Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies.

ABSTRACT: Obtaining accurate drug response data in large cohorts of cancer patients is very challenging; thus, most cancer pharmacogenomics discovery is conducted in preclinical studies, typically using cell lines and mouse models. However, these platforms suffer from serious limitations, including small sample sizes. Here, we have developed a novel computational method that allows us to impute drug response in very large clinical cancer genomics data sets, such as The Cancer Genome Atlas (TCGA). The approach works by creating statistical models relating gene expression to drug response in large panels of cancer cell lines and applying these models to tumor gene expression data in the clinical data sets (e.g., TCGA). This yields an imputed drug response for every drug in each patient. These imputed

SUBMITTER: Geeleher P 

PROVIDER: S-EPMC5630037 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature