Identifying Drug Sensitivity Subnetworks with NETPHIX

About this Class

Abstract: Phenotypic heterogeneity in cancer is often caused by different patterns of genetic alterations. Understanding such phenotype-genotype relationships is fundamental for the advance of personalized medicine. In this talk, I will present a computational method, named NETPHIX (NETwork-to-PHenotype association with eXclusivity) to identify subnetworks of genes whose genetic alterations are associated with drug response or other continuous cancer phenotypes. Leveraging interaction information among genes and properties of cancer mutations such as mutual exclusivity, we model the problem as a variant of connected set cover and obtain a subnetwork of associated genes using integer linear program (ILP) optimization. Applied to a large-scale drug screening dataset, NETPHIX uncovered gene modules significantly associated with responses for many drugs. We show that the identified modules provide important insights into drug action and can also be leveraged to suggest drug combinations. Bio: Dr. Yoo-Ah Kim is a staff scientist in the National Center for Biotechnology Information at National Institutes of Health (NCBI/NLM/NIH). Her current research focuses on algorithmic approaches in cancer network biology. Before joining NIH in 2008, she received her PhD degree in Computer Science from the University of Maryland, College Park in 2005 and was with the CSE department at the University of Connecticut, working on combinatorial optimization and graph algorithms.