Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines
Year: 2014
Type: article
Abstract: We demonstrate a method for the prediction of chemotherapeutic response in patients using only before-treatment baseline tumor gene expression data. First, we fitted models for whole-genome gene expression against drug sensitivity in a large panel of cell lines, using a method that allows every gene to influence the prediction. Following data homogenization and filtering, these models were applied to baseline expression levels from primary tumor biopsies, yielding an in vivo drug sensitivity prediction. We validated this approach in three independent clinical trial datasets, and obtained predictions equally good, or better than, gene signatures derived directly from clinical data.
Source: Genome biology
Authors: Paul Geeleher, Nancy J Cox, R Stephanie Huang
Institution: University of Chicago
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,490
Awards: Genome-wide interrogation of genetic signatures for glucocorticoid sensitivity, Incorporation of microRNA expression in pharmacogenetic prediction models, Translational Research at The University of Chicago (UL1), PAAR-Pharmacogenomics of Anticancer Agents Research Group, SPORE in Breast Cancer, Cancer Center Support Grant
OpenAlex ID: W2018663224