DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosphy in the Graduate School of The Ohio State University

By

Yadwinder S Deol, MS

Graduate Program in Molecular, Cellular and Developmental Biology

The Ohio State University

2012

Dissertation Committee:

Dr. Ramesh K Ganju, PhD (Advisor)

Dr. Xue-Feng Bai, PhD

Dr. James Waldman, PhD

Dr. Sujit Basu, MD. PhD

Copyright by

Yadwinder S Deol, MS

2012

ABSTRACT

Psoriasin (S100A7) is expressed in several epithelial malignancies including

breast cancer. Although S100A7 is associated with the worst prognosis in estrogen

α-negative (ERα-) invasive breast cancers, its role in ERα-positive (ERα+) breast cancers is relatively unknown. We investigated the significance of S100A7 in ERα+ breast cancer cells and observed that S100A7-overexpression in ERα+ breast cancer cells,

MCF7 and T47D, exhibited decreased migration, proliferation, and wound healing. These

results were confirmed in vivo in a nude mouse model system. Mice injected with

S100A7-overexpressing MCF7 cells showed significant reduction in tumor size compared with mice injected with vector control cells. Further mechanistic studies revealed that S100A7 mediates the tumor-suppressive effects via a coordinated regulation of the β-catenin/TCF4 pathway and an enhanced interaction of β-catenin and E-cadherin in S100A7-overexpressing ERα+ breast cancer cells. We observed down-regulation of β-

catenin, p-GSK3β, TCF4, cyclin D1, and c- in S100A7-overexpressing ERα+ breast

cancer cells. In addition, we observed increased expression of GSK3β. Treatment with

GSK3β inhibitor CHIR 99021 increased the expression of β-catenin and its downstream

target c-myc in S100A7-overexpressing cells. Tumors derived from mice injected with

S100A7-overexpressing MCF7 cells also showed reduced activation of the β-

catenin/TCF4 pathway.

ii Our results also demonstrated that S100A7-overexpression in MCF7 cells

increased the stability of compared to vector control cells. We found p53 to be

mainly localized in nucleus of the S100A7-overexpressing cells. Moreover, co-

immunoprecipitation studies revealed that S100A7 binds to p53 directly and both

S100A7 and p53 co-localize in the nucleus of S100A7-overexpressing cells. P53 is

generally stabilized in the nucleus and we found that phosphorylation of p53 at Serine-15

residue was enhanced in S100A7-overexpressing MCF7 cells compared to vector control

cells. Serine-15 is known to stabilize and activate p53 during cellular stresses. Further,

real time PCR p53 array showed the increased expression of the stress related such

as ATR and BRCA-1 along with genes involved in apoptosis and cell cycle arrest

pathways. We validated the differentially regulated genes of stress pathway by western

blotting and observed that S100A7-overexpression in MCF7 cells increased the

expression of ATR and its downstream molecules p-Chk1 and p-Chk2 which are known

to phosphorylate serine-15 residue of p53. We further evaluated the role of p53 and

S100A7 in an in vivo mouse model system by generating a mouse model which was

deficient in p53 expression but expressed murine S100A7 (mS100A7A10) in the

mammary glands under doxycycline treatment. After two and half months of doxycycline

treatment, we observed the development of spontaneous tumors in the fourth inguinal

mammary gland of the mouse which strengthens our finding of association between

S100A7 and p53.

S100A7-overexpression in MCF7 cells also exhibited decreased actin

polymerization as evident from decreased formation of migratory structures. Actin

iii staining revealed F-actin expression on the edges of plasma membrane in vector control

cells whereas in S100A7 overexpressing cells, actin staining was mostly intracellular.

Both serum-induced and EGF-induced migration was reduced in S100A7 overexpressing

cells compared to vector control cells. We further found that S100A7-overexpression

reduced EGF-induced activation of EGFR, AKT and ERK. Upon further analysis of the

mechanisms that regulate actin polymerization, we observed reduced activation of the

Rac1 pathway and cofilin.

In conclusion, our studies reveal for the first time that S100A7-overexpressing

ERα+ breast cancer cells exhibit tumor suppressor capabilities through a coordinated

down-modulation of the β-catenin/TCF4 and p53 pathways both in vitro and in vivo. Our

results also show that S100A7 has the ability to bind to p53 and stabilize it in the nucleus

which then activates the stress induced pathway. Moreover, we also show that S100A7 modulates the cytoskeleton by regulating actin polymerization. Since S100A7 has been shown to enhance tumorigenicity in ERα- cells, our studies suggest that S100A7 may

possess differential activities in ERα+ compared with ERα- cells.

iv

DEDICATED TO

My parents who always inspired me to achieve the best in whatever I do

My wife, who always helped me and supported me in life and graduate school

v

ACKNOWLEDGEMENTS

I would like to sincerely thank Dr. Ramesh K. Ganju for all kind of support and

help, mentorship and for providing me with the opportunity to work in his lab and giving

me the great experience in his laboratory. I am very grateful to my advisory committee

members, Dr. Sujit Basu, Dr. James Waldman and Dr. Xue-Feng Bai for their valuable time and guidance. I would like to thank all members of the Dr. Ganju lab who have been a great help throughout my stay in the lab. I would especially like to thank Dr. Mohd

Nasser who helped me with the set up of the project and also Dr. Anand Appakuddal and

Dr. Nagaraja Tirumuru who helped me when I had questions in the lab. I also thank

Michelle Van-Fossen for her help in everyday things.

vi VITA

1998...... Dasmesh Public High School, India

2002...... BS, Punjab Agricultural University, India.

2006...... MS, The Ohio State University, USA

2007 to present ...... PhD, The Ohio State University, USA

PUBLICATIONS

1. Nasser MW, Qamri Z, Deol YS, Shilo K, Leone G, Bai X-F, Zou X, Wolf R, Yuspa S and Ganju RK. 20112. S100A7 enhances mammary tumorigenesis through upregulation of inflammatory pathways. Cancer Research, 72(3):604-15.

2. Deol YS, Nasser MW, Yu L, Zou X, Ganju RK. 2011. Tumor suppressive effects of psoriasin (S100A7) are mediated through β-catenin/TCF4 pathway in positive breast cancer cells. Journal of Biological Chemistry, 286(52):44845- 54.

3. Nasser MW, Qamri Z, Deol YS, Smith D, Shilo K, Zou X, Ganju RK. 2011. Crosstalk between Chemokine Receptor CXCR4 and Cannabinoid Receptor CB2 in Modulating Breast Cancer Growth and Invasion. PLoS ONE 6(9): e23901. doi:10.1371/journal.pone.0023901

4. Anand AR, Prasad A, Bradley RR, Deol YS, Nagaraja T, Ren X, Terwilliger EF, Ganju RK. 2009. HIV-1 gp120-induced migration of dendritic cells is regulated by a novel kinase cascade involving Pyk2, p38 MAP kinase, and LSP1. Blood. Oct 22; 114 (17):3588-600.

FIELDS OF STUDY

Major Field: Molecular, Cellular and Developmental Biology

Area of Emphasis: Pathology of Breast Cancer

vii

TABLE OF CONTENTS

Abstract………………………………………………………………………………...... ii

Dedication……………………………………………………………………………...... iv

Acknowledgments……………………………………………………………………....…v

Vita……………………………………………………………………………………...... vi

List of figures………………………………………………………………………...... viii

List of Tables…………………………………………………………………………...... ix

CHAPTERS

CHAPTER 1: INTRODUCTION……………………………………………………...... 1

1.1 Breast Cancer………………………………………………………...... 1

1.2 S100 Family of …………………………………………..…...6

1.3 Psoriasin (S100A7) ………………………………………………...... 9

1.4 S100A7 and Breast Cancer………………………………………...... 14

1.5 β-Catenin/TCF 4 Pathway…………………………………………....20

1.6 β-Catenin/TCF4 Pathway and Tumorigenesis…………………...... 23

1.7 Expression of p53 and its Role in Cancer………………………....….26

1.8 Actin Cytoskeleton and its Role in Cancer ……………………....…..31 viii 1.9 Objectives of the Study…………………………………………….....34

CHAPTER 2: MATERIAL AND METHODS……………………………………...... 36

2.1 Cell Culture, Reagents and Antibodies…………………………...... 36

2.2 Constructs and Transfections…………………………………....……37

2.3 Proliferation Assay………………………………………………...... 38

2.4 Chemotaxis Assay…………………………………………………....38

2.5 Wound Healing Assay……………………………………………...... 39

2.6 Western Blotting………………………………………………..….....39

2.7 Co-Immunoprecipitation……………………………………….….....40

2.8 Confocal Microscopy…………………………………………..….....40

2.9 TCF4 Luciferase Reporter Assay………………………………….....41

2.10 Microarray Analyses……………………………………………...... 41

2.11 Quantitative Real Time Polymerase Chain Reaction (qRT-

PCR)……………………………………………………………………...42

2.12 Xenograft Mouse Model………………………………………....…43

2.13 Immunohistochemistry (IHC)…………………………………....…43

2.14 Rac1 Activation Assay…………………………………………...... 44

2.15 Real Time p53 PCR Array……………………………………….....44

2.16 Generation of Transgenic Mice…………………………………...... 45

ix 2.17 Whole-mount Analysis of Mammary Glands………………...…...... 45

2.18 Statistical Analyses……………………………………………….....46

CHAPTER 3: RESULTS……………………………………………………………...... 47

3.1 S100A7-overexpression decreases growth in ERα+ cells both in

vitro and in vivo…………………………………………………….....…47

3.1.1 S100A7-overexpression reduced proliferation in MCF7 and T47D

cells in vitro…………………..………………………………...... 47

3.1.2 S100A7-overexpression inhibits tumor growth in vivo...... …….....48

3.2 Mechanisms of growth inhibition by S100A7-overexpression in

ERα+ cells…………………………………………………………...... …49

3.2.1 Reduced β-catenin/TCF4 pathway activity is involved in S100A7-

mediated tumor-suppressive effects………………………………...... 49

3.2.2 S100A7-overexpression in ERα+ cells down-modulates β-

catenin/TCF4 pathway by regulating GSK3β and TCF4…………...... 53

3.2.3 Inhibition of GSK3β and restoration of TCF4 rescues effects of

S100A7-overexpression mediated down-regulation of β-

catenin/TCF4 pathway………………………………………...... ……...56

3.2.4 S100A7-overexpression enhances the co-localization and interaction

β-catenin and E-cadherin………………………………...... 59

x 3.3 S100A7 stabilizes and activates p53 mediated stress response pathway

in ERα+ cells…………………………….…………………...... 61

3.3.1 S100A7-overexpression increases the expression of p53………...... 61

3.3.2 S100A7 and p53 interact in S100A7-overexpressing MCF7

cells………………………………………………………………...... 62

3.3.3 S100A7 increases phosphorylation of p53 at Serine-15…..……...... 64

3.3.4 S100A7-overexpression in MCF7 cells modulates p53 signaling….65

3.3.5 S100A7-overexpression in MCF7 cells activates p53 mediated stress

response……………………………………………...... 66

3.3.6 Role of murine S100A7 (mS100A7A15) and p53 in breast

tumorigenesis……………………………………………………...... ….67

3.3.7 Generation of MMTV-rtTA/mS100A7A15/P53-/- mouse model….69

3.4 S100A7-overexpression decreases migration of ERα+ cells…………71

3.4.1 S100A7-overexpression reduces chemotaxis and wound healing in

ERα+ cells…………………………………………………………...... 71

3.5 Mechanisms mediated by S100A7-overexpression which regulate

migration of ERα+ cells……………………………………...... ………..72

3.5.1 S100A7-overexpression reduces EGF-induced signaling in

ERα+ breast cancer cells…………………………………………...... 72

3.5.2 S100A7-overexpression decreases actin polymerization…………..73 xi 3.5.3 S100A7-overexpression decreases cofilin expression……………...75

3.5.4 S100A7-overexpression in MCF7 cells decreases Rac activation....75

CHAPTER 4: Discussion……………………………………………………………...... 77

4.1 S100A7-overexpression has tumor suppressive effects in ERα+ breast

cancer cells…………………………………………………...... 77

4.2 Conclusions………………………………………………………...... 86

4.3 Future Directions…………………………………………………...... 87

Bibliography…………………………………………………………………………...... 90

xii

LIST OF TABLES

Table 1. List of primers used for Real Time – PCR………………………………..42

xiii

LIST OF FIGURES

Figure 1. Schematic representation of various stages of breast cancer development from

normal breast epithelium to metastatic stage …….…………………………….2

Figure 2. Molecular classification of breast cancer showing different sub-types of breast

cancer……………………………………………………………………..…….4

Figure 3. Structure of the S100 Dimer………………………………..…………...……...7

Figure 4. List of S100 family members and their proposed functions…………...8

Figure 5. Alignment of S100A7 protein with other homologous S100 family proteins...11

Figure 6. Proposed mechanisms of S100A7 in estrogen receptor negative breast cancer

cells ………………………………………………………………..……...... 17

Figure 7. Schematic representation of β-catenin/TCF4 pathway………………………..22

Figure 8. Schematic representation of p53 activation and cellular processes mediated by

its activation.……………………………………………………..……...... 29

Figure 9. Overview of breast cancer cell motility…………………………………….....32

Figure 10. S100A7-overexpression reduces proliferation in ERα+ cells…………….…48

Figure 11. S100A7-overexpression inhibits tumor growth in vivo……………………..50

Figure 12. S100A7-overexpression in MCF7 cells modulates genes, which are involved

in cancer and β-catenin/TCF4 pathway……………………………………...51

Figure 13. S100A7-overexpression reduces β-Catenin/TCF4 pathway in ERα+ cells at

transcription level.……………………..………...………………………...... 52 xiv Figure 14. S100A7-overexpression reduces β-Catenin/TCF4 pathway in ERα+ cells at

protein level……………………...... 54

Figure 15. S100A7-overexpression reduces expression of downstream targets of β-

catenin/TCF4 pathway in ERα+ cells...... 55

Figure 16. S100A7 regulates β-catenin/TCF4 pathway through GSK3β...... 57

Figure 17. TCF4 overexpression in S100A7 overexpressing cells restores the

oncogenicproperties...... 58

Figure 18. S100A7-overexpression enhances the co-localization and interaction between

β-catenin and E-cadherin in ERα+ breast cancer cells.……………………...60

Figure 19. S100A7-overexpression increases p53 expression in MCF7 cells……….….61

Figure 20. S100A7 interacts with p53 in S100A7 overexpressing MCF7 cells...... 63

Figure 21. S100A7-overexpression increases phosphorylation of p53 at Serine p53 in the

nucleus of S100A7-overexpressing MCF7 cells...... 64

Figure 22. RT-PCR profiler array analysis showing differential regulation of p53

signaling pathway molecules...... 66

Figure 23. S100A7-overexpression activates stress induced pathway in MCF7 cells...... 67

Figure 24. Generation of the inducible, mammary-specific mS100A7A15 bi-transgenic

mouse model...... 69

Figure 25. Development of spontaneous tumors in MMTV-rtTA/mS100A7A15/p53-/-

mice…...... 70

Figure 26. S100A7-overexpressing ERα+ MCF7 and T47D cells decreases chemotactic

activity and motility...... 71

Figure 27. S100A7-overexpression in MCF7 cells decreases EGF-induced signaling....73

xv Figure 28. S100A7-overexpression in MCF7 cells modulates actin cytoskeleton...... 74

Figure 29. S100A7-overexpression in MCF7 cells decreases cofilin expression and

decreases Rac activation.………..…..…………………………………...... 76

Figure 30. Expression of (ERα) in S100A7-overexpressing and

vector control MCF7 and T47D cells...... 79

xvi

CHAPTER 1

INTRODUCTION

1.1 Breast Cancer

Breast cancer is the most commonly occurring cancer in women as it comprises approximately one third of all malignancies in females. It is second only to lung cancer in causing cancer mortality. It is also the leading cause of death for American women between the ages of 40 and 55 (Harris et al., 1992a; Harris et al., 1992b; Harris et al.,

1992c). In the US, one out of 8 females develops breast cancer at some point in her life

(Greenlee et al., 2001). In 2011, an estimated 230,480 new cases of invasive breast cancer were diagnosed in women in the U.S., along with 57,650 new cases of non- invasive (in situ) breast cancer (www.breastcancer.org). The incidence of breast cancer has remained level since 1988 after increasing steadily for nearly 50 years and the death rate for breast cancer has been slowly declining over the past decade. These changes have been attributed to widespread use of mammography, which helps in early detection of breast cancer (Center of Disease Control and Prevention, 1992). Mortality rates due to breast cancer are highest in the very young (less than age 35) and in the very old (greater than age 75) (Smith et al., 1996). Most of the recurrences (about 60% to 80%) occur in the first 3 years and the chance of recurrence could exist for up to 20 years (Shapiro,

1 1991). The various risk factors in breast cancer include gender, age, life style, genetics,

hormonal imbalance and family history. Breast cancer occurs 100 times more frequently

in women than men. Only 5% to 6% of breast cancers are considered hereditary (Malone

et al., 1998) and about 80% of heredity breast cancers involve BRCA-1 and BRCA-2

genes. BRCA-1 and/or BRCA-2 positive women have a 50% to 85% lifetime risk of

developing breast cancer (Haber, 2002).

Figure 1. Schematic representation of various stages of breast cancer development from normal breast epithelium to metastatic stage.

The majority of the breast cancers (Ninety-five percent) are carcinomas, i.e. they arise from breast epithelial tissue (Richie and Swanson, 2003). Based on their histological origin, breast cancers are divided into 2 major types, lobular carcinoma if the cancer

2 arises in lobules or milk producing glands and ductal carcinoma if cancer arises in ducts.

Further, breast cancer can be divided into in situ carcinomas and invasive (or infiltrating) carcinomas. The in situ carcinomas may arise in either ducts forming Ductal Carcinoma in Situ (DCIS) or lobular epithelium leading to Lobular Carcinoma in Situ (LCIS). Both of these carcinomas remain confined in the tissue of their origin with no invasion of the underlying basement membrane (Richie and Swanson, 2003). These in situ carcinomas are normally non-metastatic but when there is extension of the ductal or lobular malignancy beyond the basement membrane that constitutes the epithelial border, then the malignancy is considered invasive (or infiltrating) ductal or lobular carcinoma. The potential for metastases is very high and ultimately it can lead to death in case of invasive disease. If metastases occur, cancer cells could migrate to several secondary organs such as bone, liver, brain, lungs etc. The progress of breast cancer from normal tissue to invasive and metastatic stage has been summarized in Figure 1.

Based on pathological diagnosis of breast cancer samples, breast cancer could be divided into Estrogen Receptor alpha positive (ERα+) or Estrogen Receptor alpha negative (ERα-), HER2 positive or triple negative that is ER, (PR) and HER2 negative (Subik et al., 2010). The Drug regimen for treatment of breast cancer is normally based on the pathological sub-types of breast cancer. First attempt to characterize breast cancer on molecular basis was made by Sorlie et al who used cDNA microarray and hierarchical cluster analysis (Sorlie et al. 2001). A novel finding of their analysis was that the previously characterized luminal epithelial/estrogen receptor (ER)

3 positive group could be divided into Luminal A, Luminal B and Luminal C. As shown in

Figure 2, their analysis revealed that the cancers could be classified into basal epithelial-

like group, an ERBB2-overexpressing group and a normal breast-like group based on

variations in expression. ER, HER2, and proliferation associated genes defined these subtypes.

Figure 2. Molecular classification of breast cancer showing different sub-types of breast cancer (Sorlie et al., 2001).

4 The basal-like subtype was characterized by high expression of keratins 5 and 17, laminin, and fatty acid binding protein-7 whereas the ERBB2+ subtype was characterized by high expression of several genes in the ERBB2 amplicon at 17q22.24 including ERBB2 and GRB7. Further, survival analyses on a sub cohort of patients with locally advanced breast cancer, which were uniformly treated, showed a poor prognosis for the basal-like subtype and a good prognosis for the two estrogen receptor-positive luminal subtypes. ER-negative cancers included ERBB2/HER positive, basal like cancer and normal breast-like and ER-positive cancers included groups like luminal A, Luminal

B and Luminal C. Luminal groups were characterized by high expression of hormone receptors and 70% of breast cancers fell in this category. Further, luminal B cancers had a higher grade than luminal A cancers (Sorlie et al., 2003). These types of cancers were responsive to hormone therapy but response to chemotherapy was variable. HER2 positive cancers had high expression of HER2 and low expression of ER. 15% of breast cancer samples were in this category and they were mainly ER/PR negative. These cancers were responsive to Herceptin and have poor prognosis (Sorlie et al., 2003). The third category was basal like and these cancers had high expression of basal cytokeratins, low expression of ER and associated genes, low expression of HER2 and included 15% of all breast cancer samples. They were mostly triple negative and included BRCA1 dysfunction or mutations. Further, these types of cancers were more prevalent in African

American women and they showed no response to endocrine therapy or Herceptin but were responsive only to platinum and PARP inhibitors. Further, these cancers were shown to be associated with poor prognosis.

5 1.2 S100 Family of Proteins

The S100 proteins are a family of multi-gene calcium-binding proteins and this family is comprised of 20 known human members which are coded by separate genes

(Salama et al., 2008). Genes of 16 members of this family lie on 1q21, which is known as the epidermal differentiation complex (Marenholz et al., 2004; Schafer

et al., 1995). The S100 proteins are small, acidic proteins of 10–12 kDa and are found

exclusively in vertebrates (Donato, 2003). Their name originates from the fact that these

proteins are soluble in 100% saturated ammonium sulfate at neutral pH (Moore, 1965;

Zimmer et al., 1995). The first member of S100 family was identified by Moore et al in

1965 and since then expression of S100 proteins has been demonstrated in a diverse

spectrum of tissues.

The S100 proteins consist of the Ca2+ binding EF-hand motif and have the ability

to form homodimers, heterodimers and oligomers for their physiological functions. EF-

hand motifs are calcium-binding motifs composed of two helixes (E and F) which are

joined by a loop that binds calcium. The S100 proteins have two distinct EF-hands, one

common to all EF-hand proteins on the C-terminal portion and one specific to this family

located at the N-terminus. Next to the C-terminal EF-hand region is a stretch of amino acids which is known as the C-terminal extension. Between the two EF-hand domains is the area known as the hinge. It is the C-terminal extension and hinge areas that have the most variability between the different proteins and hence, this domain is responsible for their specific biological properties (Zimmer et al., 2003). An example of S100 protein

6 member S100B showing the structure and important regions of classic S100 protein is represented in Figure 3.

Figure 3. Structure of the S100 Dimer, (A) Ca2+-free and (B) Ca2+-loaded S100B2 dimer, which is taken as an example for S100 Dimer). S100B monomer is in yellow and the other monomer is in blue. In Roman numerals are Helices, (I-IV in one monomer, and I’-IV’ in the other monomer). Ca2+ binding causes S100B monomer to reorient the helix III in relation to all other helices with reorientation of the hinge region (H), comparing A to B (Drohat et al., 1998).

Members of S100 family of proteins have been shown to possess a broad range of intracellular and extracellular functions ranging from regulation of protein phosphorylation and enzymatic activity, calcium homeostasis, regulation of cytoskeletal components and regulation of transcriptional factors (Salama et al., 2008). One of the

7 common features of S100 family of proteins is their interaction with p53, (Donato, 2003;

Grigorian et al., 2001; Mueller et al., 2005) and they have been shown to exert different effects on p53 activity directly as well as indirectly. Both S100A4 and S100B have been shown to inhibit p53 phosphorylation leading to the inhibition of its transcriptional activity, thereby compromising p53 tumour-suppressor activity whereas S100A2 has been shown to promote p53 transcriptional activity (Mueller et al., 2005). Different functions of S100 protein family including modulation of p53 activity and cellular processes mediated by their interaction have been elucidated in Figure 4.

Figure 4. List of S100 protein family members and their proposed functions

8 Several S100 family members have been shown to play a role in modulating

several cellular processes such as proliferation and metastasis. S100 protein family

members can induce cytoskeletal change whereby they can directly interact with tubulins, intermediate filaments, actin, myosin and tropomyosin (Grigorian et al., 2001).

Cytoskeleton modulations play an important role in the process of cancer metastasis

(Davies et al., 1996; Donato, 2003; Kriajevska et al., 1998). A large number of members

of the S100 family have also been shown to play a role in modulating proliferation, with

both S100A1 and S100A11 shown to inhibit cell proliferation (Donato, 2001) while other

members like S100A4 have been shown to increase cell proliferation. Since most of the

S100 family proteins are secretory proteins, they can exist extracellularly where they act

as leukocyte chemoattractants, macrophage activators and modulators of cell proliferation

(Cornish et al., 1996; Devery et al., 1994; Hiratsuka et al., 2006; Lau et al., 1995; Yen et al., 1997). These functions associate S100 protein family with a variety of pathologies such as inflammation, tumor development and metastasis. Based on their role in cell proliferation, migration, inflammation and immune modulation, it becomes evident that some S100 proteins could act as tumor promoters while others could act as tumor suppressors.

1.3 Psoriasin (S100A7)

Psoriasin also known as S100A7 is a low molecular weight protein found abundantly in keratinocytes. It was originally isolated from skin psoriatic lesions and since its position on gene is mapped to band 1q21, it was thought to play a role in

9 epidermal differentiation and proliferation (Hardas et al., 1996). S100A7 belongs to a family of structurally and functionally related proteins known as S100 proteins. S100 proteins have been shown to play an important role in exerting the effects of calcium on cell growth and differentiation (Salama et al., 2008). The amino acid sequence has revealed one EF hand motif or calcium binding side in S100A7 protein. Sequence comparison with all known human S100 proteins has showed that S100A7 is the most divergent of all of them (Figure 5) with only 25 % identity (Burgisser et al., 1995). In addition to the calcium binding site, S100A7 has been shown to possess zinc binding sites (Brodersen et al., 1999).

While there is no expression of S100A7 in normal skin, S100A7 has been shown to express abundantly in psoriatic plaques and areas of epidermal thickening

(Algermissen et al., 1996). S100A7 is also known to possess anti-microbial properties as expression of S100A7 is induced during E. coli infection which then inhibits the multiplication of E. coli (Glaser et al., 2005). Association of S100A7 with psoriasiform hyperplasia of the skin suggests a role of S100A7 in keratinocyte differentiation (Watson et al., 1998). S100A7 has been shown to express strongly in skin diseases like atopic dermatitis, mycosis fungoides, Darier’s disease, and lichen sclerosus. In all these diseases, S100A7 was more prominent in sections which had perivascular cellular infiltrates but S100A7 expression was not found in areas where there was no inflammation indicating the existence of correlation between inflammation and S100A7

10 expression (Algermissen et al., 1996). It is also reported that S100A7 can act as a

cytokine and helps in recruitment of CD4+ T cells and neutrophils (Jinquan et al., 1996).

Figure 5. Alignment of S100A7 protein with other homologous S100 family proteins. Helices are in red font and calcium binding sites are marked by asterisks (Brodersen et al., 1999).

S100A7 is expressed in both cytoplasm and nucleus and is a secreted protein that is up-regulated in keratinocytes in response to calcium and retinoic acid and during abnormal pathways of differentiation in culture. Psoriasin like other S100 proteins influences calcium mediated signal transduction and cellular events through direct target protein interactions and its targets include intermediate filaments implying a role in modulation of cytoskeleton or intracellular signal transduction (Schafer and Heizmann,

1996). It may also form homodimers or heterodimers which are essential for its

11 physiological functions like other S100 protein family members (Hessian et al., 1993).

S100A7 has a paralog known as S100A15 which is almost identical in sequence and is up-regulated during cutaneous inflammation (Wolf et al., 2008). These paralogs are differentially expressed by different cell types in the skin and they both act as chemo- attractants for leukocyte subsets. Futhermore, S100A7 is known to function through the

RAGE receptor whereas S100A15 exerts its effects through Gi protein coupled receptors

(Wolf et al., 2008).

Apart from psoriasis and skin disorders, S100A7 has been shown to be associated with various cancers such as bladder cancer, gastic cancer, breast cancer etc. The first report of S100A7 association with cancer was with respect to bladder cancer. It was reported that in Squamous Cell Carcinoma (SCC) of bladder, S100A7 expression was detected in squamous cells as well as in the urine and S100A7 expression was found to correlate with non-invasive phenotype (Celis et al., 1996). Later, proteomic analysis by

Ostergaard, (1997) showed that S100A7 is overexpressed in well differentiated bladder tumors of Squamous Cell Carcinoma (SCC) while its expression was reduced in less differentiated SCC tumors. They further showed that S100A7 expression in urine could act as a putative biomarker for follow up in patients with bladder squamous cell carcinomas (Ostergaard et al., 1999). Further, Serial analysis of Gene Expression (SAGE) of gastric cancers revealed the up-regulation of five S100 proteins including S100A7 (El-

Rifai et al., 2002). Since S100A7 expression has been associated with psoriasiform hyperplasia, it was not surprising when Alowami et al (2003) showed that in abnormal

12 epidermis, psoriasin was frequently expressed in abnormal keratinocytes in actinic keratosis, in situ and invasive squamous cell carcinoma. Interestingly, S100A7- overexpression was rarely observed in the basal epidermal layer or in superficial or invasive basal cell carcinoma. The highest levels of S100A7 expression were seen within squamous carcinoma in situ whereas in invasive squamous cell carcinoma, its expression was significantly reduced implying that down-regulation of S100A7 may be related to the onset of invasion in squamous cell carcinoma in skin (Alowami et al., 2003). Further,

S100A7 mRNA expression was found to be significantly up-regulated in samples of precancerous skin lesions, squamous cell carcinoma and basal cell carcinoma of the skin

(Moubayed et al., 2007). S100A7 was the most significantly up-regulated gene of S100 protein family in human esophageal squamous cell carcinoma when detected by RT-PCR

(Ji et al., 2004). All these studies provide evidence, which again strengthens the association of S100A7 and epithelial malignancies and cancers.

The role of S100A7 has also been associated with brain metastasis in lung cancer.

S100A7 expression was significantly up-regulated in the H226Br cell line which is a brain metastasizing cell line of non-small cell lung cancer (NSCLC) (Zhang et al., 2007).

They further showed that S100A7 protein was expressed in 10 brain metastatic tissues from NSCLC and 38 primary NSCLC tissues, again implying the association of S100A7 in lung cancer. In contrast, S100A7 was shown to express only in patient samples of squamous cell carcinoma of the lung and large cell carcinoma but not in adenocarcinomas and small cell lung cancers (Zhang et al., 2008). They further showed

13 that increase in the level of S100A7 protein in serum may serve as a potential marker for lung cancer diagnosis. Aberrant overexpression of S100A7 mRNA and protein was also found in the patient samples of Oral Squamous Cell Carcinomas and the expression was specifically high in well differentiated tumor tissues compared to moderate and poorly differentiated tumor tissues (Kesting et al., 2009).

Recently, there has been an increase in interest in developing mouse models of several diseases and in the context of S100A7., Wolf et al, 2010 developed the first

S100A7 transgenic mouse model in which the expression of S100A7 was under the K5 promoter leading to the overexpression of S100A7 in skin keratinocytes (Wolf et al.,

2010). These transgenic mice showed an elevated inflammatory response when challenged by exogeneous stimuli such as abrasion and the immune response was characterized by immune cell infiltration and increased levels of T helper and Th17 proinflammatory cytokines. Further, these effects were shown to be mediated by RAGE in this mouse model system (Wolf et al., 2010). The above studies show that S100A7- overexpression or expression is associated with various skin diseases and cancers in which S100A7 expression may play a role in pathogenesis of these diseases by regulating inflammatory pathways.

1.4 S100A7 and Breast Cancer

As discussed above, S100A7 expression has been linked to variety of cancers but perhaps, the most studied cancer in relation to S100A7-overexpression is breast cancer.

14 Leygue et al, 1996 identified expression of S100A7 through RT-PCR in the in situ

component compared to the invasive component of the same breast tissue. In the same

study, similar findings were confirmed in 32 breast samples ranging from normal to

invasive type where high expression of S100A7 was noted in DCIS samples indicating its potential role in breast cancer development and progression (Leygue et al., 1996). Moog-

Lutz et al, 1995 detected psoriasin mRNA in human invasive breast cancer cells both in

vivo and in vitro (Moog-Lutz et al., 1995). In that study, psoriasin mRNA was observed

using Northern blot analysis in 17% of the RNA samples from a small series of primary

carcinomas. However, using in situ hybridization, they detected psoriasin expression only

in a small fraction of the invasive cancer cells. In breast cancer, psoriasin expression is

generally restricted to epithelial tissues (Al-Haddad et al., 1999). In the same study, it

was shown that S100A7 correlated with estrogen and progesterone receptor negative

status and with nodal metastasis in invasive ductal carcinomas. Al-Haddad et al, also

found correlation between S100A7 expression and inflammatory infiltrates strengthening the role of S100A7 in inflammation (Al-Haddad et al., 1999). These studies were confirmed by Enerback et al, in which they showed that S100A7 expression is mainly restricted to high grade comedo type DCIS type carcinomas and in estrogen receptor

negative breast cancers (Enerback et al., 2002). Mechanistically, they showed that loss of

attachment to extracellular matrix, growth factor deprivation, and confluent conditions

dramatically up-regulate S100A7 expression in MCF10A mammary epithelial cells.

15 Since S100A7 may modulate calcium induced signaling and act as effector

molecules, there are several molecules, which are known to interact with S100A7 in

breast cancer. Emberley at al demonstrated through yeast two hybrid assays that S100A7 could interact with RanBPM which is widely expressed in tumor tissues compared to normal breast epithelium (Emberley et al., 2002). In the estrogen and progesterone receptor negative breast cancers, there is a high ratio of S100A7/RanBPM expression which implies that their interaction may play an important role in breast tumorigenesis.

Other S100A7 associated mechanisms, which have been proposed to modulate breast tumorigenesis, include interaction of S100A7 with Jab1. The interaction between Jab1

and S100A7 was shown to increase the localization of the Jab1 to the nucleus (Emberley

et al., 2003a). The increase in localization of Jab1, which is a , was

shown to cause increased activity of AP-1 and decrease in the expression of p27kip1.

Moreover, in the same study, it was shown that S100A7-overexpression in MDA-MB-

231 cells increased growth and invasion but led to decrease in cell adhesion properties.

Further, when these S100A7 overexpressing cells were injected into mammary fat pad of

nude mice, there was higher incidence of tumor formation in S100A7 overexpressing

cells compared to control (Emberley et al., 2003b). The increase in tumorigenic

properties of S100A7 in MDA-MB-231 cells was attributed to increased activity of NFκb

pathway, which is a downstream target of Jab1 (Emberley et al., 2004a). Increased

proliferation of MDA-MB-231 cells was also accompanied by increase in expression of

p-AKT (Emberley et al., 2004a). Binding of Jab1 to S100A7 as a tumorigenic step was

confirmed by mutating the Jab 1 binding site of S100A7. The mutated form of S100A7

16 was not able to bind to Jab1 and activate NFκb and AKT (Emberley et al., 2004a).

Higher correlation between p-AKT and S100A7 was also found to exist in breast tissue

samples (Emberley et al., 2005). On analyzing the cohort of ER alpha negative invasive

breast tumors, significant correlation was found between S100A7 and Jab1 (Wang et al.,

2008). They further found that high Jab1 expression in the nucleus coincided with

expression of S100A7 and EGFR. In another study in which S100A7 expression was

analyzed in estrogen receptor negative tumors, S100A7 was found to be expressed in

64% ER negative tumors and S100A7 expression (both nuclear and cytoplasmic) was associated with a shorter time to progression and poor patient survival (Emberley et al.,

2003b). The mechanisms by which S100A7 may influence pro-tumorigenic and inflammatory pathways in ER alpha negative tumors have been summarized in Figure 6.

Figure 6. Proposed mechanisms of S100A7 in estrogen receptor negative breast cancer cells (Emberley et al., 2004b).

17 Since S100A7 has been shown to be associated with breast cancer progression, it

was important to define its transcriptional control in the cells. In this context, Kennedy at

al, showed that S100A7 is one of the BRCA1-repressed targets, whereby wild type

BRCA-1 and C-myc forms complex on a promoter site of S100A7 leading to its

decreased expression (Kennedy et al., 2005). They also showed that mutated BRCA1 was

not able to repress S100A7 and therefore, in breast cancers where BRCA1 is often mutated, it will not be able to repress the S100A7 expression (Kennedy et al., 2005).

They further showed that in presence of mutated BRCA1, etoposide was able to induce

apoptosis in S100A7-overexpressing cells rendering the cells more sensitive to etoposide

induced apoptosis. Thus BRCA1 may lead to the progression of breast cancer by down

regulating S100A7 from DCIS to the invasive stage. When Krop et al., down-regulated

S100A7 in invasive breast carcinoma cell line MDA-MB-468 through shRNA, it increased the migration and invasion of MDA- MB-468 cells but there was no effect on

proliferation and survival in vitro (Krop et al., 2005). In contrast, when the same cells were injected subcutaneously into the nude mice, there was decrease in tumor formation in S100A7 overexpressing MDA-MB-468 cells which showed that S100A7 may have a different role in vitro and in vivo. S100A7 down-regulation was shown to increase

MMP13 and decrease VEGF expression suggesting that in vivo, S100A7 may increase tumorigenesis by increasing angiogenesis (Krop et al., 2005). Other mechanisms that regulate S100A7 include BCL2 and reactive oxygen species. Carlsson et al showed that

S100A7 could be induced by reactive oxygen species and PI3K inhibitor wartamannin

(Carlsson et al., 2005). They further showed that BCL2 overexpression reduces S100A7

18 expression in MCF10 cells and the results were confirmed by using another anti-oxidant

NAC (N-acetyl-cysteine) (Carlsson et al., 2005). These results indicate that S100A7

could be induced by several stresses, which may generate reactive oxygen species, and

anti-oxidant function of BCL2 and other antioxidants could inhibit the expression of

S100A7. They also showed that activation of NFkb is involved in induction of S100A7

since IKKβ inhibitor treatment failed to induce S100A7.

Other transcription factors such as estrogen receptor (ERβ) have also been shown to induce S100A7 expression as well. When Skiliris et al induced ERβ activity after doxycycline treatment; it increased the expression of S100A7 in MCF7 cells (Skliris et al., 2007). Moreover, ERβ and S100A7 expression was found to be correlated in p53 negative invasive breast cancers (Skliris et al., 2007). Cytokines like Interferon gamma, have been shown to down regulate S100A7 expression (Petersson et al., 2007) whereas oncostatin M and IL6 have been shown to induce the S100A7 expression in breast cancer cells in a dose and time dependent manner (West and Watson, 2010). Oncostatin-M and

IL6-induced S100A7 expression was mediated through Stat1, PI3K and ERK1/2, since inhibition of these molecules down modulated Oncostatin- M mediated increase in

S100A7 expression (West and Watson, 2010). Growth factor such as Epidermal Growth

Factor (EGF) has been shown to induce S100A7 expression in a dose dependent manner in both MCF7 and MDA-MB-468 cells (Paruchuri et al., 2008). Moreover, down regulation of S100A7 in MDA-MB-468 cells led to decreased activation of EGFR pathway and decreased angiogenesis (Paruchuri et al., 2008). Gene expression profiling

19 to characterize molecular signatures associated with transformation and cancer progression in a series of isogenic human breast cancer cell lines including a normal, benign, noninvasive and invasive carcinoma revealed that down-regulation of S100A7 was associated with transformation and progression of breast cancer cells (Rhee et al.,

2008). This implies that overexpression of S100A7 may confer tumor suppressive properties and in this regard, it has been shown that S100A7 down regulates β- catenin/TCF pathway in MDA-MB-468 cells (Zhou et al., 2008) which then can lead to decreased growth and metastasis.

1.5 β-Catenin/TCF 4 Pathway

The β-catenin/TCF4 pathway is a component of the in which Wnt ligands binds to Frizzled receptors (Bhanot et al., 1996; He et al., 1997;

Yang-Snyder et al., 1996) and LRP5/6 co-receptors (Pinson et al., 2000; Tamai et al.,

2000) and initiate a signal transduction pathway which involves stabilization of β-catenin.

Stabilization of β-catenin and its translocation to the nucleus enhances its transcriptional activity that leads to increased cell proliferation and differentiation (Luu et al., 2004).

Several studies have shown that activation of the Wnt/β-catenin signaling pathway plays an important role in human tumorigenesis (Behrens, 2000; Polakis, 1999; Waltzer and

Bienz, 1999). Wnt/β-catenin signaling is involved in many developmental processes and several components of this pathway are evolutionarily conserved among Drosophila,

Dictyoselium, C. elegans, Xenopus and mammals. Wnt signaling plays critical roles in cell fate specification, tissue patterning and cell division during developmental processes

20 (Willert and Nusse, 1998; Wodarz and Nusse, 1998). Canonical Wnt/β-catenin signaling is only activated when both Frizzled and LRP 5/6 receptors and co receptors respectively bind to wnt ligands. Upon binding of a wnt ligand, the scaffold protein Axin translocates to the cell membrane where it interacts with the intracellular domians of the LRPs resulting in destabilization of Axin and activation of β-catenin activity. At the same time, wnt binding to frizzled receptor leads to the phosphorylation of the disheveled protein

(Noordermeer et al., 1994) which forms the complex with APC (Tumor suppressor) and

Axin (Zeng et al., 1997) and prevents phosphorylation of β-catenin by GSK3β

(Dominguez et al., 1995; Groden et al., 1991; He et al., 1995; Sakanaka et al., 1998).

Unphosphorylated β-catenin is stabilized as it cannot be recognized by TrCP that is a component of an E3 ubiquitin ligase and thus β-catenin cannot be ubiquitinated and degraded. Stabilized β-catenin then translocates into nucleus where it binds to transcription factor TCF4 and activates expression of downstream genes such as c-myc, cyclin d1, c-jun, mmp7 etc. (Behrens et al., 1996; Molenaar et al., 1996).

Apart from acting as a transcription factor, β-catenin also plays a crucial role in mediating cell–cell adhesion. β-catenin was originally identified as a cytoplasmic protein that was shown to interact with cell adhesion molecules such as E-cadherin (Willert and

Nusse, 1998). Several cellular proteins have been identified to bind to β-catenin directly or indirectly and in normal cells, the majority of β-catenin is localized in cell-cell junctions with some in cytoplasmic or nuclear fraction due to the rapid turnover of β- catenin promoted by APC/Axin/GSK3β-complex. β-catenin expression and signaling is

21 regulated both in a Wnt dependent and independent manner. Its signaling is negatively regulated by TCF (T-Cell Factor), Groucho, ICAT (inhibitor of β-catenin and TCF4), and

HBP (histone hairpin binding protein) (Levanon et al., 1998; Roose et al., 1998; Sampson

et al., 2001; Tago et al., 2000). Other proteins that target components of β-catenin

pathway such as Axin and disheveled proteins include PP2A and Casein kinases 1 and II.

PP2A can dephosphorylate Axin whereas Casein kinases phosphorylate serine 45 of β- catenin which primes it for subsequent phosphorylation by GSK3β (Liu et al., 2002; Song et al., 2000). Alternatively, β-catenin may also be phosphorylated by Siah/Sip1 which forms a complex with APC (Liu et al., 2001). β-catenin may also be activated by Wnt independent mechanisms in mammalian cells by G-proteins, HGF (Hepatocyte Growth

Factor), IGF (Insulin Growth Factor) and Vascular Endothelial Growth Factors (VEGF)

(Carmeliet et al., 1999; Hiscox and Jiang, 1999; Playford et al., 2000). Figure 7 summarizes the β-catenin pathway and its components in a schematic diagram.

Figure 7. Schematic representation of β-catenin/TCF4 pathway (Luu et al., 2004).

22

1.6 β-Catenin/TCF4 Pathway and Tumorigenesis

β-catenin was first associated with cancer in colorectal cancers where it was found

to form a complex with APC tumor suppressor (Rubinfeld et al., 1993). Further, the

oncogenic role of β-catenin in cancer progression was strengthened when mutations were

found in β-catenin gene in colon cancers (Rubinfeld et al., 1997). The mutant form of β- catenin is more stable and always active leading to the up-regulation of proliferation causing genes like c-myc and cyclin D1. These mutations generally occur at the phosphorylating sites of GSK3β and do not allow GSK3β to phosphorylate β-catenin leading to its degradation (Luu et al., 2004). Mutations in β-catenin gene were also discovered in several cancers such as melanoma, hepatocellular carcinoma, prostate cancer, ovarian cancer etc (Luu et al., 2004). The overexpression of cyclin D1 which is a downstream factor of β-catenin activation has been found in 60% of breast cancer patients (Suarez, 1989; Zhang et al., 2007). In most cancers, β-catenin expression is increased in cytoplasmic as well as nuclear fractions (Luu et al., 2004).

Owing to its role in tumorigenesis, it becomes important to target β-catenin directly or its components for the treatment of cancer. In this context, a recombinant adenovirus was constructed to constitutively express APC and when this adenovirus was expressed in colon cancer cells, it blocked the nuclear translocation of β-catenin and inhibited the β-catenin/TCF4 pathway (Shih et al., 2000). Similarly, adenovirus mediated gene transfer of wildtype Axin-1 (a tumor suppressor) induced apoptosis in

23 hepatocellular and colorectal cancer cells that had accumulated β-catenin as a

consequence of either APC, CTNNB1 or Axin-1 mutation (Satoh et al., 2000). Other than

targeting negative regulators of β-catenin, it is also possible to directly target β-catenin or its downstream targets. In this regard, several approaches have been employed which include anti-sense, RNA interference (RNAi) and protein knockdown strategies. Two published papers evaluating the use of antisense oligonucleotides in colon cancer showed that the oligonucleotides decreased β-catenin mRNA in a dose dependent manner, as well as decreased protein levels, TCF transcription, and Cyclin D1 expression (Green et al.,

2001; Roh et al., 2001). There was also a reduction in cell proliferation, invasiveness and anchorage-independent growth. Therapeutic potential of RNAi has also been tested against β-catenin. siRNA expression in LS174T colon cancer cells by an inducible vector system decreased TCF transcription, increased G1 cell cycle arrest and cell differentiation

(van de Wetering et al., 2003). Similarly, when β-catenin was knocked down using siRNA approach in 293 and Hela cell lines, it decreased the TCF transcription and colony formation ability of cancer cells (Verma et al., 2003).

Other strategies include knocking down β-catenin at protein levels. Cong et al engineered a chimeric protein with the β-catenin binding domain of E-cadherin fused to

β-TrCP ubiquitinating protein ligase which recruited β-catenin to the cellular ubiquitin machinery for degradation (Cong et al., 2003). This degradation of β-catenin then led to decrease in growth and clonogenic ability of cells in vitro and decreased tumorigenic potential in nude mice. Small molecule inhibitors have also been used to target β-catenin

24 mediated transactivation. A small molecule that inhibited cyclic AMP response element binding protein (CBP), a p300 related co-activator of β-catenin/TCF complex selectively targeted colon cancer cells and reduced growth both in vitro and in vivo (Emami et al.,

2004). Another strategy to utilize β-catenin/TCF pathway in cancer treatment is to target downstream targets of this pathway such c-myc, c-, cox-2, cyclin D1 etc. c-Myc is an oncogene overexpressed in a variety of human cancers including melanoma, leukemia, and prostate, breast, and colon carcinomas (Dang, 1999). An anti-sense drug AVI 4126 targeted against c-myc showed significant decrease in growth and increase in apoptosis that it was used in phase 1 clinical trials (Iversen et al., 2003). Another downstream molecule of the β-catenin pathway, which is a suitable target is cyclin D1. Cyclin D1 is transcribed by the β-catenin/TCF complex and Cyclin D1 complexes with cyclin dependent kinases CDK4 and CDK6 to phosphorylate retinoblastoma (Rb), which promotes histone acetylation and gene transcription. Cell cycle progression is tightly regulated by the cyclin dependent kinases and the cyclins. CYC202 (R-Roscovitine) is a cyclin dependent kinase inhibitor and its treatment decreased cyclin D1 and Rb phosphorylation in HT29 and KM12 colon cancer cells (Whittaker et al., 2004).

Another component of β-catenin pathway is E-cadherin and loss of E-cadherin has been shown to decrease cell adhesion and contribute to tumor invasion, metastasis and cancer progression in many malignancies (Potter et al., 1999). Cadherins are transmembrane glycoproteins located in the plasma membrane of cells. Most of them mediate calcium-dependent cell-cell adhesion predominantly through homophilic

25 interaction of their extracellular domains (Behrens et al., 1996; Liu et al., 1999; Molenaar et al., 1996; Polakis, 1999). E-cadherin has been shown to bind to β-catenin and the catenin binding region of E-cadherin has been mapped to the terminal 72 amino acids

(Hoang et al., 2004). This region has been shown to contain serine residues for phosphorylation. Casein kinase II has been hypothesized to phosphorylate these residues

(Harada et al., 1999) and this phosphorylation has been shown to be important for β- catenin binding. Since, the β-catenin/TCF pathway and its components play an active role in tumorigenesis and metastasis, their targeting may be of high therapeutic value. A body of literature assigns the role of E-cadherin as both a tumor suppressor and an invasion suppressor. In addition, recent progress indicates that alterations in the cadherin-catenin system related to catenin signaling may be causally involved in tumorigenesis.

Understanding how the E-cadherin-β-catenin system participates in the multistep process of tumorigenesis will lead to the development of new molecular diagnostic tools and therapeutic strategies.

1.7 Expression of p53 and its Role in Cancer

P53 was discovered by A. Levine, P. May and L. Old in 1979 and is encoded by the TP53 gene located on the short arm of chromosome 17 (17p13.1). Its sequence is about 20 Kb and contains 11 exons, but the first exon does not and is located about 10 Kb from other exons (Lacroix et al., 2006). The p53 protein contains 393 amino acids (AA) and is composed of: (i) an N-terminal region (AA 1–42), (ii) a proline rich region (AA 63–97) which is involved in the induction of apoptosis, (iii) a DNA

26 binding core domain (AA 102–292), (iv) a tetramerization domain (AA 323–356), and

(v) a C-terminal region (AA 363–393). This C-terminal region of p53 binds to the N- terminal domain of MDM2 (murine double minute 2) and the core domain of p53 contains the most of the inactivating mutations found in different types of human cancers

(Soussi et al., 1990). In addition, there are sequences for exporting to the cytoplasm at the

N- and C-terminal ends (NES, nuclear export signal), as well as nuclear localization sequences at the C-terminal end (NLS, nuclear localization signal), enabling the regulation of subcellular localization of p53 (Lohrum et al., 2001; Poyurovsky et al.,

2010). The association of p53 with cancers was demonstrated in 1989 by Vogelstein's team (Vogelstein, 1990).

P53 is known as the guardian of the genome and it functions as a transcription factor by binding to specific DNA sequences and activating or repressing plethora of target genes. The downstream targets of p53 regulate the pathways of cell cycle arrest, apoptosis and DNA repair to maintain a dynamic equilibrium between cell growth and arrest in response to factors including DNA damage, hypoxia and starvation (Ryan,

2011). In normal tissues, p53 is expressed at very low levels so that there is not much effect on cell cycle, which may cause premature or untimely death of cells. Under normal condition, the optimum levels of p53 are maintained in cells by a negative feedback loop consisting of wild-type p53 and MDM2. MDM2 is a downstream transcriptional target of p53 and binding of MDM2 to p53 initiates the ubiquitination of p53 leading to the proteasomal-mediated degradation. However, in response to various forms of stresses

27 such as DNA damage, UV radiation or some kind of oncogenic signal, p53 gets stabilized and accumulates in nucleus, where it regulates the transcription of numerous target genes using specific DNA response elements resulting in cell cycle arrest, senescence or apoptosis through activation of genes such as p21, Bax, PUMA (p53 upregulated modulator of apoptosis), etc (Ryan, 2011).

The protein p53 can be regulated at different levels: (i) by posttranslational modifications, such as phosphorylation, sumoylation, or acetylation, (ii) by increasing the protein concentration, (iii) by cellular localization; import and nuclear export is closely regulated because the functions of p53 depend on its nuclear localization (Varna et al., 2011). Efficient transfer to the cytoplasm depends on MDM2 forming a complex with p53, which is why ubiquitin ligase activity of MDM2 is essential for nuclear export of p53. The ubiquitination of p53 by MDM2 occurs in the C-terminus domain, and it has been shown that mutations in lysine residues inhibit the nuclear export of p53 by MDM2

(Poyurovsky et al., 2010; Toledo and Wahl, 2006). The regulation of p53 and its downstream targets have been summarized in Figure 8.

28

Figure 8. Schematic representation of p53 activation and cellular processes mediated by its activation.

TP53, the gene, which encodes p53 has been found to be frequently inactivated in

several human malignancies such as cancer. It has been shown that more than 50% of

human tumors harbor mutant or nonfunctional forms of p53 that accumulate to high

concentrations in tumor cells (Soussi, 2007). About 95% of the cancer-associated

mutations in p53 occur in the thermally unstable central core DNA binding domain of the

protein which results in destabilization of the structure, abrogation of DNA binding, and

impairment of the p53 response (Bullock et al., 1997). Three types of p53 mutants have been described: (a) dominant negative mutants (Mildner et al. 1996) that inhibit the suppressive function of the residual wild-type p53 protein; (b) loss of function mutants

(Lohrum et al.) that lack suppressive function; while (c) gain of function mutants (GOF) that exhibit oncogenic properties through an array of mutant specific activities including

29 aberrant protein interactions or gene regulation. In breast cancers, TP53 mutations are found in about 30% of the cases and are associated with poor prognosis and resistance to doxorubicin treatment (Pusztai et al., 2006). The expression signatures of mutant TP53 status have been shown to include genes involved in the estrogen receptor pathway and in the control of cell proliferation which suggests a close link between p53 and estrogen receptor pathways (Goldstein et al., 2011). Recent evidence has shown that inactivation of p53 may impact tumor progression by altering cell migration and invasion as well. It is also becoming evident that mutant form of p53 may not only become transcriptionally inactive but may also acquire gain of function driving cell migration and metastasis

(Muller et al., 2011).

The wild type or mutated status of p53 has been associated with the prognosis, progression and therapeutic response of tumors. Tumor cells containing wild-type p53 are usually more sensitive to radiotherapy or chemotherapy than those bearing mutant p53.

Therefore, re-activation of wild type 53 could be one of the strategies for tumor therapy.

Several approaches have been proposed to restore or re-activate wild-type p53 function

(Mandinova and Lee, 2011). Gene therapy studies which involved introduction of wild- type p53 expression via local injection of adenovirus at the tumor site killed a high percentage of cancer cells but this strategy also resulted in high toxicity because of strong bystander effects (Roth, 2006). Another strategy to activate p53 included the use of small molecules to activate endogenous p53 in which cells harbor wild type form. The basis of this strategy is to inhibit the association between p53 and its negative regulators such as

30 MDM2. Vassilev and colleagues have identified a group of small molecules called

nutlins that target the MDM2-p53 interaction by specifically binding and dissociating

MDM2 from p53, thereby rescuing p53 from degradation and inducing cell cycle and apoptosis (Vassilev et al., 2004). Nutlins have been shown to be effective even in in vivo

studies. Another class of small molecules which inhibit MDM2 and p53 interaction

includes benzodiazepines and spiro-oxindole based compounds such as TDP665759 and

MI-319. Both of these compounds were shown to be effective in limiting tumor growth

both in vitro and in vivo (Ding et al., 2006; Grasberger et al., 2005).

1.8 Actin Cytoskeleton and its Role in Cancer

Cell migration requires consistent forward movement of the plasma membrane at

the cell's front or leading edge. Cells extend four different plasma membrane protrusions

at the leading edge: lamellipodia, filopodia, blebs, and invadopodia (Ridley, 2011). Each

of these structures uniquely contributes to migration depending on the specific

circumstances. For example, lamellipodia can extend long distances through the

extracellular matrix in vivo, pulling cells through the tissues (Friedl and Gilmour, 2009).

As shown in Figure 9, many different molecules and signaling pathways coordinate cell

migration, but the actin cytoskeleton and regulators of actin dynamics are involved in all

protrusions. Each actin regulator, in turn, is controlled by several signaling molecules,

usually including a Rho GTPase, membrane phospholipids, and protein phosphorylation.

Using biosensors, active Rac1, RhoA, and Cdc42 have been shown to localize in

lamellipodia during protrusion (Machacek et al., 2009). Activation of Rac1 by itself,

31 using a photoactivatable Rac1, is sufficient to induce lamellipodium extension (Wu et al.,

2009). Rho GTPases can be activated by multiple growth enhancing factors at the leading

edge, depending on the cell type and extracellular stimulus (Buchsbaum, 2007). RhoG

can also induce lamellipodia formation through an unknown Rac-independent pathway

(Meller et al., 2008). Regulated localization of Rho GTPases is also important for their

function. Rac is known to be recruited to the plasma membrane at the leading edge

through vesicle trafficking (Donaldson et al., 2009), and multiple phosphorylations alter

RhoGDI binding to Rho GTPases (Harding and Theodorescu, 2010).

Figure 9. Overview of breast cancer cell motility (Jiang et al., 2009)

Rac has been shown to activate the pentameric WAVE complex, but it is currently unknown whether there is any difference in the ability of the three Rac isoforms, Rac1,

Rac2, and Rac3, to interact with the complex (Takenawa and Suetsugu, 2007). Structural

32 analysis of the WAVE complex indicates that the C-terminal WCA domain of WAVE, which activates the Arp2/3 complex, is normally sequestered within the complex. It is predicted that Rac binding would induce structural rearrangements to allow the WCA

domain to become accessible on the surface (Chen et al., 2010). Rac target PAK (p21-

activated protein kinase) has also been shown to be involved in regulating the delivery of

WAVE2 to the plasma membrane (Takahashi and Suzuki, 2009). Rac also induces the

assembly of focal complexes and actin polymerization during the formation of

lamellipodia in non-metastatic (MCF-7, T47D) or moderately metastatic (Hs578T) breast

cancer cell lines. It has been shown that Rac1 inhibition resulted in effective inhibition of

migration, whereas in highly metastatic cell lines (MDA-MB-435, MDA-MB-231, and

C3L5), Rac1 inhibition stimulated cell migration (Zuo et al., 2006). In highly metastatic

cells, Rac1 inhibition was accompanied by enhanced RhoA activity, suggesting that

RhoA dominates Rac1 in regulating the intrinsic migration of these cells (Zuo et al.,

2006).

Another molecule, which is downstream of Rac and is directly involved in actin

polymerization, is cofilin. Cofilin/ADF is inhibited by phosphorylation, by binding to

phosphatidylinositol 4,5-bisphosphate, and by increased pH (van Rheenen et al., 2009).

Cdc42 and Rac act through their targets PAK and LIMK to phosphorylate and decrease

the activity of cofilin (Bernard, 2007), although RhoA/ROCK can also phosphorylate and

inhibit cofilin/ADF (Bernard, 2007). Both PAK and ROCK have been shown to regulate

cofilin phosphorylation at the leading edge (Delorme et al., 2007). The Rac target

33 NADPH oxidase, which generates reactive oxygen species (ROS), has also been implicated in lamellipodia (Nimnual et al., 2003). One possible mechanism whereby ROS could contribute to lamellipodia is through cofilin; ROS lead to cofilin dephosphorylation through activation of the cofilin phosphatase Slingshot (Kim et al., 2009). Metastasis is commonly seen in breast cancer patients and it accounts for over 90% of their deaths.

Tumor cell motility is the hallmark of invasion and is an initial step in metastasis

(Mehlen and Puisieux, 2006). Therefore, studying the motility mechanisms utilized by cancer cells would clarify some of the key events influencing metastasis in breast cancer.

In addition, identification of the molecular pathways that play a role in breast cancer cell motility will provide new diagnostic approaches and targets for the treatment of metastatic breast cancer.

1.9 Objectives of the Study

All previous studies, which have attempted to analyze the role of S100A7 in breast cancer, have focused on ER negative cells such as MDA-MB-231 and MDA-MB-

468 breast cancer cells. The current body of literature also implies that there is a differential expression of S100A7 in breast cancer samples since its expression in ER

negative breast cancer is associated with worst prognosis whereas if S100A7 is expressed

in ER positive tumors, it is not associated with worst prognosis. We hypothesize that

S100A7 may have tumor suppressive effects in ERα+ breast cancers. Therefore, we

carried out the present study to enhance our understanding of role of S100A7 in breast

34 tumorigenesis and to determine the molecular mechanisms associated with S100A7 expression specifically in estrogen receptor positive breast cancers.

35

CHAPTER 2

MATERIALS AND METHODS

2.1 Cell Culture, Reagents and Antibodies

Human breast carcinoma cell lines MCF7, T47D, and MDA-MB-231 obtained

originally from American Type Culture Collection (Manassas, VA) were grown in

DMEM (Dulbecco's Modified Eagle Medium) medium (Invitrogen, Carlsbad, CA) supplemented with 10% fetal bovine serum and 1% Penicillin Streptomycin (Invitrogen).

To determine the expression of ER alpha, MCF7 and T47D cells were cultured in phenol free DMEM supplemented with 5% charcoal treated fetal bovine serum and 1%

Penicillin-Streptomycin. The cells were incubated in incubators at 37°C and 5% carbon

dioxide and allowed to grow until the experiments were performed. Cell lines were

discarded after twenty passages and new cells were thawed for further experiments.

GSK3β inhibitor – CHIR 99021 was purchased from Stemgent, MA. Antibodies used were S100A7 (IMGENEX); β-catenin, Phospho-β-catenin, Phospho- GSK3β, GSK3β,

ATR, Phospho-p53 (Ser 15), Phospho-Chk1 and Phospho-Chk2, secondary mouse and

rabbit antibodies (Cell Signaling); and GAPDH, and p53 (Santa Cruz Biotechnology); E-

cadherin (Abcam); TCF4 and active β-catenin (Millipore); Ki67 (Neomarker) and CD31

36 (BD Pharmingen). All the antibodies were used at 1:1000 dilutions for primary antibodies

and 1:20000 for secondary antibodies.

2.2 Constructs and Transfections

The open reading frame (ORF) clone of Homo sapiens- S100A7 homolog was purchased from OriGene Technologies Inc. (Rockville, MD) and subcloned into pIRES2-

EGFP (Invitrogen). MCF7 and T47D cells were transfected with pIRES2-EGFP plasmid alone or containing S100A7 with lipofectamine according to manufacturer’s Protocol

(Invitrogen). After 24 h of transfection, cells were incubated for 3 weeks in medium containing G418 (500 μg/ml) to select the stably over-expressing S100A7 clones.

S100A7 expression in cells was analyzed by Western blotting. Vector and S100A7 transfected ERα+ cells, hereafter are termed as MCF7/Vec, T47D/Vec and

MCF7/S100A7, T47D/S100A7, respectively. TCF4 was transfected in MCF7/S100A7 in

pcDNA3.1 vector using lipofectamine according to manufacturer’s recommendations.

For siRNA studies, MCF7/Vec and MCF7/S100A7 cells were transfected with siRNA

smart pool (Dharmacon) against GSK3β using lipofectamine according to manufacturer’s

recommendations. siRNA was used at 100 nM and 200 nM concentrations to observe the

dose dependent effects. Scrambled non-targeting siRNA (200 nM) was used as control.

The cells were harvested 48 h after transfection and GSK3β; p-β-catenin and β-catenin

protein levels were determined by immunoblotting.

37 2.3 Proliferation Assay

The number of proliferating cells was determined by the MTT assay (ROCHE), which measures the reduction of 3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide to purple formazan by mitochondrial reductase of living cells. Briefly, 5x103 cells were seeded in 96-well tissue-culture plates after trypsinization and counting. Next day, 10 µl MTT was added to each well and incubated for 4 h at 37 ºC and 5% carbon dioxide. After 4 h, 100 µl of MTT solvent or solublization buffer was added and incubated overnight. Next day, the readings were measured at 570 nm using ELISA plate reader. The proliferation of the cells was measured at different days as a percentage increase in the absorbance reading at 570 nm with respect to the control (day 0). In the case of GSK3β inhibitor – CHIR 99021 (2 µM), the cells were serum starved before adding the inhibitor.

2.4 Chemotaxis Assay

Serum and EGF-induced chemotaxis in MCF7/Vec and MCF7/S100A7 was measured using 2-chambered 8 μm transwell plates. 5 X 104 cells were seeded in

duplicates in fibronectin (5ng/ml) coated upper chambers and 600 μl of 1% serum or

EGF (100 ng/ml) containing media was added to the lower chamber. The migrated cells

were stained using Hema stain and counted under the light field microscope.

38 2.5 Wound Healing Assay

The wound-healing assay allows us to study cell motility and cell interactions.

The basic principle of the assay is that, a “wound gap” in a cell monolayer is created by

scratch and the “healing” of this gap by cell migrating and growth towards the center of

the gap is monitored. The cell motility of MCF7/Vec and MCF7/S100A7 was analyzed

using this “Wound Healing Assay.” About 90% confluent cells in 6-well plates were

serum starved, then a uniform scratch was made in the middle and cells were treated with

Serum 1% and EGF (100 ng/ml). Cells were incubated at 37°C and the wound invasion

was monitored for 36 h and images were taken under phase contrast microscope at 4X

magnification.

2.6 Western Blotting

70-80% confluent cells were cultured or serum starved for 5 h prior to stimulation

(in case of EGF treatment) at 37°C. After treatment, the cells were washed, lysed and

protein concentration was measured using Bradford Reagent KIT (BioRad). Then 50 µg protein was loaded on to NuPage Bis Tris 4-12% gradient gels (Invitrogen) and the proteins were transferred to nitrocellulase membrane using semi-dry transfer at 17 V for

2 h. The membrane was blocked using 5% milk for 30 min and incubated with respective primary antibodies (1:1000 dilutions) overnight at 4°C. Then membranes were washed with 1X TBST thrice for 10 min, incubated with HRP conjugated secondary antibody for

1 h at room temperature after which the membranes were washed thrice with 1XTBST and developed using ECL reagent (Amersham bioscience).

39 2.7 Co-Immunoprecipitation

Co-immunoprecipitation was carried out with 500 µg of cell lysate which was

first cleared using Protein G plus A agarose beads (Invitrogen) with agitation at 4°C for

30 min. Then the cleared supernatant was incubated with primary antibody overnight at

4°C with constant agitation. Next day, the slurry of Protein G plus A agarose beads was added to the cell lysate for 4 h. Then the 2x lamelli reducing buffer was added to the beads after centrifugation, washed twice with 1X PBS and then the samples were subjected to SDS PAGE, as mentioned above.

2.8 Confocal Microscopy

The cells were cultured in chamber slides and fixed in 4% paraformaldehyde for

15 min at room temperature. The cells were washed thrice with 1X PBS, blocked with

5% BSA in 1X PBS/Triton for 60 min, and treated with mouse anti-E-cadherin, rabbit anti-β-catenin antibody, mouse anti-S100A7, rabbit anti-p53, rabbit anti-phospho-p53

(Ser15) or Phalloiden - 568 overnight at 4°C. The slides were washed thrice with 1X PBS

and stained with Alexa Fluor 488-labeled anti-mouse and Alexa Fluor 594-labeled secondary IgG antibodies. The cells were then washed thrice in 1X PBS, and slides were

mounted using vectashield medium with DAPI. The cells were then examined under

Olympus FV1000 Filter confocal microscope, and the images were acquired and

quantified using FV10-ASW2.0 software.

40 2.9 TCF4 Luciferase Reporter Assay

β-catenin/TCF4 pathway activity was determined using TCF4 luciferase reporter

assay. To determine luciferase reporter activity, TCF luciferase constructs (0.5 μg),

containing the wild-type (pTOPFLASH) or mutant (pFOPFLASH) TCF binding sites,

were transfected into MCF7/Vec and MCF7/S100A7 (2 × 105) using Lipofectamine. In

addition, the cells were co-transfected with an internal control (0.1 μg of pRL-TK Renilla

luciferase vector). The cells were incubated for 48 h after the transfection and then

treated with EGF for 24 h. The cells were then lysed and luciferase activity was measured

using flourometer. The experiment was repeated three times to confirm the results.

2.10 Microarray Analyses

Total RNA from MCF7/Vec and MCF7/S100A7 cells was extracted using

TRIZOL reagent (Invitrogen), per the manufacturer's protocol. Microarray analysis was

performed at The Ohio State University Medical Center genomics core facility by using an Affymetrix Microarray U133 chip containing 40,000 genes.

Microarray data was also analyzed by ingenuity pathway analysis (IPA). For gene expression study, signal intensities were quantified by Affymetrix Expression Console software. Background correction and quantile normalization was performed to adjust technical bias, and gene expression levels were summarized by RMA method. A filtering method based on percentage of arrays above noise cutoff was applied to filter out low

expression genes. Linear model was employed to detect differentially expressed genes.

In order to improve the estimates of variability and statistical tests for differential

41 expression, a variance smoothing method with fully moderated t-statistic was employed for this study. The significance level was adjusted by controlling the mean number of false positives.

2.11 Quantitative Real Time Polymerase Chain Reaction (qRT-PCR)

RNA was extracted from S100A7-overexpressing and vector control MCF7 cells using the TRIzol (Invitrogen) method. Reverse transcription was performed to produce cDNA for both type of cells and quantified using Nano-drop spectrophotometer. Real

Time PCR with SYBR Green was then performed to validate the targets of beta- catenin/TCF4 pathway such as β-catenin, GSK3β, Cyclin D1 and E-cadherin. The primers used for Real Time PCR have been listed in Table 1.

42 2.12 Xenograft Mouse Model

Female nude (nu/nu) mice, obtained from Charles River Laboratories

(Wilmington, MA), were housed under specific pathogen-free conditions. The in vivo

experiments were performed in accordance with the guidelines of our Institutional

Animal Care and Use Committee, ULAR (University lab Animal Research). MCF7/Vec

and MCF7/S100A7 (3 × 106 cells/200 μl PBS) were injected subcutaneously into the

right flank of each mouse. The mice were also injected subcutaneously with 2.5 μg of β- estradiol 17-valerate in 50 μl of Sesame oil once a week. Tumor size was assessed once a week and tumor volume was calculated using digital calipers according to the formula:

volume = length x (width)2/2. The tumors were excised, fixed in formalin and paraformaldehyde to obtain frozen and paraffin embedded sections, which were further

subjected to immunohistochemical analyses.

2.13 Immunohistochemistry (IHC)

Immunohistochemistry was performed on 4-µm sections from frozen tumor

xenografts of mice. Dissected tumors were fixed in 4% paraformaldehyde for 18–24 h

and then embedded in OCT (Tissue-Tek, Torrance, CA). Standard immunohistochemistry

techniques were used as per the manufacturer’s recommendations (Vector Laboratories,

Burlingame, CA) using the primary antibody against Ki 67 (Neomarkers, Fremont, CA) at a dilution:1/100, CD31 (BD Pharmingen, Franklin Lakes, New Jersey) at a 1:50

dilution, Cyclin D1 (1:100 dilution), E-cadherin (1:100 dilution) and β-catenin (1:50 dilution) for 60 min at RT. Vectastain Elite ABC reagents (Vector Laboratories,

43 Burlingame, CA) using avidin DH:biotinylated horseradish peroxidase H complex with

3,3'-diaminobenzidine (Polysciences, Warrington, PA) and Mayer’s hematoxylin (Fisher

Scientific, NJ) was used for detection of the bound antibodies. The nuclei for Ki67

staining and CD31 expression in vessels was quantitated in 5 random microscopic (x10)

fields per tumor.

2.14 Rac1 Activation Assay

The Rac activation was determined by using the Rac/Cdc42 activation assay kit

(Millipore). In brief, the cell lysates of MCF7/vec and MCF7/S100A7 were incubated

with 10 µg/ml p21-activated kinase (PAK)-1 agarose beads for 60 min at 4°C, according to the manufacturer’s protocol. Agarose beads were collected by centrifugation, followed by denaturation, boiling of the samples, and an equal amount of protein was loaded onto

SDS-PAGE analysis. Proteins were transferred to nitrocellulose membranes, and Western

blotting was performed by using murine anti-human Rac antibody.

2.15 Real Time p53 PCR Array

The Human p53 Signaling Pathway RT² Profiler™ PCR Array (SABiosciences,

USA) profiles the expression of 84 genes related to p53-mediated signal transduction.

The array included p53-related genes involved in the processes of apoptosis, the cell

cycle, cell growth, proliferation, and differentiation, and DNA repair. Using real-time

PCR, we analyzed the expression of a focused panel of genes related to p53 signaling

pathway with this array. The PCR array performs gene expression analysis with real-time

44 PCR sensitivity and the multi-gene profiling capability of a microarray. We isolated the

total RNA from S100A7 overexpressing and vector control MCF7 cells and converted

into cDNA using BioScience kit. cDNA template was then mixed with ready-to-use PCR

SYBR GREEN master mix, and equal volumes were aliquoted to each well of the same plate, and then real time PCR was performed according to the manufacturer’s recommendations.

2.16 Generation of Transgenic Mice

TetO-mS100A7A15 mice (Wolf et al., 2010) were cross-bred with MMTV-rtTA

(provided by Dr. Chodosh) mice to generate bi-transgenic MMTV-mS100A7A15 mice.

Transgenic littermates were genotyped by PCR using tetO-mS100A7A15 primers.

Female mice were fed with Dox-chow 1g/kg (Harlan laboratories) and mice fed with normal diet served as controls. P53-/+ mice were obtained from Dr. Schular (Wisconsin

University) and were crossbred with above generated MMTV-rtTA/mS100A7A15 to obtain MMTV-rtTA/mS100A7A15/ P53-/- mice. All transgenic and knockout mice were

kept at The Ohio State University animal facility in compliance with the guidelines and

protocols approved by the IACUC.

2.17 Whole-mount Analysis of Mammary Glands

Right inguinal mammary glands (LeClaire et al.) #4 were spread on glass slides,

fixed and stained overnight with 0.2% (w/v) carmine (Sigma) and 0.5% (w/v) aluminum

sulfate (Sigma) as described (Trimboli et al., 2009).

45 2.18 Statistical Analyses

All the experiments were repeated three or four times to confirm the results. The

results were then expressed as the mean ± SD of data obtained from these three or four

experiments performed in duplicates or triplicates. The statistical significance was determined by the Student’s t-test and value of p<0.05 was considered significant as denoted by asterisks, *.

46

CHAPTER 3

RESULTS

3.1 S100A7-overexpression decreases growth in ERα+ cells both in vitro and in vivo.

3.1.1 S100A7-overexpression reduced proliferation in MCF7 and T47D cells in vitro

To determine the role of S100A7 on tumorigenic properties of ERα+ cells, we

transfected pIRES2-EGFP-S100A7 and pIRES2-EGFP alone in ERα+ MCF7 and T47D

cells as well as ERα- MDA-MB-231 cells. High expression of S100A7 was observed in

stably S100A7 transfected MCF7 and T47D cells compared to vector control by Western

blotting (Figure 10A). We found that S100A7-overexpression significantly decreased

serum-induced proliferation by ~50% in MCF7 and T47D cells (Figure 10B and 10C)

for all the time periods. Further, when S100A7 was overexpressed in ERα- MDA-MB-

231, we observed increased in proliferation compared to vector control cells (Figure

10D). These data are in concordance with previous studies where it has been shown that

S100A7 increases proliferation of MDA-MB-231 through activation of AKT and NF kB

pathway. Therefore, our data supports that S100A7-overexpression in ERα+ cells significantly inhibits the proliferative properties of ERα+ cells and may have a differential

47 role in ERα+ and ERα- cells. In this study, we concentrated on ERα+ cells to further determine the tumorigenic mechanisms mediated by S100A7 expression.

Figure 10: S100A7-overexpression reduces proliferation in ERα+ cells. (A) S100A7 expression was analyzed in S100A7-overexpressing MCF7 and T47D and vector control cells by western blotting with anti-S100A7 antibody. GAPDH was used as a loading control. (B and C) MCF7/S100A7, MCF7/Vec, T47D/Vec and T47D/S100A7 cells were subjected to proliferation after seeding 5x103 cells in 96- well tissue-culture plates. Proliferation was measured for 4 days using MTT assay (Roche) and data was normalized against day 0. (D) Proliferation of ERα- MDA- MB-231 cells as measured by above-mentioned MTT assay.

3.1.2 S100A7-overexpression inhibits tumor growth in vivo:

To further evaluate the tumorigenic potential of S100A7 expression in ERα+ breast cancer cells in vivo, we used xenograft nude mice model. MCF7/S100A7 and

48 MCF7/Vec cells (3x106) were injected subcutaneously into the right flank of female nude

mice. We also injected mice with 2.5 μg of β-estradiol 17-valerate weekly after cell

injection. Tumor volume was monitored up to nine weeks and a dramatic decrease in

tumor size was observed in mice injected with MCF7/S100A7 compared to vector control

cells (Figure 11A, left and right panel). Hematoxylin and Eosin (H&E) staining

revealed tightly packed cells in MCF7/S100A7 tumors while cells were more spread out

in MCF7/Vec control derived tumors. We observed similar cell morphology when cells

were grown under in vitro conditions. There was also decreased expression of Ki67

(Figure 11B) and hence, reduced mitotic index in the S100A7-overexpressing tumor

(Figure 11C). Micro-vasculature was more developed in tumors formed by vector control cells compared to S100A7-overexpressing cells as shown by increased CD31 expression and larger size of micro blood vessels (Figure 11D). The average number of

CD31 positive blood vessels/field as counted from three different fields was significantly reduced in S100A7-overexpressing tumors compared to vector control (Figure 11E).

These results extended our in vitro findings of proliferation suppressive capabilities of

S100A7-overexpression to an in vivo mouse model system.

3.2 Mechanisms of growth inhibition by S100A7-overexpression in ERα+ cells

3.2.1 Reduced β-catenin/TCF4 pathway activity is involved in S100A7-mediated tumor-

suppressive effects:

49

Figure 11: S100A7-overexpression inhibits tumor growth in vivo. MCF7/S100A7 and MCF7/Vec cells were injected into the right flank of female nude mice (n=5). Mice were also injected subcutaneously with 2.5 µg β-estradiol 17-valerate weekly. Tumors were measured by digital calipers weekly for 9 weeks and volume was determined using formula, Length x (Width) 2/2. After 9 weeks, the tumors were harvested, fixed and evaluated for proliferation and angiogenesis. (A) Left panel, Representative photographs of mice and tumors 9 weeks after the injection of cells. Right panel shows the increase in tumor volume over time. (B) Ki67 staining and (C) Mitotic index as calculated by the percentage of Ki67 positive cells out of total number of cells in three random fields on the slide. (D) CD31 staining of tumors derived from mice and (E) shows the average number of micro blood vessels/field after counting CD31 positive staining from three random fields on the slide.

50 To investigate the mechanism involved in S100A7-mediated suppressive effects; we performed microarray analysis by using an Affymetrix gene chip containing 40,000 human genes. data analysis using Ingenuity Pathway analysis (IPA) revealed that the S100A7-overexpression significantly affected cellular pathways that are mostly involved in cancer; signifying the importance of S100A7 in breast tumor progression (Figure 12A). Further analyses of microarray data revealed that S100A7- overexpression down-regulates genes which are either components of canonical β- catenin/TCF4 pathway or are its downstream targets (Figure 12B). Important components of this pathway, which were differentially regulated included TCF4 (~7-fold down-regulated) and GSK3β kinase (~2.5 fold up-regulated). The downstream targets of the β-catenin/TCF4 pathway that were down-regulated included proto-oncogenes cyclin

D1 (2-fold down regulation) and c-myc (~3.5 fold down-regulated).

Figure 12: S100A7-overexpression in MCF7 cells modulates genes, which are involved in cancer and β-catenin/TCF4 pathway. Total RNA from MCF7/Vec and MCF7/S100A7 cells were analyzed by Affymetrix Human Genome U133 chip. (A) Gene ontology studies using IPA analysis of microarray data. (B) Heat-map of differentially expressed genes in MCF7/Vec and MCF7/S100A7 cells showing reduced expression of β-catenin/TCF4 pathway genes.

51 Next, we investigated the activity of β-catenin/TCF4 pathway by using TCF reporter/LEF reporter assay. As shown in Figure 13A, β-catenin/TCF4 activity in

MCF7/S100A7 was significantly reduced by 50% compared to vector control. The candidate targets obtained from microarray analysis were then validated by qRT-PCR.

The results showed a significant decrease in the expression of β-catenin and cyclin D1

(Figure 13B and 13C). However, we found an increase in the expression of E-cadherin and GSK3β (Figure 13D and 13E). These results confirm that S100A7-overexpression in ERα+ breast cancer cells down-modulates β-catenin/TCF4 pathway.

Figure 13: S100A7-overexpression reduces β-Catenin/TCF4 pathway in ERα+ cells at transcription level. (A) TCF4 luciferase reporter activity was calculated as described in materials and methods. (B-E) Total RNA from MCF7/Vec and MCF7/S100A7 cells was extracted using TRIZOL reagent (Invitrogen), per the manufacturer's protocol. RNA isolated was subjected to Syber-green qRT-PCR for β -catenin, Cyclin D1, E-cadherin and GSK3β. The primers used are listed in Table 1.

52 3.2.2 S100A7-overexpression in ERα+ cells down-modulates β-catenin/TCF4 pathway by regulating GSK3β and TCF4:

It has been shown that GSK3β phosphorylates β-catenin which is important for

the ubiquitination and proteasomal-mediated degradation of β-catenin. The increased

phosphorylation of GSK3β reduces the β-catenin phosphorylating activity of GSK3β

(Papkoff et al., 1996; Rubinfeld et al., 1996). Our studies indicate a significant increase in

phosphorylation of β-catenin and decrease in β-catenin expression in S100A7-

overexpressing MCF7 and T47D cells (Figure 14A and 14B). We also observed

increased GSK3β expression in S100A7-overexpressing MCF7 and T47D cells as well as

decreased expression of inactive phospho-GSK3β (Figure 14A and 14B). Since, GSK3β

phosphorylates β-catenin; we determined the interaction between GSK3β and β-catenin

through co-immunoprecipitation. The results showed that S100A7-overexpression

enhanced the interaction of GSK3β with β-catenin both in MCF7 and T47D cells (Figure

14C and 14D). As phosphorylation of β-catenin leads to ubiquitination-mediated

degradation, we analyzed the ubiquitination level of β-catenin and observed enhanced

ubiquitination of β-catenin in S100A7-overexpressing cells (Figure 14C and 14D).

These studies indicate that S100A7 may regulate GSK3β which in turn enhances β-

catenin phosphorylation that leads to increased ubiquitination and degradation.

Stabilized β-catenin has been shown to translocate to the nucleus where it

interacts with transcription factors of TCF/LEF-family, leading to the increased

expression of genes, such as cyclin D1 and c-myc (Papkoff et al., 1996; Rubinfeld et al.,

53 1996). These genes have been shown to play an important role in tumor development

(Behrens, 2000).

Figure 14: S100A7-overexpression reduces β-Catenin/TCF4 pathway in ERα+ cells at protein level. (A and B) Cell lysates obtained from MCF7/S100A7, MCF7/Vec, T47D/Vec and T47D/S100A7 cells were subjected to Western blotting using β-catenin, phospho-β-catenin (p-β-catenin), GSK3β or phospho-GSK3β (p- GSK3 β) antibodies. GAPDH was used as a loading control. (C and D) 500 μg cell lysates from MCF7 or T47D vector control or S100A7-expressing cells were subjected to immunoprecipitation and probed with anti-GSK3β or ubiquitin antibody. The bottom panel shows the IgG band for input. Vec = vector, IgG = immunoglobulin control, TCL = total cell lysate, IP = immunoprecipitation, and WB = Western blotting. Numbers show values of densitometric analysis.

We observed decreased expression of downstream targets of β-catenin/TCF4 pathway such as cyclin D1 (Figure 15A) and c-myc (Figure 15B) in S100A7-overexpressing cells compared to vector controls. These results were also confirmed through immunohistochemical analysis in tumors derived from MCF7/S100A7 and MCF7/Vec injected mice. As shown in Figure 15C, decreased expression of cyclin D1 and β- catenin, was observed in S100A7-overexpressing tumors. β-catenin has also been shown to modulate expression of TCF4, which has been shown to promote tumorigenesis

(Ravindranath et al., 2008). Because our initial microarray analysis revealed that

54 S100A7-overexpressing MCF7 cells exhibit decreased expression of TCF4, we analyzed the expression of TCF4 by immunoblotting and observed that its expression was significantly inhibited in MCF7/S100A7 and T47D/S100A7 cells (Figure 15D).

Similarly, significantly reduced TCF4 expression was observed in MCF7/S100A7 tumor lysates compared to vector control (Figure 15E). These results suggest that S100A7- overexpression may down-modulate β-catenin/TCF4 pathway by regulating the expression of GSK3β and TCF4.

Figure 15: S100A7-overexpression reduces expression of downstream targets of β-catenin/TCF4 pathway in ERα+ cells. (A and B) 50 μg cell lysates obtained from T47D/Vec, T47D/S100A7, MCF7/S100A7, and MCF7/Vec, cells were subjected to Western blotting using Cyclin D1 (left panel) or C-myc (right panel) anti-bodies. (C) Representative Immunohistochemical staining for cyclin D1 or β- catenin in tumors derived from mice injected with MCF7/Vec or MCF7/S100A7 cells. (D) 50 μg cell lysates were subjected to immunoblot analysis with TCF4 antibody or GAPDH. (E) 50 μg Tumor lysates were subjected to Western blotting with TCF-4 antibody. GAPDH served as a loading control in all blots.

55 3.2.3 Inhibition of GSK3β and restoration of TCF4 rescues effects of S100A7-

overexpression mediated down-regulation of β-catenin/TCF4 pathway:

To test if activity of GSK3β and TCF4 is responsible for decreased activation of

β-catenin/TCF4 pathway, we hypothesized that inhibiting GSK3β activity and restoration

of TCF4 expression may reverse the S100A7 mediated effects in ERα+ breast cancer

cells. Therefore, we treated S100A7-overexpressing MCF7 and T47D cells with CHIR

99021 (highly specific GSK3β inhibitor) and observed that CHIR 99021 treatment,

compared to vehicle control, reversed the S100A7-overexpression induced decrease in

proliferation of MCF7 and T47D cells (Figure 16A and 16C) respectively. Further,

immunoblotting experiments showed increased expression of β-catenin and its

downstream target, c-myc in inhibitor treated S100A7 over-expressing MCF7 and T47D

cells (Figure 16B and 16D). We also observed decreased phosphorylation of β-catenin in

CHIR 99021 treated S100A7-overexpressing cells which may be due to the inhibition of

GSK3β activity (Figure 16B and 16D). These results were further confirmed by siRNA approach. As shown in Figure 16E, siRNA mediated down-regulation of GSK3β increased the expression of β-catenin compared to the scrambled control in

MCF7/S100A7 cells. Furthermore, the phosphorylation of β-catenin was decreased in

GSK3β down-regulated cells (Figure 16E). Knockdown of GSK3β also significantly increased the proliferation in MCF7/S100A7 cells compared to the cells transfected with scrambled control (Figure 16F).

56

Figure 16: S100A7 regulates β-catenin/TCF4 pathway through GSK3β. (A) MCF7/Vec and MCF7/S100A7 cells were serum starved for 5 h and then treated with TDZD-8 (60 µm) and proliferation was measured using MTT assay as described in experimental procedures. (B) 50 μg cell lysates were subjected to immunoblot analysis with P-β-catenin, β-catenin or C-myc antibodies. (C) Proliferation of T47D/Vec and T47D/S100A7 cells was measured as described above for MCF-7 cells. (D) 50 μg cell lysates were subjected to immunoblot analysis with P-β-catenin, β-catenin or C-myc antibodies. GAPDH served as a loading control in all the blots. (E) & (F) siRNA mediated knockdown of GSK3β and proliferation analysis after siRNA treatment.

57 Further, to determine if restoration of TCF4 expression in S100A7-overexpressing

cells may reverse the S100A7-mediated inhibitory effects, we transfected TCF4 into

S100A7-overexpressing MCF7 cells. The results showed that the restoration of TCF4 expression increased the proliferation of S100A7-overexpressing cells (Figure 17A). In

addition, increased expression of c-myc, a downstream target of β-catenin/TCF4

pathway, was also observed in TCF4 transfected S100A7-overexpressed MCF7 cells

(Figure 17B). These results indicate that TCF4 down-regulation along with increased activation of GSK3β may be responsible for tumor suppressive effects of S100A7 in

ERα+ breast cancer cells.

Figure 17: TCF4 overexpression in S100A7 overexpressing cells restores the

oncogenic properties. (A) TCF4 was transiently transfected in MCF7/S100A7 in pcDNA3.1 vector using lipofectamine according to manufacturer’s

recommendations. 24 h after transfection, 5x103 cells were seeded in 96-well tissue culture plate and proliferation was measured using MTT assay as described in

experimental procedures. (B) 50 μg cell lysates of TCF4 and vector transfected MCF7/S100A7 were subjected to Western Blotting with anti-TCF4 or C-myc

antibodies. GAPDH served as a loading control in all the blots.

58 3.2.4 S100A7-overexpression enhances the co-localization and interaction of β-catenin and E-cadherin:

It is known that β-catenin controls E-cadherin mediated cell adhesion at the plasma membrane and regulates adherens junction molecules within the actin cytoskeletal system

(Nagafuchi, 2001; Vasioukhin and Fuchs, 2001). We observed increased E-cadherin expression both in vitro in S100A7-overexpressing MCF7 and T47D cells (Figure 18A, left panel) as well as tumor samples (Figure 18A, right panel). We also observed enhanced expression of E-cadherin in S100A7-overexpressing MCF7 and T47D cells by immunofluorescence (Figure 18B and 18C, left panel). Further analysis revealed increased co-localization of β-catenin with E-cadherin in the membranes of

MCF7/S100A7 and T47D/S100A7 cells compared to vector controls by immunofluorescence (Figure 18B and 18C, right panel). Quantification analysis of merged E-cadherin and β-catenin showed significantly enhanced co-localization as shown by the linear increase in the merged intensities of E-cadherin and β-catenin

(Figure 18B and 18C, right panels). In addition, we observed enhanced association of β- catenin with E-cadherin in the cell lysates obtained from MCF7/S100A7 (Figure 18D, left panel) and T47D/S100A7 (Figure 18D, right panel) compared to vector control. This data indicates that S100A7-overexpression might enhance cell-cell adhesion and decreased migration by regulation of β-catenin and E-cadherin in ERα+ breast cancer cells.

59

Figure 18: S100A7-overexpression enhances the co-localization and interaction between β-catenin and E-cadherin in ERα+ breast cancer cells. (A) 50 μg of cell lysates were subjected to immunoblot analysis with anti-E-cadherin antibody and GAPDH (left panel). Representative Immunohistochemical staining for anti-E- cadherin in tumors derived from mice injected with MCF7/Vec or MCF7/S100A7 cells (right panel). (B) Localization of E-cadherin and β-catenin in MCF7/S100A7, MCF7/Vec or (C) T47D/S100A7, T47D/Vec as determined by confocal microscopy. Graph shows the quantification of merged E-cadherin and β-catenin as analyzed by FV10-ASW 2.0 software (B and C right panels). (D) MCF7 (left panel) or T47D (right panel) vector control or S100A7- expressing cell lysates were subjected to immunoprecipitation and probed with anti-E-cadherin antibody. The bottom panel shows the IgG band for input. Vec = vector, IgG = immunoglobulin control, Neg = negative control, TCL = total cell lysate, IP = immunoprecipitation, and WB = Western blotting.

60 3.3 S100A7 stabilizes and activates p53 mediated stress response pathway in ERα+

cells

3.3.1 S100A7-overexpression increases the expression of p53

P53 is the master regulator and is known as the guardian of genome. It is the major tumor suppressor gene and has been associated with cellular mechanisms such as cell cycle arrest, apoptosis, proliferation etc. Several of the S100 family proteins are known to modulate p53 through the direct or indirect interaction. We analyzed the expression of S100A7 on p53 expression in S100A7 overexpressing breast cancer cells.

Upon analyzing the protein expression of p53 in S100A7 overexpressing breast cancer cells, we observed that p53 is specifically up-regulated in S100A7 overexpressing MCF7 cells compared to vector control cells (Figure 19A) but there was not much difference in the expression of S100A7 overexpressing cells and vector control cells in MDA-MB-231

(Figure 19A). The expression of p53 was specifically localized in the nucleus of S100A7 overexpressing MCF7 cells and not the cytoplasm (Figure 19B). Nuclear expression of p53 has been associated with its enhanced activity and therefore, it is possible that p53 may be getting activated in S100A7 overexpressing cells.

Figure 19: S100A7-overexpression increases p53 expression in MCF7 cells. (A) Western blot showing differential p53 expression in S100A7 overexpressing MCF7 cells compared to vector control cells. (B) Immunofluorescence staining showing p53 localization in the nucleus of S100A7 overexpressing MCF7 cells compared to vector control. 61 3.3.2 S100A7 and p53 interact in S100A7-overexpressing MCF7 cells

Several members of S100 protein family have the ability to interact with p53, therefore, we hypothesized that S100A7 may directly bind to p53 and stabilize it by preventing it from degradation. When we immuno-precipitated p53 from the cell lysates of S100A7 overexpressing MCF7 cells, we observed that S100A7 co- immunoprecipitated with p53 only in S100A7 overexpressing cells and not in vector control cells (Figure 20A). These results indicate that S100A7 has the ability to bind to p53 directly. It is possible that direct binding of p53 with S100A7 protects the p53 from ubiquitin mediated degradation. Immunofluorescence studies also showed that S100A7 and p53 both co-localize in the nucleus of S100A7 overexpressing MCF7 cells and it is feasible that the interaction between p53 and S100A7 is taking place in the nucleus. The localization of S100A7 was both in the cytoplasm as well as the nucleus (Figure 20B, upper panel). Interestingly, in another ER positive cell line T47D, which showed reduced proliferation, there was no co-localization of p53 and S100A7 in T47D cells

(Figure 20B, lower panel).

62

A

B

Figure 20: S100A7 interacts with p53 in S100A7 overexpressing MCF7 cells. (A) Cell lysates from MCF7 vector control and S100A7 overexpressing cells obtained were immunoprecipitated with p53 and blotted with S100A7. (B, upper panel) Immunofluorescence staining showing increased expression of p53 as well as its co-localization with S100A7 in the nucleus of S100A7overexpressing MCF7 cells. (B, lower panel) Immunofluorescence staining showing equal level of p53 and no interaction of p53 and S100A7 in S100A7 overexpressing T47D cells.

63 3.3.3 S100A7 increases phosphorylation of p53 at Serine-15

One of the several mechanisms of stabilization of p53 is its phosphorylation at serine 15. Serine 15 phosphorylation of p53 prevents MDM2 from binding to p53 and thereby preventing its translocation from nucleus to cytoplasm, thus escaping the ubiquitin mediated degradation. In MCF7 cells which overexpress S100A7, we observed increased phosphorylation of Serine-15 compared to vector control (Figure 21A).

Similar effect could not be observed in another ERα+ cell line T47D cells where equal levels of phosphorylation of Serine-15 was observed in S100A7 overexpressing as well as vector control cells (Figure 21B). The difference in the results between MCF7 and

T47D cells could be due to difference in p53 status in these cells. In MCF7 cells, p53 is wild type whereas in T47D cells, there is a mutated form of p53 (O'Connor et al., 1997).

64

Figure 21: S100A7-overexpression increases phosphorylation of p53 at Serine p53 in the nucleus of S100A7-overexpressing MCF7 cells. (A) Immunofluorescence staining showing increased expression of p-p53 (Ser 15) in S100A7-overexpressing MCF7 cells compared to vector control. Immunofluorescence staining was performed as mentioned above. (B) Immunofluorescence staining showing equal levels of Serine 15 phosphorylation of p53 in S100A7 overexpressing and vector control T47D cells.

3.3.4 S100A7-overexpression in MCF7 cells modulates p53 signaling

Since p53 is a master regulator and regulates wide variety of cellular processes ranging from cell cycle arrest and proliferation to cell death and apoptosis, we decided to analyze the signaling mechanisms and the processes mediated by those signaling mechanisms. In order to achieve this, we employed a powerful method of Real Time

PCR array assay to determine the regulation of genes involved in p53 signaling. The results showed that the highest up-regulated gene was apoptosis inducing protein

(p53AIP1) followed by cell cycle regulatory genes like CDK1 (Figure 22B). The other class of genes which was differentially regulated was those which are part of stress response in the cell such as ATR, BRCA-1 etc. The results are summarized in the

(Figure 22B).

65

Figure 22: RT-PCR profiler array analysis showing differential regulation of p53 signaling pathway molecules. Total RNA from S100A7-overexpressing and vector control MCF7 cells was extracted using TRIZOL method, converted to cDNA and subjected to SYBR Green RT-PCR array to analyze the expression of genes involved in p53 signaling. (A) 3D diagram of the plate lay out and the differential gene expression of all the p53 signaling molecules. (B) The candidate genes of p53 pathway which showed fold change of 2.5 or higher in S100A7- overexpressing MCF7 cells compared to vector control.

3.3.5 S100A7-overexpression in MCF7 cells activates p53 mediated stress response

P53 is known to induce stress response in lieu of any external or internal stress to the cells such as UV radiation, temperature change, oncogenic activation, etc and initiates the cell cycle arrest to give time to undergo cell repair pathways. Since our real time p53 PCR array showed differential expression of several genes, which were involved in p53 mediated stress response pathway, we confirmed the expression of those genes through western blotting. Our western blotting experiments revealed that S100A7-

66 overexpression up-regulated the expression of stress induced genes like ATR and also activated downstream kinases such as CHK1 and CHK2 which are known to phosphorylate p53 at Serine 15 (Figure 23). Moreover, we observed p53 activated stress response only in MCF7 cells (with wild type p53) and not in T47D cells. Therefore, our these results support our previous findings that p53 is phosphorylated at Serine 15 only in MCF7 cells and not in T47D cells which possesses mutated form of p53.

Figure 23: S100A7-overexpression activates stress induced pathway in MCF7 cells. Western blot analysis showing increased levels of ATR, p-Chk2 and p-Chk1 in S100A7 overexpressing MCF7 cells compared to vector control cells.

3.3.6 Role of murine S100A7 (mS100A7A15) and p53 in breast tumorigenesis

To determine the role of murine S100A7 (mS100A7A15) and p53 in breast development and progression in vivo, we generated the mice which expresses mS100A7A15 in breast tissues or mammary glands and was also deficient in p53. To generate these mice, we used MMTV-rtTA/mS100A7A15 bi-transgenic mice which were developed in our laboratory. It has been reported that murine S100A7 (mS100A7A15) is

67 up-regulated during carcinogen-induced mammary tumorigenesis (Webb et al., 2005).

Very recently K5-tTA; tetO-mS100A7A15 mice were generated for studying the role of

mS100a7a15 in psoriasis (Wolf et al., 2010). We developed MMTV-rtTA/mS100A7A15

bi-transgenic mouse model to determine the role of mS100A7A5 in breast tumorigenesis.

We generated this inducible-transgenic mouse model by crossing tetO-mS100A7A5 mice

with tetracycline-responsive transactivator protein under the murine mammary tumor

virus (MMTV-rtTA) promoter mice. In the presence of doxycycline, rtTA protein

changes its conformation and binds to tet operator (tet-O) sequences that results in expression of mS100A7A5 in mammary epithelial cells (Figure 24A). Mammary glands

(MG) derived from MMTV-mS100A7A15 mice that were subjected to Dox-chow

(1g/kg) for three months showed mS100A7A15 expression at mRNA levels (Figure 24B,

left Panel). We also observed enhanced mS100A7A5 expression in these mice by IHC

(Figure 24B, right Panel). We further identified the mS100A7A5 overexpressing cells

to be of luminal epithelial origin as these cells also express CK8 (Figure 24B, right

Panel). Further morphological examination of whole-mount virgin MG by carmine

(Figure 24C, Left Panel) or hematoxylin and eosin (H&E) (Figure 24C, Right Panel)

staining demonstrated ductal hyperplasia in the Dox-induced MMTV-mS100A7A5 mice

compared to uninduced mice. These findings indicate that overexpression of

mS100A7A5 in mouse mammary glands induces hyperplasia but not the spontaneous

tumors.

68

Figure 24: Generation of the inducible, mammary-specific mS100A7A15 bi- transgenic mouse model. (A) Schematic representation of the inducible, MMTV- mS100A7A15 (Tet-O, tet operator) mouse model system. (B, left) RT-PCR analysis of mS100A7A15 expression in mammary glands of doxycycline (Dox) induced and uninduced mice. (B, right) Immunohistochemical (IHC) analysis of mS100A7A15 and CK8 of MG from Dox treated (+Dox) and untreated (-Dox) mice. (C, left) MG from Dox treated (+Dox) and untreated (-Dox) mice were subjected to whole-mount carmine staining or (C, right) H&E staining.

3.3.7 Generation of MMTV-rtTA/mS100A7A15/P53-/- mouse model

To further test the significance of p53 and S100A7-overexpression in promoting breast tumorigenesis in vivo, we generated a mouse model, which had knockdown of p53 and also overexpress murine S100A7 under MMTV promoter. Our hypothesis is that since we observed initial hyperplasia in our original bi-transgenic model, knockdown of p53 along with increased expression of S100A7 in the breast epithelial

69 tissue may lead to a development of spontaneous breast tumors. So, we crossbred p53-/+ mice with MMTV- rtTA/mS100A7A15 mice. The breeding scheme is shown in Figure

25A. Till now, we have got one p53-/- knockout female mouse which overexpress

S100A7 under doxycycline diet and it showed mammary gland tumor formation in fourth inguinal mammary gland after two and half months (Figure 25B). As control we have also generated p53-/+ mouse, which over-expresses S100A7 and other controls are wild type p53 containing MMTV-rtTA/mS100A7A15 mice. None of these control mice have developed breast tumor after two and half months. Genotypes of these mice were determined using PCR as depicted in the gel electrophoresis (Figure 25C and 25D).

-/- Figure 25: Development of tumors in MMTV-rtTA/mS100A7A15/p53 mice. (A) Breeding scheme used to generate MMTV-rtTA/mS100A7A15/p53-/-mice (B) Representative mouse with spontaneous tumors after 10 weeks of dox treatment. (C and D)Representative gel electrophoresis pictures used to determine the genotype of mice. 70 3.4 S100A7-overexpression decreases migration of ERα+ cells

3.4.1 S100A7-overexpression reduces chemotaxis and wound healing in ERα+ cells

Increased migration, adhesion and proliferation are important characteristics of

tumorigenesis and metastasis of cancer cells. We also observed a significant decrease in

EGF induced chemotactic ability of S100A7-overexpressing MCF7 and T47D cells

(Figure 26A and 26B). In contrast, we found out that S100A7-overexpression in MDA-

MB-231 cells increased migration compared to vector control cells (Figure 26C). Wound healing assay also confirmed significantly decreased migratory abilities of S100A7- overexpressing MCF7 cells both in the presence of serum and EGF (Figure 26D).

Quantitative analysis of wound closure assay is shown in Figure 26E.

Figure 26: S100A7-overexpressing ERα+ MCF7 and T47D cells decreases chemotactic activity and motility. (A and B) The cells were subjected to EGF 4 induced migration by seeding 2x10 cells in upper chamber of 8 µm transwell plates. The migrated cells were then stained with Hema stain and counted. (C) Migration of ERα- MDA–MB-231 cells was also analyzed. (D) MCF7 cells were subjected to wound scratch assay in the presence of serum and EGF (100ng/ml). (E) The bar graph shows the quantitative analyses of wound closure assay. 71 3.5 Mechanisms mediated by S100A7-overexpression which regulate migration of

ERα+ cells

3.5.1 S100A7-overexpression reduces EGF-induced signaling in ERα+breast cancer

cells

Since we observed decreased EGF-mediated wound healing and chemotaxis, we

hypothesized that S100A7-overexpression may be down-regulating EGF-mediated signal

transduction pathways. As shown in Figure 27, reduced EGF-induced EGFR, AKT and

ERK phosphorylation was observed in MCF-7/S100A7 compared to MCF-7/Vec cells.

The quantification of all the blots also shows considerable decrease in activation of

EGFR, AKT and ERK in S100A7-overexpressing MCF7 cells (Figure 27B, 27C and

27D). These results show that pro-survival pathways like phospho-Akt and phospho-ERK may be down-regulated by S100A7-overexpression in ERα+ cells and hence there may be

a differential role of S100A7 in ERα+ and ER negative breast cancer cells.

72

Figure 27: S100A7-overexpression in MCF7 cells decreases EGF-induced signaling. (A) The cells were lysed and Western blotted with phospho-EGFR (p- EGFR), phospho-AKT (p-AKT), total AKT, phospho-ERK (p-ERK), and total ERK. Equal protein was confirmed in these samples by stripping and re-probing the blots with anti-glyceraldehyde-3-phosphotate dehydrogenase (GAPDH). Bar graphs show the quantitative analysis of (B) p-EGFR, (C) p-AKT, and (D) p-ERK expression.

3.5.2 S100A7-overexpression decreases actin polymerization

Since, there was decreased lamellipodia and migratory structure formation in

S100A7 overexpressing MCF7 cells compared to vector control (Figure 28A), we hypothesized that there may be decreased actin polymerization activity and hence reduced formation of migratory structures. Therefore, we tested actin polymerization by immunofluorescence studies and the results revealed that there is decreased actin polymerization in S100A7-overexpressing MCF7 cells compared to vector control

73 (Figure 28B). In S100A7-overexpressing cells, the F-actin filaments were mainly stained inside the cytoplasm compared to vector control cells where staining was more prominent on the membranes including migratory structures. These results show S100A7 may regulate cytoskeletal structures in ERα+ breast cancer cells.

Figure 28: S100A7-overexpression in MCF7 cells modulates actin cytoskeleton. (A) S100A7 overexpressing MCF7 cells showed decreased migratory structures compared to vector control. Phase contrast image of cultured MCF7/Vec and MCF7/S100A7 cells taken at 10x magnification. Inset image shows the representative zoomed area. (B) Actin staining was observed at the edges of plasma membrane in vector control cells whereas in S100A7 overexpressing cells, the staining was observed within cytoplasm.

74 3.5.3 S100A7-overexpression decreases cofilin expression

Our immunoflourescnece results showed that S100A7-overexpression in MCF7

cells inhibits actin polymerization and therefore, we decided to determine the expression

of the molecules which impact actin polymerization directly. In this context, cofilin has

been shown to play an important role in the activation of actin filament dynamics and it is

the downstream target of the Rac1 pathway. Cofilin has been shown to de-phosphorylate

upon Rac activation leading to the polymerization of the F-actin filaments and

lamellipodium formation (Arber et al., 1998). Our results showed increased p-cofilin

expression in the MCF-7/S100A7 compared to vector control cells (Figure 29A, left and right panels). Since p-cofilin is an inactivated form of cofilin, this may lead to decreased actin depolymerization and hence reduced formation of lamellipodium or migratory structures.

3.5.4 S100A7-overexpression in MCF7 cells decreases Rac activation

We analyzed the effect of S100A7 on Rac1 pathway which plays an important role in actin polymerization. Rac pathway is upstream of cofilin and mediates cofilin activation through intermediate kinases like PAK1 (Delorme et al., 2007). We observed that Rac activity was reduced in S100A7 overexpressing MCF7 cells compared to vector control cells at all time points upon EGF treatment. Rac activation was decreased in both

EGF treated as well untreated samples supporting that EGF induced effects are decreased

in S100A7 overexpressing ERα+ breast cancer cells (Figure 29B, left and right).

Therefore, our results show that S100A7 may inhibit actin polymerization and cell

75 migration by down regulating Rac1 pathway and hence dephosphorylation of cofilin is decreased leading to decreased severing and turnover of actin filaments in MCF7 cells.

Figure 29: S100A7-overexpression in MCF7 cells decreases cofilin expression and Rac activation. (A) Western blot analysis showing increased phosphorylation of cofilin in both S100A7 overexpressing MCF7 and T47D cells compared to vector control. (B) As measured by Rac activation assay (Millipore), S100A7- overexpression in MCF7 cells reduced Rac activation both in the absence and presence of EGF at the indicated time points. GAPDH and Total Rac served as loading control in the above blots.

76

CHAPTER 4

DISCUSSION

4.1 S100A7-overexpression has tumor suppressive effects in ERα+ breast cancer

cells

S100A7 expression has been shown to be mainly associated with high-grade

DCIS and highly invasive ERα- breast cancers (Emberley et al., 2005; Krop et al., 2005).

In addition, S100A7 down-modulation inhibits tumor growth and EGF-induced migration

in ERα- cells (Krop et al., 2005; Paruchuri et al., 2008). Moreover, overexpression of

S100A7 in ERα- breast cancer cells such as MDA-MB-231 has been shown to enhance

proliferation, migration, and invasion in vitro as well as tumor growth in vivo (Emberley

et al., 2004a; Emberley et al., 2003b). However, not much is known about its role in

ERα+ breast cancer cells. Therefore, in the present study, we characterized the role and

mechanism of S100A7 in ERα+ breast cancer cells.

The results of our study have demonstrated for the first time that S100A7

possesses tumor suppressive activity in S100A7-overexpressing ERα+ MCF7 and T47D

breast cancer cells. In our study, we observed that there was reduction in growth both in

vivo as well as in vitro when S100A7 was overexpressed in ERα+ MCF7 and T47D cells.

Proliferation of S100A7-overexpressing MCF7 and T47D cells as determined by MTT

77 assay showed significant decrease in proliferation over-time compared to vector control

cells. We also observed a significant reduction in tumor formation of estradiol treated

MCF7/S100A7 compared to MCF7/Vec control in nude mice. The results support our hypothesis that there is a differential role of S100A7 in estrogen receptor positive and negative breast cancers. Previous studies with ER negative cells have shown S100A7-

overexpression to enhance tumor growth both in vivo and in vitro (Emberley et al.,

2004a). One report has shown that S100A7-overexpression inhibits cell proliferation in

vitro and tumor growth/invasion in vivo in cells of squamous cell carcinoma of the oral

cavity (SCCOC) (Zhou et al., 2008). Several previous studies have demonstrated that

regular treatment of MCF7 cells with estrogen sustains and enhances the tumorigenic

effect of MCF7 cells in nude mice (Ray et al., 2005). Our results in xenografted nude

mice indicate that S100A7-overexpression significantly overcomes the tumor enhancing

effects of estrogen by exhibiting a marked reduction in tumor size even in the presence of

estrogen. It is plausible that S100A7 may be inhibiting tumor growth in vivo by

modulating estrogen and growth factor mediated signaling. It was recently reported that

IL-6 and Oncostatin-M treatment enhances S100A7 expression that leads to down-

regulation of expression of ERα gene (West and Watson, 2010). We have also observed

that S100A7-overexpression down regulates ERα expression in both MCF7 and T47D

cells (Figure 30).

Upon further analyzing the mechanisms behind S100A7 mediated decrease in

proliferation of ERα+ cells, our microarray results suggested the involvement of β-catenin

78 pathway since several genes of that pathway were down-regulated in S100A7

overexpressing cells. In our studies, we observed reduced expression of β-catenin both at

RNA and protein levels. We also found increased phosphorylation of β-catenin at Thr-41,

Ser-37 and/or Ser-33 phosphorylation sites in MCF7/S100A7 cells. These sites are

phosphorylated by GSK3β which are then recognized by the ubiquitin ligase complex

leading to β-catenin degradation (Amit et al., 2002). We observed increased levels of

GSK3β which may be phosphorylating β-catenin leading to its reduced expression and

degradation. Also, the phosphorylated level of GSK3β, which is the inactive form of

GSK3β, was also reduced in S100A7-overexpressing cells. GSK3β is phosphorylated by

kinases like AKT and we also observed decreased activation of AKT in S100A7-

overexpressing cells. Therefore, it is possible that S100A7 may be having some direct

effects on upstream kinases which phosphorylate GSK3β.

Figure 30: Expression of estrogen receptor alpha (ERα) in S100A7- overexpressing and vector control MCF7 and T47D cells. Western blotting with ERα antibody showed that S100A7 reduced ERα both in MCF7 and T47D cells compared to vector control. GAPDH was used as a loading control in all the blots.

We have also observed decreased expression of TCF4 which binds to β-catenin and regulates the transcription of downstream targets of β-catenin/TCF4 pathway.

Additionally, our luciferase gene reporter assay revealed inhibition of β-catenin/TCF4

79 transcriptional activity in the S100A7-overexpressing cells. Upon further analyses of the expression of various downstream targets of β-catenin/TCF4 pathway, we found decreased expression of cyclin D1 and c-myc in the S100A7-overexpressing cells. These genes are proto-oncogenes and are considered as critical mediators of proliferation, invasion and tumor progression.

The other mechanism which our studies demonstrate to be involved in S100A7- overexpression mediated reduction in proliferation is p53 signaling. p53 plays a critical role in limiting cell proliferation and inducing apoptosis in response to cellular stress/damage and abnormal function of p53 is associated with cancers (Mandinova and

Lee, 2011). In S100A7 overexpressing MCF7 cells, we observed significant increase in p53 expression compared to vector control cells. Since other S100 protein family members such as S100A8 and S100A4 have been shown to interact with p53 and modulate its functions, we determined the interaction of S100A7 and p53 in S100A7 overexpressing cells. Co-immunopreciptation experiments show that S100A7 was able to bind with p53 in S100A7 overexpressing cells compared to vector control cells.

Moreover, through immunofluorescence and confocal microscopy, we observed that enhanced levels of p53 in S100A7 overexpressing cells were particularly localized to the nucleus and there was co- localization between S1007 and p53 in the nucleus. p53 function is tightly regulated by modulation of the protein stability and under most conditions, p53 protein is undetectable primarily due to interaction of p53 with the E3 ubiquitin ligase MDM2 and consequent proteosomal degradation. Increased expression of

80 p53 in the nucleus is also associated with its enhanced activity (O'Brate and

Giannakakou, 2003). Therefore, it is feasible that increased expression of p53 is activating p53 mediated effects such as reduced proliferation in S100A7 overexpressing cells.

One of the several mechanisms of stabilization of p53 includes phosphorylation of p53 at several serine residues. Upon analyzing the phosphorylation status of p53 at serine residues, we found out that in S100A7 overexpressing MCF7 cells, phosphorylation of p53 at serine 15 was significantly higher and was mainly observed in the nucleus compared to vector control cells. This again suggests that p53 may be in the activated status in S100A7 overexpressing cells. P53 plays a critical role in limiting cell

proliferation and inducing apoptosis in response to cellular stress/damage and abnormal

function of p53 is associated with cancers. Further, p53 is known to affect cell cycle

arrest during the times of cellular stresses through UV radiation, DNA damage etc so that the cell has enough time to repair the DNA damage (Varna et al., 2011). All these cellular processes occur through different pathways and our results indicate that there may be regulation of several genes which are involved in these pathways.

To determine how the increase in p53 levels in S100A7 overexpressing cells may be affecting genes involved in different pathways, we carried out Real Time PCR Array of p53 signaling molecules. Our results showed that several genes which are part of stress induced response or are involved in cell cycle and apoptosis are up-regulated in S100A7

81 overexpressing MCF7 cells compared to vector control cells. We then analyzed the stress

response pathway and found increased expression of p-Chk1 and p-Chk2 kinases which

are known to phosphorylate p53 at Serine 15. Our results show that p53 is modified at

post translational level and post-translational modifications have been shown to play an important role in both the stabilization and activation of p53. The phosphorylation of three amino-terminal sites, Ser15, Thr18, and Ser20, impairs the interaction between p53 and MDM2 and leads to accumulation of p53. Ataxiatelangiectasia mutated (ATM) and ataxiatelangiectasia and Rad3-related (ATR) kinases have been shown to phosphorylate p53 at Ser15 after gamma-irradiation and UV radiation, respectively (Varna et al., 2011), while Ser 20 was phosphorylated by cell cycle checkpoint kinase 1 (CHK1) and cell cycle checkpoint kinase 2 (CHK2). Notably, Ser15 phosphorylation is known to be critical for p53-dependent transactivation (Dumaz and Meek, 1999). It is interesting to note that we did not observe increase in p53 levels in another ERα+ cell line T47D in

which S100A7-overexpression also inhibited the proliferation. Moreover, there was no activation of p53 induced stress response in T47D cells which suggests that effects of

S100A7 on p53 stability may be limited to cells which express wild type p53 and not

mutated form of p53 as in T47D cells. Our data suggests that S100A7-overexpression in

wild type p53 containing MCF7 cells increase p53 protein stability which may lead to

increased p53 function and subsequent cell cycle arrest or apoptosis. Further experiments

needs to be performed to determine if S00A7 overexpression in MCF7 cells which

contain wild type p53 is leading to cell cycle arrest or apoptosis or both.

82 Our in vivo results showed enhanced tumor development in MMTV- rtTA/mS100A7A15/p53-/- mouse model. Original p53-/- mouse showed development of

lymphomas as well as sarcomas but not carcinomas (Donehower et al., 1992). At least

five different groups have reported the development of p53-deficient or ‘knockout’mice.

It has been shown that tumor susceptibility in p53-deficient mice is greatly enhanced. P53

deficient mice were shown to develop tumors by 10 months of age and the mean tumor

development time was four and half months. The types of tumors observed in the p53-

deficient mice were quite varied but there was high incidence of lymphomas while soft

tissue sarcomas and osteosarcomas appear at a lower frequency. Moreover, breast tumors

were very rare in p53 -/- mice models but when these mice were crossed with transgenic

mouse models of oncogenes like wnt-1, there was increase in the development of the

mammary tumors (Donehower et al., 1995). Our results also confirm that S100A7-

overexpression in mammary glands of mouse could initiate mammary gland

tumorigenesis in presence of another oncogenic signal such as the abrogation of tumor

suppressor gene p53. These results also show that S100A7 expression in the tumors with

inactivated or mutated p53 would lead to tumorigenic effects by S100A7. These results are in accordance with our results as well as results of other groups which showed

S100A7 to have differential effects in ERα+ and ERα- tumors. ERα+ tumors have mainly

the activated or wild type form of p53 whereas triple negative tumors normally possess

mutant forms of p53. In our in vitro results also, we observed differential role of S100A7 in MCF7 and MDA-MB-231 cells. MCF7 possesses wild type p53 and are ERα+ whereas

MDA-MB-231 cells have mutant p53 and are ER negative. Moreover, we show that

83 S100A7 can increase activity of wild type p53, our results also have the implications of developing small molecules based on S100A7 structure to activate p53 function.

Cancer cell metastasis is a multi-stage process involving invasion into the surrounding tissue, intravasation, entry into the blood or lymph, extravasation, and growth at a new site. Many of these steps require cell motility, which is driven by several steps such as actin polymerization, cell adhesion and acto-myosin contraction. The first step is actin polymerization which involves the polymerization of actin monomers into polarized filaments (Ridley, 2011). These filaments, termed F-actin, are in a constant state of flux with new monomers being added at the ‘barbed’ or ‘plus’ end, and depolymerization at the ‘pointed’ or ‘minus’ end. Actin polymerization can be stimulated in many ways, including increasing the rate of monomer addition to barbed ends, nucleating new filaments, increasing the number of barbed ends, and reducing depolymerization (reviewed in (Ridley, 2011). Cofilin can increase the number of barbed ends available for polymerization by severing existing filaments (Delorme et al., 2007) and since our results show that S100A7-overexpression decreases cofilin expression, there may not be enough severing of the already formed actin filaments. This will reduce the formation of new filaments which are required for the motility of the cell in a particular direction. Moreover, we also show that Rac1 pathway has a reduced activity in

S100A7 overexpressing cells compared to vector control cells. Cofilin activity is also regulated through phosphorylation by LIM kinases and other downstream effectors of the

Rho family of GTPases, Cdc42, Rac and Rho. Further, Rac1 has been shown to regulate

84 cofilin dephosphorylation through the activity of class II PAKs (Delorme et al., 2007).

Phosphorylated cofilin is inactive form of cofilin and as our results show, S100A7- overexpression increased phosphorylation of cofilin. Therefore, reduced serum and EGF-

induced migration observed in S100A7-overexpressing may be due to inhibition of actin

polymerization which may be mediated through Rac1 and cofilin pathways.

Second step after migration of cells in the metastasis during tumorigenesis is the

attachment of the migrated cells. β-catenin has also been shown to effect the cell

adhesion and cytoskeleton properties by binding to E-cadherin (Crawford et al., 1999;

Tetsu and McCormick, 1999). In our study, S100A7-overexpression increased E-cadherin

expression which is a component of adherens junctions and a known marker of reverse

epithelial-mesenchymal transition (EMT) and epithelial integrity (Schmalhofer et al.,

2009). Its increased expression may support reduction in motility of S100A7-

overexpressing cells as well as increased attachment to substrate. We also demonstrated

increased co-localization of E-cadherin and β-catenin in S100A7-overexpressing cells.

Furthermore, there was enhanced interaction between E-cadherin and β-catenin.

Although there is increased β-catenin degradation observed in S100A7-overexpressing

cells, the increased interaction between E-cadherin and β-catenin may be explained by

the significantly increased expression of E-cadherin which may sequester non-

phosphorylated β-catenin in S100A7-overexpressing cells allowing it to escape GSK3β

mediated degradation. Therefore, our results show that S100A7-overexpression may

reduce chemotaxis and motility of ERα+ cells by reducing the actin polymerization as

85 well as by increasing the attachment or adhesion between cells through increased E-

cadherin expression and increased binding to β-catenin. The increased binding may lead

to the strong adherens junctions between the cells.

4.2 Conclusions

The results of our study demonstrates for the first time that S100A7-

overexpression inhibits proliferation, migration and wound healing in ERα+ MCF7 and

T47D breast cancer cell lines. Furthermore, we have confirmed that S100A7 induces

tumor suppressive activity in MCF7 cells in an in vivo mouse model system. These

results support our hypothesis that there is differential role of S100A7 in ERα+ and ER

negative breast cancers and therefore may play an important role in breast cancer progression and metastasis. It supports the findings that S100A7 expression is associated with good prognosis when breast cancers are ERα+ and vice versa. These results may

also have implications in developing novel treatments for ERα+ and tamoxifen-resistant

breast tumors

In addition, our results show that S100A7 mediates its anti-proliferative effects

via novel mechanismS through a coordinated regulation of the β-catenin/TCF4 and p53.

P53 is a well known tumor suppressor protein and our findings that S100A7 may activate

wild type p53 could have greater implications both in the diagnosis as well as prognosis

of breast cancer. Presently most of the methods to detect p53 expression in breast cancer

patients involve detection of mutated form of p53, reason being that mutated form of p53

86 is more stable whereas wild type p53 is expressed at low levels. Therefore, determining

the p53 status along with S100A7 and Estrogen Receptor alpha expression may prove

beneficial in determining the outcome of the disease. Also, a number of compounds that inhibit the MDM2-p53 interaction or the subsequent steps toward proteosomal degradation are under evaluation for their anti-cancer activity. Activity of S100A7 in stabilizing p53 could be useful in designing small molecules which could activate p53 leading to reduced tumorigenesis and hence increased cancer control.

Other proliferation mechanism which we demonstrate to be down-regulated by

S100A7-overexpression in ERα+ is β-catenin/TCF4 pathway. β-catenin is involved in developmental and differentiation pathways and it is no surprise that S100A7 may modulate β-catenin activity since S100A7 lies on chromosomal 1Q21, a part of epidermal differentiation complex. This raises the possibility that S100A7 may have role in differentiation pathway as well as imparting stem cell like characters to breast cancer cells. β-catenin pathway has a dual role in promoting cancer growth as increase in β- catenin expression and its translocation to nucleus activates transcription of several proliferation genes. Simultaneously, β-catenin can leave E-cadherin which unstablizes the adherens junction leading to increased metastasis. Therefore, S100A7 may regulate both

proliferation as well as migration through this pathway.

4.3 Future Directions

Results of our study have opened several new questions and the answers to them

87 would be very helpful in enhancing our knowledge about the progression and development of breast cancer. The following experiments may help us to better understand the role of S100A7 in breast tumorogenesis:

1) Since p53 is a master regulator and guardian of genome, it would be interesting to

determine if p53 expression modulates β-catenin pathway as S100A7 effect on β-

catenin pathway appeared to be indirect.

2) We showed by co-immunoprecipitation studies that S100A7 and p53 bind to each

other, therefore, it becomes very important to determine the p53 binding domains

of S100A7 so that small molecules could be generated which may help to activate

p53 in several cancers.

3) It would be also very critical to understand the relationship between Estrogen

receptor, S100A7 and p53 expressions in breast cancer. Our results show that

S100A7 down regulates ER alpha expression in MCF7 and T47D cells at both

transcription and translational levels. Previous studies have shown that estrogen

receptor and estradiol inactivates p53, therefore, it is possible that p53 expression

is enhanced because of decreased levels of estrogen receptor.

4) S100A7 bi-transgenic mice did not generate spontaneous tumors in breast tissue;

it is possible that spontaneous tumors could develop when p53 is knocked down

88 in breast tissue along with overexpression of S100A7. Our results with MMTV- rtTA/mS100A7A10/p53-/- mouse model proves this hypothesis but further studies

using mammary specific knockdown and mutated p53 mouse models are required

which would help in elucidating the role of S100A7 and p53 in vivo.

89

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