|
Abstract:
|
The Precision Medicine Initiative (PMI) aims to develop effective disease prevention and treatment approaches that consider the unique context of each individual's genes, environment, and lifestyle. One of the first PMI projects is the NCI-Molecular Analysis for Therapy Choice (NCI-MATCH), which is a clinical trial that evaluates the effectiveness of matching each patient's molecular profiles in tumor samples with targeted therapies. There are many challenges in realizing the goals set out by PMI and the NCI-MATCH program. In this talk, we focus on the analysis of the data sets in the Cancer Cell Line Encyclopedia project, the Genomics of Drug Sensitivity in Cancer project, and some of the DREAM challenges, all with the shared goal of discovering therapeutic biomarkers from the molecular profiles and other information (e.g. pathways and genome annotations) that can be used to identify patients most likely to respond to certain anticancer drug and drug-combinations. We will focus statistical analyses and biological interpretations of these data and describe various approaches that have been developed to most effectively identify predictive biomarkers.
|
