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Sourav Bandyopadhyay, PhD
Assistant Professor, Department of Bioengineering and Therapeutic Sciences, Helen Diller Family Comprehensive Cancer Center, UCSF
Connecting tumor genomics with therapeutics through multi-dimensional network modules
Wednesday, June 28
3:30 — 4:30 PM
Engineering 2 – Room 506
Abstract
Recent efforts have catalogued genomic, transcriptomic, epigenetic and proteomic changes in tumors, but understanding their functional impact remains a challenge. Determining which events are relevant in model systems requires new methods of data integration to identify a common set of pathways and molecular events. Using MAGNETIC, a new method to integrate molecular profiling data using functional networks, we identify 219 gene modules in TCGA breast cancers that capture recurrent alterations, reveal new roles for H3K27 tri-methylation and accurately quantitate various cell types within the tumor microenvironment. This modular analysis reveals that a significant portion of gene expression and methylation in tumors is poorly reproduced in cell lines due to differences in biology and microenvironment. This approach identifies modules that can be used to predict drug responses that are robust to differences between tumors and cell lines and therefore more clinically relevant. This work addresses a fundamental challenge in pharmacogenomics that can only be overcome by the joint analysis of patient and cell line data.
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