotherapy, it decrease the risk of cancer recurrence by 50% and morality by 33%, compared to chemotherapy alone [31, 65, 66].

Trastuzumab is given intravenously every three weeks for 1 year and also given to advanced patients with local or distant metastasis. Lapatinib, also a FDA approved drug which is a dual inhibitor for both epidermal growth factor receptor (EGFR) and HER2 receptor tyrosine kinases, is also used to treat advanced HER2 positive breast cancer patients mainly in a combination with other drugs [67]. Other HER2 targeting agents that are currently in use are

Pertuzumab, and Ado-trastuzumab emtansine (TDM-1) [68]. Class of drugs, like palbociclib, ribociclib, and abemaciclib, which inhibits the activity of cyclin dependent kinases (CDK), especially CDK4 and CDK6, which plays role in cell division are also used as a targeted therapy

[68]. Palbociclib and ribociclib are used in combination with certain hormone therapy drugs to treat HR positive/HER2 negative advanced breast cancer patients who are postmenopausal.

These drugs are taken orally every day for three weeks [68]. Abemaciclib is also used in combination with fulvestrant, for postmenopausal patients with HR positive/HER2 negative advanced breast cancer, who are doing worse after hormone therapy [68]. TNBC, being an aggressive type of subtype which lacks HR and HER2 overexpression, have no clinically 13 approved targeted therapy yet. Currently, lots of effort has been ongoing for the molecular characterization of TNBC, which provide some potential effective therapeutic targets and clinical trials are being conducted to test the efficacy. The most successful one so far is the poly

(ADP-ribose) polymerase (PARP) inhibitor, Olaparib, which is under phase 3 clinical trial to treat TNBC patients with BRCA1/2 mutation [69, 70]. PARP detects single strand DNA breaks

(induced by metabolites, chemicals or radiation) and initiates signaling of DNA damage repair process. The inhibition of PARP via PARP inhibitor prevents the repair of these single stranded

DNA breaks which will be accumulate and eventually turn into double stranded breaks of DNA.

When such double stranded DNA breaks are encountered by replication fork, it cannot be replicated and resulted in collapse of the fork. BRCA1/2 genes are involved in repairing DNA double strand breaks or destroy cells if they cannot repair these double strand breaks. So, if cells have either wildtype BRCA or heterozygous mutation in BRCA, they can repair the double strand break caused by PARP inhibitor. But, if cells are homozygous for the mutated BRCA1/2, they cannot repair DNA double strand breaks and are susceptible to the synthetic lethality of

PARP inhibitors [71]. Over 75% of breast cancer with BRCA1/2 mutation belongs to TNBC, suggesting PARP inhibitor might benefit these patients [71]. Other drugs which are currently under clinical trials to treat TNBC patients are; EGFR inhibitor, VEGF inhibitor, AKT inhibitor,

HDAC inhibitor, dual PI3K/mTOR inhibitor, AR antagonist, and anti PD1/PD-L1 antibodies

[72]. Studies have shown that TNBC tumors have higher EGFR expression compared to non-

TNBC tumors which led to a clinical trial of the EGFR inhibitor, cetuximab, in TNBC patients

[73]. Similarly, based on the observation that TNBC tumors express higher VEGF,

Bevacizumab (monoclonal antibody against VEGF) was tested in clinical trial in combination with docetaxel and shown to have delayed tumor progression in metastatic HER2 negative breast cancer patients [74]. Recently, studies have also shown that TNBC cancer cells have higher PD-L1 expression and tumors are usually infiltrated with PD-1 positive tumor infiltrating 14 lymphocytes (TILs), making this subtype more attractive for cancer immunotherapy [75].

Several clinical trials are studying the efficacy of immunotherapy in breast cancer patients, and their results are awaited.

1.1.4 Breast cancer Metastasis

Metastasis, defines the spread of cancer cells from their site of origin to distant organs in the body. For cancer cells to metastasize they have to undergo and complete various sequential steps, such as: separate from primary tumor, invade the surrounding tissue and basement membrane, intravasation into the bloodstream or lymphatic system, survive and travel through the blood vessel before arresting at the capillary bed of distant organ, extravasation from bloodstream into the microenvironment of distant organ, and finally survive, adapt and proliferate in the foreign microenvironment [76].

Metastasis of the breast cancer cells to the distant organ(s) and not the primary tumor itself is a primary cause of mortality in breast cancer patients. Although, metastatic and mortality incidence of breast cancer patients have significantly decreased in recent years (due to early screening and adjuvant therapies), breast cancer still remains a significant public health problem as metastasis so far is proved impossible to cure. However, with surgery and medication it is possible to have stable disease, where tumor does not grow, and sometimes even periods where test results shows no evidence of disease. The most common sites for breast cancer metastasis are bone, lungs, liver and brain. At the time of breast cancer diagnosis, about

5-8% of patients already have distant metastasis [77]. Studies have shown that, 10-15 % of breast cancer patients will develop metastasis within 3 years of their initial detection of primary tumor, however, there are enough cases where patients develop metastasis after more than 10 years of initial diagnosis [78]. The classical and longstanding model of metastasis states that, a rare subpopulation of cells in primary site acquired certain advantageous genetic alterations

15 during tumorigenesis and become metastatic cells [79]. This “genetic-selection” model which suggests that metastasis occurs at the late stage of tumorigenesis has been challenged by many other studies. It’s only recently, because of gene-expression profiling data, new model has been suggested where gene alterations or mutations can be acquired at much earlier stages of tumorigenesis than formerly accepted, suggesting the “parallel evolution” model [80-82]. This model has been observed clinically too, as women diagnosed with breast tumors less than 1 cm in diameter, and metastasis-negative who undergo a mastectomy, still have 2% chance of breast cancer-specific mortality at 5 years and a 5% chance at 10 years, suggesting dissemination may have already occurred by the time of diagnosis [83].

Like many cancers, breast cancer is highly heterogeneous in nature which makes it very difficult not only to cure but also to assess the risk factors for metastasis. Primary tumor size, presence or absence of lymph-node metastasis and histopathological grade of primary tumor are some long standing prognostic markers for risk of distant metastasis [84-86]. The metastasis risk is low for tumors under 2 cm in diameter, high for tumors within 2-5 cm and very high for tumors over 5 cm [87, 88]. However, there are 0.1-0.8 % breast cancer patients which are diagnosed with metastasis to lymph-nodes or other organ with no detectable primary tumor, known as occult breast cancer [89-91]. Similar to tumor size, tumor with low grade have low risk of metastasis whereas high grade tumors have high risk of metastasis. If the patients have no cancer cells detected in their lymph-nodes, they have low chance of having distance metastasis but the risk of distance metastasis increases if lymph-node metastasis is exhibited

[92, 93]. However, patients with small primary tumor (less than 2cm) with no lymph node metastasis at surgery, have 15%-25% chance of developing distant metastasis [94] and approximately one-third of patients with breast cancer with lymph-node metastasis have been metastasis free for 10 years after local therapy [86, 95]. Thus, improved understanding of

16 molecular mechanisms and factors leading to metastasis is critical in order to identify better predictive and prognostic markers for breast cancer recurrence and metastasis. Recently, lots of effort has been made in order to better identify the patients who might be at high risk of metastasis development.

Various studies have shown that molecular subtypes can be a very good predictive and prognostic marker of breast cancer recurrence and metastasis. Kast et al. showed that Luminal A subtype has lowest risk of recurrence, followed by luminal B, HER2 subtype and TNBC respectively [96]. Same study also showed that the distance metastasis was mostly found in

HER2 subtype which was followed by TNBC, whereas luminal A has the least case of metastasis [96]. Although, HER2 subtype had more metastatic cases, they had the best prognosis with highest survival rate since metastasis [97]. It is mainly due to the development of

Trastuzumab, which have been effective on HER2 type patients (with and without metastasis) in order to prolong the survival. Because of this, detecting the expression level of HER2 in newly diagnosed breast cancer patients’ specimen is a “standard of practice”, but adequate clinical validation is still needed to confirm the significance of HER2 as a prognostic marker. The worst survival after distance metastasis is seen in patients with TNBC subtype.

Not only a good predictive and prognostic marker of metastasis, but also some studies have shown that molecular subtypes can even predict the site of metastasis [98, 99]. It has been reported that luminal subtypes mainly metastasize to bone and less likely to lungs and brain, believed to be because of upregulation of ER target genes and down regulation of focal adhesion genes [99]. Both HER2 subtype and TNBC showed metastatic tendency towards brain and active Wnt/β-catenin pathways in TNBC plays important role in this process [100, 101]. Her2 subtype has also been shown to activate CXCR4, a chemokine receptor via HER2 activation and promote liver metastasis [102]. Lung metastasis is mostly shown by TNBC tumors [103].

17

Studies have also reported that, breast cancer cells themselves can secret some substances before metastasis which will then go to a specific organ to prime it and make a “pre-metastatic niche”, which supports the future metastatic event of cancer cells to that particular organ [104].

Study by Hiratsuka et al. demonstrated that signals from primary tumor can induce the expression of MMP9 in lung endothelial cells and macrophage, which will later promote the invasion of cancer cells into the lungs [105]. Massague group did multiple studies and performed gene expression analysis to show that metastasis of breast cancer cells to bone and lungs have different gene expression pattern suggesting metastasis exhibits tissue tropism [106,

107].

In the past decade, detecting circulating tumor cells (CTCs) in blood has shown lot of promise as a dynamic prognostic factor for metastatic breast cancer [108]. CTCs are tumor cells that extravasate from either primary tumor or metastasis and enter into the blood stream (CTCs are absent in healthy individuals) [109]. Although, detecting such disseminated cells was first started in bone marrow, this practice was soon overtaken by detecting CTCs in blood because bone marrow aspiration was painful for patients and was time consuming compared to blood withdrawn. Since the number of CTCs are very low in the blood (generally, <10 cells/ml even with metastatic cancer), they need to be enriched for detection. Enrichment of CTCs is either done by immunologic technique or by morphological technique [110]. The cells are isolated by using magnetic beads coated with antibodies with an affinity to epithelial cell surface marker that are specific to cancer cells (e.g. cytokeratin- 19, epithelial-cell adhesion molecule, cytokeratin 7/8 etc.), in immunologic technique. In morphological separation and enrichment, density gradient or filters with different pore sizes are chosen, as tumor cells are usually larger than leukocytes. Cristofanilli et al. first showed that detecting CTCs in metastatic breast cancer patients can be a useful predictor of progression-free survival and overall survival [111]. By

18 using a CellSearch® system, they found that patients with ≥ 5 CTCs/7.5 ml blood before and at first follow-up after treatment initiation have shorter progression free survival (PFS) and overall survival (OS), whereas patients with <5 CTCs/7.5 ml blood have better outcome . Same group then followed-up patients for multiple visits and reported that, patient’s assessment of CTCs during follow-up accurately and reproducibly predict the clinical outcome of metastatic breast cancer patients [112]. Patients who previously had ≥ 5 CTCs/7.5ml blood and later had nonelevated levels of CTCs (i.e. <5 CTCs/7.5 ml) had similar PFS and OS as patients who always has nonelevated level, suggesting patients are responding to treatment. Further, patients who previously had non-elevated CTCs and later had elevated CTC, had poor OS compared to patients whose CTCs remained low, but had better OS compared to patients whose CTCs level was always elevated. CellSearch® system has now been FDA-cleared to enumerate CTCs as a prognostic marker to monitor patients with metastatic breast cancer during therapy. Bidard et al. showed that, counting CTCs and monitoring its change during therapy in metastatic breast cancer patients can be a better prognostic marker of PFS and OS, compared to analyzing serum tumor marker [113]. Pierga et al. have shown that, detecting CTCs can predict early metastatic relapse after neoadjuvant chemotherapy [114]. Although, enumeration of CTCs as prognostic marker for metastatic breast cancer patients has been clinically validated, its clinical utility still needs to be proven [115].

The initial step of breast cancer metastasis requires cancer cells to loose cell-to-cell adhesion and proteins in cadherin family are shown to have played role in this process [116]. E- cadherin, which maintains cell-cell junction is down-regulated in metastatic breast cancer cells and has been reported to promote migration and metastasis [117, 118]. Simultaneously, N- cadherin is upregulated which supports the adhesion of tumor cells to the stromal cells and further promotes invasion of tumor cells into the stroma [119-121]. This epithelial to

19 mesenchymal transition (EMT) of cancer cells is believed to be associated with cancer progression and metastasis [122]. Next important step for metastasis process is to degrade extracellular matrix (ECM) and promote invasion into the surrounding tissue. This process is mainly supported by matrix metalloproteinases (MMPs) and urokinase-type plasminogen activator (uPA) system [123, 124]. MMP family includes many endopeptidases which have similar structure and function, and they mainly degrade ECM and promotes breast cancer invasion and metastasis. Several studies have reported that MMP1, MMP2 and MMP9 plays an important role in promoting breast cancer invasion, suggesting that these molecules can be used as a potential biomarker for cancer invasion and metastasis [125, 126]. uPA, a proteases, converts plasminogen to plasmin, which activates dormant MMPs and growth factors and degrade ECM [127]. Plasminogen activator inhibitor 1 or 2 (PAI1 or PAI2), an inhibitor of uPA is usually produced by stromal cells in tumor, suggesting the interaction of tumor with tumor microenvironment drives tumor progression and metastasis [128]. In breast cancer patients, using uPA and PAI1 as an independent prognostic marker for disease-free survival (DFS) and

OS has been confirmed by several studies [129-131]. Later, two separate studies showed that, instead of using as an independent marker, combined expression of of uPA and PAI is more accurate in predicting metastasis risk and patients survival [132, 133]. Elevated level of uPA and PAI1 in patients’ tumor tissue extract correlates with poor RFS and OS and is the strongest predictor of metastasis. Additionally, the expression of heparanase, which breaks down proteoglycan and aids in degradation of ECM has also been shown to be correlated with metastatic potential of breast cancer [134]. Instead of correlating just few markers to the clinical outcome, with the advancement of sequencing and DNA-microarray technology, analyzing many different markers at once is made possible. A good example of this, is a study where authors have identified a expression profile of 70 genes that can predict the probability of distance metastasis in lymph node negative breast cancer patients [135]. In future, these kind of 20 studies may provide the accurate identification of patients which might respond to certain therapy or might be at risk of developing metastasis, compared to current conventional prognostic markers.

1.2 Kinases and its classification

Kinases are enzyme which plays an important role in a biochemical process called by catalyzing the transfer of phosphate group from high-energy molecule (like

ATP) to the specific substrate. Phosphorylation of substrate will either enhance or inhibit its activity by regulating the stability and localization of substrate as well as by modulating its interaction with other molecules. Phosphorylation regulates various cellular functions and kinases play a central role in this process [136]. Kinases have been shown to play an important role in cellular metabolism, cell proliferation, differentiation, survival, and motility. Gain and/or loss of kinases function caused by point mutation, gene-amplification, or gene fusion, results in human diseases including cancer [137]. Because of this, designing inhibitors/drugs targeting kinases that are implicated in cancer or other diseases has gained interest recently [138]. In the past decade, numerous efforts have led to successful development of inhibitors of various cancer-promoting kinases. Several of the inhibitors have shown remarkable clinical efficacy and have been approved by the Food and Drug Administration [139]. Based on the substrate they phosphorylate, kinases are usually divided into three major groups: protein kinases, lipid kinases and carbohydrate kinases. Protein kinases, which phosphorylate protein molecule at various amino-acid residues (like serine, threonine, tyrosine or histidine), is the biggest group of kinases which contain majority of kinases and are most widely studied [140]. Cyclin dependent kinases

(CDKs) family and Mitogen-activated protein kinases (MAPKs) family are few examples of kinase families which belongs to this group [141, 142]. Lipid kinases group included those kinases which transfer phosphate group to lipid molecules in the cell. Phosphatidylinositol

21 kinases and sphingosine kinases belongs to this group of kinases. Carbohydrate kinases include family of kinases like pyruvate kinases, and , which transfer phosphate to a carbon molecule in carbohydrate. This thesis work is mainly focused on sphingosine kinase 1 (SPHK1), which belongs to the family of sphingosine kinase and is a key member of sphingolipids signaling pathway.

1.2.1 Sphingolipids signaling pathway

Sphingolipids family is a class of natural lipids that contain a sphingoid base backbone known as sphingosine, an unsaturated hydrocarbon chain amino alcohol made up of 18-carbon molecule [143]. These lipids mainly reside in membranes and are bioactive with important roles in signal transmission controlling various cellular processes such as, cell survival, cell differentiation and cell death. Thus, sphingolipids signaling pathway is an important cellular pathway, which is well-coordinated by various and molecules, where occupies the central hub and other molecules like sphingosine and sphingosine-1-phosphate

(S1P) are important members [144] (Figure 3). Ceramide is synthesized by various pathways like: de novo pathway, hydrolysis pathway and/or salvage pathway. De novo pathway starts with condensation of serine and palmitate giving rise to 3-keto-dihydrosphingosine, which than reduced into dihydrosphingosine, which further undergo acylation and converted into dihydroceramide [145]. Dihydroceramide is desaturated by enzyme dihydrocermide desaturase to give rise to ceramide [146]. Sphingomyelin, one of a common phospholipids in plasma membrane, is hydrolyzed by sphingomyelinase to give rise to ceramide via hydrolysis pathway

[147]. In salvage pathway, sphingolipids and glycosphingolipids are degraded buy lysosomes and free sphingosine is released, which can be trapped by ceramide synthase and converted into ceramide [148]. Ceramide, which serves as a branch point of this sphingolipids metabolism

22

Figure 3: Sphingolipids metabolism pathway showing the interconnection between various bioactive sphingolipids. Ceramide acts as a central hub in this pathway and other sphingosine and spingosine-1-phosphate. Sphingosine kinase (SK or SPHK) phosphorylates sphingosine and convert it into sphingosine-1-phosphate. CDase, ; CerS, ceramide synthase; CK, ceramide kinase; DAG, diacylglycerol; GCase, glucosyl ceramidase; GCS, glucosylceramide synthase; PC, phosphatidylcholine; SMase, sphingomyelinase; SMS, sphingomyelin synthase;

SPPase, sphingosine phosphate phosphatase; SPT, serine palmitoyl transferase. Reprinted with the permission from: Hannun YA and Obeid LM (2008): Principles of bioactive lipid signalling: lessons from sphingolipids, Nat Rev Mol Cell Biol., 9(2):139-50.

23 pathway, can then be converted into other bioactive lipid molecules (Figure 3) [144]. Ceramide can be broken down by ceramidase to form sphingosine. Other than going into salvage pathway, sphingosine can also be phosphorylated by sphingosine kinase to give rise to S1P (Figure 4).

S1P, is a novel mediator with both intracellular (as a second messenger) and extracellular (as a ligand for G-protein coupled receptors) functions, which is critical for many physiological and pathophysiological processes (Figure 4) [149-151]. The cellular level balance between these various bioactive molecules is critical for cell regulation, as multiple lines of evidence suggest that ceramide and sphingosine causes growth arrest and apoptosis [152-154], whereas S1P is pro-survival as it promotes and [155-157]. Studies also show that S1P has various intracellular targets involved in inflammation, osteoporosis, diabetes, neurodegenerative diseases and cancer [150, 158, 159]. The only exit point for this sphingolipids metabolism pathway is the irreversible cleavage of S1P by S1P , to generate ethanolamine phosphate and hexadecenal, which doesn’t have backbone of sphingoid bases

[160].

1.2.2 Sphingosine Kinase

Sphingosine kinase (SPHK) is a key enzyme in sphingolipids metabolic pathway, which transfers a phosphate group to the sphingosine backbone and give rise to S1P, a vital lipid mediator [161]. Because of this, SPHK is considered as a key enzyme which can regulate the levels of ceramide, sphingosine and S1P in cells and maintain “sphingosine rheostat” [162]. In humans, SPHK family consists of two major isoenzymes, SPHK1 and SPHK2 (Figure 5) [150].

The two isoenzymes are encoded from different locations in human: SPHK1 maps to (17q25.2) and SPHK2 maps to (19q13.2) [150]. SPHK1 and

SPHK2 differs in amino acids length and molecular size, whereby SPHK1 being 384 amino acids long and 42 kDa in molecular weight and SPHK2 being 618 amino acids long and 66 kDa

24

A. B. C.

SPHK

Figure 4: Schematics showing the various roles of Sphingosine-1-phosphate. A.

Sphingosine kinase (SPHK) catalyzes the phosphorylation of sphingosine to generate sphingosine-1-phosphate (S1P). B. S1P exerts its functions through both intracellular and extracellular pathways. C. SPHK/S1P signaling axis modulates diverse cellular functions related to cancer progression. Adapted and reprinted with the permission from: Pyne NJ and Pyne S

(2010): Sphingosine 1-phosphate and cancer. Nat Rev Cancer, 10:489-503 and Spiegel S and

Milstien S (2003): Sphingosine-1-phosphate: an enigmatic signalling lipid. Nat Rev Mol Cell

Biol., 4:397-407.

in molecular weight [163]. Despite this, they retain 45% overall identity in protein sequence and share five conserved domains (C1-C5) involved in ATP binding and catalytic activity (Figure 5)

[164]. SPHK1 isoforms display varying subcellular localization with SPHK1 mostly localized in cytoplasm and plasma membrane and SPHK2 mainly localized in nucleus, mitochondria and endoplasmic reticulum (ER) [165-167]. They also have different tissue distribution, with

SPHK1 being highly expressed in spleen, lungs and leukocytes and SPHK2 in liver, heart and

25

Figure 5: Schematic diagram of two isoenzymes of sphingosine kinase i.e. SPHK1 and

SPHK2. SPHK1 and SPHK2 have five conserved domain i.e. C1-C5. SPHK1 is 384 amino acid

(aa) long and has molecular weight of 42 kDa. SPHK2 is 618 aa long and has molecular weight of 66 kDA. ATP, ; TM, Transmembrane regions. Reprinted with the permission from: Spiegel S and Milstien S (2003): Sphingosine-1-phosphate: an enigmatic signalling lipid. Nat Rev Mol Cell Biol., 4:397-407.

kidney [163]. Because of these differences in localization and distribution, it was believed that these isoenzymes might have distinct functions. However, mouse models have suggested that these isozymes have some redundancy and compensatory functions in normal cells, as genetic knockout mice of either one isoenzyme can survive and reproduce successfully [168, 169].

Genetic knockout of both isoenzymes leads to embryonic lethality with defects in vascular and neural development [169]. Apart from mammalian cells, sphingosine kinase has been identified in Caenorhabditis elegans [170], Drosophila melanogaster [171], Arabidopsis thaliana [172],

Dictyostelium discoideum [173] and as well as in other organisms, suggesting an evolutionary conserved role of SPHK [174]. This thesis work is mainly focused on SPHK1 isoenzyme.

The first cloning of mammalian SPHK1 was of murine and done by peptide sequencing of the purified rat SPHK1 enzyme by Kohama et al. in 1998 [170]. Human form of the enzyme was cloned, after two years in 2000, based on the sequence identity with the mouse enzyme

[164, 175]. SPHK enzymes have five homology domains (C1-C5) which is conserved in both

26

SPHK1 and SPHK2 enzyme. The region containing C1-C3, and C5 domains are not specific to

SPHK enzyme and share homology with the catalytic domain of diacylglycerol (DAG) and ceramide kinase [176]. The ATP-binding site (S79GDG82xxxExxNGxxxR) is present within the

C2 domain and both serine at position 79 and glycine at position 82 forms a direct hydrogen bonding interaction with the nucleotide [163, 177]. The C4 domain is more unique to SPHK enzymes which contains sphingosine binding site, which involves a conserved aspartic acid residue at 178 to stabilize the lipid binding by making a hydrogen bond with the 4-hydroxyl of sphingosine [177]. The human SPHK1 protein sequence analysis revealed many putative sites for posttranslational modifications, like calcium/calmodulin binding sites, protein kinase C

(PKC) phosphorylation site, N-myristoylation sites and N-glycosylation site (Figure 6) [174].

Some other sites are demonstrated experimentally, such as serine at 225 position (S225) is phosphorylated by ERK1/2, which than activates SPHK1 and translocates it to plasma membrane [178]. Xia et al. showed that upon TNFα stimulation TRAF-2 will bind with SPHK1 at PPEE motif (TRAF-2 binding site from 379 to 382) [179].

The Km (Michaelis constant) of human SPHK1 for its substrate D-erythro-sphingosine is 15.6 µM and for ATP is 70-100 µM [174]. SPHK1 phosphorylation activity is optimum at near neutral pH (7.4) and presence of Mg2+ ions enhance this activity [174]. SPHK1 activity is lowered by the presence of Mn2+ and Ca2+ ions, and completely abolished by the presence of

Zn2+, Cu2+ and Fe2+ [174]. In addition, the SPHK1 enzyme activity is decreased by the presence of salt (like NaCl or KCl) and increased by the presence of detergent like Triton X-100. Bovine serum albumin on the other hand has no effect on SPHK1 activity [163].

27

Figure 6: Protein sequence of human SPHK1 showing various putative posttranslational modification sites. Modifications shown in blue have been demonstrated experimentally. DAG, diacylglycerol; PKC, Protein Kinase C; DN, Dominant Negative, NES, Nuclear export sequence; Sph, Sphingosine; ERK1/2, Extracellular Signal-Regulated Kinase 1/2; TRAF2, TNF

Receptor Associated Factor 2. Reprinted with the permission from: Taha TA, Hannun YA and

Obeid LM (2006): Sphingosine Kinase: Biochemical and Cellular Regulation and Role in

Disease. Journal of Biochemistry and Molecular Biology, 39(2): 113-131.

1.2.3 SPHK1/S1P axis and its role in cancer

SPHK1 being a key enzyme in balancing the level of sphingosine and S1P in cells, plays an important role in diverse cellular functions. Although SPHK1 has its own intrinsic catalytic activity, it can be further activated by various membrane receptors and signaling molecules resulting in increased intracellular S1P concentration. Membrane receptors like G-protein

28 coupled receptors (GPCRs), tyrosine kinase receptors and immunoglobulin receptors function as upstream activators of SPHK1 activity. Binding of ligands like acetylcholine, and S1P have been shown to activate SPHK1 activity [180-182]. Binding of agonist, like platelets derived growth factor (PDGF), nerve growth factor (NGF), vascular endothelial growth factor (VEGF) and epithelial growth factor (EGF) also mediate SPHK1 activity [183]. Cross- linking of immunoglobulin Fc receptors like FcγRI, FcγRIII, and FcεRI also activate SPHK1 activity [184, 185]. Studies have also shown that many biologically active agents like TNF-α,

PMA, vitamin D3, LPS and phorbol ester activate SPHK1 enzyme activity [183]. The widely studied and validated mechanism for SPHK1 activity is the phosphorylation of S225 site by

ERK1/2 which than causes SPHK1 to translocate from cytosol to the membrane, where it interacts with its substrate and becomes active [178]. This kind of posttranscriptional regulation of SPHK1 activity is acute and happens readily. Additionally, there are studies which show that several agents can increase SPHK1 activity via delayed pathway i.e. by increasing the level of

SPHK1 enzyme itself via enhanced transcription [186, 187]. Irrespective of the mechanism through which SPHK1 activity is enhanced, it results in the increase in production of intracellular S1P. This intracellular S1P can have two fates: act as an intracellular messenger and/or act extracellularly in autocrine or paracrine fashion [150, 188]. As an intracellular messenger, S1P can modulate the calcium level in cells by releasing the calcium from ER, can bind with TRAF2 and cause the activation of transcription factor NFκB, and mediate the VEGF induced activation of Ras and MAPK signaling [189]. Intracellular S1P can transport outside the cells and act extracellularly as an autocrine and/or paracrine ligand for S1P receptors that are present in cell surface of same cells and/or nearby cells, respectively [151]. There are five S1P receptors (S1PR1-5) identified which belong to GPCR family and have different cell specificity

[190-194]. S1PR1-3 receptors are ubiquitously expressed, S1PR4 is mainly expressed in cells of lymphoid and hematopoietic tissue and S1PR5 is expressed in spleen and white matter of central 29 nervous system (CNS) [195]. Depending on the stage of maturation and activation of cells, the

S1PRs can be differentially expressed suggesting that not all S1PRs are expressed on cells at same time [195]. The binding of S1P to these receptors activates various downstream pathways, which is critical for normal embryonic development, organogenesis, vasculature maturity, immune cell trafficking, cell survival and so on (Figure 4) [149]. It has been well established that SPHK1/S1P axis regulates the pathogenesis of various diseases such as neurodegenerative diseases, diabetes, inflammatory diseases, osteoporosis, and cancer [189, 196-201].

The first observation suggesting the role of SPHK1 in cancer progression was reported by Xia et al. in 2000 AD, and they reported that the overexpression of SPHK1 transformed the

NIH3T3 fibroblast cells [202]. Overexpression of SPHK1 in NIH3T3 cells, increased cell proliferation and colony formation in vitro and when these cells were injected into immune compromised mice they give rise to fibrosarcomas. They further showed that this SPHK1 transformation properties were enhanced in cells which overexpress mutant HRAS [202].

Although, these findings suggested that SPHK1 might function as oncogene, this notion has been challenged as there is no evidence of SPHK1 gene mutations which is associated with cancer yet. However, there are plenty of evidence that SPHK1 expression is increased in both cancer cell lines and patients tumor samples and cancers cells are dependable on SPHK1 for survival and growth, suggesting that cancer cells have non-oncogenic addiction for SPHK1

[203]. Increased expression of SPHK1, in both mRNA and/or protein levels, have been shown in various cancers such as colorectal, stomach, lungs, pancreas, brain, liver, ovary, prostate and breast [158, 204-210]. Johnson et al. showed using immunohistochemical (IHC) staining that protein expression of SPHK1 was significantly higher in NSCLC tissue compared to patient matched normal tissue [211]. In the same study, using normal/tumor matched samples form 241 patients with various cancer types (breast, uterus, ovary, lung, colon, intestine and rectum), they showed that mRNA expression of SPHK1 is higher in tumor samples compared to matched 30 normal tissue [211]. The role of SPHK1 in small intestinal adenoma progression is shown by using SPHK1 knockout mice model in which the cancer progression was delayed [212].

Kawamori et al. reported that 89% of colon cancer samples were stained strong positive for

SPHK1 vs. normal mucosa which exhibited weak or negative staining [207]. Microarray analysis of 1269 breast cancer tumor samples showed that SPHK1 expression is higher in ER negative tumors, and it is associated with poor survival [213]. SPHK1 expression was shown to be significantly overexpressed in both mRNA and protein level in primary astrocytoma compared to adjacent non-cancerous brain tissue and patients with elevated SPHK1 expression have shorter survival [214]. Also, glioblastoma multiforme (GBM) patients with higher SPHK1 expression has shorter survival time when compared to patients with low SPHK1 expression

[210]. Sukocheva et al. have shown that treatment of 17beta-estradiol in MCF-7 cells increase

SPHK1 activity and cause intracellular Ca2+ mobilization and eventually promote neoplastic growth [215]. In breast cancer cells, SPHK1 promotes cell proliferation by increasing the expression level of cyclin D1 via NFκB transcription factor [216]. SPHK1 also shows anti apoptotic function by inhibiting the translocation of cytochrome c and Smac/DIABLO from mitochondria to cytosol [162]. Studies show that SPHK1 activation is associated with radiation and chemotherapeutic resistance. Prostate cancer cells, which are radiation sensitive, have decreased SPHK1 activity after radiation, whereas in radiation resistance prostate cancer cells

SPHK1 activity did not change after radiation [217]. Treatment of radiation resistant prostate cancer cells with SPHK1 inhibitor together with radiation resulted in apoptosis [217]. This result was also recapitulated in head and neck squamous cancer cells (HNSCC) by Sinha et al. wh showed that targeting SPHK1 in radiation resistant HNSCC cells makes them sensitive to radiation both in vitro and in vivo [218]. Similar to radiation therapy resistance, role of SPHK1 in mediating chemotherapy resistance in cancer cells has been reported. PC-9 cells when treated with docetaxel showed decrease in cell viability as well as SPHK1 expression, however when 31 this cell line was overexpressed with SPHK1, they were resistant to docetaxel both in vitro and in vivo, suggesting the role of SPHK1 in chemo-resistant [219]. SPHK1 activity is associated with gemcitabine resistance in pancreatic cell line and both genetic and pharmacological inhibition of SPHK1 increase the sensitivity of pancreatic cells to gemcitabine mediated apoptosis [220]. Tamoxifen resistant MCF-7 breast cancer cells have higher expression of

SPHK1 compared to Tamoxifen sensitive MCF-7 cells, and silencing the expression of SPHK1 in resistance cells make them sensitive to Tamoxifen treatment [221]. SPHK1 also plays an important role in cancer cell migration and invasion, which increase the metastatic property of cancer cells. Sarkar et al. showed that SPHK1 plays an important role in EGF induced migration of MCF-7 breast cancer cell line [222]. Similarly, Long et al. have shown that in colorectal cancer cell line, depleting SPHK1 decreases the migration and invasion potential in transwell assay and further showed that SPHK1 is overexpressed in CRC patients’ samples and upregulation of SPHK1 is correlated with lymph node and liver metastasis [223].

SPHK1 emerges as a promising target for drug discovery in order to treat cancer because of the following reasons: it is overexpressed in various types of tumors, stimulate cell proliferation, migration, and invasion, association of SPHK1 overexpression with radiation and chemotherapy resistant, and a key controller of “ rheostat” [224, 225]. There are several SPHK1 inhibitors available and have been used in in vitro and in vivo animal experiments which are listed in Table 3 [226]. However, there is no SPHK1 specific inhibitor available in clinic yet. FTY720, a FDA approved immunomodulation drug for treating multiple sclerosis (MS), is an analog of sphingosine and modulate S1P receptor [227]. However, this drug has shown to inhibit SPHK1 in cancer cells [228, 229]. Safingol, initially identified as

PKC inhibitor but later identified to have inhibitory effect for SPHK1 is the only drug which is

32 currently in clinical trial [230]. Hopefully, with more research and clinical testing, SPHK/S1P axis modulator drugs will be approved for clinical use for cancer therapy in near future.

Table 3: List of inhibitors developed against sphingosine kinase.

SPHK inhibitors SPHK selectivity

SKi (2-(p-hydroxyanilino)- 4-(p-chlorophenyl)thiazole) or SK1-II SphK1 and SphK2 Safingol SphK1 > SphK2 L-threo-dihydrosphingosine (DHS) SphK1 and SphK2 N,N-dimethyl-D-erythro-sphingosine (DMS) SphK1 and SphK2 B‐5354c, F-12509A (Natural products) SphK1 and SphK2 ABC294735 SphK1 and SphK2 Amgen 82 SphK1 and SphK2 Amidine-based range of sphingosine analogues SphK1 and SphK2 MP-A08 SphK1 and SphK2 ST-1083 SphK1 and SphK2 PF-543 SphK1 SKI-I SphK1 Compound inhibitors 51 and 54 SphK1 Balanocarpol SphK1 VPC94075 SphK1 RB-005 SphK1 (S)-FTY720 vinylphosphonate SphK1 Genzyme SphK1 ABC294640 SphK2 SG-12 and SG14 (sphingosine analog) SphK2 SLC5111312 and SLM6041434 SphK2 F02 thiourea adduct of sphinganine SphK2 (2S,3S,4R)-Pachastrissamine SphK2 Trans-12a and Trans 12b SphK2 SLR080811, SLP120701 SphK2 K145 SphK2 Adapted and reprinted with the permission from: Hatoum D et al. (2017): Mammalian sphingosine kinase (SphK) isoenzymes and isoform expression: challenges for SphK as an oncotarget. Oncotarget, 8(22): 36898-36929.

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1.3 Fascin and its role in cancer

Fascins are evolutionary conserved, 55 kDa proteins which bind to the filamentous actin

(F-actin) and bundle them together [231]. These bundles of F-actin are important in forming extremely diverse set of sub-cellular or cell surface protrusions which are necessary for various cellular processes [232-235]. In humans there are three forms of fascin based on chromosomal location and tissue distribution: FSCN1, FSCN2 and FSCN3. FSCN1 is the most widely expressed form of fascin which is expressed in mesenchymal tissue and in the nervous system

[236]. Most of the normal epithelial cells are FSCN1 negative. FSCN1 is encoded by the FSCN1 gene and maps to the chromosome location 7p22 and located adjacent to the actin gene family member (actin B) [237]. FSCN2, is a retina-specific transcript and only expressed in inner and outer segments of retinal photoreceptor cells [238]. It is encoded by the FSCN2 gene and maps to the chromosome location 17q25 and located adjacent to the actin gene family member (actin

G1). FSCN3 is testis specific transcript, which is encoded by the FSCN3 gene and maps to the chromosome location 7q31.1 [239]. FSCN1 and FSCN2 are 56% identical to one another, whereas FSCN3 is 27% identical to FSCN1 and 28% identical to FSCN2 [237]. FSCN1 (also widely known and written as fascin), is the main focus of this thesis work.

FSCN1 is 493 amino acid (aa) long and belongs to the member of the β-trefoil fold family of proteins as it contains four β-trefoil domain (Figure 7) [240]. Each FSCN1 molecule binds with two F-actin in order to tightly pack them into parallel bundles. One of the actin binding site is located in the first β-trefoil domain between aa 37-47 in N-terminal region [240].

This region also contains highly conserved protein kinase C (PKC) phosphorylation site which is serine at position 39 [241]. The other actin binding region is not mapped, but is predicted to be in third β-trefoil domain in C-terminal region. Third and fourth β-trefoil domain also have binding region for cytoplasmic domain of the p75 neurotrophin receptor (p75NTR). The

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β-trefoil 1 β-trefoil 2 β-trefoil 3 β-trefoil 4

Figure 7: Schematic diagram (top) and ribbon structure (bottom) of human fascin-1.

Fascin-1 is composed of four β-trefoil domains arranged in two lobes: lobe 1, which consists of

β-trefoil domains F1 (residues 8–139, yellow) and F2 (residues 140–260, green) and lobe 2, which consists of β-trefoil domains F3 (residues 261–381, blue) and F4 (residues 382–493, red). Adapted and reprinted with the permission from: Sedeh RS, Federov AA, Federov EV,

Ono S, Matsumura F, Almo SC and Bathe M. (2010): Structure, Evolutionary Conservation, and Conformational Dynamics of Homo sapiens Fascin-1, an F-actin Crosslinking Protein.

Journal of Molecular Biology, 400(3): 589-604.

35 crystal structure of FSCN1 reveals that, four β-trefoil domains forms two lobes. First lobe consists of first β-trefoil and second β-trefoil domains, whereas second lobe consists of third β- trefoil and fourth β-trefoil domains (Figure 7). These two lobes are at the skew angle of 56o and electrostatic and hydrophobic interaction between theses lobes is critical for stability of protein and interaction with actin [240].

FSCN1, as an actin bundling protein, plays a key role in the assembly of filopodia, invadopodia, lamellipodial ribs, dendrites, microspikes and stress fibers, which regulates various cellular processes including cell adhesion, migration and invasion [232-235, 242-244]. During development, FSCN1 is expressed in nervous system, developing somites, mesenchyme of limb buds, skeletal and smooth muscles, which was observed in mouse embryo [236]. Mice with genetic knockout of the fscn1 gene born at normal Mendelian ratios, but almost 50% of mice reveal neonatal lethality. Surviving mice have reduced body weight with developmental defect in central nervous system. Similarly, FSCN1 is also expressed in nervous system in human embryo and in adult humans it is expressed in neuronal cells, dendritic cells, mesenchyme and vascular smooth muscle cells (VSMC). Immature dendritic cells do not express FSCN1, whereas mature dendritic cells express FSCN1 and F-actin expression localized at the dendrites.

Dendrites are dynamic projections (> 10 µm) of dendritic cells which plays an important role in immune surveillance by presenting processed antigens to immune cells. Upon blood vessel injury, FSCN1 expression mediates the formation of podosomes in VSMC which promote the migration of VSMC towards the injury [245]. One of the major factor that regulates the role of

FSCN1 in forming a cellular protrusions is the composition of extracellular matrix (ECM) environment [246]. Depending on cues provided by the ECM components, it activates the downstream receptor signaling and subsequent pathway to orchestrate the role of FSCN1.

Thrombospondin-1 (TSP-1) as a ECM matrix was shown to stimulate the FSCN1 mediated

36 spikes formation by activating GTPase Rac in cells [247]. In contrast, a study by Anilkumar et al. showed that when fibronectin (FN) was used as an extracellular matrix, it inhibits the acting bundling function of FSCN1 by activating the small GTPases and PKCα [248]. Other than ECM signaling, studies have also shown that insulin-like growth factor I (IGF-I) and nerve growth factor (NGF) also plays role in regulation of FSCN1 [249, 250]. Further, transcription factors

(like CREB and NFκB) and microRNAs (such as mir-145, mir-133a and mir-133b) are also shown to transcriptionally regulate the FSCN1 expression [251, 252].

It is becoming more evident that the upregulation of FSCN1 has been observed in various cancerous cells which then assemble the actin based protrusions which plays role in cancer cell motility and invasion. FSCN1 is routinely used in clinic as a marker for staining

Reed-Sternberg cells which are present in classical Hodgkin’s lymphoma [253]. More importantly, FSCN1 is used as a maker to distinguish classical Hodgkin’s lymphoma from diffuse large B-cell lymphoma [254]. Generally, normal epithelial cells have negative or low expression of FSCN1, but this expression is highly altered in human cancers in tissue specific manner. In 2002, Maitra et al. reported that 95% of human ductal pancreatic adenocarcinoma had high FSCN1 expression whereas 94% of adjacent nonneoplastic epithelium had no FSCN1 expression when analyzed by immunohistochemistry (IHC) [255]. Same group by using tissue microarray (TMA) later reported that the expression of FSCN1 increases with the progression of pancreatic intraepithelial neoplasia (PanIN): only 25% high FSCN1 expression in early stage

PanIN 1A whereas 57% of invasive PanIN 3 lesions have high FSCN1 expression [256].

Several other studies have further supported the notion that, FSCN1 expression correlates with the pancreatic cancer progression and tumor stage [257, 258]. FSCN1 up-regulation is also frequently seen in patients with NSCLS, more frequently in squamous cell carcinoma than in adenocarcinoma [259, 260]. Further, high FSCN1 expression correlates with the stage of the

37 disease and lymph-node metastasis and have shorter survival in patients [259, 261, 262]. Also a recent study by Teng et al. showed that, patients with advanced stage of NSCLC (stage III or

IV) have markedly increased serum FSCN1 protein level compared to healthy controls [263].

Although, not as high as pancreatic and NSCLC, other cancers such as colorectal cancer, gastric cancer, breast cancer, ovary cancer, prostate cancer and brain cancer have also shown to have

FSCN1 up-regulation [244]. Meta-analysis study conducted by Tan et al. reported that, FSCN1 expression in breast, colorectal and esophageal cancers is correlated with increased risk of mortality in patients [264]. Further, increased expression of FSCN1 is associated with increased risk of distant metastasis in gastric, colorectal and esophageal cancer [264]. In breast, the expression of FSCN1 is low in HR+ whereas high in TNBC patients [265-267].

The molecular basis of up-regulation of FSCN1 expression in cancer cells and its functional consequence is still an active area of research. So far, evidence on FSCN1 gene mutation or amplification in cancer cells is lacking, suggesting that the increased expression of

FSCN1 is mainly caused by transcriptional and/or post-transcriptional mechanism. The functional consequences of FSCN1 up-regulation is mostly studied in cancer cell lines (using

2D and 3D culture system and mouse models) and shown that it helps in formation of cellular protrusion, cell migration, invasion and proliferation [232-234, 237, 244]. The localization of the FSCN1 to the leading edge of the crawling cells, bundle the F-actin filaments and regulate the Myosin X which mediate the assembly of filopodia formation [268, 269]. In colorectal cancer, it has been shown that FSCN1 expression is upregulated which mediate the formation of filopodia at the invasive front during cancer progression [270]. In addition, a study by Li et al. showed that FSCN1 can also play an important role in the formation of invadopodia, which helps in the cancer cell invasion and metastasis [243]. Ectopic expression of FSCN1 in colon epithelial cells has increased cell motility on two dimensional laminin surface [271]. On the

38 other hand, downregulation of endogenous FSCN1 in esophageal squamous cell carcinoma has decreased cell migration [272]. Similarly, FSCN1 has been shown to play an important role in

3D extracellular matrix invasion and in vivo metastasis. Overexpression of FSCN1 in cells with low endogenous FSCN1, increases the invasion of cell in 3D culture and metastasis in vivo [244,

273, 274]. FSCN1 was also identified as one of a gene (out of 54 genes) that was over expressed in breast cancer cells that metastasize to the lungs [107]. These data suggest that FSCN1 might be a suitable therapeutic target to block tumor cell migration, invasion and metastasis. Knocking down FSCN1 expression by either shRNA or siRNA have shown to decrease cancer cell motility, invasion and metastasis [275]. Also, by using inhibitors of FSCN1, like G2 (N-(1-(4-

(trifluoromethyl) benzyl)-1H-indazol-3-yl) furan-2-carboxamide) or migrastatin have decreased tumor cells migration and invasion in vitro and metastasis in vivo [276, 277]. However, there is no FSCN1 inhibitor that is available in clinic or tested in clinical setting so far.

1.4 Hypothesis, specific aims, and significance

Breast cancer is the second leading cause of cancer death for women in the US. In terms of molecular subtypes, 10-20% of all breast cancers are triple negative, meaning the tumors lack estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 [32,

278]. TNBC tends to occur at high frequency in young women and is particularly aggressive with a high tumor recurrence rate. TNBC patients have poor overall prognosis, mainly due to early-onset metastasis [25, 32]. Also, it is well known that, it’s metastasis that kills patients and not the primary tumor. Since TNBC tumor lacks hormone receptors, patients cannot benefit from targeted therapy against these receptors. Thus, it is urgent to better understand the underlying mechanism of TNBC progression and metastasis and to use that mechanistic understanding to develop novel therapies for these patients.

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Kinases are dysregulated in many cancers, and function as the central nodes of cancer networks [279]. In the last decade, kinase inhibitors have shown remarkable efficacy in cancer treatment and a number of them have been approved by FDA as anti-cancer drugs. So, the rationale for my study is that, if we can identify a kinase(s) which is specifically overexpressed in TNBC and plays a role in TNBC progression and metastasis, we can use inhibitor against that kinase(s) as a therapy for TNBC patients. To identify kinase gene(s) that are overexpressed in TNBC, I performed bioinformatics analysis on publicly available data set comparing clinical specimens of TNBC and non-TNBC tumors. Sphingosine kinase 1 (SPHK1) was identified as a top candidate kinase gene, as it was overexpressed in TNBC tumors compared to non-TNBC tumors in patients. SPHK1 catalyzes the phosphorylation of sphingosine, an amino alcohol, to generate sphingosine-1-phosphate (S1P), which is a bioactive lipid signaling mediator with both intracellular (as a second messenger) and extracellular (as a ligand for G-protein coupled receptors) functions [150]. Based on this in silico analysis of clinical samples, I hypothesize that up-regulation of SPHK1 causes dysregulation of certain gene(s) or cellular pathway(s) to promote triple negative breast cancer metastasis, thus making SPHK1 an effective therapeutic target for TNBC patients. I proposed three Specific

Aims to investigate my hypothesis:

Aim 1. To determine the expression level of SPHK1 in TNBC tumors and cell lines, I will perform in silico analysis and western blotting to examine the expression level of SPHK1 in

TNBC tumors and cell lines respectively.

Aim 2. To dissect a role and underlying molecular mechanism of SPHK1-mediated breast cancer metastasis, I will 1) evaluate the functional role of SPHK1 in promoting metastasis and

2) identify SPHK1-regulated gene(s) or pathway(s) to promote metastasis in TNBC cells using unbiased approaches.

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Aim 3. To explore the potential of SPHK1 as therapeutic target of breast cancer metastasis, I will use pre-existing SPHK1 kinase inhibitors and test the effects of SPHK1 inhibition on breast cancer metastasis.

This thesis work provide an effective targeted therapy option that is urgently needed for

TNBC patients. This study also provide novel insights on how sphingosine kinase 1 promotes metastasis and empower us to develop future treatment options to more effectively prevent/intervene TNBC progression and metastasis, leading to long term improved patient care.

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Chapter 2: Materials and methods

2.1 Cell culture

Human cancer cell lines (MCF-7, T47D, BT474, HCC1954, HCC70, Hs578T, MDA-

MB-231, MDA-MB-435, and MDA-MB-436) and a mouse breast cancer cell lines (4T1, and

Met-1fvb2) were obtained from the American Type Culture Collection. Mouse breast cancer cell line E0771 and Met-1fvb2 were purchased from CH3BioSystems and Lonza respectively.

These cell lines were verified by the MD Anderson Cancer Center Cell Line Characterization

Core Facility. BC3-p53WT and BC3-p53KD were kindly provided by Dr. Helen Piwnica-

Worms [280]. Cells were cultured in Dulbecco modified Eagle medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and 0.1% penicillin-streptomycin under humidified

o conditions with 5% CO2 at 37 C. Various sizes of plastic cell culture plates were used to grow cells in two-dimensional (2D) culture. All cell lines were tested for mycoplasma contamination by using the MycoAlert Mycoplasma Detection Kit (Lonza) according to the manufacturer’s instruction and were found to be negative.

2.2 Antibodies and reagents

Rabbit polyclonal antibody against SPHK1 (HPA022829) and FSCN1 (HPA005723) were purchased from Sigma-Aldrich. Mouse polyclonal antibody against FSCN1 (sc-46675) was bought from Santa Cruz Biotechnology, and mouse monoclonal antibody against FSCN1

(sc-46675) was bought from Cell Signaling Technology. Mouse monoclonal anti-β-actin antibody (A5441) was from Sigma-Aldrich, and anti-Ki67 antibody (M7240) was from Dako.

Normal rabbit IgG (2729), NFκB p65 (8242), and H3K4me3 (9727) were all from Cell

Signaling. The in situ cell death detection kit (TUNEL technology, 11684817910) was from

Roche. The horseradish peroxidase–linked secondary antibodies against mouse (NA931) and rabbit (NA934) were from GE Healthcare. Actinomycin D (A9415) was from Sigma-Aldrich. 42

2.3 Generation of stable cell lines

To overexpress SPHK1, retroviral vector pWZL-Neo-Myr-Flag-DEST containing the

SPHK1 open reading frame (ORF) under the control of CMV promotor with G418 (100 µg/ml) as selection marker was used (kindly provided by Dr. Jean J. Zhao). Empty vector was used as a control. To stably knock down SPHK1 in MDA-MB-435, Hs578T, and BC3-p53 KD cells, we used two small hairpin RNA (shRNA) constructs, targeting the SPHK1 3’ untranslated region, were cloned into the pGIPZ lentiviral vector (RefSeq NM_001142601, Open Biosystems) with puromycin (2 µg/ml) as selection marker. Non-silencing shRNA was used as a control. To overexpress FSCN1, retroviral vector pLenti6/V5-DEST containing the FSCN1 open reading frame under the control of CMV promotor with blasticidin (3 µg/ml) as selection marker was used (plasmid #31207, Addgene). Lentiviral vector with mCherry sequence was used as a control. Lentiviral vectors (with ORFs or shRNA) were transfected into the packaging cell line

293T, together with a packaging DNA plasmid (psPAX2) and an envelope DNA plasmid

(pMD2G), through Lipofectamine transfection. After 48 h, viruses were collected, filtered, and incubated with target cells in the presence of 8-10 μg/mL Polybrene for 24 h. The infected cells were selected with suitable selection markers, with concentration mentioned above, to generate the stable clone.

2.4 Western blotting

Total cell lysates were collected with immunoprecipitation lysis buffer (20 mM Tris [pH

7.5], 150 mM NaCl, 1 mM EDTA, 1 mM EGTA, 1% Triton X-100, 2.5 mM sodium pyrophosphate, 1 mM beta-glycerophosphate, 1 mM sodium orthovanadate, 1 mM phenylmethylsulfonyl fluoride, and protease inhibitor cocktail). Whole-cell lysates were obtained by sonication followed by centrifugation. Protein concentration was measured with the

BCA Protein Assay Kit (Pierce). Equal amounts of cell lysates were subjected to electrophoresis

43 with use of sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to polyvinylidene difluoride membranes (Bio-Rad). The membranes were blocked with 5% milk or

5% bovine serum albumin in phosphate-buffered saline with 0.05% tween 20 (PBS-T) for 30 min and then incubated with primary antibody overnight at 4oC. The next day, the membranes were washed three times with PBS-T (10 min each) and incubated with secondary antibody (5% milk in PBS-T) for 60 min, and signals were detected with the PierceTM ECL Western Blotting

Substrate (32106, Thermo Scientific) according to the manufacturer’s instructions.

2.5 RNA extraction, reverse transcriptase–polymerase chain reaction (RT-PCR), and quantitative real-time PCR (qPCR)

Total RNA from cells was isolated by using Trizol reagent (Invitrogen) according to the manufacturer’s instructions. A 1-µg sample of total RNA was reverse transcribed to complementary DNA by using the iScript cDNA Synthesis Kit (Bio-Rad) according to the manufacturer’s instructions. Then, an equivalent volume (1 µL) of complementary DNA

(cDNA) was used as a template for quantitative real-time PCR (qPCR). For the probe-based assay, the reaction was performed with use of the Kapa Probe Fast ABI Prism qPCR kit (Kapa

Biosystems) and the StepOnePlus instrument (Applied Biosystems) according to the manufacturers’ instructions. The TaqMan Gene Expression primers for SPHK1

(Hs00184211_m1) were obtained from Applied Biosystems. The threshold cycles for specific targets were normalized to the threshold cycles of 18S RNA (4310893E, Applied Biosystems) for calculating relative differences. For the SYBR green-based assay, 1 µL of cDNA was used as a template for quantitative real-time PCR with iQTM SYBR Green Supermix (Biorad) and the

StepOnePlusTM (Applied Biosystem) instrument according to the manufacturer’s instruction.

The RNA expression rate was quantified by the relative quantification (2-Δ ΔCt) method, and 18S expression was used as the internal control. The primers that were used are listed in Table 4.

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Table 4: Primers used for qRTPCR.

Gene Primers

SPHK1 F: 5’-AACTACTTCTGGATGGTCAG -3’

R: 5’-TCCTGCAAGTAGACACTAAG -3’

FSCN1 F: 5’-CCAGGGTATGGACCTGTCTG-3’

R: 5’-CGCCACTCGATGTCAAAGTA-3’

MYC F: 5’- AAACACAAACTTGAACAGCTAC-3’

R: 5’-ATTTGAGGCAGTTTACATTATGG-3’

18S F: 5’-AACCCGTTGAACCCCATT-3’

R: 5’-CCATCCAATCGGTAGTAGCG-3’

2.6 Cell proliferation assay

Experimental cells and control cells were plated at 1 × 104 cells/plate in triplicate in six- well culture plates. At 24, 48, and 72 h, cells were trypsinized, and live cells were enumerated using a hemocytometer. For assays using 3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide (MTT), cells were plated at 1000 cells/well in triplicate in 96-well cell culture plates.

Three hours before each time point (24, 48, and 72 h), 20 μl of 5 mg/ml MTT in PBS (pH 7.5) were added into 200 µl of culture medium and incubated at 37oC in the dark. The medium with

MTT was removed, and 100 μl of DMSO was added into each well after incubation. After the wells were mixed, the absorbance was determined at 570 nm and 620 nm with a microtiter plate reader (BioTek).

2.7 Migration assay and invasion assay

Transwell chambers were used for both migration and invasion assays. For the migration

45 assay, cells (1 × 105 cells/chamber) were resuspended in DMEM without FBS and added to the top chambers of a 24-well transwell plate (8-µm pore size; Costar). The bottom chamber was filled with FBS-containing DMEM as an attractant. After 24-72 h of incubation, the non- migrated cells on the top side of the membrane were removed with Q-tips. The migrated cells on the bottom side of the membrane were fixed with 4% paraformaldehyde and stained with crystal violet for visualization. For the invasion assay, an identical protocol was followed, except that transwell chambers were coated with 50 µl of Matrigel (356321, Corning) and incubated at

37oC for 20 min before cells resuspended in DMEM without FBS were added. Migrated or invaded cells were imaged in a bright-field microscope (Olympus IX70) in three fields for each well and quantified with use of ImageJ software.

2.8 Animal experiments

All procedures and experimental protocols involving mice were approved by the

Institutional Animal Care and Use Committee at The University of Texas MD Anderson Cancer

Center.

Female nude mice (6 weeks old, 4-7 mice per group as indicated in figures and/or figure legends) were orthotopically injected with human cancer cells (2 × 105 cells for MDA-MB-435 and MDA-MB-231 cells, 1 × 106 cells for BC3-p53KD cells; cells were resuspended in 50:50 mixture of Matrigel in PBS) into mammary fat pads (MFPs), and tumors were allowed to develop for an indicated number of days. Tumor sizes were measured with digital calipers twice a week, and tumor volumes were calculated with use of a modified ellipsoidal formula: 1/2 ×

(length × width2). MFP tumors were surgically excised with survival surgery, and the mice were further monitored for an indicated number of weeks for spontaneous metastasis. All mice were euthanized at indicated times, and lungs were harvested, fixed and processed. Lungs were than

H&E stained and the number of metastatic lesions were counted with use of a microscope.

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For the in vivo treatment experiment, 47 BALB/c female mice (6 weeks old) were orthotopically injected with 50,000 4T1 cells (resuspended in a 50:50 mixture of Matrigel in

PBS) into MFPs. Mice were randomized into 4 groups (10-15 mice per group as indicated at day

7 when the tumors were palpable at a 2- to 4-mm diameter. Mice were given one of the following intraperitoneally (i.p.) every 3 days: vehicle (20% Captisol®, Cydex Pharmaceuticals), safingol (5 mg/kg, Cayman Chemical), bortezomib (0.5 mg/kg, EMD Millipore), or both safingol and bortezomib. Mice were euthanized when the tumor size reached the institutional euthanasia criteria, and tumors as well as lungs were harvested. For the time-matched experiment, when the first mice from any group reached the euthanasia criteria, five mice from each group were randomly picked and euthanized, and tumors and lungs were harvested. The remaining mice in each group were used for survival analysis.

2.9 cDNA microarray and analysis

Unbiased platform, HumanHT-12_v4 (Illumina), was applied for gene profiling of MFP tumors and matched spontaneous lung metastasis formed by control and SPHK1 knockdown

MDA-MB-435 cells in collaboration with the cDNA microarray core facility at MD Anderson

Cancer Center. Gene cluster maps for MFP and lung metastasis samples were generated by using sequence analysis of microarray (SAM) analysis. To identify SPHK1-regulated genes in

435 cells, R software and limma software packages were used to identify differentially expressed genes using a 1.5-fold change threshold and an adjusted p value cutoff at 0.01.

Ingenuity Pathway Analysis (IPA) software (http://www.ingenuity.com) was used to perform the functional annotation and pathway analysis of the differentially expressed genes. Gene set enrichment analysis was performed on MFP microarray data with use of an online tool

(http://software.broadinstitute.org/gsea/index.jsp), as described previously [281].

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2.10 Plasmids construction

A human FSCN1 genomic fragment comprising -1,375/+147 bp flanked with KpnI and

Xhol restriction enzyme sites, was synthesized with use of high-fidelity PCR (KAPA HiFiTM,

KAPA Biosystems), according to the manufacturer’s instructions. The sense and anti-sense primers used were 5’- agcaggtaccagccacaacgtcagtgtctg-3’ and 5’- tcttactcgaggtacttgttgccgcagttga-3’, respectively. The PCR product was gel-purified and inserted upstream of the luciferase gene in the KpnI and XhoI cut promoterless pGL3luc (basic) vector.

Genomic fragments comprising -333/+147 bp and -93/+147 bp were constructed with use of

Gibson Assembly (NEB), according to the manufacturer’s instructions. Primers were designed with use of the web tool NEBuilderTM (http://nebuilder.neb.com/) to insert fragment into KpnI and XhoI cut promoterless pGL3luc (basic) vector. The following primer sequences were used:

-333/+147 bp (forward: 5’-atttctctatcgataggtacAGCGAGGCTTGGGGTCGG-3’/reverse: 5’- gcttacttagatcgcagatcAACGCCTCGGCCGTCAGG-3’); -93/+147 bp (forward: 5’- atttctctatcgataggtacCGCGCGGAGCCAGGGGCG-3’/reverse: 5’- gcttacttagatcgcagatcAACGCCTCGGCCGTCAGGTACTTGTTG-3’). The constructs were verified by restriction digestion and by Sanger sequencing.

2.11 Site-directed mutagenesis

Nucleotides within the NFκB transcription factor binding sites of the FSCN1 promoter were altered by site-directed mutagenesis by using Q5 site-directed mutagenesis kit (NEB) according to the manufacturer’s instructions. Wild-type FSCN1 promoter (-333/+147 bp) in the pGL3luc (basic) vector, which has two NFκB binding sites at very close proximity, was used as a template to introduce mutation at three nucleotides that affect both binding sites. The sense and anti-sense primers used were 5’- GTCCGAGGTGATGGACATCAGGGG-3’ and 5’-

ACCCCGACCCCAAGCCTC -3’, respectively. Mutated promoter fragments were sequenced to

48 verify the presence of mutations.

2.12 Transient transfection and luciferase reporter assay

Plasmid DNAs were amplified in Escherichia coli Top10 strain (Invitrogen) and purified by using the E.Z.N.A Plasmid Maxi Kit (Omega Bio-tek). Plasmids were transiently transfected, along with pRL Renilla Luciferase control reporter vector (Promega), into cells by liposome- mediated DNA transfer with Lipofectamine 3000 (Invitrogen), according to the manufacturer’s instructions. For 3D culture, cells were first grown in low attachment plates, and 4 h after

Lipofectamine transfection, Matrigel was added to the medium to a final concentration of 5%.

The Dual-Luciferase Reporter Assay System (Promega), along with a 20/20n Luminometer

(Turner Biosystems), was used after 48 h to measure reporter luciferase activities and normalized to Renilla luciferase activity in the cell extracts. The protocol was followed according to the manufacturer’s instructions.

2.13 ChIP assay

Procedures for chromatin isolation and immunoprecipitation were performed as previously described.[282] Normal IgG, NFκB p65, and H3K4me3 antibodies were used at 2 µg per reaction in immunoprecipitation. Co-precipitated DNA (2 µl) was analyzed by quantitative

PCR. The forward and reverse primers used for amplification of the NFκB binding region in the

FSCN1 promoter (-333/+147 bp) were as follows: forward: 5’-

CTCAAACCTCGCTCGTCCTT-3’ and reverse: 5’- CATCACCCCTCACAACCCC -3’.

2.14 SPHK1 kinase activity

SPHK1 activity in cytosol was determined as described previously[283]. Briefly, cell were harvested in Sphingosine kinase buffer (20 mM Tris-HCL [pH 7.4], 20% glycerol, 1 mM mercaptoethanol, 1 mM EDTA, 1 mM sodium orthovanadate, 15 mM NaF, 10 μg/ml leupeptin

49 and aprotinin, 1 mM phenylmethylsulfonyl fluoride, 0.5 mM 4-deoxypyridoxine, and 40 mM β- glycerophosphate) and lysed with repeated freeze-thawing. SPHK1 kinase activity was measure

32 in the presence of sphingosine (50 μM) Triton X-100 [γ- P]ATP (10 μCi, 1 mM) and MgCl2

(10 mM). The radioactive labeled S1P is separated by thin layer chromatography on Silica gel

(Whatman, #4410221) by using 1-butanol/methanol/acetic acid/water (80:20:10: 20, v/v) as a solvent system and visualized by autoradiography.

2.15 Three-dimensional (3D) cell culture

3D culture was performed in either an 8-well chamber slide (BD Falcon) or in Costar 6- well plate with ultra-low attachment surface (Corning). For the 8-well chamber, 100 µl of

Matrigel was added to the bottom of each chamber and incubated at 37oC for 20 min. Cells of interest were mixed in culture medium with 5% Matrigel and added to each well to a final concentration of 1500 cells/well. For 6-well plates with low attachment, 2 × 105 cells of interest that were mixed into the culture medium with 5% Matrigel were added to each well. The culture medium with 5% Matrigel was replaced every 3 days throughout the assays. When necessary,

Cell Recovery Solution (BD Biosciences) was used to remove Matrigel and collect cells at the end of the experiment.

2.16 Quantification of 3D invasiveness

Indicated cells were grown in 3D culture in 8-well chamber culture slides. Images of the spheroid structures at multiple fields were obtained with use of a microscope at the indicated time, and invasive structures per field were counted. Structures that had projections coming out from the main spheroid body were counted as invasive structures.

2.17 mRNA stability assay

Equal numbers of 435 shSCR and 435 shSPHK1.1 cells were plated in a 6-well low-

50 attachment plate with 5% Matrigel and incubated for 3 d at 37oC. Cells were treated with 5

µg/mL actinomycin D for 1, 2, 4, 8, 12, and 16 h. Total RNA was extracted after each time- point by using TRIzol reagent (Invitrogen), and quantitative PCR was performed to determine the relative mRNA level of FSCN1. MYC was used as the positive control.

2.18 Immunohistochemical analysis

The excised MFP tumors were fixed in 10% neutral buffered formalin and embedded in paraffin for immunohistochemical (IHC) staining. The paraffin sections were deparaffinized in xylene and rehydrated, and then heat-induced epitope retrieval was performed in 0.01 mol/L citrate buffer (pH 6.0). Endogenous peroxidase activity was blocked for 10 min in 3% hydrogen peroxide. Nonspecific binding was blocked with a serum-free protein block (Dako) for 1 h at room temperature. The slides were incubated with indicated primary antibodies at 4°C overnight. Immunodetection was performed with the LSAB2 system (DakoCytomation); color was developed with 3-3’-diaminobenzidine, and hematoxylin was used for counterstaining.

TUNEL staining was done in paraffin sections with use of an in situ cell death detection kit,

POD (11684817910, Roche), according to the manufacturer’s instructions.

2.19 Case selection, tissue microarray (TMA) construction and analysis

Formalin-fixed and paraffin-embedded (FFPE) material were obtained from surgically resected breast cancer specimens from the Breast Tumor Bank at M. D. Anderson Cancer

Center from 2001 to 2013 (Houston, TX). Tumor tissue specimens obtained from 117 triple negative breast cancers were histologically examined, classified using the World Health

Organization (WHO) classification of Breast Tumors and selected for TMA construction. After histologic examination, tumor TMAs were prepared using triplicate 1-mm-diameter cores per tumor. All the archival paraffin-embedded tumor samples were coded with no patient identifiers. Detailed clinical and pathologic information, including demographic, pathologic

51

TNM staging, overall survival, and time of recurrence were collected.

Standard IHC staining of SPHK1, p-NFκB and Fascin were performed on these TMA slides as described previously and patients were divided into two groups for each of the individual markers using a cutoff values described below. Protein expression levels were evaluated based on the staining intensity (SI) and percentage of positive cells (PP). H score, was calculated by multiplying the PP by the corresponding SI (1 weak, 2 moderate, and 3 strong), giving a maximum score of 300 (100% X 3). Score was average of three cores for each case. H scores of SPHK1 < 100 were considered SPHK1 low and scores of SPHK1 ≥ 100 were considered SPHK1 high. Similarly, H scores of FSCN1 < 100 were considered FSCN1 low and scores of FSCN1 ≥ 100 were considered FSCN1 high. For pNFκB staining, the subcellular localization was evaluated and samples were scored either as nuclear positive or nuclear negative. If more than or equal to 5% of total cancer cells have positive nuclear staining of pNFκB, they are considered pNFκB high, and those samples with either negative staining or less

5% of cells with positive nuclear staining of pNFκB are considered pNFκB low.

Survival analysis were performed as a combined marker analysis of the three markers. In combined marker analysis, patients were divided into two groups: a) patients with low expression of all three markers or low expression of one or two of the three markers i.e. SPHK1 and/or pNFκB and/or FSCN1 low, and b) patients with high expression of all three markers i.e.

SPHK1 and pNFκB and FSCN1 high. Overall survival (OS) was defined as the time from surgery until death by any cause. Disease-free survival (DFS) is defined as the time from surgery until diagnosis of documented relapse (local or regional relapse or distant metastasis).

Distance metastasis-free survival (DMFS) is defined as the time from surgery until diagnosis of documented distant metastasis. Survival rates were compared by using the log-rank test, and hazard ratios were calculated by using a multivariable Cox proportional hazards model. All

52 statistical analysis were performed using IBM SPSS Statistics 24 and survival graphs were generated using GraphPad Prism (Prism 6; GraphPad Software Inc.).

2.20 Bioinformatics, statistics, and survival analysis

GEO2R analysis, a Web-based application for analyzing gene expression in Gene

Expression Omnibus (GEO) data sets, was performed as described elsewhere [284]. The

Kaplan-Meier plotter, a Web-based tool, was used for survival analysis [285]. Survival rates were compared by using the log-rank test, and hazard ratios were calculated by using a multivariable Cox proportional hazards model. For correlation analysis, expression values of

SPHK1 and FSCN1 from patient samples were downloaded from The Cancer Genome Atlas

(TCGA) and Curtis breast dataset [286]. GraphPad Prism (Prism 6; GraphPad Software Inc.) was used to generate a correlation graph and calculate the Pearson coefficient (r) from the downloaded data. All statistical analyses were performed by using GraphPad Prism. The data were analyzed by either one-way analysis of variance (multiple groups) or a t test (two groups).

Differences with P < 0.05 (two-sided) were considered statistically significant. *p<0.05,

**p<0.01, ***p<0.001 by two-tailed t-test.

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Chapter 3: Expression of SPHK1 in TNBC tumors and cell lines

3.1 SPHK1 is overexpressed in TNBC tumors

To identify the kinase gene(s) that are overexpressed in TNBC, I performed GEO2R analysis (GSE27447) between TNBC and non-TNBC tumor samples from patients [287]. Only

4 kinase genes were in the top 100 differentially expressed genes, of which SPHK1 was the only kinase that was overexpressed in TNBC tumors compared with its levels in non-TNBC tumors

(Figures 8A and 8B). To further validate this finding, the breast cancer microarray data available from the TCGA was analyzed and I observed that SPHK1 is significantly upregulated in patient samples with the basal subtype when compared with patient samples with other biomarker status (Figure 8C). Survival analysis performed with use of the online tool Kaplan-

Meier (KM)-plotter indicated that expression of SPHK1 is significantly associated with poor relapse-free survival in patients with ER-, PR-, and HER2-negative status with a basal subtype

(Figure 8D).

3.2 SPHK1 is overexpressed in TNBC cell lines

SPHK1 in multiple human breast cancer cell lines was measured using qPCR and western blotting and found that TNBC cell lines show relatively higher expression of SPHK1 in both mRNA (Figures 9A and 9B) and protein (Figure 9C) levels compared with levels in cell lines of other breast cancer subtypes. Similarly, mouse TNBC cell line 4T1 has higher expression of SPHK1 for both mRNA (Figure 9D) and protein level (Figure 9E) compared to mouse non-TNBC cell lines Met-1fvb2 and E0771. These data suggest that SPHK1 is overexpressed in TNBC tumor and cell lines, so we next studied the role of SPHK1 in TNBC progression and metastasis.

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Figure 8: SPHK1 is overexpressed in TNBC tumors. (A) List of all kinases that are present in top 100 differentially expressed genes after GEO2R analysis of GSE27447 dataset. (B) Gene expression profile graph of SPHK1 in TNBC and non TNBC patients as analyzed by GEO2R analysis of GSE27447 dataset. (C) Box-and-whisker plot showing the expression of SPHK1 in normal breast tissue and various subtypes of breast cancer tissue. (D) Kaplan-Meier plotter was used to generate a survival curve of TNBC patients, which were stratified based on the SPHK1 expression (n = 112). Lum, Luminal; HR, Hazard ratio. Figure (C) in collaboration with Dr. Jun

Yao.

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Figure 9: SPHK1 is overexpressed in TNBC cell lines. (A) Quantitative reverse transcriptase

PCR (qRT–PCR) showing the relative expression of SPHK1 in various human breast cancer cell lines. (B) Gene expression profile graph of SPHK1 in TNBC and non-TNBC human cancer cell lines as analyzed by GEO2R analysis of GSE32474 dataset. (C) Western blotting analysis showing the SPHK1 expression in various human breast cancer cell lines as indicated. (D)

Quantitative reverse transcriptase PCR (qRT–PCR) showing the relative expression of SPHK1 in various mouse breast cancer cell lines. (E) Western blotting analysis showing the SPHK1 expression in various mouse breast cancer cell lines as indicated. Data are representative of at least three independent experiments and are represented as mean ± SEM.

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Chapter 4: Role of SPHK1 in TNBC progression and metastasis

4.1 SPHK1 overexpression increases metastatic related properties in vitro

Gain-of-function study was performed to understand the role of SPHK1 in breast cancer progression and metastasis. For this study, MDA-MB-231 cell line was chosen, since they express relatively low levels of endogenous SPHK1 compared with levels in other TNBC cell lines. Control (231 em vec) and SPHK1-overexpression (231 SPHK1) cells were generated using lentiviral transfection system, and SPHK1 overexpression was validated at both mRNA

(Figure 10A) and protein levels (Figure 10B). SPHK1-overexpression cells also showed increase in S1P production as detected by an in vitro kinase assay (Figure 10C). Overexpressing

SPHK1 increased the migrative (Figure 10D) and invasive (Figure 10E) potential of cells in vitro but showed no significant differences in in vitro cell proliferation (Figure 10F).

4.2 SPHK1 overexpression promotes spontaneous metastasis to lungs in mice.

The control and SPHK1 overexpression cells were then orthotopically injected into nude mice, and MFP tumors were allowed to form for 28 days. MFP tumors were excised with survival surgery on day 28, and the mice were monitored for about 10 more weeks for spontaneous metastasis (Figure 11A). Consistent with in vitro proliferation data, there was no significant difference in MFP tumor size between control and SPHK1-overexpression cells by day 28 (Figure 11B). Spontaneous metastasis, as measured by the number of metastatic lesions in the lungs, was significantly higher in mice injected with SPHK1-overexpression cells than in mice injected with control cells (Figure 11C). These data suggest that although SPHK1 expression in tumor cells did not affect tumor growth, it was sufficient to promote spontaneous metastasis to the lungs.

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Figure 10: SPHK1 overexpression increases metastatic related properties in vitro. (A) qRT-

PCR showing the relative expression of SPHK1 in mRNA level in MDA-MB-231 cells transduced with empty vector or SPHK1 overexpressing vector. (B) A western blot showing the expression of SPHK1 in protein level in MDA-MB-231 cells transduced with empty vector or

SPHK1 overexpressing vector. (C) In vitro kinase assay for the detection of sphingosine-1- phosphate (S1P) in indicated cells. Transwell migration (D) and invasion (E) assay of control or

SPHK1 overexpression MDA-MB-231 cells, and representative image is shown (left) along with quantification (right). (F) In vitro cellular proliferation of control or SPHK1 overexpression

MDA-MB-231 cells when cultured for indicated time. Data are representative of at least three independent experiments and are represented as mean ± SEM. *, p < 0.05, **, p < 0.01 and ***, p < 0.001, n.s., non-significant. Scale bar: 200 µm.

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Figure 11: SPHK1 overexpression promotes spontaneous metastasis to lungs in mice. (A)

Schematic representation of in vivo experimental design and plan followed for control or

SPHK1 overexpression MDA-MB-231 cells. (B) In vivo mammary fat pad (MFP) tumors image

(left) and growth curve (right) in nude mice with orthotopic injection of 231 em vec and 231

SPHK1 cells. (C) The number of spontaneous metastatic lesions in lungs were quantified from

H&E stained lung sections from cohorts of nude mice with orthotopic injection of 231 em vec and 231 SPHK1 cells (left). Data are represented as mean ± SEM. *, p < 0.05, **, p < 0.01 and

***, p < 0.001, n.s., non-significant.

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4.3 SPHK1 knockdown decreased metastatic related properties in vitro

Next, I wanted to determine whether SPHK1 is required for breast cancer progression and metastasis. For this, I stably knocked down SPHK1 in two TNBC cell lines (MDA-MB-435 and Hs578T) and in a TNBC patient-derived xenograft cell line (BC3-p53KD) by using

SPHK1-targeting shRNA (shSPHK1). Non-targeting scrambled shRNA (shSCR) was used to generate a control cell line. SPHK1 knockdown was validated at the mRNA level by using qRT-

PCR (Figure 12A) and at protein levels with Western blotting (Figure 12B).The clone with the highest knockdown efficiency (i.e., shSPHK1.1) was picked for further experiments. SPHK1 knockdown cells (MDA-MB-435 and Hs578T) exhibited decreased S1P production, which was detected via an in vitro kinase assay (Figure 12C). Knocking down SPHK1 in all three cell lines did not result in any significant differences in in vitro cell proliferation (Figure 12D). Reduced

SPHK1 levels in MDA-MB-435 and Hs578T cells decreased the migration and invasion potential of cells in vitro (Figures 12E-H).

4.4 SPHK1 knockdown decreased spontaneous metastatic spread to the lungs in mice

SPHK1 knockdown MDA-MB-435 and BC3-p53KD cells along with respective control cells were orthotopically injected into nude mice, and MFP tumors were allowed to form; these tumors were monitored regularly. MFP tumors were resected by survival surgery on day 28 for mice injected with MDA-MB-435 cells and on day 54 for mice injected with BC3-p53KD cells

(Figures 13A and 13B). Consistent with in vitro proliferation data, there was no significant difference in primary tumor growth (Figures 13C and 13D) or in proliferation (Figures 14A and

14B) between control and SPHK1 knockdown cells in both models. However, TUNEL staining of MFP tumors showed that tumors formed by SPHK1 knockdown cells had more apoptotic cells than did tumors formed by control cells (Figures 14C and 14D).

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Figure 12: SPHK1 knockdown decreased metastatic related properties in vitro. (A) qRT–

PCR showing the relative expression of SPHK1 in MDA-MB-435 (left), Hs578T (middle) and

BC3-p53KD (right) cells transduced with lentiviral vectors expressing control shRNA (shSCR)

61 or SPHK1 targeting shRNA (shSPHK1.1 or shSPHK1.2). (B) A western blot showing the expression of SPHK1 in MDA-MB-435 (top), Hs578T (middle) and BC3-p53KD (bottom) cells transduced with lentiviral vectors expressing control shRNA (shSCR) or SPHK1 targeting shRNA (shSPHK1.1 or shSPHK1.2). (C) In vitro kinase assay for the detection of sphingosine-

1-phosphate (S1P) in indicated cells. (D) In vitro cellular proliferation of MDA-MB-435 (Left),

Hs578T (Middle) and BC3-p53KD (Right) cells transduced with lentiviral vectors expressing control shRNA (shSCR) or SPHK1 targeting shRNA (shSPHK1.1 or shSPHK1.2). (E) Control or SPHK1 knockdown MDA-MB-435 cells were subjected to transwell migration assay. Cells invading Matrigel were imaged and representative image is shown (left) along with quantification (right). (F) Control or SPHK1 knockdown MDA-MB-435 cells were subjected to transwell invasion assay using matrigel. Cells migrating through transwell membrane were imaged and representative image is shown (left) along with quantification (right). (G) Control or

SPHK1 knockdown Hs578T cells were subjected to transwell migration assay. Cells invading

Matrigel were imaged and representative image is shown (left) along with quantification (right).

(H) Control or SPHK1 knockdown Hs578T cells were subjected to transwell invasion assay using matrigel. Cells migrating through transwell membrane were imaged and representative image is shown (left) along with quantification (right). Data are representative of at least three independent experiments and are represented as mean ± SEM. *, p < 0.05, **, p < 0.01 and ***, p < 0.001, n.s., non-significant. Scale bar: 200 µm.

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Figure 13: SPHK1 knockdown decreased spontaneous metastatic spread to the lungs in mice. (A, B) Schematic representation of in vivo experimental design and plan followed for control or SPHK1 knockdown cells: MDA-MB-435 cells (A) and BC3-p53KD cells (B). (C, D)

MFP tumor growth curve in nude mice with orthotopic injection of control or SPHK1 knockdown cells: MDA-MB-435 cells (C) and BC3-p53KD cells (D). (E, F) Representative image of H&E-stained lung sections (right) and quantification of number of spontaneous metastatic lesions (left) from cohorts of nude mice with orthotopic injection of control or

SPHK1 knockdown cells: MDA-MB-435 cells (E) and BC3-p53KD cells (F). Data are represented as mean ± SEM. *, p < 0.05, **, p < 0.01, and ***, p < 0.001, n.s., non-significant.

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Figure 14: IHC staining of xenograft primary tumor formed in nude mice. (A, B)

Representative IHC staining (right) of Ki67 and its quantification (left) on xenograft primary tumor formed by control or SPHK1 knockdown cells: MDA-MB-435 cells (A) and BC3-p53KD cells (B). (C, D) Representative TUNEL staining (right) and its quantification (left) on xenograft primary tumor formed by control or SPHK1 knockdown cells: MDA-MB-435 cells (C) and

BC3-p53KD cells (D). *, p < 0.05, **, p < 0.01, and ***, p < 0.001, n.s., non-significant. Scale bar: 50 µm. In collaboration with Dr. Qingling Zhang.

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To determine whether SPHK plays any role in spontaneous metastasis, we monitored the mice injected with both cell lines after primary tumor resection. Lungs were harvested 47 days after resection in mice bearing MDA-MB-435 tumors and 187 days after resection in mice bearing BC3-p53KD tumors (Figures 13A and 13B). A significant decrease in the number of spontaneous lung metastatic lesions were observed in mice injected with SPHK1 knockdown cells compared with mice injected with control cells in both MDA-MB-435 (Figure 13E) and

BC3-p53KD (Figure 13F) models.

Together, these data suggest that although SPHK1 is dispensable for primary breast tumor growth, it plays an important role in promoting spontaneous metastasis of breast cancer to lungs. However, how SPHK1 promotes metastasis needs to be further evaluated.

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Chapter 5: Molecular mechanism of SPHK1-mediated TNBC

metastasis

5.1 Identification and validation of the FSCN1 as a SPHK1 regulated gene

SPHK1 is a critical lipid kinase with pleiotropic effects on various cellular functions[150]. To dissect the molecular mechanism using an unbiased approach, a microarray analysis on primary tumor samples and matched spontaneous lung metastasis samples from mice with orthotopic injection of 435 shSCR and 435 shSPHK1.1, were performed to gain a comprehensive and detailed picture of SPHK1-modulated genes. Gene cluster maps were generated to confirm the quality and consistency between samples (Figures 15A and 15B).

SPHK1-regulated differentially expressed gene list from primary tumor samples were subjected to Ingenuity Pathway Analysis (IPA). IPA revealed cancer as one of a diseased pathway associated with SPHK1 and FSCN1 was identified as a top SPHK1-regulated gene involved in cancer cell migration, invasion, and metastasis (Figures 15C and 15D). The FSCN1 gene was upregulated in 435 shSCR samples and downregulated in 435 shSPHK1.1 samples, in both primary tumor and spontaneous lung metastasis, which was further validated by qRT-PCR

(Figures 15E and 15F) and western blotting (Figures 15G and 15H) in in vivo samples, which were used for microarray analysis.

5.2 Correlation between SPHK1 and FSCN1 gene expression in breast cancer patients’ samples

Using two different breast cancer patients’ datasets, I showed that gene expression of

SPHK1 correlated with the gene expression of FSCN1 and that expression of both genes were higher in TNBC patients (Figures 16A and 16B). Similar to SPHK1 expression, FSCN1 expression was also upregulated in TCGA patients’ samples with a basal subtype compared with

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Figure 15: Identification and validation of the FSCN1 as a SPHK1 regulated gene. (A, B) Heat-map of unsupervised hierarchical clustering of differentially regulated genes in MFP primary tumor samples (A) and spontaneous lung metastasis (SLM) samples (B) from 435 shSCR and 435 shSPHK1.1 cells after microarray analysis. (C) Significantly altered disease pathways associated with differentially regulated genes between MFP tumor samples of 435 shSCR and 435 shSPHK1.1 cells after IPA. (D) Venn diagram representing the number of upregulated genes in MFP tumor samples from 435 shSCR cells, compared to 435 shSPHK1.1 cell, that are involved in migration, invasion, and metastasis pathways as identified by IPA. (E, F) qRT-PCR showing the relative expression of FSCN1 in mRNA level in MFP primary tumor samples (E) and SLM samples (F) from 435 shSCR and 435 shSPHK1.1 cells. ***, p < 0.001. (G, H) Western blot showing expression of fascin at the protein level in MFP primary tumor samples (G) and SLM samples (H) from 435 shSCR and 435 shSPHK1.1 cells. Figure (A and B) in collaboration with Dr. Jun Yao.

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Figure 16: Correlation between SPHK1 and FSCN1 gene expression in breast cancer patients’ samples. (A, B) Correlation between SPHK1 expression and FSCN1 expression in primary tumor samples of breast cancer patients from TCGA dataset (A) and Curtis breast dataset (B). Red circle represents TNBC patients and black circle represents patients with other subtypes. (C) Box-and-whisker plot showing the expression of FSCN1 in normal breast tissue and various subtypes of breast cancer tissue. (D) Kaplan-Meier plotter was used to generate a survival curve of TNBC patients, which were stratified based on the SPHK1 expression (n =

112). ***, p < 0.001. Figure (C) in collaboration with Dr. Jun Yao.

68 patients’ samples with other biomarker status (Figure 16C); furthermore, FSCN1 expression correlated with the poor survival in breast cancer patients with ER-, PR-, and HER2-negative status with a basal subtype (Figure 16D).

5.3 SPHK1 metastasis function is mediated by FSCN1

FSCN1 (product of the FSCN1 gene) proteins organize F-actin into parallel bundles and are required for the formation of actin-based cellular protrusions [234]. It plays a critical role in cell migration, motility, and adhesion and in cellular interactions [233, 288]. To confirm whether FSCN1 can mediate SPHK1 metastasis, I performed ectopic expression of FSCN1 in

SPHK1 knockdown cells and validated expression in both the mRNA level (Figure 17A) and protein level (Figure 17B). Ectopic expression of FSCN1 showed no advantages in cell proliferation (Figure 17C). However, ectopic expression of FSCN1 rescued the migrative

(Figures 18A and 18B) and invasive (Figures 18C and 18D) potential of SPHK1 knockdown cells in vitro. Furthermore, ectopic expression of FSCN1 in SPHK1 knockdown cells rescued the spontaneous metastatic potential in vivo (Figure 18E), indicating that the SPHK1 metastasis function is mediated by FSCN1.

5.4 SPHK1 regulates FSCN1 expression in 3D culture but not in 2D culture

Surprisingly, SPHK1-mediated expression of FSCN1 in both mRNA (Figure 19A) and protein (Figure 19B) levels was regulated in 3D culture but not in 2D culture in vitro. Just adding matrigel on 2D culture or growing cells on low-attachment plates without matrigel was not sufficient to modulate FSCN1 expression, suggesting that the extracellular matrix, which is formed in 3D culture, is required for SPHK1-mediated FSCN1 expression (Figures 20A and

20B). Various studies have shown that FSCN1 is important for invadopodia assembly to promote protrusive invasion, so the invasion potential of SPHK1-modulated cells in 3D culture was tested [243, 289]. After 10 days in 3D matrigel culture, control cells had many protrusive

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Figure 17: Ectopic expression of FSCN1 in SPHK1 knockdown cells. (A) qRT–PCR showing the relative expression of FSCN1 in 435 shSPHK1.1 cells (left) and Hs578T shSPHK1.1 cells (right) transduced with either lentiviral vectors expressing mCherry or FSCN1.

(B) A western blot showing the expression of FSCN1 in 435 shSPHK1.1 cells (top) and Hs578T shSPHK1.1 cells (bottom) transduced with either lentiviral vectors expressing mCherry or

FSCN1. (C) In vitro cellular proliferation of 435 shSPHK1.1 cells (left) and Hs578T shSPHK1.1 cells (right) transduced with either lentiviral vectors expressing mCherry or FSCN1.

). Data are representative of at least three independent experiments and are represented as mean

± SEM. *, p < 0.05, **, p < 0.01 and ***, p < 0.001, n.s., non-significant.

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Figure 18: SPHK1 metastasis function is mediated by FSCN1. (A) Quantification (left) and representative images (right) of transwell migration assay of various cells: 435 shSCR, 435 shSPHK1.1, 435 shSPHK1.1 mCherry and 435 shSPHK1.1 FSCN1. (B) Quantification (top) and representative images (bottom) of transwell migration assay of Hs578T shSPHK1.1 cells transduced with either mCherry or FSCN1. (C) Quantification (left) and representative images

71

(right) of transwell invasion assay (with matrigel) of various cells: 435 shSCR, 435 shSPHK1.1,

435 shSPHK1.1 mCherry and 435 shSPHK1.1 FSCN1. (D) Quantification (top) and representative images (bottom) of transwell invasion assay (with matrigel) of Hs578T shSPHK1.1 cells transduced with either mCherry or FSCN1. (E) The number of spontaneous metastatic lesions in lungs were quantified from H&E stained lung sections from cohorts of nude mice with orthotopic injection of 435 shSPHK1.1 cells transduced with either mCherry or

FSCN1 (left). Representative image of H&E stained lung sections are shown (right). Data are representative of at least three independent experiments (For A, B, C, D) and are represented as mean ± SEM. *, p < 0.05, **, p < 0.01 and ***, p < 0.001, n.s., non-significant. Scale bar: 200

µm.

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Figure 19: SPHK1 regulates FSCN1 expression in 3D culture but not in 2D culture. (A) qRT-PCR showing the relative expression of FSCN1 in mRNA level in MDA-MB-435 (left),

BC3-p53KD (middle) and Hs578T (right) cells transduced with either control shRNA (shSCR) or shRNA targeting SPHK1 (shSPHK1) in two dimensional (2D) and three dimensional (3D) culture system. (B) A western blot showing the expression of FSCN1 in protein level in MDA-

MB-435 (left), BC3-p53KD (middle) and Hs578T (right) cells transduced with either control shRNA (shSCR) or shRNA targeting SPHK1 (shSPHK1) in 2D and 3D culture system. Data are representative of at least three independent experiments and are represented as mean ± SEM. *, p < 0.05, **, p < 0.01 and ***, p < 0.001, n.s., non-significant.

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Figure 20: SPHK1 regulation of FSCN1 requires extracellular matrix, and control 3D invasiveness. (A) Representative brightfield images showing the cell morphology of MDA-MB-

435 cells, transduced with either control shRNA (shSCR) or SPHK1 targeting shRNA

(shSPHK1.1), cultured in 2D culture plate or low attachment culture plate with or without

Matrigel. (B) qRT-PCR showing the relative expression of FSCN1 in MDA-MB-435 cells, transduced with either control shRNA (shSCR) or shRNA targeting SPHK1 (shSPHK1), cultured in 2D culture plate or low attachment (LA) culture plate with or without Matrigel

(MG). (C, D) Representative brightfield images (left) and quantification of the percentage of invasive structures with projections (right) of MDA-MB-435 (C) and BC3-p53KD cells, transduced with either control shRNA (shSCR) or SPHK1 targeting shRNA (shSPHK1.1), when grown in 3D culture condition. Data are represented as mean ± SEM. ***, p < 0.001. Scale bar:

200 µm.

74 structures projecting into the surrounding matrix, whereas SPHK1 knockdown cells remained largely round with very few projections (Figures 20C and 20D). Further quantification showed that knocking down SPHK1 reduced the invasive structure in 3D culture (Figures 20C and

20D), most likely via downregulation of FSCN1 expression. To date, these data suggest that

SPHK1 promotes spontaneous metastasis by upregulating FSCN1 expression, but how SPHK1 upregulates FSCN1 expression is still unclear.

5.5 SPHK1 regulates FSCN1 by increasing the transcriptional rate via NFκB transcription factor

Based on our previous microarray data and qRT-PCR validation data, we hypothesize that SPHK1 regulates FSCN1 at the transcriptional level. To test this hypothesis, I decided to check mRNA stability and the transcriptional rate of FSCN1 in SPHK1-modulated cells.

Actinomycin D treatment was performed in SPHK1-modulated cells and found that there was no significant difference in FSCN1 mRNA stability between control and SPHK1 knockdown cells (Figure 21A), suggesting that SPHK1 does not play a role in FSCN1 mRNA stability.

Stability of MYC mRNA was used as a positive control to make sure that the assay was working

(Figure 21B).

To check the transcriptional rate, the FSCN1 promoter region (-1376/+147 bp) was cloned into pGL3 basic vector, which has a luciferase reporter gene, and promoter activity assay was performed, which showed that SPHK1 played a role in increasing the transcriptional rate of the FSCN1 gene transcription in 3D but not in 2D culture (Figure 21C). From this point, we performed all luciferase promoter activity assay in a 3D culture system, unless otherwise mentioned.

Next, to find the minimal promoter region, I performed 5’ deletion of -1376/+147 bp plasmid and generated -333/+147 bp and -93/+147 bp plasmids (Figure 21D). The -333/+147 bp

75

Figure 21: SPHK1 plays role in increasing the transcriptional rate of FSCN1 gene transcription but not the mRNA stability. (A, B) FSCN1 mRNA stability (A) assay with Actinomycin D treatment for various time-points in 435 shSCR and 435 shSPHK1.1 cells, and MYC mRNA stability (B) was measured as positive control. (C) Relative promoter activity assay in 435 shSCR and 435 shSPHK1.1 cells transduced with luciferase reporter plasmid containing FSCN1 promoter (-1376/+147 bp) cultured in 2D and 3D culture system. Firefly luciferase activity is reported after normalizing to renilla activity, which is used as internal control for transfection variability. (D) Schematic diagram of various 5’ deletion constructs (- 1376/+147 bp, -333/+147 bp, -93/+147 bp) of FSCN1 promotor region. (E) Promoter activity assay in MDA-MB-435 (left) and Hs578T (right) cells transduced with either control shRNA (shSCR) or shRNA targeting SPHK1 (shSPHK1) in 3D culture system. Various 5’ deletion constructs as mentioned before were transduced into these cell lines and firefly luciferase activity is reported which is normalized to renilla activity. NT, Non transfecting. Data are representative of at least three independent experiments and are represented as mean ± SEM. *, p < 0.05, **, p < 0.01 and ***, p < 0.001, n.s., non-significant. 76 region in the FSCN1 promotor was sufficient for transcription, whereas the transcription was significantly reduced while using plasmid with -93/+147 bp region of FSCN1 promoter (Figure

21E). This suggests that the -333/-93 bp region in FSCN1 promoter is important for SPHK1- mediated transcription. It is well known that transcription factors play a role in transcriptional regulation, so by using online software (PROMO), various transcription factor binding sites were identified within the -333/-93 bp region of FSCN1 promoter, one of which is NFκB

(Figure 22A). Various studies have shown that SPHK1 plays a role in NFκB activation, which was the case in our system, too (Figure 22B) [216]. Also, gene set enrichment analysis (GSEA) of microarray data showed that MFP tumor from 435 shSCR has upregulation of tumor necrosis factor (TNF) signaling compared with the tumor from 435 shSPHK1.1, which is one of the most potent physiological inducers of transcription factor NFκB (Figure 22C) [290]. Thus, this study is focused on NFκB.

To determine the importance of the NFκB binding region in FSCN1 promoter, site- directed mutation of the NFκB binding region was performed which was followed by promoter activity assay (Figures 22A and 22D). Mutation of the NFκB binding region reduces the FSCN1 promoter activity (Figure 22E); a similar result was seen when using NFκB inhibitor (Figure

22F). ChIP assay was also performed, which showed that binding of NFκB is more enriched in the FSCN1 promoter region in control cells than in SPHK1 knockdown cells (Figure 22G).

Together, these data suggest that SPHK1 regulates FSCN1 gene expression at the transcriptional level via the NFκB transcription factor.

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Figure 22: SPHK1 upregulates FSCN1 gene expression at transcriptional level through

NFκB transcription factor. (A) Schematic diagram (top) showing various transcription factor binding sites in FSCN1 promoter region (-333/-93 bp). NFκB wild-type (WT) binding sequence and NFκB mutant (M) sequence and mutated nucleotides are shown in gray (bottom). (B) A western blot showing the expression of p-NFκB and total NFκB in 435 shSCR and 435 shSPHK1.1 cells grown in 2D and 3D culture system. (C) GSEA shows an enrichment for TNF pathway genes in MFP tumor samples from 435 shSCR cells versus 435 shSPHK1.1 cells. (D)

Nucleotide sequence of FSCN1 promoter region with WT and mutant NFκB binding sequence.

(E) Relative promoter activity assay in 435 shSCR and Hs578T shSCR cells, transduced with luciferase reporter plasmid containing -333/+147 bp FSCN1 promoter with NFκB WT or NFκB

M sequence, cultured in 3D culture system. Firefly luciferase activity is reported after

78 normalizing to renilla activity, which is used as internal control for transfection variability. (F)

Relative promoter activity assay in 435 shSCR cells transduced with luciferase reporter plasmid containing -333/+147 bp FSCN1 promoter, cultured in 3D culture system. Cells were treated with either NFκB control (C) drug or NFκB inhibitor (I). (G) MDA-MB-435 (left) and Hs578T

(right) cells transduced with either control shRNA (shSCR) or shRNA targeting SPHK1

(shSPHK1) in 3D culture system. Chromatin immunoprecipitation (ChIP) was performed with antibodies against IgG (negative control), NFκB and H3K4me3 (positive control). Binding to the FSCN1 promoter region was quantified by qPCR from immunoprecipitated DNA, and fold enrichment was calculated relative to IgG. Data are representative of at least three independent experiments and are represented as mean ± SEM. *, p < 0.05, **, p < 0.01 and ***, p < 0.001, n.s., non-significant. Figure (C) in collaboration with Dr. Jun Yao.

79

Chapter 6: Potential of SPHK1 as therapeutic target of breast

cancer metastasis

6.1 Combined Expression of SPHK1, pNFκB and FSCN1 in TNBC patients correlates with poor survival

Earlier, by doing TCGA data analysis I showed that SPHK1 and FSCN1 expression was higher in TNBC patients and those patients with higher expression of SPHK1 and FSCN1 has worst survival (Figures 8D and 16D). However, these analysis were only based on RNA levels and information on protein expression was missing. So, immunohistochemical staining of

TNBC TMAs were performed to evaluate the protein expression of SPHK1, p-NFκB and

FSCN1 in TNBC patients’ samples. The clinical and pathological features of TNBC patients are presented in Table 5. Of 117 total cases, only 115, 106, and 110 had sufficient tissue for

SPHK1, pNFκB and FSCN1 expression analysis respectively. High expression of SPHK1, pNFκB and FSCN1 was observed in 59.2% (68/115), 67% (71/106) and 62.7 % (69/110) of

TNBC samples respectively (Figure 23A). Representative staining showing the high and low expression of each marker is shown in Figure 23B. Our previous experiments suggested that

SPHK1/NFκB/FSCN1 axis might promote TNBC metastasis, therefore, expression of SPHK1, pNFκB and FSCN1 were combined and correlated to clinical outcome. In this combined analysis, patients were divided into two groups: a) SPHK1 and/or pNFκB and/or FSCN1 low, and b) SPHK1 and pNFκB and FSCN1 high. The patients with high expression of all three markers were associated with worst clinical outcome compared to the group of patients with low expression of all three markers or low expression of one or two of the three markers. Survival analysis showed that there is significant association for OS (p = 0.017), DFS (p = 0.04) and

DMFS (p = 0.013) between combined-marker expression and clinical outcome in this TNBC

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Table 5: Clinical and pathological features of triple negative patient cohort used for TMA.

In collaboration with Dr. Hua Guo.

Features N (%) Age < 50 yrs 49 (41.9) ≥ 50 yrs 68 (58.1) Histology subtype Invasive ductal carcinoma 112 (95.7) Invasive lobular carcinoma 1 (0.9) Others 4 (3.4) Tumor grade G1 0 (0) G2 12 (10.3) G3 105 (89.7) Neoadjuvant chemotherapy Yes 26 (23.4) No 85 (76.6) Distant metastasis Yes 25 (21.4) No 92 (78.6) Death Yes 27 (23.1) No 90 (76.9) pT stage pT1 59 (53.2) pT2 41 (36.9) pT3 8 (7.2) pT4 3 (2.7) pN stage pN0 76 (69.7) pN1 23 (21.1) pN2 7 (6.4) pN3 3 (2.8) Total 117 • Age range from 26.3 to 80.3 years old, with median age 53.8 years. • Tumor size range from 0.4 to 15 cm, with median size 2.0 cm. • Follow up time range from 2.2 to 191.9 months, with median time 54.3 months. • Distant metastasis sites include lung, brain, bone, liver, skin, and chest wall.

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Figure 23: Combined Expression of SPHK1, pNFκB and FSCN1 in TNBC patients correlates with poor survival. (A) Graph showing the percentage of TNBC patients with high and low expression of SPHK1, pNFκB and FSCN1. (B) Representative image of immunohistochemical staining showing the high and low expression of each marker as mentioned in (A). Figure magnification: 10X and inset magnification: 20X. (C) Kaplan–Meier curves showing OS, DFS and DMFS among TNBC patients classified two different groups based on the combined expression of SPHK1, pNFκB and FSCN1. Group a, consist of patients with low expression of all three markers or low expression of one or two of the three markers, and group b, consist of patients with high expression of all three markers. In collaboration with

Dr. Hua Guo.

82 patients (Figure 23C). These data suggest that higher expression of SPHK1 and FCSN1 together with activated NFκB in primary tumor of TNBC patients can serve as a predictive biomarker for local recurrence or distant metastasis and poor survival.

6.2 Targeting SPHK1 and the NFκB signaling pathway decreased tumor progression and spontaneous metastasis to the lungs

The above results suggest that SPHK1 might be a potential therapeutic target that could inhibit breast cancer metastasis to the lungs. Safingol (SAF) is used as a SPHK1 inhibitor in this study, which is used in clinical trials. Safingol treatment decreased SPHK1 expression in protein level in both 435 cells (Figure 24A) and 4T1 cells (Figure 24B) in vitro. Although, safingol treatment in 4T1 cells decreased SPHK1 expression in both 2D and 3D culture, this treatment decreased FSCN1 expression in 3D but not in 2D culture, similar to our previous observation

(Figure 24C). Previous data showed that SPHK1 regulates FSCN1 via the NFκB transcription factor, thus the efficacy of NFκB inhibitor was also tested, either as a single agent or in combination with SPHK1 inhibitor, in breast cancer progression and metastasis. Bortezomib is used as the NFκB inhibitor, which is an FDA-approved drug for multiple myeloma.

I then determined whether safingol alone or in combination with bortezomib could prevent breast cancer progression and metastasis in a 4T1 orthotopic breast cancer mouse model. 4T1 cells (50,000 cells/mice) were injected into the MFPs of mice and primary tumor was allowed to grow. On day 7, when the primary tumor was palpable, mice were randomized into four groups and treated with one of the following intraperitoneally for 3 weeks: (a) vehicle,

(b) safingol alone (5 mg/kg, i.p., every 3 days), (c) bortezomib alone (0.5 mg/kg, i.p., every 3 days), or (d) safingol plus bortezomib. Tumor growth and mice weights were monitored regularly. The single treatment of either safingol or bortezomib had no significant effects on primary tumor growth, whereas the combination treatment showed significant delay in primary

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Figure 24: Targeting SPHK1 and the NFκB signaling pathway decreased tumor progression and spontaneous metastasis to the lungs. (A, B) A western blot showing the expression of SPHK1 in MDA-MB-435 cells (A) and 4T1 (B) cells treated with either vehicle or

Safingol for indicated time. (C) A western blot showing the expression of SPHK1 and FSCN1 in 4T1 cells grown in 2D and 3D culture system. Cells were treated with either vehicle or

Safingol. (D) MFP tumor growth curve in BALB/c mice with orthotopic injection of 4T1 cells.

Once the tumor reached the palpable size, mice were randomized into four groups for the following treatments: vehicle, Safingol (5 mg/kg) only, Bortezomib (0.5 mg/kg) only, and combination of both Safingol (SAF) and Bortezomib (BOR). Treatment was given

84 intraperitoneally (i.p.) every 3 days. (E) Kaplan–Meier survival curve with death as an end point for BALB/c mice with tumors from of 4T1 cells and have undergone various treatments as mentioned in (D). (F) Graph showing the weight of mice during various treatments as mentioned in (D). (G) Graph showing the tumor weight of five mice, in various treatment groups as mentioned in (D), euthanized on same day (21 days after treatment) for time matched experiment. (H) The number of spontaneous metastatic lesions in lungs were quantified from

H&E stained lung sections from cohorts of mice in various treatment groups and euthanized on same day for time matched experiment, as mentioned in (G). Data are representative as mean ±

SEM. *, p < 0.05, **, p < 0.01 and ***, p < 0.001, n.s., non-significant.

85 tumor progression (Figure 24D). Compared with vehicle treatment, overall survival was significantly prolonged with safingol only, bortezomib only, and combination treatment by increasing the median survival from 31 days to 37 days, 40 days, and 47 days, respectively

(Figure 24E). There was no significant difference in body weight of mice with vehicle treatment or drug treatment, suggesting that drug treatment, either as a single agent or in combination, did not induce any acute toxicity (Figure 24F).

For the time-matched experiment, five mice from each group were euthanized at day 21 after treatment, as three mice from vehicle group were flagged for euthanasia because of tumor burden on that day. The weight of the primary tumor was not significantly different between the vehicle-treated group and single-treatment group, but combination treatment significantly reduced the primary tumor weight (Figure 24G). Although treatment with safingol alone and with bortezomib alone had no effect on primary tumor growth, these treatments significantly reduced spontaneous metastasis to the lung (Figure 24H). Combination treatment showed further reduction in lung metastasis compared to single treatment (Figure 24H). To make sure that the drug treatment is actually working, immunohistochemical staining of SPHK1 and pNFκB were performed in primary tumor samples excised from mice under time-matched experiment. Safingol treatment decreased the SPHK1 expression and Bortezomib treatment decreased the nuclear staining of pNFκB compared to vehicle treatment, suggesting that the drug is targeting the molecules of interest (Figures 25A and 25B). Combination treatment decreased the expression of SPHK1, FSCN1 and the nuclear staining of pNFκB compared to vehicle treatment (Figures 25A and 25B). Also, combination treatment showed the decrease in cell proliferation and increased in apoptotic cells compared to vehicle treatment, as shown by

Ki67 staining and TUNEL staining respectively (Figures 25A and 25B).

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Figure 25: Immunohistochemistry staining of various markers in primary tumor samples excised from mice under time-matched experiment, as mentioned in 24(D). (A, B)

Representative image (A) and quantification (B) of immunohistochemical staining of various markers in primary tumor sample of mice, injected orthotopically with 4T1 cells, and undergone various treatments. Data are representative as mean ± SD. *, p < 0.05, **, p < 0.01 and ***, p <

0.001, n.s., non-significant. Scale bar: 100 µm. In collaboration with Dr. Hua Guo.

87

Chapter 7: Discussion and future directions

In this study, I sought to identify kinases that are overexpressed in TNBC patients and promote metastasis, which can be a viable therapeutic target. In silico analysis and tissue microarray analysis of patients’ samples showed that expression of SPHK1 was significantly higher in TNBC patients and was associated with poor survival. Both in vitro and in vivo data presented here further suggested that SPHK1 plays a role in promoting spontaneous metastasis.

Mechanistically, I found that SPHK1 plays a role in regulating the expression of FSCN1 at the transcriptional level via NFκB transcription factor in order to promote metastasis. Finally, this study reported that targeting SPHK1 and NFκB was sufficient to block spontaneous metastasis of TNBC cells to the lungs in mice (Figure 26).

About 15%-20 % of all breast cancer patients are diagnosed as having TNBC, and these patients do not respond to receptor-targeted therapies that are currently available for patients with other subtypes [32]. It has also been reported that patients diagnosed as having TNBC tumors tend to have poor overall survival, and their tumors are ~2.5 times more likely to metastasize within 5 years than are tumors in other subtypes [291]. Although patients with

TNBC are typically responsive to chemotherapy, they have a high risk of disease recurrence

(either at the primary or metastatic site) [292]. Therefore, understanding the molecular mechanism(s) that plays a role in TNBC progression and metastasis has become a critical area of research.

By performing bioinformatics analyses in few number of patients, I identified that

SPHK1 was overexpressed in TNBC patients compared to non-TNBC patients, which was further validated in a large cohort of patients from TCGA database. SPHK1 converts sphingosine to S1P, a biologically active lipid that has an important role in regulating the growth, survival, and migration of mammalian cells, angiogenesis, and inflammation [150].

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Figure 26: Graphical abstract. (Left) Expression of SPHK1 was significantly higher in TNBC tumors and cell lines. High SPHK1 expression upregulates the

FSCN1 gene expression in order to promote metastasis. FSCN1 gene transcription was dependent on SPHK1 and mediated via NFκB transcription factor. (Right)

Targeting SPHK1 and NFκB with small molecule inhibitors was sufficient to block spontaneous metastasis of TNBC cells to the lungs in mice.

89

Although initial findings that overexpression of SPHK1 in fibroblast cells induced spontaneous transformation of fibroblast cells suggested that SPHK1 is an oncogene, this notion has been questioned again recently and is open to debate [158]. However, there is strong evidence associating expression of SPHK1 (both in mRNA and protein level) and the development and progression of various cancers [150, 158]. SPHK1 has been shown to be activated by estrogen and to promote estrogen-dependent tumorigenesis in the estrogen receptor–positive human breast cancer cell line MCF-7 [222]. More recently, some studies have shown that SPHK1 expression is elevated in TNBC tumors and plays a role in TNBC cancer cell growth in vitro and in vivo [205]. Several other studies on breast cancer and other cancer types, have shown that SPHK1, in particular, plays a role in cancer cell proliferation [205, 216,

222, 293]. In contrast, I found that SPHK1 was dispensable for both TNBC cell proliferation in vitro and TNBC cells tumor growth in vivo, in both gain- and loss-of-function studies. Recent studies of SHK1-specific inhibitor PF-543 reported that SPHK1 had no effect on the proliferation of various cancer cells including TNBC cell line MDA-MB-231, which supports the finding of this study [293, 294]. Possible explanation for this might be that the TNBC cell lines that are used in this work are highly aggressive with various genetic alterations; thus

SPHK1 alone might not be sufficient to have a significant effect on cell proliferation. Although, there was no significant difference in cell proliferation, MFP tumors formed by SPHK1 knockdown cells have increased apoptosis, as shown by TUNEL staining, compared to MFP tumors formed by control cells. Apoptotic cells were more towards the core region, whereas outer layers of cells in the tumor were proliferative, which could partially explained why we do not see signifiant difference in primary tumor growth, between control and SPHK1 knockdown cells. However, the necrotic core, formed by quiescent or dead cells, was larger in tumors formed by SPHK1 knockdown cells compared to control cells. More importantly, both gain- and loss-of-function studies showed that SPHK1 plays a role in modulating the metastatic-related 90 properties in cancer cells in vitro and in promoting spontaneous metastasis in vivo, but the underlying mechanism is not well understood. Thus, in this study major focus was on understanding how SPHK1 promotes cancer cell invasion and metastasis.

Although most cancer funding and research are directed towards the treatment and prevention of primary cancer, the sad reality is that almost 90% of cancer mortality is due to metastasis [295, 296]. Usually metastasis is considered to be a late event in cancer progression, but metastatic cancer cells have to fulfill evolutionarily challenging steps for the successful initiation and formation of metastasis [76]. The process of metastasis is selective for cells that succeed in all steps, i.e., transformation, survival in primary site, invasion, embolization, survival in the circulation, arrest in a distant capillary bed, and extravasation into and multiplication within the organ parenchyma [76]. In this study, a spontaneous metastasis model was used to determine whether SPHK1 plays a role in metastasis, since this model recapitulates all of the steps involved in the multistep process of the metastatic cascade

[297]. To mimic the clinical condition, primary tumors were excised once they reached a certain size with survival surgery and distant metastases were allowed to form in the mice spontaneously. Although experimental metastasis models, in which tumor cells are directly injected into the systemic circulation to establish metastasis in distant sites, are widely used in metastasis research, they do not recapitulate all of the steps required for metastasis [297]. It will be interesting to delineate, which particular steps of metastatic cascade is modulated by

SPHK1? In future, experimental metastasis assay (like tail vein injection) could be performed for SPHK1 modulated cells, which could provide an information about the role of SPHK1 in later steps of metastasis cascade (i.e. survival in blood stream, extravasation and outgrowth in foreign micro environment). By performing both spontaneous metastasis and experimental metastasis assays on SPHK1 modulated cells, we could better understand the role of SPHK1 in various steps of metastasis cascade. 91

To find a suitable experimental model for this study, four non-TNBC and six TNBC human breast cancer cell lines were screened for SPHK1 expression. Although expression of

SPHK1 was high in MDA-MB-231 cells compared with MCF-7 cells, findings similar to the study by Datta et al., the endogenous level of SPHK1 in MDA-MB-231 cells was low compared with levels in other TNBC cell lines [205]. Because of this, MDA-MB-231 cell line was used for both in vitro and in vivo gain-of-function studies. PDX cell line BC3-p53KD had moderately high SPHK1 expression and was used for loss-of-function studies (in vivo experiments and 3D culture experiments). TNBC cell lines Hs578T and MDA-MB-435 had higher expression of endogenous SPHK1 than did other breast cancer cell lines. Since MDA-MB-435 is a highly tumorigenic cell line, it was used for the loss-of-function study in both in vitro and in vivo experiments. Although some studies have suggested that MDA-MB-435 is a melanoma cell line, our laboratory has previously shown that MDA-MB-435 cells secrete milk lipids, and several other studies have used it as a breast cancer cell line, too [298, 299]. Hs578T cells are not very tumorigenic when injected orthotopically into nude mice (data not shown); thus this cell line was used only for in vitro loss-of-function studies.

Exogenous expression of SPHK1 in MDA-MB-231 cells significantly increased the transwell migration and invasion in vitro and increased spontaneous metastasis to the lungs in nude mice. Furthermore, knocking down SPHK1 significantly decreased transwell migration and invasion in vitro and decreased spontaneous metastasis to the lungs in nude mice. These results support the idea that SPHK1 expression is vital for invasion and metastatic potential of breast cancer cells. Despite some reports suggesting that the SPHK1/S1P axis modulates the

MAPK/ERK pathway and EGFR pathways to promote invasion and metastasis in some cancer types, the mechanism by which SPHK1 promotes spontaneous TNBC metastasis is not well understood [300, 301]. To understand how SPHK1 regulates TNBC metastasis, an unbiased approach was used and microarray analysis of in vivo tumor samples from control and SPHK1 92 knockdown cells were performed. The differentially expressed genes, between control and

SPHK1 knockdown tumor samples, identified by microarray were subjected to IPA analysis, and the FSCN1 was identified as a top candidate gene evolved in migration, invasion, and metastasis pathways.

FSCN1 is a cytoskeletal actin bundling protein that binds and packages actin filaments into tertiary structures to enhance cell motility, migration, and adhesion [233, 234, 244]. Studies have shown that FSCN1 is overexpressed in various cancers such as cancers of the colon [302], lungs [259], breast [267, 271], ovaries [303], pancreas [257], skin [304], and brain [305], whereas its expression is either absent or very low in normal epithelial cells [244]. Tumor cells with high expression of FSCN1 have increased protrusions such as filopodia and invadopodia, which help in migration and extracellular matrix invasion of such tumor cells, suggesting the association of FSCN1 in metastasis [233, 242-244, 264]. FSCN1 has been shown to be a key regulator of breast cancer metastasis. Knocking down FSCN1 or inhibiting FSCN1 with small chemical compounds in 4T1 mouse breast cancer cells blocks cancer metastasis

[276].

Although, it is becoming more clear that upregulation of FSCN1 expression in cancer cells aids in metastasis, the changes that lead to the upregulation of FSCN1 need further characterization. Here, I showed that upregulation of SPHK1 in breast cancer cells promotes metastasis by enhancing FSCN1 expression and that furthermore, ectopic expression of FSCN1 rescued the metastatic potential of SPHK1 knockdown cells. These results suggested FSCN1 as a novel downstream effector of SPHK1 in promoting tumor cell, migration, invasion, and metastasis.

Of interest, in this study, modulation of FSCN1 by SPHK1 occurred in either a 3D culture system or in in vivo tumor samples, but not in a 2D culture system. In a 3D culture system, cells grow as spheroids and interact with the surrounding matrix in all three dimensions, 93 closely mimicking the cells and extracellular matrix interaction found in in vivo [306], whereas in 2D culture, cells grow as a monolayer on a flat surface and there is no extracellular matrix formation [306]. Previously, it was reported that the interaction of cells with the extracellular matrix is required for the regulation of FSCN1 and the formation of cell membrane protrusions

[243, 289]. Experimental observation in this study showed that, adding Matrigel into 2D culture medium or growing cells as spheroids in a low-attachment plate without Matrigel was not sufficient for the modulation of FSCN1 expression, further supporting the importance of an extracellular matrix. This cellular interaction with an extracellular matrix might explain why

SPHK1-related modulation of FSCN1 was observed only in 3D culture or in in vivo tumor samples. It will be interesting to identify which distinct upstream signaling events on cancer cells and/or components in Matrigel are involved in this process, which will be a focus for future experiments. In this study, matrigel was used as an extracellular matrix component in 3D culture systems, which is made up of approximately 60% laminin, 30% collagen IV and 8% entactin. There are other matrix components such as fibronectin and thrombspondin-1, which have shown to differentially regulate FSCN1 activity [246]. Performing future experiments in various extracellular matrix components, could allow us to understand whether regulation of

FSCN1 expression by SPHK1 is specific to matrigel or is a general mechanism with all extracellular matrix components.

Identifying a mechanism by which SPHK1 regulates the expression of FSCN1 was of interest. Since, experimental data showed that regulation of FSCN1 by SPHK1 occurs at both the transcriptional and translational levels, this study primarily focused at studying the role of

SPHK1 on transcriptional regulation of FSCN1. Previous studies have shown that activation of

SPHK1/S1P signaling causes activation or inhibition of various transcription factors, including

NFκB, E2F, c-Myc, and Sp1, which then enhances or suppresses cell proliferation, apoptosis, and/ or inflammation[216, 307, 308]. By performing a luciferase promoter activity assay in 94 control and SPHK1 knockdown cells, I showed that FSCN1 promoter activity was significantly decreased in SPHK1 knockdown cells, suggesting the regulation of FSCN1 expression was dependent on SPHK1 at the transcriptional level. A 240-bp region within FSCN1 promoter responsible for this regulation was identified and NFκB binding sites were present within this region. Also, several other groups have found that NFκB is required for the expression of

FSCN1 in metastatic cancer cells, indicating that NFκB may mediate a metastatic phenotype by specifically regulating the FSCN1 gene expression [309, 310]. However, whether FSCN1 expression is regulated by SPHK1 via the NFκB signaling pathway remains unknown. Either by mutating the NFκB binding site or by using NFκB inhibitor, I showed that FSCN1 promoter activity was decreased in cells with high SPHK1 expression. Furthermore, a chip assay was performed to show that binding of NFκB to the FSCN1 promoter region was decreased in

SPHK1 knockdown cells compared with control cells. These data suggest that FSCN1 gene expression at the transcriptional level was dependent on SPHK1 through NFκB transcriptional factor.

The role of the SPHK1/S1P axis has been well defined to regulate immune responses mainly by affecting lymphocytes trafficking, activating innate immune cells, and regulating inflammation [159]. For these reasons, a syngeneic mouse model was used for in vivo therapeutic experiments. There has been much interest recently in targeting the SPHK1/S1P pathway in many cancer types, and many drug compounds have been developed [224]. One of the criteria for selecting drugs for therapeutic experiments is that the drugs are already in clinical trials or have been FDA-approved for any diseases, since repositioning FDA-approved drugs are quicker. Safingol [(2S, 3S)-2-aminooctadecane-1, 3-diol], initially identified as a PKC inhibitor but later found to be more potent toward SPHK1, was used in this study as a SPHK1 inhibitor. Also, safingol is the only SPHK1-specific inhibitor that is used in a clinical trial [230].

Although a few drugs have been developed against FSCN1, none have been used so far in a 95 clinical trial. NFκB inhibitor bortezomib, a FDA-approved drug against multiple myeloma, was also used in our study either as a single agent or in combination with the SPHK1 inhibitor [311].

Treatment with safingol alone did not inhibit tumor growth significantly, supporting previous in vitro and in vivo results. Bortezomib treatment also had no significant effect on tumor growth. However, combination treatment significantly delayed tumor progression, suggesting a complex interaction between these two drugs that warrants further investigation. In time-matched experiment, despite having no effect on primary tumor growth, both the safingol and bortezomib treatments showed significant decrease in spontaneous metastasis to the lungs, which was further decreased upon combination treatment. Furthermore, there was a significant increase in mice survival with combination treatment. As both of these inhibitors are clinically applicable, therapies combining these drugs may be effective in reducing the process of tumor progression and metastasis in TNBC patients, which needs to be tested clinically. Further studies are necessary in order to improve the understanding of these drugs effect on the tumor microenvironment in vivo, which will enable us to achieve better outcome with these drugs in clinical trials. In fact, it would be extremely interesting to test the benefits of using these drug combination in clinic as an adjuvant treatment after surgery in order to prevent metastasis and/or recurrences, especially for those patients whose primary tumor has higher expression of SPHK1 and/or FSCN1. In addition, these drugs could be tested in clinic as a perioperative therapy during surgical resection of primary tumors or in combination with chemotherapy in neoadjuvant or adjuvant setting by performing clinical trials [312]. This study also suggests that expression of SPHK1/NFκB/FSCN1 axis in the primary tumor can be a predictive marker for metastasis which needs to be clinically validated.

96

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Vita

Sunil Acharya was born in Syangja, Nepal on January 17, 1984, the son of Mathura

Acharya and Dilleshwor Acharya. He received the degree of Bachelor of Technology in

Biotechnology from Kathmandu University, Dhulikhel, Nepal in 2007. In August of 2008 he enrolled for Master’s degree program in Biotechnology which was a collaborative program between two institutes: Stephen F. Austin State University at Nacogdoches, Texas and The

University of Texas Health Science at Tyler, Texas. He graduated with a Master of Science in

Biotechnology in December 2010. In August of 2011, he entered The University of Texas MD

Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences. Sunil is intending to graduate with a doctorate degree in Cancer Biology in May 2018.

Permanent address:

Ghar no. 55.16, Shangrila Margha

Pokhara, Kaski, Nepal

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