Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data.

ABSTRACT:

Motivation

Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make results difficult to interpret.

Results

We developed Kinase Addiction Ranker (KAR), an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells. We applied KAR to predict kinase dependency of 21 lung cancer cell lines and 151 leukemia patient samples using published datasets. We exper

SUBMITTER: Ryall KA 

PROVIDER: S-EPMC4675831 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature