A Landscape of Pharmacogenomic Interactions in Cancer

Abstract

SummarySystematic studies of cancer genomes have provided unprecedented insights into the molecular nature of cancer. Using this information to guide the development and application of therapies in the clinic is challenging. Here, we report how cancer-driven alterations identified in 11,289 tumors from 29 tissues (integrating somatic mutations, copy number alterations, DNA methylation, and gene expression) can be mapped onto 1,001 molecularly annotated human cancer cell lines and correlated with sensitivity to 265 drugs. We find that cell lines faithfully recapitulate oncogenic alterations identified in tumors, find that many of these associate with drug sensitivity/resistance, and highlight the importance of tissue lineage in mediating drug response. Logic-based modeling uncovers combinations of alterations that sensitize to drugs, while machine learning demonstrates the relative importance of different data types in predicting drug response. Our analysis and datasets are rich resources to link genotypes with cellular phenotypes and to identify therapeutic options for selected cancer sub-populations.

Prognostic, predictive, and pharmacogenomic assessments of CDX2 refine stratification of colorectal cancer

“…(Iorio et al ., 2016). Based on mRNA expression, 16/46 (35%) cell lines were scored as CDX2‐negative.…”

“…For drug sensitivity validation analyses, gene expression data and natural‐log‐transformed IC50 drug sensitivity values were retrieved from http://www.cancerrxgene.org/downloads (Iorio et al ., 2016) (accessed on April 3, 2017).…”

A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination prediction

“…We also acquired deep molecular characterization of these same cell lines, including somatic mutations, copy-number alterations, DNA methylation, and gene expression profiles (Fig. 1A-C) measured before drug treatment 11 .…”

“…Synergy was commonly assigned to compound pairs targeting directly downstream of a mutated, amplified or over-expressed oncogenic driver, particularly those associated with monotherapy activity. To systematically test the association of monotherapy predictive biomarkers to combination synergy, we focused on Cancer Gene Census genes 11 for whom at least three of the 85 cell lines harbored genetic variants. The resulting 148 genes (45 mutated and 103 copy number altered) were then systematically tested for their association to monotherapy response of the 118 compounds (averaging replicates) across the 85 cell lines.…”

“…Mutations -Mutations were called with CAVEMAN 42 and PINDEL 43 as reported in 11 . Variants were provided without further filtering, including putative passenger mutations, germline variants and potential cell line artefacts, which are in total 75,281 mutations in 85 cell lines.…”