Ovarian cancer results from the dysregulation, in normal ovarian epithelial cells, of genes responsible for the control of critical biological processes. Since their discovery 20 years ago, microRNAs have increasingly been implicated in that dysregulation due to their role mediating gene expression; changes in microRNA expression levels in cancer have been linked with tumor growth, proliferation and metastasis. Their imputed involvement in cancer has led to the possibility of their use as biomarkers and to their potential clinical use. Using mRNA and microRNA microarray analysis to compare human gene expression in normal ovarian surface epithelial (OSE) cells and epithelial ovarian cancer (EOC) cells, we explored the interactions between microRNAs and genes. First, we validated in silico predictions of microRNA targets by comparing them with in vitro evidence after exogenous microRNA transfection. We found that pairs of microRNAs with identical 7-nt (nucleotide) seed regions shared 88% of their predicted targets and 55% of their in vitro targets, confirming the importance of the seed as a targeting mechanism. But more importantly, we found that even a single nucleotide change in the seed region can result in a significant shift in the set of targeted genes, implying strong functional conservation of the seeds and their corresponding binding sites. Next, we discovered a 3-element network motif which explains the upregulation of nearly 800 genes in ovarian cancer which, as predicted microRNA targets, might be expected to be down- regulated. This model shows that, under certain circumstances, repressor genes which are down- regulated in cancer can apparently override the repressive effects of microRNAs, resulting in the upregulation of predicted microRNA targets. Finally, we developed a phenomenological network model, based on the Pearson correlation of microarray gene expression data, to identify subnetworks dysregulated in cell cycle and apoptosis. While our methodology reported many genes previously associated with ovarian cancer, it significantly suggested potentially oncogenic genes for further investigation. This network model can easily be extended to identify dysregulated genes in other cancers.

Women with advanced ovarian cancer generally have a poor prognosis but there is significant variability in survival despite similar disease characteristics and treatment regimens. The aim of this study was to determine whether psychosocial factors predict survival in women with ovarian cancer, controlling for potential confounders.

Menopause is associated with disorders such as osteoporosis and ovarian cancer. It is unclear whether the postmenopausal ovary retains steroidogenic capacity and how it can impact the development of these disorders. The present studies used the VCD-treated follicle-depleted mouse model of menopause to test the hypothesis that residual ovarian tissue retains steroidogenic capacity following ovarian failure and, thus, affects the development of these disorders. Microarray technology was used to evaluate gene expression in residual ovarian tissue of follicle-depleted mice compared to that in ovaries from cycling animals. Among the genes identified were those encoding proteins for synthesis of androgens. Steroidogenic capacity of residual ovarian tissue was further evaluated by determining the expression of genes and proteins involved in ovarian steroidogenesis, and by measuring levels of circulating and rostenedione and gonadotropins. Follicle-depleted ovaries were enriched in mRNAs for androgenic enzymes, receptors involved in the internalization of cholesterol, and luteinizing hormone receptor. Increased circulating levels of FSH and LH and detectable and rostenedione were measured throughout the study. Protein for 3β-hydroxysteroid dehydrogenase, 17α- hydroxylase/17,20-lyase and luteinizing hormone receptor was detected in follicledepleted ovaries by Western blot analysis and localized by immunofluorescence staining. The contribution of retaining residual ovarian tissue to accelerated bone loss following ovarian failure was evaluated by comparing bone mineral density from young and aged VCD-treated mice to that in age-matched ovariectomized (OVX) animals. Retaining residual ovarian tissue resulted in protection against accelerated bone loss in young but not aged VCD-treated mice. Whether residual ovarian tissue is more susceptible to development of ovarian neoplasms compared to ovaries from cycling animals was addressed by combining the VCD-treated mouse with the DMBA model of ovarian carcinogenesis. VCD-treated follicle-depleted mice that received DMBA developed Sertoli-Leydig cell tumors while no tumors were observed in cycling animals. Residual ovarian tissue following ovarian failure appears to have a protective effect against loss of bone integrity, but a detrimental effect on development of ovarian neoplasms. Findings from these studies: provided evidence of a physiological role for residual ovarian tissue following ovarian failure, and furthered the use of the VCD-treated mouse as a relevant model for menopause and associated disorders.

Ovarian cancer is the leading cause of gynecologic cancer death among women in the United States, claiming the lives of more than 15,000 women each year. Women who receive this diagnosis must make rapid, critical medical decisions that impact survival and quality of life. Two studies were conducted to obtain pilot data related to the health preferences of ovarian cancer patients and their oncologists. Forty-one eligible patients and 34 eligible physicians participated in this study. Six hypothetical health states were developed based on possible outcomes of ovarian cancer treatment strategies. Participants were asked to rate these health states using a visual analog scale and the standard gamble chance board. A series of exploratory hypotheses were tested to obtain guidance for future research. Patients under surveillance had significantly lower preferences for all health states than patients receiving chemotherapy or physicians. Overall, patients were very consistent across health states with the level of risk they were willing to take, while physicians were significantly more likely to avoid risk when the treatment strategy presented involved improved treatment efficacy, even when associated with higher toxicity and poor emotional well being. These findings show the need for additional research and suggest that research in medical decision making must examine health choices made by patients separately, depending on their current treatment status, but not necessarily by current self-reported health status, time since diagnosis or by recurrent/non-recurrent disease.

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Philosophiae Doctor - PhD / Introduction: Globally, there are over 190,000 new reported cases of ovarian cancers per annum. This comprises 3% to 4% of all cancers in women. Ovarian cancer is one of the leading causes of deaths in women. Ovarian cancer is the second most diagnosed gynaecological malignancy and over all the fifth cause leading to death among all types of cancer in the UK in 2004. More than 70% of epithelial ovarian cancers are diagnosed at an advanced stage. Consequently, the prognosis is poor and the mortality rate high. Thus, the survival rate is affected by how far the disease has progressed or spread. A dire need exists to identify ovarian cancer biomarkers, which could be used as good indicators of expression in ovarian cancer cells in vitro Aim: The aim of this study was to analyse selected cancer biomarkers, which are currently under intense investigation for their suitability to diagnose epithelial ovarian cancer at an early stage. These biomarkers were analysed in terms of their in vitro expression in normal epithelial cells and ovarian cancer cell lines, which allows for their genomic and proteomic classification. The expression analysis of each biomarker is related to the malignancy of a tumour and, therefore, advocates its use for potential future improvement of sensitive tumour markers. Methods: The primary human ovarian surface epithelial cell line (HOSEpiC), SKOV-3 cells and the OAW42 human epithelial ovarian tumour cell lines were used to evaluate the selected cancer biomarkers. Cells were cultured using appropriate media and supplements, and real-time quantitative polymerase chain reaction (RT-PCR) utilized to validate expression levels of the following genes: HDAC1, HDAC2, HDCA3, HDAC5, HDAC6, HDAC7, HDAC8, LPAR1, LPAR2, MUC16 and FOSL1, against normal housekeeping genes GAPDH and HPRT. In addition, immunocytochemistry was also used in the validation process of the aforementioned genes. Significance: ovarian cancer cells express gene signatures, which pose significant challenges for cancer drug development, therapeutics, prevention and management. The present study is an effort to explore ovarian cancer biomarkers to provide a better diagnostic method that may offer translational therapeutic possibilities to increase five- year survival rate. Results: HDAC5, HDAC6, LPAR1, LPAR2 and MUC16 expressed distinctively in ovarian cancers matched to other tissues or cancer types have already been identified by RT-QPCR and confirmed by immunocytochemistry and efforts to generate monoclonal antibodies to the other six genes (HDAC1, HDAC2, HDAC3, HDAC7, HDAC8 and FOSL1) encoded proteins are underway. Conclusions: here we provide strong evidence suggesting that HDAC5, HDAC6, LPAR1, LPAR2, except MUC16 are up regulated in ovarian cancer. These data were confirmed by examining Human Protein Atlas (HPA) databases, in addition to protein expression of HDAC5, HDAC6, LPAR1, LPAR2 and MUC16 in cells cytoplasm. For future prospective, using other techniques that assess the variant expression that could explain the release of these gene candidates into the circulation with serum tumour markers, and protein expression will be strengthened.

The PI3K/Akt/mTOR and MAPK pathways are frequently altered in ovarian cancer cells, making them potential candidates for targeted therapy. A more complete understanding of the complex interactions between the different proteins within the two pathways would assist in developing more effective treatment strategies to help overcome therapy resistance. The purpose of this project was to understand the phosphoproteomic changes in response to PI3K/mTOR inhibition in ovarian cancer cells and to identify potential mechanisms that may lead to targeted therapy resistance. To investigate the effect of inhibiting PI3K/mTOR at the cellular level in ovarian cancer, PI3K (LY294002), mTOR (rapamycin) and dual PI3K/mTOR (BEZ235) inhibitors were used to treat a panel of ovarian cancer cell lines. All tested cells, irrespective of PI3K/Akt/mTOR and MAPK pathways mutational status, responded to the three inhibitors. BEZ235 treatment produced greater cell inhibition than the monotargeted agents, while PTENmutated cell lines were more responsive to mTOR blockade than inhibition of PI3K alone. The phosphoproteomic changes in the cell lines were evaluated over a time course after treatment with the inhibitors, stimulated by heregulin, and studied using reverse phase protein array analysis. The results revealed that the decreased expression of pAkt (Thr308) appears to be a biomarker of sensitivity for LY294002 and BEZ235 in both PEO4 and A2780 cells, while upregulation of pAkt (Ser473) is an indicator for effective rapamycin treatment within the same cell lines. Increased pAkt (Ser473) expression after rapamycin treatment in PEO4 cells is believed to be due to the S6K1-mTORC2-Akt feedback loop. It was observed that pERK was upregulated upon BEZ235 treatment, which suggested the presence of cross talk between the PI3K/Akt/mTOR and MAPK pathways. A combination of BEZ235 and PD-0325901 (MEK inhibitor) treatments inhibited both pAkt (Ser473) and pERK, which also produced significant inhibition in cell proliferation compared to monotherapy treatment. The data also revealed a novel finding in ovarian cancer that prolonged (24h) treatment with rapamycin sensitises mTORC2 in PEO4 cells under heregulin stimulation. Moreover, network correlation and clustering analysis using the phosphoproteomic data identified significant correlations between the expression of pmTOR (Ser2481), and both p-cRaf (Ser259 and Ser338). Sin1 knockdown was performed in PEO4 cells and showed significant downregulation in the expression of pAkt (Ser473) and upregulation in pERK expression, indicating the role of Sin1 to regulate both the PI3K/Akt/mTOR and MAPK pathways potentially via mTORC2 and Ras. Phosphoproteomic profiling was performed on 469 ovarian cancer tissue samples using TMA and IHC analysis. Several significant associations were discovered between the phosphoproteomic data and the different clinicopathological parameters. High expression of pmTOR (Ser2448) was correlated with poorer overall survival in patients with ovarian endometrioid carcinoma compared to patients with low expression (p < 0.024). This implies that pmTOR (Ser2448) expression may potentially be a prognostic marker for patients with ovarian endometrioid carcinoma. In conclusion, I present dynamic phosphoproteomic profiling of the PI3K/Akt/mTOR and MAPK pathways in ovarian cancer, suggesting novel feedback loops and cross talk that could play a role in resistance mechanisms to these therapies. Combination treatment showed an additive effect on cell growth offering an approach to overcome drug resistance.