Anticancer drug sensitivity prediction in cell lines from baseline gene expression through recursive feature selection.

ABSTRACT:

Background

An enduring challenge in personalized medicine is to select right drug for individual patients. Testing drugs on patients in large clinical trials is one way to assess their efficacy and toxicity, but it is impractical to test hundreds of drugs currently under development. Therefore the preclinical prediction model is highly expected as it enables prediction of drug response to hundreds of cell lines in parallel.

Methods

Recently, two large-scale pharmacogenomic studies screened multiple anticancer drugs on over 1000 cell lines in an effort to elucidate the response mechanism of anticancer drugs. To this aim, we here used gene expression features and drug sensitivity data in Cancer Cell Line Encyclopedia (CCLE) to build a predictor based on Support Vector Machine

SUBMITTER: Dong Z 

PROVIDER: S-EPMC4485860 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature