Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines.

Geeleher P, Cox NJ, Huang RS
Genome Biol. 2014 15 (3): R47

PMID: 24580837 · PMCID: PMC4054092 · DOI:10.1186/gb-2014-15-3-r47

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.

MeSH Terms (14)

Algorithms Antineoplastic Agents Biomarkers, Tumor Breast Neoplasms Carcinoma, Non-Small-Cell Lung Cell Line, Tumor Drug Resistance, Neoplasm Female Gene Expression Regulation, Neoplastic Genome, Human Humans Models, Genetic Multiple Myeloma Predictive Value of Tests

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