Next March 02 at 12 am it will take place the seminar "Multi-omic analysis of subtype evolution and heterogeneity in high-grade serous ovarian carcinoma" by Levi Waldron from Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, Institute for Implementation Science in Population Health, City University of New York. New York, USA.

Abstract

High-grade serous ovarian carcinoma (HGSOC) is characterized by widespread genomic alteration, limited treatment options, and poor prognosis. Studies of bulk transcriptome profiles have identified gene expression-based subtypes of high-grade serous ovarian carcinoma (HGSOC) as a basis for targeted therapy. However it remains unclear the extent to which these subtypes are reflections of the tumor microenvironment, and whether divergence occurs early or late in tumorigenesis. We employ a novel approach using recurrent copy number lesions as approximate markers of subtype, in conjunction with clonality analysis of those lesions, to infer the evolutionary timing of transcriptome subtype divergence in The Cancer Genome Atlas HGSOC cases. We complement multi'omic analysis of bulk tumors with single-cell RNA-seq analysis of six tumors. The results refute an "intrinsic subtype" model of HGSOC evolution, but instead support a development in which tumors develop from an early differentiated spectrum to a late proliferative spectrum, along a timeline characterized by increasing genomic instability and subclonal expansion, along with changes in immune and stromal infiltration. This model explains ambiguity in subtype classification as the result of assigning discrete, mutually exclusive subtypes to a genomically complex process of tumor evolution, and highlights that any targeted therapies should target early events in tumor evolution. Finally, this presentation outlines curated public databases and analysis methods developed in R/Bioconductor to enable this and related analyses.