Kevin Eng

Department of Biostatistics and Medical Informatics

UW-Madison

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Advanced-stage epithelial ovarian cancer is the leading cause of death due to gynecological malignancy and, unlike other cancers, the five-year survival rate has remained relatively constant for the last 30 years. This mortality is attributable to heterogeneous disease, frequent recurrence and acquired chemoresistance, all of which complicate the attempt to improve treatment outcomes and to generate models of the disease.

In the main, I will discuss a number of hypotheses derived from our analysis of the Cancer Genome Atlas' ovarian pilot project, a multi-modal and high-throughput molecular survey. Our focus on patterns of expression in frequently-mutated "core" signaling pathways motivates statistical models that profile individual disease, correlate with response to drug therapies and promise individual prognosis. Two shorter vignettes will discuss our early results from studies of specific pathways/mechanisms and developing statistical models of the clinical disease management process.