Re-using public data to resolve the nature of ovarian cancer molecular subtypes

April 7th 2016
Versione stampabile

Venue: Edificio Povo 2, via Sommarive nr. 9, Povo (Tn) - Room B101
 At 2:00 p.m.

  • Levi Waldron​ -  Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY

Ovarian cancer is a molecularly heterogeneous disease in which the majority of patients present clinically similar disease, but can exhibit dramatically different response to treatment.  Several major studies have reported to describe part of this heterogeneity as molecular subtypes based on gene expression, while others have been unable to do so. This study helps resolve the nature of ovarian cancer molecular subtypes by two approaches: 1) assessing the robustness and association to patient outcome by comparative meta-analysis using all relevant publicly available data, and 2) determining the likely chronology of subtype differentiation in tumor evolution by analysis of allele frequencies of subtype-associated DNA short variants in data from The Cancer Genome Atlas (TCGA). I will also discuss our work developing Bioconductor infrastructure to simplify the representation and analysis of multi-assay -omics experiments, and to provide integrated datasets for key publicly available cancer -omics projects such as the TCGA.