Molecular genetic etiology of ovarian cancer

Ovarian cancer is the fifth leading cause of cancer death among women in Western Europe and the United States and has the highest mortality rate of all gynecologic cancers. Approximately 75% of cases of epithelial ovarian carcinoma are diagnosed at advanced-stage (III/IV) with disseminated intra-peritoneal metastases, such that the majority of patients succumb to the disease within 5 years. Mortality from the disease has changed little over the last several decades. Despite such dismal statistics, our understanding of the molecular etiology that underlies ovarian cancer development, progression and response to therapy remains incomplete. The recent development of DNA microarrays enables the simultaneous measurement of expression of thousands of genes in a single sample, providing a molecular phenotyping not evident by traditional clinical, molecular or histopathologic methods. This thesis outlines the characterization of genome-wide expression patterns that underlie ovarian cancer development and metastasis, as well as clinical behavior relating to likelihood of optimal surgical resection, response to chemotherapy, and ultimate survival. Individual genes that contribute to the expression profiles are analysed further to delineate their specific role in ovarian cancer development and progression. Additionally, the contribution of a low penetrance polymorphic allele in the progesterone receptor gene as a risk factor for the development of the disease is examined in a large population-based case-control trial. Our data suggest that microarray analysis can facilitate the characterization of the molecular basis to ovarian cancer development, metastasis, and response therapy. Specific genes identified in this analysis represent not only potential biomarkers for the presence and clinical behavior of ovarian cancers, but appealing therapeutic targets. Our findings suggest that gene-expression profiles can be developed that can be applied in the clinic to not only provide prognostic information, but predict response to specific chemotherapeutic agents, enabling treatments to be tailored to individual patients with ovarian cancer

Micro-RNA profiles associated with endometrial cancer development and response to cisplatin and doxorubicin chemotherapy

A method predicting of cancer chemoresponse of the population of cancer cells to the one or more chemotherapeutic agents. Our ability to treat patients with advanced stage and recurrent endometrial cancer is hampered by an incomplete understanding of the molecular basis of disease development and response to therapy. A novel class of gene products called microRNA (miRNA) has recently been implicated in the etiology of several different human cancers. Altered levels of expression of specific miRNAs may contribute to cancer development in a variety of cancers such as endometrial cancer and may also influence response to cytotoxic chemotherapy or other cancer treatments. Evidence is provided that differential expression of miRNAs contributes to endometrial carcinogenesis and further associates with sensitivity of endometrial cancer cells to various chemotherapeutic agents including cisplatin and doxorubicin chemotherapy. MiRNA profiles and their gene targets show promise as biomarkers of endometrial cancer chemo-response, and as a novel class of therapeutic targets for patients with endometrial cancer

Cancer platinum resistance detection and sensitization method

The phosphorylation status of the BAD protein is a determinant of ovarian cancer cell responsiveness to platinum chemotherapy. Indirect manipulation of BAD phosphorylation status influences cisplatin sensitivity. BAD phosphorylation represents a biomarker that predicts platinum sensitivity and is a therapeutic target to increase platinum sensitivity. The methods employ phospho-specific antibody against a particular amino acid residue or site. Phospho-specific protein characterization methods include immunohistochemical (IHC), flow cytometric, immunofluorescent, capture-and-detection, or reversed phase assay

Luminescence characterization of quantum dots conjugated with biomarkers for early cancer detection

Luminescent semiconductor quantum dots (QDs) conjugated with biomolecules to serve as sensitive probes for early detection of the cancer cells, specifically for ovarian cancer and lung cancer, which represents the most lethal malignancies. The luminescence characterization of the bin-conjugated QDs with cancer specific antigens using linkage molecules. Photo-enhancement is measured at various laser density power, temperatures and laser wavelengths