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Roles of epidermal growth factor receptor and its ligands in ovarian cancer Xin, Qiu 2015

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ROLES OF EPIDERMAL GROWTH FACTOR RECEPTOR AND ITS LIGANDS IN OVARIAN CANCER  by Xin Qiu B.Sc., Shandong University, 2003 M.Sc., Academy of Military Medical Science, 2007   A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF   DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Reproductive and Developmental Sciences)   THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) July 2015 © Xin Qiu, 2015   ii Abstract The overexpression of epidermal growth factor receptor (EGFR) has been shown in ovarian cancer and is associated with poor prognosis of this malignant disease. Thus, exploring the EGFR-mediated cell signaling in ovarian cancer may deepen our understanding of this disease. The down-regulation of E-cadherin may promote cell proliferation, motility and invasiveness, leading to the cancer progression. We have previously demonstrated that epidermal growth factor (EGF), amphiregulin (AREG) and transforming growth factor-α (TGF-α), all of which bind exclusively to EGFR, down-regulate E-cadherin expression and induce ovarian cancer cell invasion. In this study, we showed that, as was the case for the effect of EGF, the TGF-α- and AREG-induced down-regulation of E-cadherin expression involved both EGFR and HER2. However, in contrast to the cases of EGF and AREG, the transcription factor Snail was not required for the TGF-α-induced down-regulation of E-cadherin expression. This study showed that TGF-α uses common and divergent molecular mediators to regulate E-cadherin expression and cell invasion. Cyclooxygenase-2 (COX-2) has been shown to participate in cancer metastasis by down-regulating E-cadherin expression, and elevated expression of COX-2 has been reported in ovarian cancer. We have previously demonstrated that COX-2-derived prostaglandin E2 (PGE2) promotes cell invasion in human ovarian cancer. In this study, we showed that EGF/EGFR-induced cell invasion was mediated by the elevation of COX-2 expression and PGE2 production in an E-cadherin-independent manner. Aside from the pro-invasive effect, EGF may strongly promote the cell proliferation. Connexin 43 (Cx43) has been shown to regulate cell proliferation, and this gap junction protein can be regulated by EGF. To date, the functional role of EGF in regulating Cx43 expression in human ovarian cancer has never been investigated. Interestingly, we demonstrated that  iii EGF/EGFR up-regulated Cx43 expression through the activation of Akt1. Functionally, Cx43 may act as a negative regulator of EGF/EGFR-induced cell proliferation in human ovarian cancer, in a gap junction-independent manner.  Overall, our studies provide important insights into the molecular mechanisms regulating EGF-stimulated human ovarian cancer cell invasion and proliferation.    iv Preface A version of Chapter 3 has been published  Qiu X, Cheng JC, Klausen C, Fan QL, Chang HM, So WK, Leung PC. (2015) Transforming growth factor-α induces human ovarian cancer cell invasion by down-regulating E-cadherin in a Snail-independent manner. Biochem Biophys Res Commun. 461:128-35.  A version of Chapter 4 has been published Qiu X, Cheng JC, Chang HM, Leung PC. (2014) COX2 and PGE2 mediate EGF-induced E-cadherin-independent human ovarian cancer cell invasion. Endocr Relat Cancer. 21:533-43.  A version of Chapter 5 has been accepted  Qiu X, Cheng JC, Klausen C, Chang HM, Fan QL, Leung PC. (2014) EGF-induced connexin43 negatively regulates cell proliferation in human ovarian cancer. Journal of Cellular Physiology. JCP-14-0514.  A version of Appendix has been submitted Qiu X, Klausen C, Cheng JC, Leung PC. (2014) CD40 ligand induces caspase and mitochondria-independent, but RIP1-dependent, cell death in low-grade serous but not serous borderline ovarian tumor cells.  I was responsible for the experimental designs and conducted all the experiments in all chapters and appendix. I wrote the manuscripts which were revised by Dr. Christian Klausen and my supervisor.       v Table of Contents Abstract ........................................................................................................................................... ii Preface............................................................................................................................................ iv Table of Contents .............................................................................................................................v List of Tables ................................................................................................................................. vii List of Figures .............................................................................................................................. viii List of Abbreviations...................................................................................................................... ix Acknowledgements ........................................................................................................................ xi Chapter 1. Introduction ....................................................................................................................1  Ovarian cancer.................................................................................................................... 1 1.11.1.1 Overview .................................................................................................................. 1 1.1.2 Classification of ovarian cancers .............................................................................. 2 1.1.3 Subtypes of epithelial ovarian cancers ..................................................................... 2 1.1.4 Origin of epithelial ovarian cancer ........................................................................... 5  Epidermal growth factor receptor (EGFR) and its cognate ligands ................................... 6 1.21.2.1 Overview .................................................................................................................. 6 1.2.2 EGFR structure and signaling................................................................................... 7 1.2.3 EGFR ligands ........................................................................................................... 8 1.2.4 EGFR and its ligands in tumors ................................................................................ 9 1.2.5 EGFR-targeted therapies for cancers ...................................................................... 10  Epithelial-mesenchymal transition (EMT) ....................................................................... 12 1.31.3.1 Overview ................................................................................................................ 12 1.3.2 E-cadherin structure and regulation ........................................................................ 12 1.3.3 E-cadherin in cancer cell invasion .......................................................................... 15  Cyclooxygenase 2 (COX-2) ............................................................................................. 16 1.41.4.1 Overview ................................................................................................................ 16 1.4.2 COX-2 structure and regulation ............................................................................. 17 1.4.3 Roles of COX-2 in health and disease .................................................................... 19  Connexin43 (Cx43) .......................................................................................................... 20 1.51.5.1 Overview ................................................................................................................ 20 1.5.2 Cx43 structure and regulation ................................................................................. 20 1.5.3 Functional roles of Cx43 in embryogenesis and disease development .................. 22 Chapter 2. Rationale and objectives ...............................................................................................25 Chapter 3. Transforming growth factor-α induces human ovarian cancer cell invasion by down-regulating E-cadherin in a Snail-independent manner.........................................................28  vi  Introduction ...................................................................................................................... 28 3.1 Material and methods .................................................................................................... 29 3.2 Results ............................................................................................................................. 32 3.3 Discussion ....................................................................................................................... 35 3.4Chapter 4. COX-2 expression and PGE2 production mediate EGF-induced E-cadherin-independent human ovarian cancer cell invasion .......................................................44  Introduction ..................................................................................................................... 44 4.1 Material and methods .................................................................................................... 46 4.2 Results ............................................................................................................................. 49 4.3 Discussion ....................................................................................................................... 52 4.4Chapter 5. EGF-induced connexin43 negatively regulates cell proliferation in human ovarian cancer .............................................................................................................................................63  Introduction ...................................................................................................................... 63 5.1 Material and methods ..................................................................................................... 65 5.2 Results ............................................................................................................................. 67 5.3 Discussion ....................................................................................................................... 70 5.4Chapter 6. Conclusion ....................................................................................................................82  Summary .......................................................................................................................... 82 6.1 Discussion ....................................................................................................................... 85 6.26.2.1 What are the genomic profiles of my cell line model? ........................................... 85 6.2.2 Is there a correlation between E-cadherin and Cx43 expression levels? ................ 87 6.2.3 What are the clinical implications of my findings to EGFR-targeting therapy? .... 88  Limitations of this study and future directions.......................................................... 90 6.3 Conclusion ....................................................................................................................... 90 6.4References ......................................................................................................................................93 Appendix ......................................................................................................................................127 CD40 ligand induces caspase and mitochondria-independent, but RIP1-dependent, cell death in low-grade serous but not serous borderline ovarian tumor cells ................................... 127 A.1 Introduction............................................................................................................. 127 A.2 Materials and methods ............................................................................................ 129 A.3 Results..................................................................................................................... 133 A.4 Discussion ............................................................................................................... 137  vii List of Tables Table 1.1 Summarized histologic subtypes of ovarian epithelial cancer and their characteristics. ................................................................................................................. 23 Table 6.1 Mutations in SKOV3, OVCAR4 and OVCAR5 cells. .................................... 92    viii List of Figures Figure 1.1 Schematic depicting ErbBs and its congnate ligands. .................................... 24 Figure 3.1 Down-regulation of E-cadherin is required for TGF-α-, AREG- or EGF-induced SKOV3 ovarian cancer cell invasion. ....................................................... 39 Figure 3.2 EGFR is required for TGF-α-, AREG- or EGF-induced down-regulation of E-cadherin. ...................................................................................................................... 40 Figure 3.3 HER2 is involved in the down-regulation of E-cadherin by TGF-α, AREG or EGF. ................................................................................................................................. 41 Figure 3.4 Snail and Slug are differentially involved in TGF-α-, AREG- or EGF-induced down-regulation of E-cadherin. ....................................................................................... 42 Figure 4.1 EGF induces COX-2 expression in SKOV3 and OVCAR5 cells. ................. 57 Figure 4.2 EGFR is required for the EGF-induced up-regulation of COX-2 expression.58 Figure 4.3 The EGF-induced down-regulation of E-cadherin does not require COX-2. 59 Figure 4.4 The Akt signaling pathway is involved in EGF-induced COX-2 expression. 60 Figure 4.5 Efficacy testing of inhibitors. ......................................................................... 61 Figure 4.6 CREB is not involved in EGF-induced COX-2 expression. .......................... 61 Figure 4.7 COX-2 and PGE2 are involved in EGF-induced cell invasion. ..................... 62 Figure 5.1 Kaplan–Meier survival curve for HGSC with EGFR elevation and OncoPrints of up-regulation of related genes. .................................................................................... 74 Figure 5.2 Endogenous expression of EGFR. ................................................................. 74 Figure 5.3 EGF up-regulates Cx43 expression in SKOV3 and OVCAR4 cells.............. 75 Figure 5.4 EGFR is required for EGF-induced Cx43 expression.................................... 76 Figure 5.5 EGF induces ERK1/2 and Akt phosphorylation in SKOV3 and OVCAR4 cells. ......................................................................................................................................... 77 Figure 5.6 EGF-induced Cx43 expression is mediated by PI3K/Akt1 signaling. ........... 78 Figure 5.7 Cx43 negatively regulates EGF-induced cell proliferation. ........................... 79 Figure 5.8 Suppression of EGF-induced cell proliferation by Cx43 is gap junction-independent. ...................................................................................................... 80 Figure 5.9 Correlation between Cx43 expression and overall survival rate. ................... 81 Figure 6.1 The summary of the present study.................................................................. 91     ix List of Abbreviations ANOVA: Analysis of variance AP1: Activator Protein 1 AREG: Amphiregulin BTC: Betacellulin COX: Cyclooxygenase Cx: connexin EGF: Epidermal growth factor EGFR: Epidermal growth factor receptor EMT: Epithelial-mesenchymal transition EOC: Epithelial ovarian cancer EPR: epiregulin ER: Endoplasmic reticulum or Estrogen receptor ERK1/2: Extracellular signal-regulated kinase 1/2  FIGO: International Federation of Gynecology and Obstetrics GJ: Gap junction GJIC: Gap junction intercellular communication HB-EGF: Heparin-binding EGF  HGSC: Low-grade serous carcinomas IL-1: Interleukin-1 JNK: c-Jun NH2-terminal kinase LGSC: Low-grade serous carcinomas  LOH: Loss of heterozygosity LPS: Lipopolysaccharide  x mAbs: Monoclonal antibodies  MAPK: Mitogen-activated protein kinase miRNAs: MicroRNAs  NF-ĸB: Nuclear factor-ĸB  NSAIDs: Nonsteroidal anti-inflammatory drugs ODDD: Oculodentodigital dysplasia OSE: Ovarian surface epithelium PGs: Prostaglandins PI3K: Phosphatidylinositol 3-kinase PKC: Protein kinase C PTB: Phospho-tyrosine binding  PTEN: Phosphatase and tensin homolog PTGS: Prostaglandin-endoperoxide synthase RTK: Receptor tyrosine kinases RT-qPCR: Reverse transcription quantitative real-time PCR SBOT: Serous borderline tumors  SH2: Src homology 2 Sp1: Specificity Protein 1 TGF-α: Transforming growth factor-α TKIs: Tyrosine kinase inhibitors TNF-α: Tumor necrosis facor-α TX: Thromboxane  WHO: World Health Organization WT1: Wilms tumor 1   xi Acknowledgements First of all, I would like to express my deepest gratitude to my supervisor, Dr. Peter C.K. Leung, for his invaluable support and patient supervision of my PhD project. In addition, I would like to express my sincere gratitude to my supervisory committee members, Dr. Blake Gilks, Dr. Mark Carey and Dr. Xuesen Dong for their continuous guidance of and invaluable comments on my project.  My sincere thanks also goes to Dr. Christian Klausen for his excellent advice, comments and mentorship.  I would like to thank my colleagues in Dr. Leung’s lab, particularly Dr. Jung-Chien Cheng and Dr. Hsun-Ming Chang, for their constant assistance, support and friendship.  A special thank you to Ms. Roshni Nair and her family for their heartwarming care and love that made the place I live such a wonderful home for me.   Finally, I would like to thank my family for their unlimited love, understanding and support in my life.     1 Chapter 1.  Introduction  Ovarian cancer 1.11.1.1 Overview Ovarian cancer is the fifth most lethal death type of cancer and the leading cause of death in gynecological malignancies. In the United States, it is estimated that approximately 21,980 new cases of ovarian cancer would be diagnosed in 2014, causing 14,270 deaths (1). The Canadian Cancer Society estimated that approximately 2,700 new cases of ovarian cancer would be diagnosed (10.8 per 100,000 women) and would cause approximately 4.7% of the cancer-related death among women in Canada during 2014 (2). Ovarian cancer normally has no obvious symptoms in its early stage, until it has advanced into the peritoneal cavity, where it can be detected in the majority of the patients (3). However, clinical studies showed that some women might experience several nonspecific symptoms, such as enlargement of the abdomen (the most common sign), urinary symptoms, back pain, irregular bleeding and bloating. In most cases, patients do not exhibit any of these symptoms until the tumor has reached an advanced stage. That is why ovarian cancer is often called a “silent killer” (4,5). Currently, the absence of an effective screening method for the early detection of ovarian cancer combined with the deficiency of specific clinical symptoms of its existence attributes to the presence of advanced-stage ovarian cancer at diagnosis in most patients. The conventional treatment for this disease is chemotherapy followed by cytoreductive surgery, and sometimes radiotherapy (6,7). Although improvements in the chemotherapeutic and surgical treatments have been made, the overall survival rate has not changed appeciably during the past 50 years.  2 The overall 5-year survival rate is 45%, with most patients (61%) being diagnosed at advanced stages (FIGO stages III and IV) and having low 5-year survival rates (27%). However, if the disease is detected at FIGO stages I, the 5-year survival rate dramatically increases to 92% (8). 1.1.2 Classification of ovarian cancers    Ovarian cancer is a heterogeneous disease that is challenging to treat. According to the World Health Organization (WHO), ovarian tumors can be broadly classified into 3 groups based on their derivation, including sex cord-stromal tumors, germ cell tumors and epithelial tumors. Sex cord-stromal tumors, such as fibromas, granulosa cell tumors and thecomas, account for approximately 7% of ovarian cancers and can arise from stromal cells, granulosa cells and thecal cells, respectively. Germ cell tumors, such as choriocarcinomas and dysgerminomas, are believed to originate from primordial germ cells, and account for approximately 3-7% of ovarian cancers. Most germ cell tumors arise in children and adolescents. Epithelial ovarian cancers, the most common type, account for the majority of ovarian cancers, approximately 90% (9). 1.1.3 Subtypes of epithelial ovarian cancers Based on their histological characteristics, the epithelial ovarian tumors can be divided into four main subtypes, comprising serous, endometrioid, clear cell, and mucinous carcinomas (Table 1.1) (10).  Ovarian serous carcinomas account for 60% of the ovarian epithelial cancers, and are positive for the immunomarkers ER (estrogen receptor) and WT1 (Wilms tumor 1). The Shih and Kurman group suggested a dualistic model for explaining the development of serous ovarian carcinomas based on the clinicopathological and molecular genetic characteristics, from which ovarian serous carcinoma could be divided into two types, HGSCs (high-grade serous  3 carcinomas) and LGSCs (low-grade serous carcinomas). Conventional HGSCs develop directly from the ovarian surface epithelium, fallopian tubes or unidentified precursor lesions, whereas LGSCs develop from benign serous cystadenomas via non-invasive serous borderline ovarian tumors (SBOTs), in a stepwise manner (11,12). HGSCs account for approximately 90% of ovarian serous carcinomas and frequently occur in patients between the ages of 55-65 years. The majority of patients with HGSCs are diagnosed at an advanced stage, with tumors present in both ovaries (84%), and have a poor prognosis (13). HGSCs show a mixture of papillary, glandular, nested and diffuse/solid growth patterns. The mitotic rate of HGSCs is very high, and they contain abundant apoptotic bodies. HGSCs are frequently characterized by TP53 genetic mutations (>95%) and high chromosomal instability (14). Germline mutations of BRCA (BRCA1 or BRCA2) genes are related to hereditary HGSCs (15). Up to 80% of HGSCs show good responsiveness to carboplatin and paclitaxel-based chemotherapies, although most exhibit recurrence (16). LGSCs account for 10% of serous carcinomas and show a micropapillary growth pattern. The majority (74-77%) of LGSCs are bilateral at presentation. LGSCs and HGSCs generally have mutually exclusive genetic mutations, with mutations in the BRAF, KRAS and ERBB genes occurring in the former. Moreover, KRAS and BRAF mutations are far more frequent in the former than are ERBB2 mutations (17,18). In contrast to HGSCs, LGSCs do not have TP53 or germline BRCA genetic mutations. Compared with HGSCs, LGSCs display notorious resistance to conventional chemotherapeutic drugs, such as carboplatin and paclitaxel. Schmeler et al. showed that after a median of six cycles of platinum-based chemotherapeutic treatment, only 4% of patients showed a complete regression, 88% had stable disease and 8% had tumor progression (19). Endometrioid carcinomas, which account for 10-20% of epithelial ovarian cancers, are  4 associated with endometriosis and affect women during the post-menopausal ages. Low-grade endometrioid carcinomas are characterized by CTNNB1 (38-50%) and PTEN genetic mutations (20%), whereas high-grade endometrioid carcinomas are associated with TP53 and BRCA1 mutations. Most endometrioid carcinomas are diagnosed at stage I or II and show good responsiveness to platinum-based chemotherapies, which accounts for these types of ovarian cancers having the most favorable prognosis among all subtypes, with 5-year survival rates of 63-78% (15,16). Clear cell carcinomas are responsible for approximately 10% of epithelial ovarian cancers and often arise from endometriotic cysts. The mean age of patients with stage I or II at presentation is 57 years, and the 5-year survival rates for patients is 55-69%, although clear cell carcinomas are resistant to platinum-based chemotherapies and are associated with Trousseau syndrome (cancer-related venous thrombosis). Clear cell carcinomas show PIK3CA gene mutations (33%) and up-regulated expression of the transcription factor HNF-1ß (15,16,20). ARID1A mutations, identified in one-third of low-grade endometrioid carcinomas, are also found in nearly half of clear cell carcinomas (21). Mucinous carcinomas account for less than 5% of epithelial ovarian cancers and affect women aged 40-50 years, presenting as large (>13 cm) unilateral tumors. Mucinous tumors are characterized by the presence of KRAS and HER2 gene mutations. Several studies suggest that mucinous tumors have the same histological characteristics as Brenner tumors, and the origins of both of these tumor types are puzzling (15,16,20,22). Recently, the two-pathway carcinogenesis model was proposed to divide the epithelial ovarian tumors into 2 categories: type I and type II tumors. Type I tumors include low-grade serous carcinomas, low-grade endometrioid carcinomas, mucinous carcinomas, clear cell carcinomas and malignant Brenner tumors. Type II tumors comprise high-grade serous  5 carcinomas, high-grade endometrioid carcinomas, carcinosarcomas, and undifferentiated carcinomas (11,20). The type I tumors are indolent and show slow progression; in addition, BRAF, KRAS or ERBB2 gene mutations are the common genetic alterations in these types of tumors (~67% in serous carcinoma), which rarely occur in type II carcinomas (13,17). In contrast, type II tumors are aggressive and show rapid progression, and they have TP53 gene mutations in most cases (50-80%), which type I tumors do not harbor (11). The different subtypes of ovarian cancer are distinct diseases that require different research designs and clinical management regimens. 1.1.4 Origin of epithelial ovarian cancer The origin of epithelial ovarian cancer (EOC) has long been debated. In 1971, the incessant ovulation theory was proposed by Fathalla, which postulated that repeated ovulation causes repeated minor trauma to the surface epithelium and that the subsequent repair of the surface epithelium leads to the formation of inclusion cysts, which in turn contribute to malignant transformation (23). There is substantial evidence supporting this OSE (ovarian surface epithelium) origin theory based on its potential stemness and developmental history (24,25). Several studies also demonstrated that the OSE of animal models or cultured human OSE cells could be transformed to malignant tumors exhibiting the properties of epithelial ovarian cancer (26-30).  In 2001, Piek et al. were the first to report the presence of dysplastic lesions in prophylactically removed fallopian tubes of women with BRCA mutations that predispose them to developing ovarian cancer (31). In 2004, the concept that the epithelium in the fimbriae of the fallopian tubes might be another source of HGSCs was proposed by the same authors (31). An early form of serous carcinoma in the surface of the fimbria termed “serous tubal intraeptithelial  6 carcinoma (STIC)” displaying similar HGSC histology without invasion was identified as a precursor to HGSC (32,33). TP53 gene mutations, which are characteristic of HGSCs, were also detected in concurrent STIC, providing evidence supporting that HGSCs originate from the epithelium of fimbriae (34). Moreover, increasing evidence suggests that STIC develops from p53 signature, a lesion of benign-appearing tubal epithelium with a p53 mutation. (32,33). Another study also showed that human fallopian tube secretory epithelial cells could be genetically manipulated to transform to high-grade Müllerian carcinomas similar to HGSCs (35). The similar precursor lesion of HGSC has not identified in the ovary. In spite of a myriad of studies on the origin of EOC, this issue has not been conclusively resolved.  Epidermal growth factor receptor (EGFR) and its cognate ligands 1.21.2.1 Overview EGFR, also known as ErbB-1 or HER1, belongs to the ErbB family of receptor tyrosine kinases, which includes three other distinct but structurally related receptors, ErbB-2 (HER2/neu), ErbB-3 (HER3) and ErbB-4 (HER4). The ErbB receptors are type I transmembrane receptors that can be structurally divided into three parts, an extracellular domain, a single transmembrane domain, and an intracellular domain (36). The extracellular domain is highly glycosylated and is responsible for ligand binding. The transmembrane domain is hydrophobic and maintains the receptor within the plasma membrane to relay the external signals to the interior of a cell. The intracellular domain contains a tyrosine kinase domain that is highly conserved among the members of the ErbB receptor family, with the exception of ErbB-3 (36,37). ErbB-3 contains an asparagine substitution of aspartic acid at 814 in the tyrosine kinase domain, which abolishes its kinase activity (38).  7 The members of the ErbB receptor family are activated by binding to their ligands, the EGF-family growth factors, which can be categorized into three groups based on their ligand binding affinity and specificity. The first group of ligands is comprised of amphiregulin (AREG), epidermal growth factor (EGF), epigen and transforming growth factor-α (TGF-α), all of which bind exclusively to EGFR. The second group of ligands includes betacellulin (BTC), epiregulin (EPR) and heparin-binding EGF (HB-EGF), which bind to both EGFR and ErbB-4. The remaining group of ligands is composed of neuregulins (NRGs), also known as heregulins (HRGs) or neu differentiation factors (NDFs), which can be divided into two subgroups based on their receptor-binding specificity. NRG-3 and HRG-4 bind to only ErbB-4, whereas NRG-1 and NRG-2 bind to both ErbB-3 and ErbB-4 (36,37). The schematic representations of the ErbB family and its ligands are shown in Figure 1.1. 1.2.2 EGFR structure and signaling EGFR was first discovered by Carpenter et al. as the specific receptor for EGF and was thus named epidermal growth factor receptor (39,40). EGFR is a 170 kDa heavily N-glycosylated protein composed of 1186 amino acids. The extracellular domain contains 621 amino acids that can be further divided into four sub-domains, DΙ, DΙΙ, DΙΙΙ, DΙV (41). DΙ and DΙΙΙ are responsible for ligand binding, although DΙΙΙ is the major contributor, with an approximately 400 nM binding affinity for EGF (42). Both DΙΙ and DΙV are rich in cysteines and contain several small disulfide-bonded modules. When EGFR exists in monomeric form, the DΙΙ/DΙV interaction maintains the receptor in an autoinhibited conformation through burying the dimerization arm of DΙΙ with DΙV. However, ligand binding to the receptor causes a conformational change from the autoinhibited state to an extended state. The released dimerization arm of DΙΙ mediates the contact of receptors to form dimers. In contrast to EGFR,  8 HER2 remains in an extended conformation even in the monomeric form, which gives it a priority to form heterodimers with other members of the ErbB family of receptors (41,43,44). Following receptor dimerization, the tyrosine residues of the intracellular domain are phosphorylated by the tyrosine-kinase domain through transphosphorylation (44). The phosphorylated tyrosine residues serve as docking sites for cellular downstream adaptor proteins containing SH2 (Src homology 2) or PTB (phospho-tyrosine binding) domains, which in turn induce multiple downstream signaling pathways, such as the MAPK and PI3K/Akt pathways, to promote various cellular functions, including proliferation, angiogenesis, and cytoskeletal rearrangements (37,41,44). 1.2.3 EGFR ligands Among the EGF-family growth factors, AREG, EGF and TGF-α bind exclusively to EGFR. These ligands are all characterized by a conserved EGF motif containing three intramolecular disulfide bonds that mediates the specificity of their binding to receptors. They are synthesized as type Ι transmembrane precursors and then are processed into soluble ligands through extracellular cleavage (45). AREG was initially identified in conditioned medium of phorbol 12-myristate 13-acetate-treated human breast adenocarcinoma MCF-7 cells (46). The AREG gene is situated on chromosome 4 (4q13-4q21), and the precursor gene product is a 252-amino acid protein with a molecular weight of approximately 34-36 kDa, which is proteolytically cleaved into the mature soluble protein (~ 10 kDa), which is composed of 84 amino acids (47). The reason for the prefix “amphi” being in its name is that it has been reported to have both stimulatory and inhibitory effects on cell growth (45,48). EGF was originally isolated due to its ability to accelerate incisor eruption and eyelid  9 opening in newborn mice (49). EGF is synthesized as a 1207-amino acid precursor with a molecular weight of approximately 170 kDa, which is then cleaved to form the mature peptide (~ 6 kDa), which is composed of 53 amino acids. The EGF gene is located on human chromosome 4q25 (45,48).  TGF-α was first reported in 1976 as a component of retrovirally transformed murine fibroblastic cells that was functionally related to EGF (50). TGF-α is initially synthesized as a 160-amino acid transmembrane protein (~22 kDa); this protein is processed to form the mature peptide (~ 5.6 kDa) containing 50 amino acids. The mature TGF-α protein exhibits a secondary structure similar to that of EGF with which it shares 30-40% sequence homology. The TGF-α gene is located on human chromosome 2q13 (51,52).    1.2.4 EGFR and its ligands in tumors Increased expression of EGFR has been detected in both human breast cancer cell lines and breast carcinomas (53-55). The increased expression of EGFR has been shown to be associated with a poor prognosis and a lack of response to endocrine therapy in patients with breast cancer (48). EGFR overexpression has been detected in 35-70% of primary ovarian carcinomas, whereas in normal ovarian tissues, the level of EGFR expression is very low (48,56). In addition, in ovarian cancer metastases and advanced-stage ovarian cancers, a higher level of EGFR expression has been reported compared with that in primary tumors, indicating that EGFR plays an important role in disease progression (57-59). It has been shown that EGFR overexpression is associated with a poor prognosis for ovarian cancer patients (60). The overexpression of EGFR caused the transformation of the mouse embryonic fibroblast cell line NIH-3T3 in the presence of exogenous EGF (61). Fischer rat fibroblast cells (Rat-1) and normal rat kidney cells (NRK) could be transformed by overexpression of TGF-α, whereas NIH-3T3 cells could be transformed  10 only by the overexpression of both EGFR and TGF-α (62-64). These data indicated that EGFR alone is not able to induce transformation. However, various lines of evidence showed that EGFR blockade leads to significant growth suppression in various types of human carcinoma cells both in vitro and in vivo, suggesting EGFR as a therapeutic target (65). In fact, advances in clinical strategies for cancer treatment have been made through targeting EGFR.  EGF has been detected in both human breast cancer cell lines and primary invasive breast cancers (48). Moreover, the expression of EGF is correlated with a poor prognosis in patients with breast cancer (66). EGF is expressed in a small moiety of primary ovarian carcinomas (28%) at a level lower than that of TGF-α (67,68). TGF-α expression is observed in human breast tumors but not in the surrounding stromal cells (48,69). A similar expression pattern was observed in ovarian tissues. TGF-α is expressed in most primary ovarian carcinomas whereas it undetectable or expressed at a very low level in the normal ovary (67,68,70,71). TGF-α treatment has been reported to both stimulate and inhibit the growth of human ovarian cancer cells (72-74). A similar bifunctional growth modulation has been demonstrated in AREG-treated human breast and ovarian carcinoma cells (46,75). AREG has been shown to be overexpressed in ovarian carcinomas relative to normal ovary tissues. Moreover, the level of AREG expression is much higher than that of TGF-α and EGF in ovarian cancer cell lines and tissues and the peritoneal fluid of ovarian cancer patients (76-78).  1.2.5 EGFR-targeted therapies for cancers Given the importance of EGFR in tumor growth and survival, therapeutic agents targeting EGFR activity have been developed for cancer treatment. Two major groups of agents are most widely used, monoclonal antibodies (mAbs) and tyrosine-kinase inhibitors (TKIs) (44,79).  Anti-EGFR mAbs compete with ligands for binding to the extracellular domain of the  11 receptors, blocking the ligand-induced EGFR activation and promoting receptor internalization (44,79). Among the mAbs available, cetuximab was the first to be approved and is the one most utilized for the treatment of metastatic colorectal and head/neck cancer (44,80). Compared with that of EGF or TGF-α, cetuximab has a higher binding affinity for EGFR and can bind to EGFRvΙΙΙ (a constitutively active EGFR mutant) (81,82). It has also been demonstrated that cetuximab induced the internalization of EGFRs, which is followed by its degradation and the blockage of its nuclear transport (44). Cetuximab has been found to have various anti-tumor activities, including cell growth inhibition, invasion prevention, angiogenesis blockage, cell cycle arrest, apoptosis induction, and chemotherapy-sensitivity enhancement (83-86). However, the first clinic trial of cetuximab on patients with ovarian cancer yielded an unsatisfactory result, with only 4% of patients experiencing a partial response (87).  TKIs are small synthetic molecules that compete with adenosine triphosphate (ATP) for binding to the intracellular tyrosine-kinase domain of receptors. They have a lower level of specificity compared with mAbs and a short half-life (41,43). Gefitinib is an orally active, quinazoline-derived, reversible small molecular inhibitor (41,88). This TKI has shown anti-tumor activity in various tumor cell lines and human tumor xenografts (88-90). Previous studies showed that gefitinib had limited clinical activity in patients with recurrent ovarian carcinoma (91,92). Erlotinib, another TKI, is also an orally active, quinazoline-derived small reversible molecular inhibitor (41,79). It has been demonstrated that erlotinib induced apoptosis and blocked cell-cycle progression (93). In patients with non-small cell lung cancers, the rate of response to erlotinib treatment was 12% and an increased survival was observed (94). However, in patients with stage III-IV epithelial ovarian cancer, adding erlotinib to carboplatin-paclitaxel did not yield improved results in a phase II study (95).  12  Epithelial-mesenchymal transition (EMT) 1.31.3.1 Overview Epithelial-mesenchymal transition (EMT) is a reversible biological process in which epithelial cells lose their characteristic attributes and transdifferentiate into migratory, invasive mesenchymal cells (96). The reverse process of EMT, mesenchymal-epithelial transition (MET), which is also involved in cellular morphogenetic regulation, has been relatively rarely studied compared with EMT (97). The EMT can be divided into three types based on the functional distinctions. Type 1 EMT occurs during blastocyst implantation, embryogenesis and organ development, during which fibrosis or an invasive phenotype is not induced. Type 2 EMT is associated with tissue regeneration, organ fibrosis and wound healing, in which inflammation is often involved. Type 3 EMT occurs in neoplastic cells and is associated with cancer progression and metastasis (96). E-cadherin, one of the classical cadherins, is considered a prototypical cadherin and plays an essential role in maintaining the normal epithelial structure (98,99). During type 3 EMT, the level of E-cadherin (epithelial marker) expression often decreases, accompanied by the up-regulation of N-cadherin (mesenchymal marker) expression, a process known as cadherin switching (100,101). However, decreased E-cadherin expression is not always coupled by increased N-cadherin expression, suggesting that cadherin switching is most likely cell-type dependent (102).  1.3.2 E-cadherin structure and regulation Cadherins constitute a large family of membrane-bound glycoproteins that play important  13 roles in mediating cell-cell adhesion. E-cadherin is one of the classical cadherins (type Ι) and is considered the prototypical cadherin (98). E-cadherin is encoded by the CDH1 gene, which is located on human chromosome 16q22.1. The CDH1 gene encompasses 16 exons and 15 introns with a CpG island present in intron 1 (103). The newly synthesized E-cadherin polypeptide is directed to the ER (endoplasmic reticulum) via a short signal sequence, which is later cleaved. The mature form of E-cadherin (120 kDa) comprises a large ectodomain, a single transmembrane domain and a short cytoplasmic domain. The extracellular domain contains five tandemly repeated motifs called “extracellular cadherin (EC)” domains (EC1-EC5) that are responsible for the homophilic interactions of E-cadherin proteins, particularly via the EC1 domain (104). The intracellular domain can be further divided into two subdomains, a juxtamembraneous domain (JMD) and a catenin-binding domain (CBD). These domains contain cadherin homology (CH) 2 and 3 motifs, respectively, whereas CH1 is located on EC1 (105). E-cadherin is regulated at various levels, including genetic, epigenetic and transcriptional levels (106). CDH1, the gene encoding E-cadherin, is frequently associated with the loss of heterozygosity (LOH) in a variety of human carcinomas, including endometrial, ovarian, breast and gastric cancers (107-110). Inactivating mutations have also been identified, specifically in gastric cancers and sporadic lobular breast cancers (108,110). Epigenetically, promoter methylation and the acetylation of histone have been reported to suppress E-cadherin expression (111,112). At the transcriptional level, several transcription factors have been demonstrated to mediate the silencing of E-cadherin expression, including members of the snail family, the basic helix-loop-helix (bHLH) family and the zinc finger homeobox (ZFH) family, by binding to E-boxes located in the CDH1 promoter (113). The Snail superfamily can be divided into two subgroups, the Snail and Scratch families.  14 The Snail and Slug transcription factors belong to the Snail subgroup, and their role in the EMT process has been widely studied. These proteins contain a divergent N-terminal domain and a highly conserved C-terminal region that contains four to six zinc fingers (C2H2 type) that bind to specific DNA sequences, the E-box elements, to regulate transcription (114). Although both of these proteins can bind to the E-box elements of the E-cadherin promoter, it seems that they recruit different sets of molecules to prevent E-cadherin expression (113). Several lines of evidence have shown that the expression of Snail is associated with the down-regulation of E-cadherin expression and the increased ability of cells to metastasize (115-118). Slug is structurally different from Snail in the intermediate region, where Slug contains a specific amino-acid sequence called the Slug domain, whereas Snail has a serine-proline-rich domain (113). Slug has also been shown to be a transcriptional repressor of E-cadherin expression by binding to E-box elements in the E-cadherin gene promoter with a lower affinity compared with that of Snail (119). Slug was shown to play an important role in the induction of EMT during vertebrate development (120). In addition, several lines of evidence showed that the expression of Slug was associated with the down-regulation of E-cadherin expression in a variety of cancers (119,121,122). Members of the basic helix-loop-helix (bHLH) family contain a common structure consisting of two parallel amphipathic α-helices joined by a short loop, which is responsible for their binding to DNA at a consensus-sequence E-box element. The bHLH proteins are homo- or hetero-dimeric proteins found in eukaryotes (113,123). E12 and E47, which are encoded by the same gene E2A, are produced through alternative splicing (124). It was shown that E12 and E47 act as repressors of E-cadherin expression during both development and tumor progression (125). Twist1 and Twist2, which exhibit a high degree of sequence similarity, are highly conserved members of the bHLH protein family (126). The ectopic expression of Twist results in  15 the loss of E-cadherin, leading to EMT and contributing to tumor metastasis (127,128).  ZEB1 and ZEB2 constitute the ZEB subfamily in vertebrates, which belongs to the zinc finger homeodomain (ZFH) family. ZEB1 and ZEB2 are encoded by different genes, ZFHX1A and ZFHX1B, respectively. Both of these proteins contain two zinc-finger clusters at the two termini and a central homeodomain. The zinc-finger clusters mediate the interactions of ZEB and DNA E-box elements (113). The expression of ZEB1 and ZEB2 has been reported to be associated with the down-regulation of E-cadherin expression and the increased invasion of human cancer cells (129-131). 1.3.3 E-cadherin in cancer cell invasion The loss of E-cadherin expression is an important event in the EMT. The lack of E-cadherin has been reported at sites of the EMT during development and cancer progression. A correlation between the down-regulation of E-cadherin expression and a higher carcinoma invasive potential has been demonstrated in many types of epithelial tumors. In nude mice, E-cadherin-negative cell lines, compared to the E-cadherin-expressed cell lines, show higher levels of tumorigenicity. Clinically, the down-regulation of E-cadherin expression is often associated with an advanced grade of tumor and a shorter patient survival period (97,132). However, E-cadherin is not expressed in the normal OSE, except in the lining of inclusion cysts and epithelial invagination into the stroma (133), whereasE-cadherin is detected clearly in both normal glandular and squamous epithelia obtained from fallopian tube (134). Strong expression of E-cadherin was detected in benign and borderline ovarian tumors using an immunohistochemical technique, whereas the levels of E-cadherin were significantly lower in malignant adenocarcinomas. Despite that, correlations were found between a reduced level of E-cadherin expression and a high tumor grade, the presence of peritoneal seeding and a low  16 overall survival rate in patients with ovarian cancer (135,136). In mouse ovarian tumor cells, an extremely low level of E-cadherin was expressed in cells with high metastatic potential, whereas weakly metastatic cells expressed high levels of E-cadherin (137). It was demonstrated that ascites cells derived from primary tumors had significantly lower levels of the E-cadherin transcript than did their solid-tumor counterparts and that ascites cells were 4-fold more invasive than were solid-tumor cells in vitro, which was consistent with the differences of their E-cadherin levels (138). Knocking down E-cadherin expression using siRNA was reported to promote the metastasis of ovarian cancer cells (139). Our recent studies demonstrated that EGF induced the invasion of human ovarian cancer cells and down-regulated the expression of E-cadherin through various signaling pathways; moreover, the forced overexpression of E-cadherin inhibited the basal invasiveness of human ovarian cancer cells (140-145). Taken together, all these data indicate that E-cadherin down-regulation is involved in ovarian cancer cell invasion.  Cyclooxygenase 2 (COX-2) 1.41.4.1 Overview Cyclooxygenase (COX), also known as prostaglandin-endoperoxide synthase (PTGS), is a bifunctional enzyme that catalyzes the transformation of arachidonic acid into prostaglandins (PGs) through cyclooxygenation. During this conversion process, COX catalyzes the transformation of arachidonic acid into PGG2 by adding two molecules of O2 to arachidonic acid in the cyclooxygenase site of COX during the first step, after which PGG2 is reduced to PGH2 through dissociation from the cyclooxygenase site and relocates to the peroxidase active site of  17 COX. PGH2 is highly unstable and is subsequently converted to a variety of PGs, including PGD2, PGE2, PGF2 and PGI2, and thromboxane (TX) A2 (146-148).  PGs are released from cells and play important roles in the local environment in an autocrine and/or paracrine manner. PGs are involved in diverse physiological functions, including bone metabolism, renal homeostasis, gastric cytoprotection, blood clotting and inflammation (146). Given the various roles that PGs play and the rate-limiting step of PG synthesis by COX, nonsteroidal anti-inflammatory drugs (NSAIDs) were developed for the treatment of a variety of abnormal physiological conditions through inhibiting COX activity (149).  1.4.2 COX-2 structure and regulation Three isoforms of COX, COX-1, COX-2 and COX-3, have been described. COX-1 is constitutively expressed in most tissues and maintains their homeostasis, whereas COX-2 expression is induced by various stimuli, including cytokines, mitogens and hypoxia (150,151). COX-3 is a variant of COX-1 and is expressed mainly in the cerebral cortex and heart (152). The COX-2 gene is located on human chromosome 1 and encompasses 8 kb including 10 exons. The COX-2 promoter displays several transcriptional regulatory elements, including a TATA box, nuclear factor-ĸB (NF-ĸB) response elements and AP-2 sites (148). COX-2 protein has four functional motifs, an N-terminal signal peptide, a dimerization domain, a membrane-binding domain and a catalytic domain. The catalytic domain can be further divided into two subdomains, the cyclooxygenase and peroxidase sites (148). Newly synthesized COX-2 polypeptide is directed to ER (endoplasmic reticulum) via its signal peptide, which is later cleaved. Two COX-2 molecules are held together via the interaction of their dimerization domains. Heterodimers of COX-1 and COX-2 do not exist. The membrane-binding domain  18 consists of four tandem amphipathic helices that form a hydrophobic surface that monotonically inserts into lipid bilayers, including those of the luminal ER (endoplasmic reticulum) membrane and the nuclear envelope (146,148).  As an immediate-early response molecule, COX-2 expression is rapidly induced by a variety of stimuli, including lipopolysaccharide (LPS), interleukin-1 (IL-1), tumor necrosis factor-α (TNF-α) and EGF. It was shown that LPS-induced COX-2 expression occurs through the activation of the mitogen-activated protein kinase (MAPK) and protein kinase C (PKC) pathways, followed by the involvement of the NF-ĸB response element and the NF-IL6 and CRE sites in the COX-2 promoter in macrophage/monocytic cells (153). IL-1 has been shown to up-regulate COX-2 expression through multiple signaling pathways, including the extracellular signal-regulated kinase 1/2 (ERK1/2), c-Jun NH2-terminal kinase (JNK), P38 mitogen-activated protein kinase, and NF-ĸB pathways in human colon carcinoma HT29 cells (154). The TNF-α-induced up-regulation of COX-2 expression is mediated by multiple signaling molecules, such as tyrosine kinases, PLC-γ2 and NF-ĸB, in human lung epithelial cells (155). Previous studies have shown that EGF strongly induced COX-2 expression through different signaling pathways in human glioma cell lines and lung adenocarcinoma cells (156,157). Taken together, these data indicated that there is redundancy in the signaling pathways that regulate COX-2 expression and that such pathways are cellular context-dependent. The 3’-untranslated region (3’-UTR) of COX-2 mRNA mediates its post-transcriptional regulation. A cis-acting AU-rich element (ARE) composed of six clusters of AUUUA sequence motifs was found within this 3’-UTR (158). Trans-acting ARE-binding proteins mediate the stability of COX-2 mRNA. To date, several ARE-binding proteins have been reported to effect the COX-2 3’-UTR. Among these proteins, HuR and Apobec-1 stabilize COX-2 mRNA and lead to the up-regulation of COX-2 expression (159,160), whereas CUGBP2 and T-cell  19 intracellular antigen 1 (TIA-1) have been demonstrated to prevent COX-2 expression through translational inhibition (161,162). MicroRNAs (miRNAs) can repress the expression of their target mRNAs by imperfectly binding to the 3’-UTR of the targeted transcripts (163). MiR-101a and miR-199a have been shown to be involved in the down-regulation of COX-2 expression in mice (164). 1.4.3 Roles of COX-2 in health and disease The results of a targeted deletion of the COX-2 gene showed that COX-2 plays an important role in renal development and function in postnatal mice (165). Studies using an animal model showed that inhibiting COX-2 activity resulted in a reduction of inflammatory cell infiltrate and decreased inflammation of the synovium, suggesting that COX-2 plays an important role in the inflammation of arthritis (166). Up-regulated COX-2 expression has been detected in osteoarthritis-affected cartilage and synovial membrane biopsies taken from patients (167,168). Rofecoxib and celecoxib, which are specific COX-2 inhibitors, have been approved for the treatment of pain and rheumatoid arthritis, respectively, and do not have gastroduodenal toxicity (169). Several studies have shown a correlation between the decreased risk of developing Alzheimer’s disease (AD) and NSAID (nonsteroidal anti-inflammatory drugs) usage, indicating involvement of COX in AD development (170,171). In addition, it has been shown that COX-2 expression was up-regulated in the hippocampal pyramidal layer of sporadic AD patients. Moreover, AD is characterized by the presence of β-amyloid-containing plaques, and the COX-2 level has been demonstrated to correlate with the density of amyloid plaques, indicating that the COX-2 level could be an indicator of the progression of dementia in early AD (172,173).  There is increasing evidence that COX-2 expression is elevated in several types of human  20 cancers, including skin, liver, breast and lung cancers (174-176). Previous studies have shown that specific COX-2 inhibitors can reduce the growth of liver, breast and colorectal tumors (175,177,178), which suggested that COX-2 is involved in tumor proliferation. Elevated COX-2 expression has also been detected in malignant ovarian tumors (179), and a high level of COX-2 expression is correlated with a poor prognosis and overall survival rate in patients with ovarian cancer (180,181).  Connexin43 (Cx43) 1.51.5.1 Overview To date, 21 members of the connexin family have been identified in humans. The connexins are integral membrane proteins, generally named “connexin” (Cx) followed by their predicted molecular weights in kilodaltons (182). Six Cx molecules form a ring structure with a hydrophilic pore at the center, which is called the connexon or hemichannel. A specialized structure is formed by the head-to-head assembly of two connexon, each provided by an adjacent communicating cell. This specialized structure is a gap junction (GJ) channel that anchors the plasma membranes and directly connects the cytoplasm of two neighboring cells to mediate the exchange of a variety of small hydrophilic molecules, such as ions, metabolites and second messengers (183-185). More than ten and even up to thousands of GJ channels densely assemble to form a structure called a GJ plaque (185). Among the Cxs, Cx43 is the most abundantly expressed and well-studied Cx protein (185,186).  1.5.2 Cx43 structure and regulation Cx43 is encoded by the GJA1 gene, which is located on human chromosome 6. The GJA1  21 gene can be divided into 3 parts (from 5’ to 3’), an exon containing part of the 5’-untranslated region (5’-UTR), an intron, and a second exon composed of the remaining part of the 5’-UTR, a protein-coding sequence, and the 3’-UTR (187). Cx43 is a tetra-spanning membrane protein containing two extracellular loops, one intracellular loop, 4 transmembrane domains and cytoplasmic N- and C-termini. The C-terminus is the primary region targeted for posttranslational modification and can bind interacting proteins to transduce signaling pathways (185,188). Cx43 expression is regulated by several mechanisms at different levels in response to various physiological and pathological stimuli (189,190). The presence of Activator Protein 1 (AP1) and Specificity Protein 1 (Sp1) binding sites in the proximal promoter region of the human Cx43 gene has been demonstrated. In addition, both Sp1 and c-Jun are required for its maximal promoter activity, thereby contributing to the transcriptional regulation of Cx43 expression (191). Cx43 undergoes post-translational modifications, among which phosphorylation is the most studied (192). Cx43 was shown to be directly phosphorylated by casein kinase 1, which led to the assembly of Cx43 into GJs (193). EGF was shown to induce the phosphorylation of Cx43 via the MAP kinase pathway to mediate gap-junction intercellular communication (GJIC) (194). Given that GJ are highly controlled dynamic structures, the turnover rate of Cx must be tightly regulated. 12-O-tetradecanoylphorbol-13-acetate (TPA) induces the ubiquitination of Cx43, accompanied by Cx43 hyperphosphorylation, eventually leading to its internalization and degradation in rat liver IAR20 epithelial cells (195). A similar effect was observed after EGF treatment in the same cell lines (196). Additionally, through interacting with various proteins, such as ZO-1, microtubules, and caveolin-1, Cx43 could crosstalk with other cellular signaling pathways to mediate diverse cellular functions (192,197-199).   22 1.5.3 Functional roles of Cx43 in embryogenesis and disease development In 1995, the first report of the results of a Cx43 knockout study was published; the Cx43 knockout mice died at birth due to a cardiac malformation, which suggested that Cx43 plays an essential role in heart development (200). In the same year, the mutation of the Cx43 gene was linked to the human heart disease visceroatrial heterotaxia (201). Inactivation of Cx43 gene in the cardiomyocytes of mice led to narrowing of the ventricular outlet region, hypertrophy of the ventricular myocardium and impaired development, which eventually caused their death (202). In addition to having a role in heart development, Cx43 has been reported to play an important role in wound repair. Down-regulated Cx43 expression resulted in a dramatically improved rate of wound healing through increasing the proliferation rate of endothelial cells (203,204). Oculodentodigital dysplasia (ODDD) is a rare autosomal genetic disease characterized by developmental anomalies of the eyes, teeth and limbs. Mutations in the Cx43 gene have been shown to be responsible for this disorder (205-208). Down-regulated Cx43 expression has been reported in several types of human tumors, indicating its role in tumor progression. Cx43 is highly expressed in ovarian surface epithelial cells but its level is dramatically reduced in ovarian cancer cells (209,210). A similar expression pattern has been observed in brain, lung and skin carcinomas (211-213). In dysplastic regions of the human cervix, the level of Cx43 expression is dramatically reduced compared with that in the normal epithelia. More importantly, the expression of Cx43 attenuated the growth of tumor xenografts (214). In breast cancer cells, down-regulated Cx43 expression promoted an aggressive phenotype by increasing the level of vascular endothelial growth factor expression and down-regulating the expression of the anti-angiogenesis protein thrombospondin-1(215). Collectively, these data indicate that the loss of Cx43 may contribute to neoplastic progression.   23 Revelations of the important roles of Cx43 in embryogenesis and disease development have prompted studies of its possible clinical therapeutic potential. The anti-cancer drug Coleusin Factor has been shown to exert its anti-tumor effects through up-regulating Cx43 expression (216). Deeper understanding of the molecular mechanisms underlying the roles of Cx43 under physiological and pathological conditions could lead to the development of therapeutics for the prevention and treatment of Cx43-linked diseases. Table 1.1  Table 1.1 Summarized histologic subtypes of ovarian epithelial cancer and their character-istics. HGSC: High grade serous carcinoma; LGSC: Low grade serous carcinoma; EC: Endometrioid carcinoma; CCC: Clear cell carcinoma; MC: Mucinous carcinoma; STIC: Serous tubal intraepithelial carcinoma  24  Figure 1.1 Schematic depicting ErbBs and its congnate ligands. ErbB family contains ErbB1, ErbB2, ErbB3, and ErbB4. ErbB1 and ErbB4 are intact functional receptors; ErbB2 lacks its ligand-binding domain and ErbB3 has a deficient tyrosine kinase do-main. The receptors are activated by binding to their ligands.    25 Chapter 2. Rationale and objectives Ovarian cancer is the fifth most lethal type of cancer and the leading cause of death due to gynecological malignancies in developed countries. Elevated levels of EGFR expression have been demonstrated in ovarian cancers and are associated with poor prognoses. E-cadherin is a well-characterized tumor suppressor, and we have previously shown that EGF induced invasion of human ovarian cancer cells by down-regulating E-cadherin expression through various signaling pathways. Although AREG, EGF and TGF-α bind exclusively to EGFR, these molecules have diverse functions and can act either redundantly or differentially. Recently, studies in my lab have demonstrated that AREG and TGF-α also suppress E-cadherin expression and induce cell invasion, although whether they use the same molecular mediators is unknown. Therefore, the aim of this study was to compare the underlying molecular mechanisms mediating the effects of TGF-α, AREG and EGF on E-cadherin expression. COX-2 is a key enzyme that catalyzes the transformation of arachidonic acid into prostaglandins. COX-2 and E-cadherin expression have been shown to be inversely correlated in a variety of human cancers. Elevated COX-2 expression has been detected in malignant ovarian tumors, and high levels of COX-2 expression are correlated with a poor prognosis and poor overall survival for ovarian cancer patients. EGF has been shown to strongly induce COX-2 expression in human glioma cell lines and lung adenocarcinoma cells. Treatment with a combination of COX-2 inhibitors and EGFR inhibitors inhibits the progression of various human cancers. However, it is unknown whether COX-2 expression can be induced by EGF treatment in human ovarian cancer cells or whether COX-2 is directly involved in EGF-induced tumor progression. In addition to exerting an invasion-stimulating effect, EGF is a well-characterized pro-proliferative hormone in human cancers. The level of Cx43 expression is frequently  26 down-regulated in human ovarian cancers and moreover, Cx43 has been shown to regulate cellular proliferation. Although EGF regulates Cx43 expression in many cell types, it is unclear whether EGF regulates Cx43 expression in human ovarian cancer cells. Additionally, it is unknown whether Cx43 is involved in the EGF-stimulated proliferation of human ovarian cancer cells.  Aim of the study: The general aim of my study was to examine the molecular mechanisms that control the proliferation and invasion of epithelial ovarian cancer cells by EGFR ligands using in vitro cell models. The specific objectives of this study were the following:  Objective 1: To investigate the comparative role of EGFR ligands on E-cadherin expression (presented in Chapter 3) 1) To examine the requirement for the AREG-, TGF-α-, and EGF-induced down-regulation of E-cadherin expression in cell invasiveness; 2) To investigate the involvement of EGFR and HER2 in the AREG-, TGF-α-, and EGF-induced down-regulation of E-cadherin expression; 3) To explore wether the transcriptional repressors Snail and Slug mediate the AREG-, TGF-α-, and EGF-induced down-regulation of E-cadherin expression. Objective 2: To investigate the role of COX-2 in EGF-induced cell invasion (presented in Chapter 4) 1) To examine the effect of EGF on COX-2 expression;   27 2) To investigate the effect of COX-2 on the EGF-induced down-regulation of E-cadherin expression; 3) To examine the downstream signaling pathways of EGF-induced COX-2 expression;  4) To determine the role of COX-2 in EGF-induced cell invasion. Objective 3: To investigate the role of Cx43 in EGF-induced cell proliferation (presented in Chapter 5) 1) To examine the effect of EGF on Cx43 expression; 2) To examine the downstream signaling pathways of EGF-induced Cx43 expression; 3) To investigate the role of Cx43 in EGF-stimulated cell proliferation.   28 Chapter 3. Transforming growth factor-α induces human ovarian cancer cell invasion by down-regulating E-cadherin in a Snail-independent manner  Introduction 3.1Ovarian cancer is the fifth most common cause of cancer death in women and the leading cause of death from gynecological cancers in developed countries (1,217). Epidermal growth factor receptor (EGFR) has been shown to be overexpressed in ovarian cancer and is associated with poor prognosis (60). EGFR, also known as ERBB1 or HER1, belongs to the ERBB family of receptor tyrosine kinases, which includes three other members, HER2 (ERBB2), HER3 (ERBB3) and HER4 (ERBB4) (218). Multiple cognate ligands, including transforming growth factor-α (TGF-α), amphiregulin (AREG), epidermal growth factor (EGF), heparin-binding EGF, epiregulin and betacellulin can bind to and activate EGFR. AREG, EGF and TGF-α have been shown to bind exclusively to EGFR while the other ligands can also bind other ERBB family receptors (45,219,220). In ovarian cancer, AREG, EGF and TGF-α are expressed and act as autocrine factors to regulate disease progression (221-223).  Although AREG, EGF and TGF-α bind exclusively to EGFR, they have diverse functions and can act either redundantly or differentially. AREG has been shown to have a lower affinity for EGFR compared with EGF or TGF-α (224). Additionally, binding between AREG and heparin and heparan sulfate proteoglycans can potentiate its bioavailability and activity (225). A previous study has shown that treatment with AREG, but not TGF-α, induces a spindle-like morphology in MDCK cells (226). Interestingly, AREG concentrations in peritoneal fluid of ovarian cancer patients are higher than those of TGF-α (78). Similarly, AREG levels are also higher than EGF or TGF-α levels in ovarian cancer tissues and cell lines (76,77). These results strongly suggest that these three EGFR ligands (AREG, EGF and TGF-α) may have differing roles in ovarian cancer development and/or progression.   29 Cadherins constitute a large family of cell membrane glycoproteins that play important roles in mediating cell-cell adhesion. E-cadherin is a prototypical classical cadherin that plays an essential role in maintaining normal epithelial structure (98,99). E-cadherin is a well-characterized tumor suppressor, best-known for its important functions in epithelial-mesenchymal transition (EMT). During EMT, down-regulation of E-cadherin expression leads to loss of epithelial characteristics and acquisition of a mesenchymal phenotype, which promotes cell proliferation, motility and invasiveness and contributes to cancer progression (99,227).  We have shown that EGF induces human ovarian cancer cell invasion by down-regulating E-cadherin expression through various signaling pathways (140-142,145). Recently, we demonstrated that AREG and TGF-α also suppress E-cadherin and induce cell invasion (228), though whether they use the same molecular mediators remains unknown. Therefore, the aim of this study was to compare the underlying molecular mechanisms mediating the effects of TGF-α, AREG and EGF on E-cadherin expression.  Material and methods 3.2Cell culture The SKOV3 human ovarian cancer cell line was obtained from the American Type Culture Collection (Manassas, VA). Cells were grown in a 1:1 (v/v) mixture of M199/MCDB105 medium (Sigma-Aldrich, Oakville, ON) supplemented with 10% fetal bovine serum (FBS; Hyclone Laboratories Inc., Logan, UT). The cultures were maintained at 37°C in a humidified 5% CO2 atmosphere.  30 Antibodies and reagents The monoclonal anti-E-cadherin and anti-N-cadherin antibodies were obtained from BD Biosciences (Mississauga, ON). Monoclonal anti-α-Tubulin and polyclonal anti-EGFR antibodies were obtained from Santa Cruz Biotechnology (Santa Cruz, CA). The monoclonal anti-HER2, anti-Snail and polyclonal anti-Slug antibodies were obtained from Cell Signaling Technology (Danvers, MA). Horseradish peroxidase-conjugated goat anti-mouse IgG and goat anti-rabbit IgG were obtained from Bio-Rad Laboratories (Hercules, CA). Human epidermal growth factor (EGF) and AG1478 were obtained from Sigma. Recombinant human amphiregulin and TGF-α were purchased from R&D (Minneapolis, MN). AG825 was obtained from Tocris Bioscience (Bristol, UK).  Small interfering RNA (siRNA) transfection and protein overexpression To knockdown endogenous EGFR, Snail, Slug or HER2, cells were transfected with 50 nM ON-TARGETplus SMARTpool siRNA (Dharmacon Research, Inc., Lafayette, CO) using Lipofectamine RNAiMAX (Invitrogen, Burlington, ON). siCONTROL non-targeting siRNA (Dharmacon) was used as a transfection control. For protein overexpression, pcDNA-GFP and pcDNA-E-cadherin-GFP were transfected into cells using Lipofectamine LTX (Invitrogen). The empty pcDNA3.1-EGFP vector was obtained from Invitrogen (Burlington, ON). A human E-cadherin-containing pcDNA3.1-EGFP vector (plasmid 28009) was purchased from Addgene (Cambridge MA). Western blots Cells were lysed in lysis buffer (Cell Signaling Technology, Danvers, MA), and total protein concentration was determined using a DC protein assay kit with BSA as standard (Bio-Rad  31 Laboratories). Equal amounts of protein were separated by SDS polyacrylamide gel electrophoresis and transferred to PVDF membranes. After blocking with Tris-buffered saline containing 5% non-fat dry milk for 1 hour, the membranes were incubated overnight at 4°C with primary antibodies followed by incubation with the HRP-conjugated secondary antibody. Immunoreactive bands were detected with an enhanced chemiluminescent substrate (Pierce, Rockford, IL). Films were scanned and quantified by densitometry using Scion image software (Scion Corp). E-cadherin and N-cadherin levels were normalized to α-Tubulin levels. Real-time quantitative PCR (RT-qPCR) Total RNA was extracted using TRIzol (Invitrogen) according to the manufacturer's instructions. Reverse transcription was performed with 3 µg RNA, random primers and M-MLV reverse transcriptase (Promega, Madison, WI). The primers used for SYBR Green RT-qPCR were as follows: E-cadherin, 5'-ACA GCC CCG CCT TAT GAT T-3' (sense) and 5'-TCG GAA CCG CTT CCT TCA-3' (antisense); EGFR, 5'-GGT GCA GGA GAG GAG AAC TGC-3' (sense) and 5'-GGT GGC ACC AAA GCT GTA TT-3' (antisense); Snail, 5'-CCC CAA TCG GAA GCC TAA CT-3' (sense) and 5'-GCT GGA AGG TAA ACT CTG GAT TAG A-3' (antisense); Slug, 5'-TTC GGA CCC ACA CAT TAC CT-3' (sense) and 5'-GCA GTG AGG GCA AGA AAA AG-3' (antisense); HER2, 5'-AAC TGC ACC CAC TCC TGT GT-3' (sense) and 5'-TGA TGA GGA TCC CAA AGA CC-3' (antisense); and GAPDH, 5'-GAG TCA ACG GAT TTG GTC GT-3' (sense) and 5'-GAC AAG CTT CCC GTT CTC AG-3' (antisense). RT-qPCR was performed using an Applied Biosystems 7300 Real-Time PCR System (Perkin-Elmer) equipped with a 96-well optical reaction plate. All RT-qPCR results represent the mean from at least three independent experiments conducted in triplicate. Relative quantification of mRNA levels was performed by the comparative Ct method using GAPDH as the reference gene and the formula 2∆∆Ct.  32 Invasion assay Invasion assays were performed in Boyden chambers as previously described, with minor modifications (229). Cell culture inserts (24-well, pore size 8 μm; BD Biosciences, Mississauga, ON) pre-coated with growth factor-reduced Matrigel (40 μl, 1 mg/ml; BD Biosciences) were used for the invasion assays. The cell culture inserts were seeded with 1 x 105 cells in 250 μl of medium supplemented with 0.1% FBS. Medium with 10% FBS (750 μl) was added to the lower chamber and served as a chemotactic agent. After incubation for 48 hours, non-invading cells were removed from the upper side of the membrane and the cells on the lower side of the membrane were fixed with cold methanol and air dried. The cell nuclei were stained with Hoechst 33258 and counted by epifluorescence microscopy using Northern Eclipse 6.0 software (Empix Imaging, Mississauga, ON). Each individual experiment was performed in triplicate (i.e., three inserts), and five microscopic fields were counted per insert. Statistical analysis Results are presented as the mean ± SEM of at least three independent experiments. The results were analyzed by one-way ANOVA and Tukey’s multiple comparison test using PRISM software. Significant differences were defined as p<0.05.  Results 3.3TGF-α increases cell invasion by down-regulating E-cadherin  Previous studies on MDCK kidney cells demonstrated differential effects of AREG and TGF-α on cell morphology (226); however, comparative effects of EGFR ligands on ovarian cancer cell morphology have not been examined. Similar to EGF, treatment of SKOV3 cells with  33 TGF-α or AREG induced EMT-like morphological changes from a cobblestone-like shape to a fibroblast-like, spindle-shaped appearance (Figure 3.1A). Next, we compared the time-dependent effects of EGFR ligands on E-cadherin mRNA levels in SKOV3 cells. As shown in Figure 3.1B, treatment with TGF-α, AREG or EGF induced equivalent reductions in E-cadherin mRNA levels by 6 hours, with maximal reductions observed by 24 hours. Western blot analysis showed that treatment with these EGFR ligands also produced comparable decreases in E-cadherin protein levels (Figure 3.1 C) though, like AREG (228), neither EGF nor TGF-α affected N-cadherin protein levels (Figure 3.1D). To confirm that E-cadherin loss contributes to TGF-α-induced cell invasion, we overexpressed E-cadherin in SKOV3 cells and examined cell invasiveness in response to TGF-α treatment. As shown in Figure 3.1C, compared to cells transfected with empty vector, cells transfected with E-cadherin expression vector displayed increased E-cadherin protein levels that were insensitive to treatment with TGF-α, AREG or EGF. Invasion assay results showed that E-cadherin overexpression decreased basal invasiveness and attenuated TGF-α-induced cell invasiveness (Figure 3.1E). These results indicate that, as for AREG and EGF, down-regulation of E-cadherin plays a key role in TGF-α-induced ovarian cancer cell invasion. EGFR is required for TGF-α- and AREG-induced down-regulation of E-cadherin  To examine whether EGFR is required for TGF-α- or AREG-induced down-regulation of E-cadherin, the EGFR-specific inhibitor AG1478 was used to block EGFR function. RT-qPCR and Western blot analyses showed that treatment of SKOV3 cells with AG1478 abolished the down-regulation of E-cadherin mRNA and protein by TGF-α or AREG (Figure 3.2A and B). We also employed a siRNA-mediated knockdown approach to exclude possible off-target effects from pharmacological inhibition. As shown in Figure 3.2C and D, treatment with EGFR siRNA  34 significantly down-regulated endogenous EGFR mRNA and protein levels. Additionally, EGFR knockdown abolished the down-regulation of E-cadherin mRNA and protein levels by TGF-α and AREG. These results confirm that, similar to EGF, both TGF-α and AREG suppress E-cadherin expression via EGFR. HER2 is involved in TGF-α- and AREG-induced down-regulation of E-cadherin  HER2 has no identified ligand; however, it can be activated by dimerizing with other ligand-bound ERBB family receptors (230,231). We previously demonstrated that HER2 is involved in EGF-induced down-regulation of E-cadherin in ovarian cancer cells (140), though whether the same is true for TGF-α or AREG is unknown. As shown in Figure 3.3A and B, treatment of SKOV3 cells with the HER2-specific inhibitor AG825 partially attenuated the down-regulation of E-cadherin mRNA and protein levels by TGF-α or AREG. Similarly, TGF-α- and AREG-induced down-regulation of E-cadherin mRNA and protein levels was attenuated by siRNA-mediated knockdown of HER2 (Figure 3.3C and D). These results indicate that HER2 contributes to the suppression of E-cadherin by TGF-α and AREG in ovarian cancer cells. TGF-α-induced down-regulation of E-cadherin is Snail-independent The transcription factors Snail and Slug are well-characterized negative regulators of E-cadherin expression (113). Though we have previously demonstrated that Snail and Slug are required for AREG-induced ovarian cancer cell invasion, it is not known whether they are required for TGF-α-, AREG- or EGF-induced E-cadherin down-regulation. Similar to AREG and EGF, treatment of SKOV3 cells with TGF-α induced time-dependent increases in the mRNA levels of both Snail and Slug, with maximal effects occurring after 3 hours (Figure 3.4A). Western blot analyses confirmed the stimulatory effects of TGF-α on Snail and Slug protein  35 levels (Figure 3.4B). Next, we used siRNA-mediated knockdown of Snail or Slug to examine their involvement in TGF-α-, AREG- or EGF-induced E-cadherin down-regulation. As shown in Figure 3.4C, treatment with Snail or Slug siRNA abolished the up-regulation of Snail and Slug protein levels by TGF-α, AREG or EGF. Interestingly, TGF-α-induced reductions in E-cadherin protein levels were unaffected by Snail knockdown, whereas those of AREG and EGF were partially reversed (Figure 3.4D). In contrast, Slug knockdown attenuated the suppressive effects of all three EGFR ligands on E-cadherin protein levels (Figure 3.4E). These results indicate that the down-regulation of E-cadherin by TGF-α in ovarian cancer cells differs from that of AREG and EGF in that it is Snail-independent.  Discussion 3.4TGF-α, AREG and EGF bind exclusively to EGFR which is frequently overexpressed in ovarian cancer and associated with poor prognosis (45,219). We have previously demonstrated that EGF (141) and AREG (228) induce ovarian cancer cell invasion by down-regulating E-cadherin. However, it remained unknown if the same is true for TGF-α and whether these three EGFR ligands use the same molecular mediators. We now show that similar to AREG and EGF, TGF-α induces ovarian cancer cell invasion by down-regulating E-cadherin expression. In comparing the molecular determinants of EGFR ligand-induced E-cadherin down-regulation, we also demonstrate that, as for EGF, EGFR is required and HER2 is involved in the effects of TGF-α and AREG on E-cadherin. Interestingly, both Snail and Slug are involved in the suppression of E-cadherin by AREG and EGF, whereas the effects of TGF-α are mediated by Slug, but not Snail.  EGFR signaling is known to regulate various cellular functions that play important roles in modulating multiple developmental, physiological and pathological processes (37,220). In mice,  36 Egfr knockout results in embryonic to perinatal lethality due to pleiotropic abnormalities (232-234). However, mice deficient in Tgf-α, Areg, Egf or all three ligands combined are viable (235). Differences in viability between receptor and ligand knockout may result from ERBB family receptor heterodimerization, where other ERBB ligands can compensate for the loss of these three Egfr ligands and maintain Egfr activity. Moreover, Tgf-α, Areg and Egf knockout mice each exhibit different developmental defects, which indicate a variety of potentially unique biological functions for these EGFR ligands. Here, we focused only on the effects of TGF-α, AREG and EGF on E-cadherin and cancer cell invasion, but whether these three ligands utilize common or divergent molecular mechanisms to regulate other biological functions will be an interesting question for future investigation.  Though HER2 is a member of the ERBB family, it does not bind EGF-like ligands and functions instead as a heterodimerization partner for other ligand-bound ERBB family receptors (230,231). Amplification or overexpression of HER2 is frequent in many types of human cancers, including ovarian cancer (236,237). HER2 has been shown to potentiate EGFR-induced signaling through the formation of heterodimers with EGFR (238,239). In ovarian cancer, treatment with pertuzumab, a HER2 dimerization inhibitor, induces anti-tumor activity in xenograft models (240). In addition, we have shown that HER2 is involved in EGF-induced E-cadherin down-regulation and ovarian cancer cell invasion (140), though whether it is involved in the corresponding effects of TGF-α and AREG remains unknown. Our study is the first to show that blocking HER2 activity, either pharmacologically or by knockdown, partially inhibits the suppressive effects of TGF-α and AREG on E-cadherin expression. Together with our previous results, these findings indicate that a subset of TGF-α-, AREG- and EGF-induced effects involve HER2, and that simultaneous EGFR and HER2 inhibition may be necessary to produce optimal therapeutic effects in ovarian cancers driven by elevated EGF-family-ERBB  37 signaling.  Although Snail and Slug are well-known transcriptional repressors of E-cadherin (119,241), whether they function redundantly or differentially is not fully understood. Previous studies have shown that the binding affinity of Snail for the mouse E-cadherin promoter is higher than that of Slug (119), and that Slug overexpression does not affect E-cadherin expression in rat bladder cancer cells (242). In human breast cancer, while both Snail and Slug can repress E-cadherin expression in vitro, only Slug expression correlated with E-cadherin down-regulation in vivo (121). Likewise, expression of Slug but not Snail was negatively correlated with E-cadherin expression in human bladder cancer (243). These results indicate that the repressive effects of Snail and Slug on E-cadherin expression are variable, and may be cell-type or context dependent. Though we have previously demonstrated that TGF-α, AREG and EGF can induce Slug and/or Snail expression and E-cadherin down-regulation in human ovarian cancer cells (141,228), the direct involvement of Snail and/or Slug in the effects of these ligands on E-cadherin has never been demonstrated. Interestingly, our results indicate that although these ligands have comparable effects on E-cadherin, they use common and divergent molecular mediators to achieve these effects. Specifically, while both Snail and Slug are involved in AREG- and EGF-induced E-cadherin down-regulation, the effects of TGF-α on E-cadherin do not involve Snail. In addition to Snail and Slug, other transcription factors have been shown to repress E-cadherin expression, such as Twist and ZEB1 (244). We have previously demonstrated that AREG can up-regulate ZEB1 in ovarian cancer cells, however it was not required for AREG-induced cell invasion (228). Future studies will be required to compare the effects of TGF-α, AREG and EGF on Twist and ZEB1 expression, and to examine their roles in the effects of these ligands on E-cadherin expression and ovarian cancer cell invasion.  In summary, this study demonstrates that TGF-α induces ovarian cancer cell invasion by  38 down-regulating E-cadherin. Similar to EGF, TGF-α- and AREG-induced E-cadherin down-regulation involves both EGFR and HER2. However, whereas the effects of TGF-α on E-cadherin are mediated by Slug, but not Snail, both Snail and Slug mediate the effects of AREG and EGF on E-cadherin. This study shows that TGF-α uses common and divergent molecular mediators to regulate E-cadherin expression and cell invasion.    39  Figure 3.1 Down-regulation of E-cadherin is required for TGF-α-, AREG- or EGF-induced SKOV3 ovarian cancer cell invasion. A, Cells were treated without (Ctrl) or with 100 ng/ml TGF-α, AREG or EGF for 24 hours, and cell morphology was assessed by phase contrast microscopy. B, Cells were treated with 100 ng/ml TGF-α, AREG or EGF and E-cadherin mRNA levels were analyzed at different time-points by RT-qPCR. C, Cells were transfected with empty vector (Vector) or vector encoding human E-cadherin (E-cadherin) for 48 hours and then treated with 100 ng/ml TGF-α (T), AREG (A) or EGF (E) for another 24 hours. E-cadherin protein levels were analyzed by Western blot (quantified data are normalized to α-Tubulin and are expressed relative to DMSO-treated controls). D, Cells were treated for 24 h with 100 ng/ml T, A or E and N-cadherin protein levels were analyzed by Western blot. E, Cells were transfected for 48 hours with empty vector or E-cadherin vector, seeded onto Matrigel-coated transwell inserts, and cultured for an additional 48 hours with or without 100 ng/ml TGF-α, AREG or EGF. Non-invading cells were wiped from the upper side of the filter, and the nuclei of the invading cells were stained with Hoechst 33258. The right panel shows summarized quantitative results and the left panel shows representative images of the invasion assays. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).  40  Figure 3.2 EGFR is required for TGF-α-, AREG- or EGF-induced down-regulation of E-cadherin. A and B, SKOV3 cells were pretreated for 1 hour with AG1478 (10 µM) and then treated with 100 ng/ml TGF-α (T), AREG (A) or EGF (E) for 24 hours. E-cadherin mRNA (A) and protein (B) levels were analyzed by RT-qPCR and Western blot, respectively. C and D, Cells were transfected for 48 hours with 50 nM control siRNA (si-Ctrl) or EGFR siRNA (si-EGFR) and then treated with 100 ng/ml TGF-α (T), AREG (A) or EGF (E) for 24 hours. E-cadherin and EGFR mRNA (C) and protein (D) levels were analyzed by RT-qPCR and Western blot, respectively. Quantified data are normalized to α-Tubulin and are expressed relative to DMSO-treated (B) or si-Ctrl-treated (D) controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).   41  Figure 3.3 HER2 is involved in the down-regulation of E-cadherin by TGF-α, AREG or EGF. A and B, SKOV3 cells were pretreated for 1 hour with AG825 (10 µM) and then treated with 100 ng/ml TGF-α (T), AREG (A) or EGF (E) for 24 hours. E-cadherin mRNA (A) and protein (B) levels were analyzed by RT-qPCR and Western blot, respectively. C and D, Cells were transfected for 48 hours with 50 nM control siRNA (si-Ctrl) or HER2 siRNA (si-HER2) and then treated with 100 ng/ml TGF-α (T), AREG (A) or EGF (E) for 24 hours. E-cadherin and HER2 mRNA (C) and protein (D) levels were analyzed by RT-qPCR and Western blot, respectively. Quantified data are normalized to α-Tubulin and are expressed relative to DMSO-treated (B) or si-Ctrl-treated (D) controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).  42  Figure 3.4 Snail and Slug are differentially involved in TGF-α-, AREG- or EGF-induced down-regulation of E-cadherin. A, SKOV3 cells were treated for varying amounts of time with 100 ng/ml TGF-α, AREG or EGF and RT-qPCR was used to measure Snail and Slug mRNA levels. B, Cells were treated for 3 hours with 100 ng/ml TGF-α, AREG or EGF and Snail and Slug protein levels were analyzed by Western blot. C, Cells were transfected for 48 hours with 50 nM control siRNA (si-Ctrl), Snail  43 siRNA (si-Snail) or Slug siRNA (si-Slug) and then treated with 100 ng/ml TGF-α (T), AREG (A) or EGF (E) for 3 hours. Snail and Slug protein levels were analyzed by Western blot. D, Cells were transfected for 48 hours with 50 nM control siRNA (si-Ctrl) or Snail siRNA (si-Snail) and then treated with 100 ng/ml TGF-α (T), AREG (A) or EGF (E) for 24 hours. E-cadherin protein levels were analyzed by Western blot. E, Cells were transfected for 48 hours with 50 nM control siRNA (si-Ctrl) or Slug siRNA (si-Slug) and then treated with 100 ng/ml TGF-α (T), AREG (A) or EGF (E) for 24 hours. E-cadherin protein levels were analyzed by Western blot. Quantified data are normalized to α-Tubulin and are expressed relative to si-Ctrl-treated controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).         44 Chapter 4. COX-2 expression and PGE2 production mediate EGF-induced E-cadherin-independent human ovarian cancer cell invasion    Introduction 4.1Epithelial ovarian cancer accounts for approximately 90% of all ovarian malignancies. It is the leading cause of gynecological cancer death in developed countries because the majority of patients present with disseminated disease, for which the average five-year survival rate is very low (217,245). Epidermal growth factor receptor (EGFR) is up-regulated in many types of human cancers (246-248). Overexpression of EGFR in human ovarian cancer is associated with poor prognosis and disease progression (60,218,223,249). Our recent studies have demonstrated that epidermal growth factor (EGF) induces human ovarian cancer cell invasion by down-regulating the expression of the cell-cell adhesion molecule E-cadherin through various signaling pathways (140-145).  Cyclooxygenases (COX) are rate-limiting enzymes for conversion of arachidonic acid into prostaglandins. Prostaglandin E2 (PGE2) is an important prostaglandin that acts in an autocrine/paracrine manner to regulate various physiologic and pathologic functions (250). Two isoforms of COX, COX-1 and COX-2, have been described. COX-1 is constitutively expressed in most tissues and maintains homeostasis, while COX-2 expression is induced by various stimuli, including cytokines, mitogens and hypoxia (150,151). There is increasing evidence that COX-2 expression is elevated in several types of human cancers, including skin, liver, breast and lung cancer (174-176). Elevated COX-2 expression has been detected in malignant ovarian tumors (179), and high levels of COX-2 expression are correlated with poor prognosis and overall survival in human ovarian cancer (180,181). Compelling data indicates that regular use of non-steroidal anti-inflammatory drugs (NSAIDs), which primarily target the activity of COX, is associated with reduced incidence of various cancer types, including HGSC (251,252).  45 Though there is a difference between COX-2 causing cancers versus COX-2 inhibitors being used to treat cancers, many studies have shown that COX-2-specific inhibitors can reduce the growth of liver, breast and colorectal tumors (175,177,178) and combination of COX-2 inhibitors with other anti-cancer therapies shows a promising effect on cancer treatment (253,254). Previous studies have demonstrated that treatment with a combination of COX-2 inhibitors and EGFR inhibitors inhibits the progression of various human cancers (255-257). However, whether COX-2 is directly involved in EGF-induced tumor progression remains unclear. Many growth factors and cytokines induce COX-2 expression (258). Previous studies have shown that EGF strongly induces COX-2 expression in human glioma cell lines and lung adenocarcinoma cells (156,157). It was previously showed that gonadotropins induce ovarian cancer cell invasion and that this effect is mediated by COX-derived PGE2 production (259). However, it is unknown whether COX-2 expression can be induced by EGF treatment in human ovarian cancer cells. The aim of this study was to determine whether COX-2 mediates EGF-induced cell invasion in human ovarian cancer cells. Our results show that EGF treatment increases COX-2 expression and PGE2 production in two human ovarian cancer cell lines, SKOV3 and OVCAR5. However, COX-2 is not involved in the EGF-induced down-regulation of E-cadherin. EGF regulation of COX-2 expression is mediated by the phosphatidylinositol-3-kinase (PI3K)/Akt signaling pathway. Moreover, inhibition of COX-2 and prostaglandin E synthase (PGES) attenuates EGF-induced cancer cell invasion. These results demonstrate that COX-2 and PGE2 are involved in EGF-induced human ovarian cancer cell invasion.   46  Material and methods 4.2Cell culture  The SKOV3 human ovarian cancer cell line was obtained from the American Type Culture Collection (Manassas, VA). The OVCAR5 ovarian cancer cell line was kindly provided by Dr. T.C. Hamilton (Fox Chase Cancer Center, Philadelphia, PA). Cells were grown in a 1:1 (v/v) mixture of M199/MCDB105 medium (Sigma-Aldrich, Oakville, ON) supplemented with 10% fetal bovine serum (FBS; Hyclone Laboratories Inc., Logan, UT). The cultures were maintained at 37°C in a humidified 5% CO2 atmosphere. Antibodies and reagents Monoclonal anti-E-cadherin antibody was obtained from BD Biosciences (Mississauga, ON). Polyclonal anti-COX-2 antibody was obtained from Abcam (Toronto, ON). Monoclonal anti-α-Tubulin and polyclonal anti-EGFR antibodies were obtained from Santa Cruz Biotechnology (Santa Cruz, CA). The polyclonal anti-phospho-Akt, anti-Akt, anti-phospho-CREB1 and anti-CREB1 antibodies were obtained from Cell Signaling Technology (Danvers, MA). The horseradish peroxidase-conjugated goat anti-mouse IgG and goat anti-rabbit IgG were obtained from Bio-Rad Laboratories (Hercules, CA). Human epidermal growth factor (EGF), LY294002 and AG1478 were obtained from Sigma. Wortmannin was obtained from Calbiochem (Gibbstown, NJ). NS-398 was purchased from Caymen Chemical (Ann Arbor, MI). Small interfering RNA (siRNA) transfection and protein overexpression To knockdown endogenous EGFR, CREB, Akt or PGES, cells were transfected with 50 nM ON-TARGETplus SMARTpool siRNA (Dharmacon Research, Inc., Lafayette, CO) using  47 Lipofectamine RNAiMAX (Invitrogen, Burlington, ON). siCONTROL Non-targeting siRNA (Dharmacon) was used as a transfection control. For protein overexpression, Myc-tagged DN-Akt (Upstate, Billerica, MA, USA) was transfected into cells using Lipofectamine 2000 (Invitrogen). Western blots The cells were lysed in lysis buffer (Cell Signaling Technology, Danvers, MA), and total protein concentrations were determined using a DC protein assay kit with BSA as standard (Bio-Rad Laboratories). Equal amounts of protein were separated by SDS polyacrylamide gel electrophoresis and transferred to PVDF membranes. After blocking with Tris-buffered saline containing 5% non-fat dry milk for 1 hour, the membranes were incubated overnight at 4°C with primary antibodies followed by incubation with the HRP-conjugated secondary antibody. Immunoreactive bands were detected with an enhanced chemiluminescent substrate (Pierce, Rockford, IL).  Real-time quantitative PCR (RT-qPCR) Total RNA was extracted using TRIzol (Invitrogen) according to the manufacturer's instructions. Reverse transcription was performed with 3 µg RNA, random primers and M-MLV reverse transcriptase (Promega, Madison, WI). The primers used for SYBR Green RT-qPCR were as follows: E-cadherin, 5'-ACA GCC CCG CCT TAT GAT T-3' (sense) and 5'-TCG GAA CCG CTT CCT TCA-3' (antisense); COX-2, 5'-CCC TTG GGT GTC AAA GGT AA-3' (sense) and 5'-GCC CTC GCT TAT GAT CTG TC-3' (antisense); EGFR, 5'-GGT GCA GGA GAG GAG AAC TGC-3' (sense) and 5'-GGT GGC ACC AAA GCT GTA TT-3' (antisense); CREB1, 5'-AAA ACC AAC AAA TGA CAG TT-3' (sense) and 5'-TGG ACT GTC TGC CCA TTG G-3' (antisense); and  48 GAPDH, 5'-GAG TCA ACG GAT TTG GTC GT-3' (sense) and 5'-GAC AAG CTT CCC GTT CTC AG-3' (antisense). RT-qPCR was performed using an Applied Biosystems 7300 Real-Time PCR System (Perkin-Elmer) equipped with a 96-well optical reaction plate. All RT-qPCR results represent the mean from at least three independent experiments conducted in triplicate. Relative quantification of mRNA levels was performed by the comparative Cq method using GAPDH as the reference gene and the formula 2–∆∆Cq. Prostaglandin E2 ELISA  A human PGE2-specific ELISA assay was performed according to the manufacturer’s instructions (Cayman Chemical). The culture media were collected from treated cells, and the PGE2 levels in the culture media were measured by ELISA. The PGE2 levels were normalized to the protein concentrations from the cell lysates. The normalized PGE2 values from the treated cells are represented as relative values compared to the control cells. Invasion assay The invasion assays were performed in Boyden chambers as previously described, with minor modifications (229). Cell culture inserts (24-well, pore size 8 μm; BD Biosciences, Mississauga, ON) pre-coated with growth factor reduced Matrigel (40 μL, 1 mg/mL; BD Biosciences) were used for the invasion assays. The cell culture inserts were seeded with 1 x 105 cells in 250 μL of medium supplemented with 0.1% FBS. Medium with 10% FBS (750 μL) was added to the lower chamber and served as a chemotactic agent. After incubation for 48 hours, non-invading cells were removed from the upper side of the membrane and the cells on the lower side of the membrane were fixed with cold methanol and air dried. The cell nuclei were stained with Hoechst 33258 and counted by epifluorescence microscopy using Northern Eclipse 6.0  49 software (Empix Imaging, Mississauga, ON). Each individual experiment was performed in triplicate (i.e., three inserts), and five microscopic fields were counted per insert. Statistical analysis Results are presented as the mean ± SEM of at least three independent experiments. The results were analyzed by one-way ANOVA and Tukey’s multiple comparison test using PRISM software. Significant differences were defined as p<0.05.  Results 4.3EGF treatment induces COX-2 expression  To determine whether EGF treatment can induce COX-2 expression in human ovarian cancer cells, we treated two human ovarian cancer cell lines (SKOV3 and OVCAR5) with 100 ng/mL EGF for different lengths of time and examined COX-2 mRNA and protein levels. As shown in Figure 4.1A, EGF treatment resulted in the up-regulation of COX-2 mRNA levels in both SKOV3 and OVCAR5 cells, with the most significant degree of up-regulation occurring after 1 hour of treatment. In addition, we also examined the stimulatory effect of different concentrations of EGF (1, 10, 50 and 100 ng/mL) on COX-2 mRNA levels. As shown in Figure 4.1B, treatment with 50 and 100 ng/mL EGF significantly induced COX-2 mRNA levels in SKOV3 cells, while in OVCAR5 cells COX-2 mRNA levels only could be significantly induced by 100 ng/mL EGF treatment.  Moreover, Western blot analyses showed that treatment with EGF for 3 and 6 hours significantly up-regulated COX-2 protein levels (Figure 4.1C). To confirm that EGFR is required for EGF-induced COX-2 expression, we blocked EGFR activation with the EGFR-specific inhibitor AG1478. RT-qPCR and Western blot analyses showed that AG1478 blocked EGF-induced up-regulation in COX-2 mRNA and protein levels  50 (Figure 4.2A and B). We further confirmed the involvement of EGFR in EGF-induced COX-2 expression by small interfering RNA (siRNA)-mediated knockdown of EGFR. As shown in Figure 4.2C and D, EGFR mRNA and protein levels were significantly down-regulated in the presence of EGFR siRNA. In addition, the siRNA-mediated down-regulation of EGFR attenuated the EGF-induced elevation in COX-2 mRNA and protein levels. It has been shown that the binding of EGF to EGFR rapidly induces clustering and internalization of the ligand-receptor complexes, ultimately resulting in lysosomal degradation of both EGF and its receptor (260). This process was supported by the data in Figure 4.2D, which showed that EGFR was down-regulated in SKOV3 and OVCAR5 cells in response to EGF treatment. COX-2 is not required for EGF-induced down-regulation of E-cadherin We previously demonstrated that EGF induces human ovarian cancer cell invasion by down-regulating E-cadherin expression through various signaling pathways (140-145). However, it is unclear whether COX-2 is involved in EGF-induced down-regulation of E-cadherin in human ovarian cancer cells. To test this, a selective COX-2 inhibitor, NS-398, was used to block COX-2 activity. Consistent with our previous studies, EGF down-regulated E-cadherin mRNA levels in both SKOV3 and OVCAR5 cells. Interestingly, treatment with NS-398 did not affect basal or EGF-down-regulated E-cadherin mRNA levels (Figure 4.3A). Western blot analyses showed that treatment with NS-398 also had no effect on basal and EGF-down-regulated E-cadherin protein levels (Figure 4.3B).  Active Akt is required for COX-2 induction by EGF We previously showed that the PI3K/Akt signaling pathway is involved in gonadotropin-induced COX-2 expression in human ovarian cancer cells (259). Therefore, we  51 asked whether the Akt signaling pathway is also involved in EGF-induced COX-2 expression. Treatment with EGF increased the levels of phosphorylated Akt in both SKOV3 and OVCAR5 cells (Figure 4.4A). To examine the involvement of PI3K/Akt signalling in EGF-induced up-regulation of COX-2 expression, two PI3K inhibitors, wortmannin and LY294002, were used. Treatment with wortmannin and LY294002 abolished EGF-induced Akt phosphorylation in both cell lines (Figure 4.5). In addition, the EGF-induced up-regulation in COX-2 mRNA and protein levels was attenuated by co-treatment with wortmannin and LY294002 (Figure 4.4B and C). To avoid off-target effects of the pharmacological inhibitors and further confirm that Akt is involved in EGF-induced COX-2 expression, a dominant negative Akt mutant (DN-Akt) was used to block Akt activity. Although overexpression of DN-Akt resulted in an up-regulation in basal COX-2 protein levels, the EGF-induced COX-2 protein levels were attenuated by DN-Akt overexpression (Figure 4.4D). Moreover, EGF-induced COX-2 protein levels were abolished by siRNA-mediated knockdown of Akt (Figure 4.4E). Notably, knockdown of Akt did not affect the basal levels of COX-2 protein. Taken together, these results clearly indicated that the PI3K/Akt signaling pathway is required for EGF-induced COX-2 expression in human ovarian cancer cells.  CREB does not mediate EGF-induced COX-2 expression  The cAMP response element (CRE) has been identified as one of the central regulatory elements in the COX-2 promoter region and cAMP response element-binding protein (CREB) is well known to be involved in the regulation of COX-2 gene expression in a variety of cells (261,262). Thus, we examined the involvement of CREB signaling pathway in EGF-induced COX-2 expression. Treatment with EGF increased the levels of phosphorylated CREB in both SKOV3 and OVCAR5 cells (Figure 4.6A). Interestingly, contrary to our expectations,  52 siRNA-mediated knockdown of CREB did not affect the EGF-induced COX-2 mRNA and protein levels (Figure 4.6B and C). This indicated that CREB does not play a role in EGF-induced COX-2 expression in human ovarian cancer cells. COX-2 and PGE2 mediate EGF-induced cell invasion PGE2 is the most common prostaglandin derived from COX-2 (250). To determine whether EGF-induced COX-2 expression contributes to the production of PGE2, we measured PGE2 protein levels in the culture medium by ELISA after 1, 3 and 6 hours EGF treatment. As shown in Figure 4.7A, treatment with EGF for 3 and 6 hours significantly up-regulated PGE2 production in both SKOV3 and OVCAR5 cells. Importantly, treatment with NS-398 abolished EGF-induced PGE2 production (Figure 4.7B).  To determine whether COX-2 and PGE2 are involved in EGF-induced cell invasion, we performed a Matrigel-coated Transwell invasion assay. Consistent with previous studies, we found that EGF stimulates significant cell invasion in both SKOV3 and OVCAR5 cells. Treatment with NS-398 did not affect the basal level of invasiveness but attenuated EGF-stimulated cell invasion (Figure 4.7C).  We previously showed that treatment with PGE2 stimulates human ovarian cancer cell invasion (259). To examine whether COX-2-derived PGE2 also contributes to EGF-induced cell invasion, we used an siRNA-mediated knockdown approach to inhibit the expression of PGES. As shown in Figure 4.7D, treatment with PGES siRNA did not affect the basal level of invasiveness but attenuated EGF-stimulated cell invasion. Taken together, our results indicated that COX-2 and its derivative, PGE2, are involved in EGF-induced human ovarian cancer cell invasion.  Discussion 4.4Overexpression of EGFR and COX-2 in human ovarian cancer is correlated with poor  53 prognosis and survival rate (180,181,263). This suggests that EGF/EGFR and COX-2 are important in the development and progression of human ovarian cancer. We previously showed that EGF can induce ovarian cancer cell invasion through a complex signaling network (140-145). However, it is unknown whether COX-2 mediates EGF-induced ovarian cancer cell invasion. In the present study, we showed that EGF induced COX-2 expression and PGE2 production in two human ovarian cancer cell lines, SKOV3 and OVCAR5, through activation of the PI3K/Akt signaling pathway. Moreover, inhibition of COX-2 and PGE2 attenuated the ovarian cancer cell invasion induced by EGF. These results indicate that COX-2 and its derivative PGE2 are involved in EGF-induced cell invasion in human ovarian cancer cells. COX-2 is known to be involved in the regulation of E-cadherin expression in other human cancers (264,265). Treatment of gastric cancer cells with celecoxib, a specific COX-2 inhibitor, leads to the up-regulation of E-cadherin expression at both the mRNA and protein levels (265). In human non-small-cell lung carcinoma cells, inhibition of COX-2 by genetic or pharmacologic methods increases E-cadherin expression (264). In this study, we showed that treatment with the selective COX-2 inhibitor NS-398 did not affect EGF-induced down-regulation of E-cadherin. These results indicate that the requirement of COX-2 in EGF-induced down-regulation of E-cadherin may depend on the type of cancer.  PGE2 stimulates cell invasion in many cancers via an autocrine/paracrine mechanism (259,266-269). We previously showed that PGE2 acts in an autocrine/paracrine fashion in ovarian cancer cells to up-regulate matrix metalloproteinase (MMP)-2 and MMP-9 expression, which in turn contribute to gonadotropin-induced cell invasion (259). We have previously shown that the down-regulation of E-cadherin mediates EGF-induced ovarian cancer cell invasion (140-145). However, our previous results indicate that although EGF-induced invasion is significantly reduced in E-cadherin overexpressing ovarian cancer cells, it is not completely  54 abolished (141). This would suggest the presence of additional, E-cadherin-independent, mechanisms for EGF-induced ovarian cancer cell invasion. It has been shown that additional mechanisms such as enhanced protease activity/secretion, changes in actin cytoskeleton and enhanced motility are involved in EGF-induced cell invasion (270,271). Because inhibiting COX-2 did not affect the EGF-induced down-regulation of E-cadherin in ovarian cancer cells, it is possible that COX-2-derived PGE2 may mediate EGF-induced cell invasion by regulating MMP expression in an autocrine/paracrine fashion.   EGF induces COX-2 expression in different types of human cancer (156,157,272). However, the underlying molecular mechanism that mediates EGF-induced COX-2 expression in human ovarian cancer is unknown. We and other groups have shown that PI3K/Akt signaling is required for gonadotropin- and IGF-1-induced COX-2 expression, but it was unclear whether the same is true for EGF-induced COX-2 expression (259,273). In human cervical cancer cells, EGF-induced COX-2 expression is attenuated by treatment with either of two PI3K inhibitors: wortmannin and LY294002 (272). In this study we showed that treatment with wortmannin or LY294002 attenuated EGF-induced COX-2 expression in ovarian cancer cells. We further confirmed the involvement of Akt in EGF-induced COX-2 expression by overexpressing DN-Akt or specific Akt siRNA, both of which could avoid the non-specific effects of pharmacological inhibition. Taken together, our results clearly indicated for the first time that PI3K/Akt signaling plays an important role in mediating EGF-induced COX-2 expression in ovarian cancer cells.  It has been reported that the transcription factor CREB is involved in COX-2 regulation by binding to the cyclic AMP response element (CRE) in the COX-2 promoter which displays several transcriptional regulatory elements, including a TATA box, NF-кB response elements and AP-2 sites (148,261,262,274,275). However, it is unknown whether CREB regulates  55 EGF-induced COX-2 expression in human ovarian cancer cells. In this study, we found that CREB is not involved in EGF-induced COX-2 expression. These results suggested that other molecules mediate the induction of COX-2 expression by EGF in ovarian cancer cells. NF-кB and c-Jun participate in LPS-induced COX-2 expression in mouse macrophages (276). In rat insulinoma cells, CREB and the Ets family members Ets-1and Elk-1 increase COX-2 promoter activity, while STAT1 inhibits COX-2 promoter activity (277). In human monocytes, ESE-1 binds to and increases the activity of the COX-2 promoter (278). A recent study showed that the FOXM1/Sp1 complex binds to the Sp1-binding site in the COX-2 promoter to mediate EGF-induced COX-2 expression in human glioma cells (279). Moreover, the evidence that transcription factors including NF-кB, Ets-1and Sp1 can be activated by PI3K/Akt signaling makes them promising candidates for regulating EGF-induced COX-2 expression (280-282). Future research is needed to determine the transcriptional regulatory mechanisms that mediate EGF-induced COX-2 expression in ovarian cancer cells. Metastasis is a complex multistep process and responsible for the major cause of cancer-related death. The ability of cancer cells to invade the surrounding basement membrane and detach from the primary tumor site is defined as invasion during the early phase of metastasis (283,284). Thus, a deeper understanding of cell invasion may shed light on the fight against cancers. In the present study, we used cell line model to examine the cell invasiveness; however, the in vitro effects do not always translate into changes in actual tumor behavior in vivo. Increasing evidence shows that the normal epithelium architecture, tumor microenvironment and host immune system can influence the invasive ability of tumors (283,285). For example, the mesothelial cell layer that lines the abdominal cavity functions as an intrinsic barrier to prevent ovarian tumors spread (286), whereas tumor-associated fibroblasts promote tumor progression (287). Clearly, the in vitro cell line model does not preserve any of  56 these features. Thus, additional in vivo experiments need to be done to further confirm the results we have drawn from the cell line model.  In summary, our results demonstrate that EGF induces COX-2 expression and PGE2 production in human ovarian cancer cells. In addition, we show that COX-2 expression is not involved in the EGF-induced down-regulation of E-cadherin. Moreover, EGF-induced COX-2 expression is mediated by the PI3K/Akt signaling pathway. Inhibition of COX-2 as well as PGE2 attenuates EGF-stimulated cell invasion. This study provides important insights into the molecular mechanisms that mediate EGF-stimulated human ovarian cancer cell invasion.    57  Figure 4.1 EGF induces COX-2 expression in SKOV3 and OVCAR5 cells. A, Cells were treated with vehicle control (Ctrl) or 100 ng/mL EGF. COX-2 mRNA levels were analyzed at different time-points by RT-qPCR. The dashed lines separate minite, a unit for measuring time, from hour, another one unit. B, Cells were treated with increasing concentrations of EGF (1, 10, 50 and 100 ng/mL) for 1 hour. COX-2 mRNA levels were analyzed by RT-qPCR. C, Cells were treated with vehicle control (Ctrl) or 100 ng/mL EGF for 1, 3 and 6 hours. COX-2 protein levels were analyzed by western blot (quantified data are normalized to α-Tubulin and are expressed relative to 1hr-group controls). Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).  58   Figure 4.2 EGFR is required for the EGF-induced up-regulation of COX-2 expression. A and B, cells were pretreated for 1 hour with AG1478 (10 µM) and then treated with 100 ng/mL EGF for 1 hour (mRNA) or 3 hours (protein). COX-2 mRNA (A) and protein (B) levels were analyzed by RT-qPCR and western blot, respectively. C and D, Cells were transfected for 48 hours with 50 nM control siRNA (si-Ctrl) or EGFR siRNA (si-EGFR) and then treated with EGF for 1 hour (mRNA) or 3 hours (protein). COX-2 mRNA (A) and protein (B) levels were analyzed by RT-qPCR and western blot, respectively. Quantified data are normalized to α-Tubulin and are expressed relative to DMSO-treated (B) or si-Ctrl-treated (D) controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).   59  Figure 4.3 The EGF-induced down-regulation of E-cadherin does not require COX-2. Cells were pretreated for 1 hour with NS-398 (10 µM) and then treated with 100 ng/mL EGF for 1 hour (mRNA) or 3 hours (protein). E-cadherin mRNA (A) and protein (B) levels were analyzed by RT-qPCR and western blot, respectively. Quantified data are normalized to α-Tubulin and are expressed relative to DMSO-treated controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).   60  Figure 4.4 The Akt signaling pathway is involved in EGF-induced COX-2 expression. A, Cells were treated with vehicle control (Ctrl) or 100 ng/mL EGF for 5, 10 or 30 minutes, and the levels of phosphorylated Akt were analyzed by western blot. B, Cells were pretreated for 1 hour with wortmannin (1 µM) or LY294002 (10 µM) and then treated with 100 ng/mL EGF for 1 hour (mRNA) or 3 hours (protein). COX-2 mRNA (B) and protein (C) levels were analyzed by RT-qPCR and western blot, respectively. D, Cells were transfected with 1 µg pcDNA3 plasmid (Vector) or dominant-negative Akt (DN-Akt) for 48 hours and then treated with EGF for 3 hours. The COX-2 protein levels were analyzed by western blot. The arrow indicates Myc-tagged DN-Akt. E, Cells were transfected for 48 hours with 50 nM control siRNA (si-Ctrl) or Akt siRNA (si-Akt) and then treated with EGF for 3 hours. COX-2 protein levels were analyzed by western blot. Quantified data are normalized to α-Tubulin and are expressed relative to DMSO-treated (C), vector-treated (D) or si-Ctrl-treated (E) controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).   61  Figure 4.5 Efficacy testing of inhibitors. Cells were pretreated for 1 hour with wortmannin (1 µM) or LY294002 (10 µM) and then treated with 100 ng/mL EGF for 10 minutes. The levels of phosphorylated Akt were analyzed by western blot.   Figure 4.6 CREB is not involved in EGF-induced COX-2 expression. A, Cells were treated with vehicle control (Ctrl) or 100 ng/mL EGF for 5, 10 or 30 minutes, and the levels of phosphorylated CREB were analyzed by western blot. B and C, Cells were transfected for 48 hours with 50 nM control siRNA (si-Ctrl) or CREB siRNA (si-CREB) and then treated with EGF for 1 (mRNA) or 3 hours (protein). COX-2 mRNA (B) and protein (C) levels were analyzed by RT-qPCR and western blot, respectively. Quantified data are normalized to α-Tubulin and are expressed relative to si-Ctrl-treated controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).  62  Figure 4.7 COX-2 and PGE2 are involved in EGF-induced cell invasion. A and B, Cells were treated with 100 ng/mL EGF for 1, 3 and 6 hours (A). Cells were pretreated for 1 hour with NS-398 (10 µM) and then treated with 100 ng/mL EGF for 3 hours (B). The PGE2 protein levels in the culture medium were analyzed by ELISA. C and D, Cells were pretreated for 1 hour with NS-398 (10 µM) (A), or cells were transfected with 50 nM control siRNA (si-Ctrl) or PGES siRNA (si-PGES) for 48 hours (B). Following pretreatment or transfection, the cells were treated with vehicle control (Ctrl) or 100 ng/mL EGF seeded into Matrigel-coated transwell inserts and cultured for additional 48 hours. Non-invading cells were removed from the upper side of the filter, and the nuclei of the invasive cells were stained with Hoechst 33258. The top panel shows representative fluorescence images from the invasion assay. The scale bar represents 200 µm. The bottom panel summarizes the quantitative results, which are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).         63 Chapter 5. EGF-induced connexin43 negatively regulates cell proliferation in human ovarian cancer   Introduction 5.1Gap junctions, composed of integral membrane connexin proteins, are specialized channel structures that directly connect the cytoplasm of adjacent cells to allow the exchange of a variety of small hydrophilic molecules, such as ions, metabolites and second messengers (183,184). The human connexin family contains at least 21 members that are usually named “connexin” (Cx) followed by their predicted molecular weights. Encoded by the GJA1 gene, Cx43 is a well-studied and widely expressed connexin protein with multiple functions in normal and neoplastic cells (182). In rat osteoblast and myoblast cells, enhanced Cx43 expression increases cell proliferation (288,289). In contrast, immortalized mouse embryonic fibroblasts derived from Cx43-knockout embryos grow faster and have a higher saturation density than those of wild-type embryos (290). Likewise, down-regulation of Cx43 has also been shown to promote cell growth in human breast cancer cells (215).  Epithelial ovarian cancer is the most common ovarian malignancy and the leading cause of death among gynecological cancers. The overall 5-year survival rate is 45%, with most patients (61%) being diagnosed at advanced stages (FIGO stages III and IV) and having low 5-year survival rates (27%). However, if the disease is detected when still localized (FIGO stages I), the 5-year survival rate is much higher (92%) (8). Though considered for many years as one disease, recent advances in our understanding of epithelial ovarian cancer have firmly established five subtypes that are now considered to be distinct diseases (291). The endometrioid, clear cell, and mucinous subtypes are frequently confined to the ovary at diagnosis, whereas most high- or low-grade serous ovarian carcinomas present with higher stage diseases. In particular,  64 high-grade serous ovarian carcinomas comprise 70% of all epithelial ovarian cancers and account for 90% of deaths (291). Overexpression of epidermal growth factor receptor (EGFR) has been found in a variety of human cancers (246-248). In epithelial ovarian cancer, elevated EGFR expression is correlated with poor prognosis and disease progression (292). EGF has been shown to regulate Cx43 expression, though its effects differ depending on the cell type. For example EGF treatment has been shown to up-regulate Cx43 expression in cultured porcine preantral follicles, rat granulosa cells, and human kidney epithelial cells (293-295). In contrast, EGF down-regulates Cx43 in rat astrocytes and liver epithelial cells (196,296). It has been reported that Cx43 is frequently reduced in various types of cancer (297). For example, Cx43 expression levels in ovarian cancer cell lines were found to be lower than in cultured ovarian surface epithelial cells (209). Similarly, immunohistochemical analyses confirmed the near absence of Cx43 in many epithelial ovarian cancers compared to extensive expression in the ovarian surface epithelium (210). Overexpression of Cx43 in SKOV3 human ovarian cancer cells decreases cell proliferation and tumorigenicity (298). Together, these studies suggest that Cx43 may exert tumor suppressor-like functions in ovarian cancer. Given the importance of EGF in ovarian cancer tumorigenesis, we sought to examine whether EGF can regulate Cx43 expression and to clarify the role of Cx43 in EGF-induced ovarian cancer cell proliferation. We show that EGF treatment up-regulates Cx43 expression in two human ovarian cancer cell lines, SKOV3 and OVCAR4. In addition, our results indicate that the PI3K/Akt1, but not MEK/ERK1/2, signaling pathway is involved in EGF-induced Cx43 up-regulation. Knockdown of Cx43 enhances basal and EGF-induced cell proliferation, whereas Cx43 overexpression reduces the proliferative effects of EGF in a gap junction-independent manner. These results demonstrate that Cx43 acts as a negative regulator of EGF-induced cell  65 proliferation in human ovarian cancer.  Material and methods 5.2Cell culture and EGF treatment  The non-serous SKOV3 ovarian cancer cell line was obtained from American Type Culture Collection (Manassas, VA). The high-grade serous OVCAR4 ovarian cancer cell line was kindly provided by Dr. T.C. Hamilton (Fox Chase Cancer Center, Philadelphia, PA). Cells were maintained in a 1:1 (v/v) mixture of M199/MCDB105 medium (Sigma-Aldrich, Oakville, ON) supplemented with 10% fetal bovine serum (FBS; Hyclone Laboratories Inc., Logan, UT) at 37°C in a humidified 5% CO2 atmosphere. Cells were starved for 24 hours prior to treatment with EGF. For proliferation assays, treatments were repeated every 24 hours for up to 2 days. Antibodies and reagents Monoclonal anti-α-Tubulin and polyclonal anti-EGFR antibodies were obtained from Santa Cruz Biotechnology (Santa Cruz, CA). Polyclonal anti-phospho-Akt1/2/3 (S473), anti-Akt1/2/3, anti-phospho-ERK1/2, anti-ERK1/2 and anti-Cx43 antibodies were obtained from Cell Signaling Technology (Danvers, MA). A horseradish peroxidase-conjugated goat anti-mouse IgG and goat anti-rabbit IgG were obtained from Bio-Rad Laboratories (Hercules, CA). Human epidermal growth factor (EGF), AG1478 and carbenoxolone were obtained from Sigma. PD98059 and Wortmannin were obtained from Calbiochem (Gibbstown, NJ).      Small interfering RNA (siRNA) transfection and Cx43 overexpression To knockdown endogenous EGFR, ERK1/2, Akt1 or Cx43, cells were transfected with 50 nM ON-TARGETplus SMARTpool siRNA (Dharmacon Research, Inc., Lafayette, CO) using  66 Lipofectamine RNAiMAX (Invitrogen, Burlington, ON). siCONTROL Non-targeting siRNA (Dharmacon) was used as a transfection control. To overexpress Cx43, cells were transfected with 1µg empty vector or vector encoding full-length human Cx43 (Gene Copoeia, Rockville, MD) using Lipofectamine LTX (Invitrogen). Western blots Cells were lysed in lysis buffer (Cell Signaling Technology, Danvers, MA) with protease inhibitor cocktail (Sigma), and the protein concentrations were determined using the DC Protein Assay with BSA as the standard (Bio-Rad Laboratories). Equal amounts of protein were separated by SDS polyacrylamide gel electrophoresis and transferred to PVDF membranes. After blocking with Tris-buffered saline containing 5% non-fat dry milk for 1 hour, the membranes were incubated overnight at 4°C with primary antibodies, followed by incubation with the HRP-conjugated secondary antibody. Immunoreactive bands were detected with an enhanced chemiluminescent substrate followed by exposure to CL-XPosure film (Pierce, Rockford, IL).  MTT and Trypan blue exclusion assays MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) (Sigma) was used to determine cell viability. Cells were seeded in a 24-well plate (2x104/well in 500 μL of medium) and treated as described. At the end of the treatment period, MTT was added to a final concentration of 0.5 mg/mL and then incubated for 4 hours. Medium was removed, DMSO was added to each well to dissolve the crystals, and absorbances were measured at 490 nm using a spectrophotometer microplate reader. The Trypan blue exclusion assay was used as a secondary measure of cell viability. Cells were seeded at a density of 5x104/well in 12-well plates. The number of viable cells was counted  67 by Trypan blue dye exclusion using a hemocytometer and expressed as a percentage relative to vehicle-treated control. Statistical analysis The results are presented as the mean ± SEM of at least three independent experiments. The data were analyzed by a one-way ANOVA and Tukey’s multiple comparison test using PRISM software. Significant differences were defined as P<0.05.  Results 5.3EGF up-regulates Cx43 in human ovarian cancer cells  Previous studies have demonstrated strong correlations between elevated EGFR expression and poor survival in epithelial ovarian cancer (292). Likewise, Kaplan-Meier analysis of high-grade serous ovarian carcinomas from The Cancer Genome Atlas (TCGA) showed that elevated EGFR mRNA is associated with reduced overall survival (Log-rank P = 0.001391, median 38.2 vs. 44.5; Figure 5.1A). To investigate the connection between Cx43 and the EGFR system, we then examined what proportion of TCGA cases with elevated Cx43 mRNA displayed up-regulation of EGFR, ERBB2/HER2 and/or EGFR ligands. We found that at least one element of the EGFR system was up-regulated in 39 of 59 (66%) samples with elevated Cx43, suggesting a potential connection between the EGFR system and Cx43 (Figure 5.1B). Next, we used SKOV3 and OVCAR4 ovarian cancer cell lines to directly examine whether EGF treatment can up-regulate Cx43 expression. Both cell lines are known to express EGFR, though its levels in OVCAR4 cells are much lower than in SKOV3 cells (Figure 5.2). Treatment with 100 ng/mL EGF induced time-dependent increases in Cx43 protein levels in both SKOV3 and OVCAR4 cells; however, EGF treatment did not influence Cx43 mRNA levels (Figure 5.3A  68 and B). Maximal effects of EGF on Cx43 protein levels were observed 6 hours after EGF treatment and persisted until at least 24 hours. In addition, treatment with 50 or 100 ng/mL EGF induced comparable increases in Cx43 protein levels in both cell lines (Figure 5.3C). As treatment with 10 ng/mL EGF only up-regulated Cx43 protein levels in OVCAR4 cells, we therefore used 50 ng/mL EGF in all subsequent experiments. EGFR is required for EGF-induced Cx43 expression To confirm the involvement of EGFR in EGF-induced Cx43 expression, we pretreated cells with the ATP-competitive EGFR tyrosine kinase inhibitor AG1478 (299,300). EGF-induced increases in Cx43 protein levels were abolished by AG1478 in both SKOV3 and OVCAR4 cells (Figure 5.4A). To avoid potential off-target effects from pharmacological inhibition, the involvement of EGFR was further confirmed using an siRNA-mediated knockdown approach. As shown in Figure 5.4B, transfection with EGFR siRNA significantly down-regulated EGFR levels and abolished EGF-induced Cx43 up-regulation.  EGF-induced Cx43 expression is mediated by PI3K/Akt1 signaling To investigate the signaling pathways mediating EGF-induced Cx43 expression, we first examined the activation of ERK1/2 and Akt following treatment with EGF for 10, 30 or 60 minutes. As shown in Figure 5.5, treatment with EGF increased the levels of phosphorylated ERK1/2 and Akt at all time-points in both SKOV3 and OVCAR4 cells. Moreover, EGF-induced activation of ERK1/2 and Akt was completely blocked by treatment with AG1478 (Figure 5.6A). Next, we used specific inhibitors of MEK and PI3K to determine which pathway is required for EGF-induced Cx43 up-regulation. As shown in Figure 5.6B, pretreatment with the PI3K inhibitor Wortmannin abolished the up-regulation of Cx43 by EGF, whereas pretreatment with the MEK  69 inhibitor PD98059 was without effect. To avoid potential off-target effects of these pharmacological inhibitors, the roles of ERK1/2 and Akt1 were further confirmed using specific siRNAs. As shown in Figure 5.6C, transfection with ERK1/2 or Akt1 siRNAs specifically down-regulated ERK1/2 or Akt1 protein levels. Consistent with our inhibitor studies, only knockdown of Akt1 attenuated the EGF-induced up-regulation of Cx43 protein levels in both SKOV3 and OVCAR4 cells (Figure 5.6C). These results clearly demonstrate that EGF-induced Cx43 expression in human ovarian cancer cells is mediated by the PI3K/Akt1 signaling pathway.  Cx43 negatively regulates EGF-stimulated ovarian cancer cell proliferation It has been shown that the modulation of Cx43 can regulate cell proliferation in many types of cells. However, it remains unknown whether the EGF-induced up-regulation of Cx43 expression contributes to cell proliferation in human ovarian cancer cells. Thus, to examine the function of Cx43 in regulating basal and EGF-induced ovarian cancer proliferation, the siRNA-mediated knockdown approach was used. As shown in Figure 5.7A, transfection of a siRNA targeting Cx43 significantly down-regulated the basal and EGF-induced up-regulation of Cx43 protein levels. MTT assay results showed that treatment with EGF for 48 hours stimulated cell proliferation in both SKOV3 and OVCAR4 cells. Interestingly, the knockdown of Cx43 not only increased basal cell proliferation but also enhanced EGF-stimulated cell proliferation (Figure 5.7B). It has been shown that different treatments may alter the mitochondrial metabolic activity of cells, which results in considerable variation of MTT assay (301). Therefore, the effects of Cx43 knockdown on EGF-induced cell proliferation were further confirmed by the trypan blue exclusion assay. Similar to the results obtained using the MTT assay, knockdown of Cx43 increased the cell number and enhanced the EGF-increased cell number in both SKOV3 and OVCAR4 cells (Figure 5.7C). Next, we performed forced-expression studies to further confirm  70 the role of Cx43 in EGF-induced cell proliferation. As shown in Figure 5.7D, cells transfected with vector encoding human Cx43 had significantly increased Cx43 protein levels compared to cells transfected with empty vector. In both MTT and Trypan blue exclusion assays (Figures 5.7E and F), overexpression of Cx43 significantly reduced EGF-induced cell proliferation, whereas only modest, non-significant reductions of basal cell proliferation were observed. Taken together, our results indicated that EGF-induced Cx43 acts as a negative regulator in EGF-stimulated human ovarian cancer cell proliferation. Suppression of EGF-induced cell proliferation by Cx43 is gap junction-independent Though principally known for its role in gap junctional communication, increasing evidence suggests that Cx43 may also have a range of gap junction-independent functions (302). To determine if the suppressive effects of Cx43 on EGF-induced cell proliferation are gap junction-dependent, we used the well-known gap junction inhibitor carbenoxolone (303). Treatment of SKOV3 and OVCAR4 cells with carbenoxolone abolished both basal and EGF-induced gap junctional intercellular communication (assessed by scrape-loading dye transfer assay; Figure 5.8A). Furthermore, co-treatment with carbenoxolone did not affect basal Cx43 protein levels (Figure 5.8B), nor did it alter the suppressive effects of Cx43 overexpression on EGF-induced cell viability (Figure 5.8C), suggesting a gap junction-independent mechanism.  Discussion 5.4Our results demonstrate that treatment with EGF up-regulates Cx43 expression by activating PI3K/Akt1 signaling. Moreover, we show that Cx43 negatively regulates EGF-stimulated ovarian cancer cell proliferation, likely via a gap junction-independent mechanism. The present study used two ovarian cancer cell lines that are most likely  71 representative of high-grade serous and non-serous subtypes of epithelial ovarian cancer. In particular, recent genomic and immunocytochemical studies strongly suggest that OVCAR4 cells are of high-grade serous origin (21,304). In contrast, while immunocytochemical studies suggest SKOV3 cells closely resemble the high-grade serous subtype, ARID1A and PIK3CA mutations, HNF-1β expression, and mismatch repair deficiencies point to a clear cell or endometrioid origin (304). Interestingly, SKOV3 cells have been shown to display clear cell histology when grown as xenografts (305). That Cx43 is induced by EGF and negatively regulates EGF-stimulated cell proliferation in both cell lines suggests this pathway may operate similarly in both serous and non-serous subtypes. Future studies will be required to investigate in more detail the potential translational relevance of this pathway to each individual subtype of epithelial ovarian cancer. EGF has been shown to positively or negatively regulate Cx43 expression depending on the cell type in question. Stimulatory effects of EGF on Cx43 have been described in porcine preantral follicles, rat granulosa cells, human kidney epithelial cells, human neural progenitor cells, and glioblastoma cells (293-295,306,307); whereas suppressive effects have been observed in rat astrocytes and liver epithelial cells (196,296). In keeping with the cell context-dependent regulation of Cx43 by EGF, multiple signaling pathways have been variably described to mediate both positive and negative effects. For example, treatment with the MEK inhibitor PD98059 blocks EGF-induced down-regulation of Cx43 in rat astrocytes (296) and liver epithelial cells (196). In contrast, MEK/ERK1/2 signaling has been shown to mediate EGFR-induced Cx43 expression in glioblastoma cells (307). We now demonstrate that EGF-induced Cx43 expression is not mediated by MEK/ERK1/2 signaling in ovarian cancer cells. Rather, our results suggest that the up-regulation of Cx43 is mediated solely by PI3K/Akt1 signaling. Similarly, previous studies in human epididymal cells have demonstrated that  72 PI3K/Akt signaling mediates EGF-induced increases in Cx43 protein levels (308). Interestingly, the cytoplasmic domain of Cx43 is known to be phosphorylated by Akt as well as a number of other kinases, including ERK1/2, Src and protein kinases A and C (192,309-311). As phosphorylation has been shown to modulate connexin trafficking, assembly, degradation and gating, future studies will be required to determine the precise mechanism by which EGF-induced PI3K/Akt signaling contributes to elevated Cx43 protein levels and cellular functions in ovarian cancer cells.  Down-regulation of Cx43 has been shown to be correlated with reduced survival in several types of human cancer (312-314). Consistent with these findings, in vitro studies have demonstrated suppressive effects of Cx43 on cell proliferation in glioblastoma (310,315,316), lung cancer (317), and ovarian cancer (298). Our data similarly suggest that Cx43 acts as a negative regulator of both basal and EGF-induced cell proliferation in ovarian cancer cells. Tumor suppressor-like effects of Cx43 are also suggested by its inhibitory effects on basal and EGF-induced invasion in rat keratinocytes (318). However, Cx43 has also been shown to enhance the invasiveness of glioblastoma (316,319) and liver cancer cells (320), though whether the same is true for ovarian cancer cells remains unknown. Potential pro-invasive/migratory effects of Cx43 in ovarian cancer warrant future investigation as they could explain why elevated Cx43 mRNA is associated with reduced overall survival in the TCGA dataset for high-grade serous ovarian carcinoma (Log-rank P = 0.048463; Figure 5.9).  Though connexins are best known for their roles in gap junctional intercellular communication, there is increasing evidence to support a variety of gap junction-independent functions, especially in tumor biology (192,310). Indeed, we now show that the suppressive effects of Cx43 on EGF-induced ovarian cancer cell proliferation are independent of gap junctional communication. In rat liver cancer cells, forced-expression of Cx43 down-regulates  73 cell proliferation independently of gap junctional function (321). Similarly, treatment with the gap junction inhibitor carbenoxolone did not alter the suppressive effects of Cx43 on EGF-induced cell invasion in keratinocytes (318). To date, a handful of studies have demonstrated that Cx43 can regulate cell proliferation by modulating the expression of cell cycle regulatory proteins. For example, overexpression of Cx43 in either HeLa cells or primary human fibroblasts has been shown to induce G1 phase delay and prolong the duration of mitosis by increasing p21 expression (322). Likewise, Cx43 has been shown to inhibit G1/S phase transition by increasing p27 expression in a variety of cancer cell lines (323,324). Recently, Cx43 was found to interact with heat shock cognate protein 70, thereby preventing the nuclear translocation of cyclin D1 and inhibiting G1/S phase transition (325). In addition to modulating cell cycle regulatory proteins, studies suggest that Cx43 interacts with the scaffold protein caveolin-1 (199), and that this interaction contributes to the regulation of cell invasiveness by Cx43 in keratinocytes and glioblastoma cells (316,318). Future studies are required to characterize, in detail, the gap junction-independent mechanisms mediating the suppressive effects of Cx43 on EGF-induced ovarian cancer cell proliferation. In summary, our results demonstrate that EGF up-regulates Cx43 expression by activating EGFR and PI3K/Akt1 signaling. In addition, we show that Cx43 negatively regulates EGF-stimulated ovarian cancer cell proliferation, likely via a gap junction-independent mechanism. These results increase our understanding of the biological functions of Cx43 and provide important insight into the molecular mechanisms regulating EGF-stimulated human ovarian cancer cell proliferation.    74  Figure 5.1 Kaplan–Meier survival curve for HGSC with EGFR elevation and OncoPrints of up-regulation of related genes. A, High-grade serous ovarian carcinomas with mRNA expression data from The Cancer Genome Atlas (TCGA, Nature 2011, n=489) were queried for up-regulation of EGFR using the cBioPortal for Cancer Genomics. Up-regulation was defined as expression above the 85th percentile (Z-score > 1.0364; Type “EGFR: EXP> 1.0364” in Enter Gene Set box). Overall survival differences between unaltered samples and those with elevated EGFR are displayed as Kaplan-Meier survival curves with a P value from a Log-rank test. B, To investigate the connection between Cx43 (GJA1) and the EGFR system, high-grade serous ovarian carcinomas with mRNA expression data were queried to determine what proportion of cases with elevated Cx43 expression displayed up-regulation of EGFR, ERBB2/HER2 and/or EGFR ligands (EGF, amphiregulin (AREG), transforming growth factor-α (TGF-α), epigen (EPGN), heparin-binding EGF (HBEGF), betacellulin (BTC), epiregulin (EREG). Elevation/up-regulation was defined as expression above the 85th percentile (Z-score > 1.0364) and results are visualized by means of an OncoPrint.    Figure 5.2 Endogenous expression of EGFR. EGFR protein levels in SKOV3 and OVCAR4 cells were analyzed by Western blot.    75  Figure 5.3 EGF up-regulates Cx43 expression in SKOV3 and OVCAR4 cells. A and B, Cells were treated with vehicle control (Ctrl) or 100 ng/mL EGF and Cx43 mRNA (A) and protein (B) levels were analyzed at different time-points by RT-qPCR and Western blot, respectively. C, Cells were treated with increasing concentrations of EGF (10, 50 and 100 ng/mL) for 6 hours and Cx43 protein levels were analyzed by Western blot. Quantified data are normalized to α-Tubulin and are expressed relative to controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (P<0.05).  76  Figure 5.4 EGFR is required for EGF-induced Cx43 expression. A, Cells were pretreated with AG1478 (10 µM) for 1 hour and then treated with 50 ng/mL EGF for 6 hours. Cx43 protein levels were analyzed by Western blot. B, Cells were transfected with 50 nM control siRNA (si-Ctrl) or EGFR siRNA (si-EGFR) for 48 hours and then treated with EGF for 6 hours. Cx43 protein levels were analyzed by Western blot. Quantified data are normalized to α-Tubulin and are expressed relative to DMSO-treated (A) or si-Ctrl-treated (B) controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (P<0.05).  77  Figure 5.5 EGF induces ERK1/2 and Akt phosphorylation in SKOV3 and OVCAR4 cells. Cells were treated with vehicle control (Ctrl) or 50 ng/mL EGF for 10, 30 or 60 minutes, and the levels of phosphorylated ERK1/2 and Akt were analyzed by Western blot. Quantified data of p-ERK1/2 and p-Akt are normalized to total ERK1/2 and Akt, respectively, and are expressed relative to 10min-treated controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (P<0.05).    78   Figure 5.6 EGF-induced Cx43 expression is mediated by PI3K/Akt1 signaling. A, Cells were pretreated with AG1478 (10 µM) for 1 hour and then treated with EGF for 10 min. Levels of phosphorylated ERK1/2 and Akt were analyzed by Western blot. B, Cells were pretreated with PD98059 (10 µM) or Wortmannin (1 µM) for 1 hour and then treated with 50 ng/mL EGF for 6 hours. Cx43 protein levels were analyzed by Western blot. C, Cells were transfected with 50 nM control siRNA (si-Ctrl), ERK1 and ERK2 siRNA (si-ERK1/2) or Akt1 siRNA (si-Akt1) for 48 hours and then treated with EGF for 6 hours. Cx43 protein levels were analyzed by Western blot. Quantified data are normalized to α-Tubulin and are expressed relative to DMSO-treated (B) or si-Ctrl-treated (C) controls. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (P<0.05).  79  Figure 5.7 Cx43 negatively regulates EGF-induced cell proliferation. A, Cells were transfected with 50 nM control siRNA (si-Ctrl) or Cx43 siRNA (si-Cx43) for 48 hours and then treated with EGF for 6 hours. Cx43 protein levels were analyzed by Western blot. B and C, Cells were transfected with 50 nM control siRNA (si-Ctrl) or Cx43 siRNA (si-Cx43) for 48 hours and then treated with EGF for another 48 hours. Cell viability (B) and cell number (C) were analyzed by MTT and Trypan blue exclusion assays, respectively. D, Cells were transfected with empty vector (Vector) or vector encoding human Cx43 (Cx43) for 24 hours and Cx43 protein levels were analyzed by Western blot. Quantified data are normalized to α-Tubulin and are expressed relative to si-Ctrl-treated (A) or Vector (D) controls. E and F, Cells were transfected with empty vector (Vector) or vector encoding human Cx43 (Cx43) for 24 hours and then treated with EGF for another 48 hours. Cell viability (E) and cell number (F) were analyzed by MTT and Trypan blue exclusion assays, respectively. Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (P<0.05).  80  Figure 5.8 Suppression of EGF-induced cell proliferation by Cx43 is gap junction-independent. A, Fully confluent cells were treated with 100 ng/mL EGF for 6 hours in the presence or absence of 25 µM CBX. The GJIC was measured by monitoring the transfer of fluorescent dye between cells, and images were captured using a fluorescence microscope (top panel). The corresponding bright field micrographs are shown in the bottom panel. B, Cells were treated with vehicle control (H2O) or carbenoxolone (CBX; 25 µM) for 48 hours and Cx43 protein levels were analyzed by Western blot. C, Cells were transfected with empty vector (Vector) or vector encoding human Cx43 (Cx43) for 24 hours, pretreated with CBX (25µM) for 1 hour, and then treated with EGF for further 48 hours. Cell viability was analyzed by MTT assay and results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (P<0.05).    81   Figure 5.9 Correlation between Cx43 expression and overall survival rate. High-grade serous ovarian carcinomas with mRNA expression data from The Cancer Genome Atlas (n=489) were queried for up-regulation of Cx43 using the cBioPortal for Cancer Genomics. Up-regulation was defined as expression above the 85th percentile (Z-score > 1.0364). Overall survival differences between unaltered samples and those with elevated Cx43 are displayed as Kaplan-Meier survival curves with a P value from a Log-rank test.      82 Chapter 6. Conclusion  Summary 6.1Ovarian cancer is the leading cause of death in gynecological malignancies largely due to the lack of effective methods for its early detection, which results in most patients presenting with advanced-stage disease (3). The 5-year survival rate is approximately 92% when the disease is confined to the ovaries, whereas the survival rate dramatically drops to only 27% when the tumor has progressed to the advanced stages (ΙΙΙ and ΙV) (326). The overexpression of EGFR has been detected in most ovarian cancers and is associated with a poor prognosis (56,60). Moreover, in metastases and advanced-stage ovarian cancers, a higher level of EGFR has been reported (58). Therefore, studying the mechanisms underlying EGFR signaling in human ovarian cancer cells may provide a deeper understanding of ovarian tumor progression and possibly identify new therapeutic targets for the treatment of this disease. Through EMT, cancer cells acquire migratory and invasive abilities (96). The loss of E-cadherin, one of the classical cadherins, plays an essential role in EMT. Lower levels of E-cadherin were expressed in mouse ovarian tumor cells with a higher metastatic ability (137). Previous studies in my lab recently showed that EGF and AREG induce invasion and down-regulate E-cadherin expression in human ovarian cancer cells (140-142,145,228). However, whether TGF-α, another EGF-like ligand that binds exclusively to EGFR, promotes cellular invasion through down-regulating E-cadherin expression was unknown. As shown by the results described in Chapter 3, TGF-α induced EMT-like morphological changes in a widely used ovarian cancer cell line, SKOV3. Moreover, overexpression of E-cadherin attenuated the basal and TGF-α-induced invasiveness of SKOV3 cells. These results indicated the requirement for down-regulated E-cadherin expression in the TGF-α-induced invasion of human ovarian  83 cancer cells. The results of using inhibitor- and siRNA-mediated approaches confirmed the involvement of EGFR in the TGF-α-induced loss of E-cadherin. Unlike EGFR, HER2 must dimerize with other c-erbB receptors to be activated because it lacks a ligand-binding domain (230,231). Our previous study demonstrated the involvement of HER2 in the EGF-induced down-regulation of E-cadherin expression (140). Therefore, I also examined the possible involvement of HER2 in the TGF-α-induced down-regulation of E-cadherin expression, and the same results were obtained. Given the well-known transcriptional repressive effect of Snail and Slug on E-cadherin expression (113), their possible involvement in the down-regulation of E-cadherin expression was examined. The siRNA-mediated knockdown of Slug expression attenuated the EGF, AREG and TGF-α-induced down-regulation of E-cadherin expression, whereas unexpected and interestingly, knocking down Snail expression did not alter the inhibitory effect of TGF-α on E-cadherin expression, although silencing Snail expression lessened the EGF and AREG-induced decrease in the E-cadherin level. To our knowledge, these are the first results showing that TGF-α uses underlying mechanisms different from those of EGF and AREG to repress E-cadherin expression. Increased COX-2 expression has been detected in human ovarian cancers and is correlated with a poor prognosis and poor overall survival (179-181). A combination of COX-2 and EGFR inhibitors prevent the progression of a variety of types of human tumors (255-257). In chapter 4, I described the results of testing whether COX-2 contributed to the EGF-induced cell invasion. I showed that the COX-2 level was increased by EGF treatment. The level of the most common prostaglandin derived from COX-2 activity, PGE2, was also significantly up-regulated. Additionally, the activation of the PI3K/Akt signaling pathway was required for the EGF-induced up-regulation of COX-2 expression. Moreover, EGF-induced cell invasion was dramatically attenuated when the increase in the level of COX-2 or PGE-2 was blocked. We  84 previously demonstrated that down-regulating E-cadherin expression promoted EGF-induced cell invasion.  Thus, a specific COX-2 inhibitor, NS-398, was used to co-treat cells with EGF, and the levels of E-cadherin were examined. The results showed that COX-2 was not required for the EGF-induced decrease in E-cadherin expression. These findings suggested that COX-2 expression and PGE2 production mediated the EGF-induced E-cadherin-independent invasion of ovarian cancer cells. The function of Cx43, which is widely expressed in human tissues, in cellular proliferation is controversial and cellular context-dependent (215,289). The effect of EGF on Cx43 expression is also controversial and cellular context-dependent (196,293). ). However, whether Cx43 can be regulated by EGF and is involved in EGF-induced proliferation of human ovarian cancer cells is unknown. Therefore, as described in Chapter 5, I investigated the function of Cx43 in ovarian cancer. My results showed that EGF/EGFR signaling could up-regulate Cx43 expression in ovarian cancer cells. Treatment with EGF led to the activation of downstream ERK and Akt signaling. However, inhibiting PI3K/Akt but not ERK prevented the EGF-induced up-regulation of Cx43 expression. In addition, my results showed that knocking down Cx43 expression enhanced the EGF-stimulated increase in the cell proliferation rate, suggesting that the increased level of Cx43 induced through EGF acted as a brake to the EGF signaling-mediated promotion of ovarian cancer cell proliferation. To our knowledge, these are the first results to show that Cx43 may function as a negative regulator of EGF signaling.   Figure 6.1 shows a summary of the results of the present study.   85  Discussion 6.26.2.1 What are the genomic profiles of my cell line model? Established cancer cell lines are widely used as important research tools and have been considered representative of bona-fide tumors in a variety of studies of in vitro cancer models. Epithelial ovarian cancer is a heterogeneous disease that can be broadly divided into four major subtypes, serous, endometrioid, clear cell and mucinous carcinomas, as shown in Table 1.1 (10). The different subtypes possess different molecular abnormalities; thus, the need for specific treatments for each subtype has been voiced. Most HGSCs have TP53 genetic mutations. In addition, the hereditary HGSCs have been reported to carry germline mutations in BRCA genes (BRCA1 or BRCA2) (15). In contrast to HGSCs, TP53 genetic mutations are rarely found in LGSCs, low-grade endometrioid, clear cell and mucinous carcinomas. Mutually exclusive mutations in the BRAF, KRAS and ERBB2 genes have been detected in LGSCs (17,18). Low-grade endometrioid and clear cell carcinomas are characterized by CTNNB1, PTEN and PIK3CA mutations, respectively. The majority of mucinous carcinomas have mutations in the KRAS and HER2 genes. I am aware that the available cell lines may not be proper models of a particular disease. Thus, when working with cancer cell lines, we should consider whether they display the biological characteristics of primary malignancies. In this study, I used three ovarian cancer cell lines, SKOV3, OVCAR4 and OVCAR5, to conduct the experiments. These cell lines were derived more than 10 years ago from sources of non-specified histological origins and have been passaged at least 10 times (21). To obtain the detailed genomic profiles of these cell lines, we searched the publicly available cBioPortal for Cancer Genomics, which provides genetic  86 amplification, homozygous deletion, missense mutation, truncating mutation and inframe mutation data for cancers. Based on the information of Broad-Novartis Cancer Cell Line Encyclopedia (CCLE) available through cBioPortal, OVCAR4 cells have 39 mutations, including missense mutations in TP53, which is a hallmark of HGSCs, as well as 2614 copy-number alterations (CNAs) in its chromosomes and SKOV3 cells have 64 mutations and 1729 CNAs, whereas information regarding OVCAR5 cells was not present in this dataset. When we changed the cell-line resource database from CCLE to the US National Cancer Institute (NCI) database, information regarding 60 human tumor cell lines were found, showing that OVCAR4 cells have 39 mutations and 1464 CNAs, OVCAR5 cells contain 99 mutations and 98 CNAs and SKOV3 cells have 218 mutations and 1088 CNAs. Interestingly, TP53 was not listed as mutated in OVCAR4 cells in the NCI-60 database, but was listed as mutated in the CCLE database and the Catalogue of Somatic Mutations in Cancer (COSMIC) database, another resource for cell-line data. Additionally, using immunohistochemical (IHC) staining for TP53, Anglesio et al. scored all three of these cell lines as “null mutation” lines. Moreover, Anglesio et al. suggested that OVCAR4 and OVCAR5 cells are HGSC cells, and Domcke et al. also suggested OVCAR4 cells are likely HGSC cells (they did evaluate OVCAR5 cells) (21,304). In contrast, although the results of an IHC study suggested that SKOV3 cells closely resemble HGSC cells, their ARID1A and PIK3CA mutations, level of HNF-1β expression, and DNA mismatch-repair deficiencies indicate a clear cell or endometrioid origin (304). Interestingly, SKOV3 cells have been shown to display clear cell histological features when grown as xenografts (305). Thus, OVCAR4 and OVCAR5 cells are suitable in vitro models for HGSC, whereas SKOV3 cells appear more consistent with a non-serous subtype of ovarian cancer.  Figure 6.2 shows the Oncoprint graphical summaries of the genetic alterations, 14 of importance to this study, including those in the genes encoding EGFR, CDH1, GJA1 and COX2,  87 our proteins of interest, which were of wild type in the SKOV3, OVCAR4 and OVCAR5 cell lines according to the NCI-60 database.     HGSCs are the most prevalent and the most studied ovarian cancer subtype; however, my studies were not intended to be specific to any one subtype. As described in Chapter 3, I used only the SKOV3 cell line to examine the downstream signaling of TGF-α; thus, additional confirmation may be required to confidently extrapolate the results to HGSCs or other subtypes in general. As described in Chapters 4 and 5, we demonstrated that EGF induced the expression of COX-2 or Cx43 in SKOV3/ OVCAR5 cells (Chapter 4) or SKOV3/OVCAR4 cells (Chapter 5), respectively, suggesting the EGF-mediated COX-2 and Cx43 pathways may operate similarly in both serous and non-serous ovarian cancer subtypes. Future studies will be required to investigate in more detail the potential translational relevance of these pathways to each subtype of epithelial ovarian cancer. 6.2.2 Is there a correlation between E-cadherin and Cx43 expression levels? There is much evidence showing that the loss of GJIC and Cx43 leads to a higher incidence of tumorigenesis. Moreover, restoration of GJIC and the normal Cx43 level inhibits tumor growth (327). In addition to its GJIC-dependent functions, Cx43 has also been reported to act in a GJIC-independent manner (192). Gap junction plaques have been shown to be embedded into adherens junctions, which are composed primarily of cadherins (328). E-cadherin, a well-studied cadherin molecule, is expressed at cell-cell contact points to maintaining the normal epithelial structure (98).  There is accumulating evidence showing that the levels of E-cadherin and Cx43 expression are related. The levels of E-cadherin and Cx43 expression are correlated in a variety of types of tumors, including non-small cell lung cancers (NSCLCs) and gastric cancers (329,330). A good  88 correlation between the level of GJIC and the level of E-cadherin protein was observed in several mouse epidermal cell lines (331). The concurrently reduced expression of both E-cadherin and Cx43 is associated with advanced-stage gastric tumors, and their lymph-node metastasis (330). A similar correlation between the reduction of both the E-cadherin and Cx43 levels and clinical pathological features was also observed in NSCLC cells (332). Moreover, in NSCLC cells, the overexpression of Cx43 strongly induced E-cadherin expression (332). The forced expression of E-cadherin led to the restoration of GJIC between melanoma cells and keratinocytes (333). In mouse epidermal cells, Cx43-mediated GJIC was suggested to be controlled by E-cadherin (331). Taken together, these data indicated that the expression Cx43 and E-cadherin might be regulated by one another. However, it is not known whether Cx43 expression is regulated by E-cadherin or vice versa unknown in human ovarian cancer cells, particularly under EGF-treatment conditions. Further study will be required to address this question. 6.2.3 What are the clinical implications of my findings to EGFR-targeting therapy? As mentioned in the Introduction section, EGFR-targeted therapies for human cancers have been developed but they have not been proven effective for ovarian cancers. Unfortunately, the reasons for the poor response are controversial. A recent study demonstrated that the up-regulated expression of either ERBB2 or heregulin (which belongs to the NRG-1 group, the members of which bind ERBB3 and ERBB4) cause resistance to the EGFR-directed therapeutic antibody cetuximab through the activation of ERBB2 signaling (334). Moreover, it has been shown that combined treatment with cetuximab and an ERBB2-targeted agent inhibited the growth of human squamous and bladder carcinoma  xenografts (334,335). More importantly, the combined inhibition of EGFR and ERBB2 exerted overt, long-lasting tumor-regressive effects in  89 patient-derived metastatic colorectal carcinoma xenografts (336). In addition, several studies demonstrated that inhibiting pan-ERBB provided results superior to those obtained from selective ERBB inhibition (337-339). Our results (Chapter 3) indicated that ERBB2 contributed to the EGFR activation-induced promotion of cell invasion through the suppression of E-cadherin expression in ovarian cancer cells. Thus, compensation by other ERBB family members, such as ERBB2, could be an explanation for ovarian cancers being refractory to EGFR-targeted therapies. Therefore, the dual inhibition of EGFR and ERBB2 or even pan-ERBB inhibition might improve the outcomes of patients with ovarian cancer.  Other than compensation by other ERBB family members, mutations in molecules involved in downstream pathways of EGFR that lead to EGFR-independent signaling activation could contribute to the resistance to anti-EGFR therapies. KRAS, BRAF and PIK3CA mutations have been reported to be associated with resistance to anti-EGFR treatment (340-342). Therefore, the tumor subtypes should be considered when using an anti-EGFR therapy to treat ovarian cancer because different subtypes of epithelial ovarian cancer possess different molecular abnormalities. However, my results showed that EGF-induced COX2 and Cx43 expression in different ovarian cancer cell lines, indicating that the COX2 and Cx43 signaling pathways had the same effects regardless of differences in the genetic abnormalities of these lines.  Moreover, different mutation sites in the same gene might have different responses to anti-EGFR drugs. In comparison with patients with other KRAS-mutated metastatic colorectal tumors, patients with p.G13D-mutated (KRAS codon 13-mutated) tumors have longer overall and progression-free survival when treated with cetuximab (343). Therefore, personalized cancer therapy will be beneficial in meeting each patient’s need.  90  Limitations of this study and future directions 6.3As discussed previously, I am aware that the cell lines cultured in an artificial environment may not fully represent true ovarian tumors in the peritoneal microenvironment in vivo. Moreover, different cell lines possess different sets of genetic mutations that may not reflect those in the original tumors. However, our in vitro models were easily accessed and allowed me to directly manipulate the molecules of interest to examine the detailed downstream molecular mechanisms that mediated ovarian tumor progression. Although the genetic mutations of the various cell lines differed, our results showed that EGF-induced COX-2 (Chapter 4) or Cx43 (Chapter 5) expression regulated cell invasion or proliferation, respectively, regardless of the genomic differences. Thus, my study provided useful information for understanding the cellular mechanisms underlying the characteristics of ovarian cancer cells, particularly those involving EGFR signaling.   Given the limitations of the present study, in the future, a three-dimensional cell culture system that could mimic the in vivo conditions, created using established cell lines that display the same molecular genetic signatures as those of primary tumors and a mouse xenograft model, will provide us opportunities to study the biology of ovarian tumors in vivo and help us to examine new therapeutic targets of EGFR signaling.   Conclusion 6.4The present study has emphasized the role of EGFR in the regulation of human ovarian cancers. 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In contrast, LGSCs are rare and are generally considered to develop from benign serous cystadenomas through serous borderline ovarian tumors (SBOT). SBOTs are slow-growing, non-invasive epithelial neoplasms that have a better prognosis compared with other types of ovarian cancer (11,12,345). Previous studies in my lab have shown that inhibition of p53 or treatment with epidermal growth factor or transforming growth factor-β1 increase SBOT cell invasion by inducing epithelial-mesenchymal transition which suggests a possible mechanism that mediates the progression from SBOT to LGSC (143,346-348). However, many SBOTs recur as LGSCs that display poor responsiveness to conventional chemotherapy and for which survival rates are <50% (344,345,349). Thus, the development of novel, targeted therapeutic strategies is likely required to significantly improve patient survival. CD40, a transmembrane glycoprotein belonging to the tumor necrosis factor receptor (TNFR) superfamily, is expressed by a wide range of cell types including immune, endothelial  128 and epithelial cells.  Engagement of CD40 with its ligand, CD40L, has been shown to play important roles in a variety of physiological and pathological processes, especially in immunity (350,351). In addition, CD40 expression has been demonstrated in several types of cancer, including colon, lung, cervical, bladder and prostate cancer (352). However, reported functions of CD40 in tumor cells vary, with both pro-apoptotic and anti-proliferative effects observed depending on the cellular context (353-355). Alternatively, some studies have shown that CD40 activation may promote the neoplastic transformation and growth of normal cells (356-358). Expression of CD40 has been demonstrated in ovarian cancer cell lines and tumor samples, but not in normal ovarian tissue, suggesting that CD40 may play an important role in ovarian tumors (359-363). Indeed, CD40L-CD40 signaling has been shown to induce growth inhibitory effects in HGSC cells (359,360,362-364); however, the therapeutic potential of CD40 in LGSC and SBOT has not been evaluated.  In the present study, we report for the first time elevated CD40 expression in a significant proportion of LGSCs compared to SBOTs. Moreover, CD40 expression is elevated in LGSC-derived MPSC1 cells compared to SBOT3.1 cells, and CD40L treatment induces cell death via CD40 only in MPSC1 cells. Neither pan-caspase inhibitor nor caspase-3 small interfering RNA has any effect on CD40L-induced MPSC1 cell death. Moreover, CD40L-induced cell death was unaffected by individual or combined knockdown of the mitochondrial proteins apoptosis-inducing factor (AIF) and endonuclease G (EndoG). Interestingly, our results suggest that receptor-interacting protein 1 (RIP1) is involved in CD40L-induced MPSC1 cell death. These results demonstrate that CD40L induces caspase and mitochondria-independent, but RIP1-dependent, cell death in LGSC cells.  129 A.2 Materials and methods Cell culture The SBOT3.1 (365,366) and MPSC1 (367) cell lines were kindly provided by Dr. Nelly Auersperg (Department of Obstetrics and Gynaecology, University of British Columbia, Canada) and Dr. Ie-Ming Shih (Department of Pathology, Johns Hopkins Medical Institutions, USA), respectively. SBOT3.1 cells were grown in a 1:1 (v/v) mixture of M199/MCDB105 medium (Sigma-Aldrich, Oakville, ON) supplemented with 10% fetal bovine serum (FBS; Hyclone Laboratories Inc., Logan, UT). MPSC1 cells were maintained in RPMI 1640 medium (Invitrogen, Burlington, ON) supplemented with 10% FBS. Cells were cultured at 37°C in a humidified atmosphere containing 5% CO2 and 95% air. Patient samples Frozen samples of primary tissue were obtained from the Ovarian Cancer Canada Tumor Bank with informed patient consent following approval from the University of British Columbia and British Columbia Cancer Agency Research Ethics Board. A cube of tissue was quickly removed from the cryovial, minced using a scalpel blade and transferred to a tube containing cell lysis buffer (Cell Signaling Technology, Danvers, MA) with protease inhibitor cocktail (Sigma-Aldrich). Lysates were passed at least 5 times each through 18- and 22-gauge needles. Extracts were centrifuged at 20,000 x g for 10 min at 4°C to remove cellular debris and supernatants were transferred to a clean microcentrifuge tube. Samples were stored at –80°C until assayed by Western blot as described below.   130 Antibodies and reagents Mouse monoclonal anti-α-Tubulin, goat polyclonal anti-actin (C-11) and rabbit polyclonal anti-CD40 (N-16) antibodies were obtained from Santa Cruz Biotechnology (Santa Cruz, CA). Polyclonal anti-caspase-3 antibody was obtained from Cell Signaling Technology. Horseradish peroxidase-conjugated goat anti-mouse IgG and goat anti-rabbit IgG were obtained from Bio-Rad Laboratories (Hercules, CA). Recombinant human sCD40 ligand (CD40L) was obtained from Peprotech (Rocky Hill, NJ). 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), necrostatin-1, and 1-methyl-L-tryptophan (1-MT) were purchased from Sigma-Aldrich. Boc-D-FMK was purchased from Abcam.  Small interfering RNA (siRNA) transfection  To knockdown endogenous CD40, caspase-3, AIF or EndoG, cells were transfected with 50 nM ON-TARGETplus SMARTpool siRNA or ON-TARGETplus Non-targeting Control Pool (Dharmacon Research, Inc., Lafayette, CO) using Lipofectamine RNAiMAX (Invitrogen, Burlington, ON).  Western blot analysis Cells were washed with cold PBS and lysed in lysis buffer (Cell Signaling Technology) containing protease inhibitor cocktail (Sigma-Aldrich). Extracts were centrifuged at 20,000 x g for 10 min at 4°C and protein concentrations were determined using the DC Protein Assay (Bio-Rad Laboratories) with BSA as the standard. Equal amounts of protein were separated by SDS polyacrylamide gel electrophoresis and transferred to polyvinylidene fluoride membranes. After blocking with Tris-buffered saline containing 5% non-fat dry milk for 1 hr, the membranes  131 were incubated overnight at 4°C with primary antibodies followed by incubation with peroxidase-conjugated secondary antibody. Immunoreactive bands were detected using enhanced chemiluminescent substrate (Pierce, Rockford, IL) followed by exposure to CL-XPosure film (Thermo Fisher, Waltham, MA). Films were scanned and quantified by densitometry using Scion image software (Scion Corp., Frederick, MD, USA). CD40 and cleaved caspase-3 levels were normalized to α-tubulin. Alternatively, CD40 levels in primary tumor samples were normalized to actin.  Reverse transcription quantitative real-time PCR (RT-qPCR) Total RNA was extracted using TRIzol Reagent (Invitrogen) according to the manufacturer's instructions. Reverse transcription was performed with 3 µg RNA, random primers and M-MLV reverse transcriptase (Promega, Madison, WI). RT-qPCR was performed using an Applied Biosystems 7300 Real-Time PCR System equipped with 96-well optical reaction plates. Each 20 μl reaction contained 1× SYBR Green PCR Master Mix (Applied Biosystems), 100 ng cDNA and 250 nM of each specific primer. The primers used for SYBR Green RT-qPCR were: CD40, 5'-CTG TTT GCC ATC CTC TTG GT-3' (sense) and 5'-CGA CTC TCT TTG CCA TCC TC-3' (antisense); CD40L, 5'-ATT GGG TCA GCA CTT TTT GC-3' (sense) and 5'-TCA CAA AGC CTT CAA ACT GG-3' (antisense); and GAPDH, 5'-GAG TCA ACG GAT TTG GTC GT-3' (sense) and 5'-GAC AAG CTT CCC GTT CTC AG-3' (antisense). The specificity of each assay was validated by dissociation curve analysis and agarose gel electrophoresis of PCR products. Assay performance was validated by evaluating amplification efficiencies by means of calibration curves, and ensuring that the plot of log input amount vs. ∆Cq has a slope <|0.1|. Alternatively, TaqMan gene expression assays were used for AIF, EndoG and GAPDH (Hs00377585_m1, Hs01035290_m1 and Hs02758991_g1, respectively; Applied Biosystems). Each 20 μL TaqMan reaction contained  132 1× TaqMan Gene Expression Master Mix (Applied Biosystems), 100 ng cDNA and 1× TaqMan gene expression assay (containing primers and probe). The PCR parameters for SYBR Green and TaqMan RT-qPCR were 50°C for 2 minutes, 95°C for 10 minutes, and 40 cycles of 95°C for 15 seconds and 60°C for 1 minute. All RT-qPCR results represent the mean of at least three separate experiments and each sample was assayed in triplicate. Relative quantification of mRNA levels was performed by the comparative Cq method with GAPDH as the reference gene and using the formula 2–∆∆Cq.  MTT and Trypan blue exclusion assays For the MTT assay cells were seeded at a density of 2 × 104 cells/well in 48-well plates and treated as described. MTT was added to a final concentration of 0.5 mg/mL, the cells were incubated for 4 h and the medium was removed. DMSO was added to each well and absorbances were measured at 490 nm using a microplate reader. For the Trypan blue exclusion assay cells were seeded at a density of 5 × 104 cells/well in 12-well plates and treated as described. Viable cell numbers were counted by Trypan blue dye exclusion using a hemocytometer. Results are expressed as a percentage relative to vehicle treated control. Statistical analysis Results are presented as the mean ± SEM of at least three separate experiments, and were analyzed by t-test or one-way ANOVA followed by Student-Newman-Keuls multiple comparison test using PRISM software (GraphPad Software, Inc., San Diego, CA). Significant differences were defined as P < 0.05.  133 A.3 Results   Expression of CD40 in SBOT- and LGSC-derived cell lines and primary tumor samples A previous study analyzing the DNA methylation profiles of ovarian serous neoplasms indicated that CD40 is hypomethylated in LGSCs compared to SBOTs, suggesting the expression of CD40 may be higher in LGSCs than in SBOTs (368). To test this hypothesis, we examined CD40 expression levels in SBOT-derived SBOT3.1 cells and LGSC-derived MPSC1 cells. CD40 mRNA (Figure A.1A) and protein (Figure A.1B) levels were higher in MPSC1 cells than in SBOT3.1 cells. Since many CD40-expressing cells also express CD40L, we also examined the expression of CD40L in these two cell lines. As shown in Figure A.1C, CD40L mRNA was undetectable in both SBOT3.1 and MPSC1 cells. These results suggest that both SBOT3.1 and MPSC1 cells express CD40, but that CD40 levels are much higher in LGSC-derived MPSC1 cells. Next, we used Western blot to measure CD40 protein levels in frozen tissues from eight SBOTs and five LGSCs. As shown in Figure A.1D, CD40 protein levels were elevated in 3 of 5 LGSC samples compared to weak or no expression in the SBOT samples. CD40L induces cell death via CD40 in MPSC1 but not SBOT3.1 cells  Growth inhibitory and pro-apoptotic effects of CD40 activation have previously been demonstrated in HGSC cells (359,360,362-364), however its effects on SBOT and LGSC cells are unknown. To investigate the effects of CD40L on SBOT and LGSC, SBOT3.1 and MPSC1 cells were treated for 48 h with 500 ng/mL recombinant human CD40L and morphology was assessed by phase contrast microscopy. As shown in Figure A.2A, treatment with CD40L did not affect the morphology of SBOT3.1 cells; however, it significantly decreased the number of  134 MPSC1 cells, suggesting potential pro-apoptotic effects of CD40L in MPSC1 cells. To expand on these findings, MPSC1 and SBOT3.1 cells were treated for 24, 48 or 72 h with different concentrations of CD40L (20, 100 or 500 ng/mL) and cell viability was examined by the MTT assay (Figures A.2B and C). CD40L treatment did not diminish SBOT3.1 cell viability but reduced that of MPSC1 cells in both a time- and concentration- dependent manner, with the most significant reductions occurring 72 h after treatment. To further confirm these effects on cell viability, we measured viable cell numbers by Trypan blue exclusion assay following treatment with 500 ng/mL CD40L for 24, 48 or 72 h. In agreement with our MTT results, CD40L treatment induced time-dependent reductions in viable MPSC1 cell numbers but did not alter SBOT3.1 cell viability (Figures A.2D and E). Moreover for both methods, the number of viable cells at 72 h was significantly lower than at 24 or 48 h, indicating that CD40L-induced decreases in MPSC1 cell viability are mediated, at least in part, by increased cell death.  To confirm that CD40 is required for CD40L-induced cell death in MPSC1 cells, we examined the effects of CD40L on cell viability following siRNA-mediated knockdown of endogenous CD40 expression. Pre-treatment for 24 h with CD40 siRNA significantly reduced CD40 protein levels (Figure A.3A), and reversed the effects of subsequent treatment with CD40L (500 ng/mL, 72 h) on cell viability as assessed by MTT or Trypan blue exclusion assays (Figures A.3B and C).  Caspase-3 is activated during CD40L-induced MPSC1 cell death Next, we sought to determine if apoptosis, a well-known form of programmed cell death, was involved in CD40L-induced MPSC1 cell death. Cleavage and activation of caspase-3, a critical executioner caspase, is often associated with apoptotic cell death (369,370). Thus, we used Western blot to measure cleaved caspase-3 levels in MPSC1 cells following treatment for  135 24 or 48 h with CD40L (100 or 500 ng/mL). CD40L treatment increased the levels of cleaved caspase-3 after 48 h in MPSC1 cells (Figure A.4A). Consistent with our cell viability results, treatment of SBOT3.1 cells for 48 h with CD40L (100 or 500 ng/mL) did not alter the levels of cleaved caspase-3 (Figure A.4B). Importantly, CD40L-induced increases in cleaved caspase-3 levels were abolished by pre-treatment of MPSC1 cells for 24 h with CD40 siRNA (Figures A.4C). These results indicate that CD40L/CD40 signaling can activate caspase-3 in LGSC-derived MPSC1 cells but not SBOT3.1 cells.  CD40L-induced MPSC1 cell death is caspase-independent  To determine if activated caspase-3 is directly involved in CD40L-induced cell death, MPSC1 cell viability and cleaved caspase-3 levels were examined in the presence or absence of an irreversible pan-caspase inhibitor (Boc-D-FMK). Pre-treatment for 2 h with 20 µM Boc-D-FMK completely blocked CD40L-induced increases in cleaved caspase-3 levels (Figure A.5A). Surprisingly, pre-treatment with Boc-D-FMK (20, 50 or 100 µM) did not reverse, or even attenuate, the effects of CD40L (500 ng/mL, 72 h) on cell viability as measured by MTT assay (Figure A.5B). To confirm these findings, we examined the effects of CD40L on MPSC1 cell viability following siRNA-mediated knockdown of caspase-3. As shown in Figure A.5C, pre-treatment for 24 h with caspase-3 siRNA significantly reduced pro-caspase-3 protein levels, but did not alter the effects of subsequent treatment with CD40L (500 ng/mL, 72 h) on cell viability as measured by MTT assay. These results suggest that CD40L-induced cell death in LGSC-derived MPSC1 cells is caspase-independent.  CD40L induces mitochondria-independent but RIP1-dependent MPSC1 cell death Mitochondria are central to the control of cell death, and mitochondria-dependent cell death  136 is characterized by the release of mitochondrial proteins into the cytoplasm that are capable of inducing caspase-dependent or caspase-independent cell death (371,372). AIF and EndoG are mitochondrial proteins that are known to translocate to the nucleus and cause chromatin condensation and DNA cleavage in a caspase-independent manner (373,374). To determine whether AIF and/or EndoG are required for CD40L-induced MPSC1 cell death, we examined the effects of CD40L on cell viability following siRNA-mediated knockdown of endogenous AIF and/or EndoG. Pre-treatment for 24 h with AIF and/or EndoG siRNA significantly reduced AIF and EndoG mRNA levels (Figure A.6A), but did not alter the effects of subsequent treatment with CD40L (500 ng/mL, 72 h) on cell viability as measured by MTT assay (Figure A.6B). These results suggest that CD40L-induced cell death in LGSC-derived MPSC1 cells is mitochondria-independent. RIP1 kinase has emerged as an important regulator of caspase-independent cell death (375,376). To determine whether RIP1 is required for CD40L-induced cell death, MPSC1 cell viability was measured in the presence or absence of an allosteric inhibitor of RIP1 (necrostatin-1). Interestingly, pre-treatment for 2 h with 150 nM necrostatin-1 completely blocked CD40L-induced reductions in cell viability as measured by MTT assay (Figure A.6C). However, several studies have shown that necrostatin-1 also inhibits indoleamine-2,3-dioxygenase (IDO) (377,378). To exclude the possible involvement of IDO, MPSC1 cells were pre-treated for 2 h with the IDO inhibitor 1-methyl-L-tryptophan (1-MT, 150 nM) prior to being treated for 72 h with 500 ng/mL CD40L. As shown in Figure A.6D, CD40L-induced reductions in cell viability were not affected by treatment with 1-MT, indicated that CD40L-induced MPSC1 cell death is RIP1-dependent.  137 A.4 Discussion Invasive LGSCs display poor responsiveness to conventional chemotherapy, thus novel therapeutic strategies are urgently required to improve patient survival. We now show that CD40 protein levels are elevated in a significant proportion of LGSCs, perhaps as many as half, compared to weak or no expression in SBOTs. These results are consistent with a previous study suggesting hypomethylation of CD40 in LGSCs compared to SBOTs (368), though future studies will be required to confirm an epigenetic basis for elevated CD40 expression in LGSCs. Importantly, we show for the first time that treatment with CD40L induces cell death in LGSC-derived MPSC1 cells via CD40 activation. Thus, recombinant human CD40L or agonistic anti-CD40 could represent novel treatment options for patients with LGSC displaying elevated CD40. Anti-tumor effects for CD40L-CD40 signaling have been shown in various types of CD40-positive tumors, with direct apoptotic cell killing accounting for much of the response (379-383). Indeed, recombinant CD40L treatment of CD40-positive HGSC xenografts in severe combined immunodeficient mice induced significant apoptosis and tumor destruction, and increased the efficacy of suboptimal doses of cisplatin (364). In addition to directly inducing tumor cell death, CD40-targeted treatments can stimulate general immune activation and have demonstrated utility as cancer immunotherapies, for which CD40 expression on tumor cells is not necessary (384). Activation of CD40 on antigen-presenting cells licenses them to stimulate T-killer cells to exert killing responses (385). Several studies have demonstrated the effectiveness of CD40 ligation in triggering the elimination of tumor cells by T-killer cells (386,387). Moreover, CD40-induced anti-tumor effects have also been shown to involve activated macrophages (388,389) as well as B cells and natural killer cells (390-392). In this context, patients with SBOT or LGSC displaying weak or no expression of  138 CD40 may still benefit from CD40-targeted therapies due to the enhancement of antigen-presenting cell function and the activation of T cells and natural killer cells. Patients with CD40-positive LGSC could also benefit from enhanced immune activation, including opsonization effects if treated with anti-CD40 antibody. Future studies investigating the potential of CD40-targeted therapies on CD40-positive and -negative LGSCs in vivo will be of great interest. Cell death can occur in several ways including necrosis, apoptosis and necroptosis. Apoptosis, a form of programmed cell death, is accompanied by a host of morphological and biochemical features, including plasma membrane blebbing, cell shrinkage, chromatin condensation, apoptotic bodies, DNA fragmentation and phosphatidylserine exposure (393,394). Caspases are the primary effectors of apoptotic cell death and caspase-3 is considered an important executioner owing to its activation of the endonuclease CAD, which can degrade chromosomal DNA (395). Interestingly, though treatment with CD40L resulted in caspase-3 activation, it was not required for CD40L-induced MPSC1 cell death. Moreover, redundant effects from other caspases are unlikely since CD40L-induced cell death was unaffected by pre-treatment with the broad-spectrum caspase inhibitor Boc-D-FMK. Interestingly, beyond their critical roles in apoptosis, increasing evidence suggests a variety of non-apoptotic functions of caspases (396,397). For example, caspase-3 is transiently activated and functions as a key protease in the processes of erythroid differentiation (398) and maturation (399). Caspase-3 has also been shown to inhibit B cell cycling (400), promote adult hematopoietic stem cell quiescence (401), and mediate embryonic stem cell differentiation (402). Thus, CD40L-induced caspase-3 activation in LGSC cells could indicate additional non-apoptotic roles that warrant further investigation. Caspase-independent forms of cell death have also been described, often involving the  139 release of mitochondrial proteins such as AIF and EndoG (371,372,403). Upon release, AIF and EndoG translocate to the nucleus where they induce DNA fragmentation and chromosome condensation (373,374,403). Though caspase-independent, CD40L-induced MPSC1 cell death does not appear to involve AIF and/or EndoG. Rather, our RIP1 inhibitor (necrostatin-1) findings suggest that CD40L treatment induces necroptosis, a form of controlled necrosis characterized by a dependency on RIP1 or RIP3 when caspases, especially caspase-8, are inhibited (376,404-406). RIP1-mediated necroptosis is becoming increasingly recognized as an important form of caspase-independent cell death (375,376). However, pro-apoptotic roles for RIP1 have also been described in caspase-dependent, death receptor-mediated cell killing (407,408). In EJ bladder cancer cells, RIP1 has been shown to mediate CD40L-induced caspase-8 activation and apoptosis, the latter being partially inhibited by necrostatin-1 and completely abolished by pan-caspase inhibitor (409). Since the relationship of RIP1 to necroptosis or apoptosis varies depending on the cellular context, future research will be required to determine the molecular determinants of CD40L-induced cell death in LGSCs.   In summary, we have shown that CD40 is up-regulated in a significant proportion of LGSCs (including LGSC-derived MPSC1 cells) compared to SBOTs. CD40L treatment induces caspase- and mitochondria-independent cell death in MPSC1 but not SBOT3.1 cells. Moreover, our results suggest that RIP1 is involved in CD40L-induced MPSC1 cell death. These findings provide insight into the function and therapeutic potential of the CD40L-CD40 system in LGSCs.    140     Figure A.1 Expression of CD40 in SBOT- and LGSC-derived cell lines and primary tumor samples.   A and B, RT-qPCR and Western blot were used to measure endogenous CD40 mRNA and protein levels in SBOT-derived SBOT3.1 cells and LGSC-derived MPSC1 cells. Quantitative results are expressed as the mean ± SEM of at least three independent passages and values without a common letter are significantly different (p<0.05). C, Endogenous CD40L mRNA levels in SBOT3.1 and MPSC1 cells were measured by RT-qPCR. THP-1 human acute monocytic leukemia cells were used as a positive control and RT-qPCR products were analyzed by agarose gel electrophoresis. D, Western blot was used to measure endogenous CD40 protein levels in MPSC1 cells (positive control) and frozen tissues from primary SBOTs and LGSCs. Quantitative results (left) are expressed as the mean ± SEM and were analyzed by unpaired two-tailed t-test.   141  Figure A.2 CD40L induces cell death in MPSC1 not SBOT3.1 cells.   A, Cells were treated for 48 h with vehicle control (Ctrl) or 500 ng/mL recombinant human CD40L and cell morphology was assessed by phase contrast microscopy. Scale bar: 200 µm. B and C, Cells were treated for 24, 48 or 72 h with vehicle control (Ctrl) or different concentrations of CD40L and cell viability was examined by the MTT assay. D and E, Alternatively, viable cell numbers were measured by Trypan blue exclusion assay following treatment for 24, 48 or 72 h with vehicle control (Ctrl) or 500 ng/mL CD40L. Results are expressed as the mean ± SEM of at least three independent experiments. Values without a common letter are significantly different (p<0.05).  142  Figure A.3 CD40 is required for CD40L-induced cell death.  A, MPSC1 cells were transfected for 24 h with 50 nM control siRNA (si-Ctrl) or CD40 siRNA (si-CD40) and knockdown efficiency was examined by Western blot. Following transfection as described in (A), MPSC1 cells were treated for 72 h with vehicle control (Ctrl) or 500 ng/mL CD40L and cell viability (B) and cell number (C) were analyzed by MTT and Trypan blue exclusion assays, respectively. Results are expressed as the mean ± SEM of at least three independent experiments. Values without a common letter are significantly different (p<0.05).  Figure A.4 Caspase-3 is activated during CD40L-induced MPSC1 cell death.  A, Cleaved caspase-3 levels were measured by Western blot following treatment of MPSC1 cells for 24 or 48 h with vehicle control (Ctrl) or CD40L (100 or 500 ng/mL). B, SBOT3.1 cells were treated for 48 h with vehicle control (Ctrl) or CD40L and cleaved caspase-3 levels were measured by Western blot. C, MPSC1 cells were transfected for 24 h with 50 nM control siRNA (si-Ctrl) or CD40 siRNA (si-CD40) and then treated for another 48 h with vehicle control (Ctrl) or CD40L (500 ng/mL). CD40 and cleaved caspase-3 were analyzed by Western blot and quantified cleaved caspase-3 levels (right) are expressed as the mean ± SEM of at least three independent experiments. Values without a common letter are significantly different (p<0.05).  143  Figure A.5 CD40L-induced MPSC1 cell death is caspase-independent.  A, Cells were pre-treated for 2 h with or without 20 μM Boc-D-FMK and then treated for 48 h with vehicle control (Ctrl) or CD40L (500 ng/mL). Cleaved caspase-3 levels were measured by Western blot. B, Cell viability was measured by MTT assay following treatment for 72 h with vehicle control (Ctrl) or CD40L (500 ng/mL) in the presence or absence of different concentrations of Boc-D-FMK (20, 50 or 100 μM). C, Cells were transfected for 24 h with 50 nM control siRNA (si-Ctrl) or caspase-3 siRNA (si-Casp3) and knockdown efficiency was examined by Western blot (left). Transfected cells were treated for 72 h with vehicle control (Ctrl) or CD40L (500 ng/mL) and cell viability was measured by MTT assay. Results are expressed as the mean ± SEM of at least three independent experiments. Values without a common letter are significantly different (p<0.05).  144  Figure A.6 CD40L induces mitochondria-independent but RIP1-dependent cell death in MPSC1 cells.  A, Cells were transfected for 24 h with 50 nM control siRNA (si-Ctrl), AIF siRNA (si-AIF) or EndoG siRNA (si-EndoG) and knockdown efficiency was examined by RT-qPCR. B, Cells were transfected for 24 h with the indicated siRNAs alone or in combination prior to being treated for 72 h with vehicle control (Ctrl) or CD40L (500 ng/mL). Cell viability was measured by MTT assay. C and D, Cell viability was measured by MTT assay following treatment for 72 h  with vehicle control (Ctrl) or CD40L (500 ng/mL) in the presence or absence of 150 nM necrostatin-1 (C) or 1-MT (D). Results are expressed as the mean ± SEM from at least three independent experiments. Values without a common letter are significantly different (p<0.05).   

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