Abstract 2385: Systematic characterization of kinase inhibitors reveals heterogeneity in responses by class and cell line

Abstract

Abstract Several publications have addressed concerns surrounding drug response screens by pointing out sources of variability and by presenting recommendations for better experimental methods and more robust analytical approaches. In the presented profiling effort, we integrated the latest advances in drug response measurement and focused on data diversity and quality rather than on breadth. We selected 32 breast cancer cell lines with a strong bias towards triple negative lines as well as 4 cell lines established from relevant patient-derived xenografts. We evaluated a panel of clinically relevant kinase inhibitors using a microscopy-based drug response assay to measure drug potency, and to quantify drug efficacy in terms of growth inhibition (GR metrics) and cell death. The use of the GR metrics to quantify drug sensitivity enabled us to identify and study differences between cytostatic and cytotoxic responses. This systematic dose response dataset is complemented by measurements of baseline mRNA expression levels by RNAseq and endogenous protein levels by shotgun mass spectrometry across all cell lines. The completeness and controlled conditions under which these data sets were collected provide confidence in their integration. The baseline RNA and protein expression levels were used to build predictors of the measured drug responses with the goal of identifying the biological processes responsible for the differences in sensitivity across drugs and cell lines. Differences in the phenotypic responses of cell lines to kinase inhibitors with the same nominal targets have been investigated, and associated with variable inhibitor polypharmacology. Citation Format: Caitlin E. Mills, Marc Hafner, Dejan Juric, Peter K. Sorger. Systematic characterization of kinase inhibitors reveals heterogeneity in responses by class and cell line [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2385. doi:10.1158/1538-7445.AM2017-2385