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Title: Molecular genetic etiology of ovarian cancer
Author: Lancaster, Johnathan Mark
ISNI:       0000 0004 2747 4257
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2005
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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.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available