Abstract P2-07-03: Systematic characterization of kinase inhibitors reveals heterogeneity in responses by class and cell line

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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 dose 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 transcript expression levels by mRNAseq, quantification of absolute abundance of ˜12,000 proteins, and relative phosphoprotein levels by shotgun mass spectrometry across all cell lines. Additionally, the baseline activity of transcription factors and kinases were inferred from the mRNA (using VIPER) and phosphoprotein (using kinase enrichment analysis) data, respectively. The complementarity of these multi-omics data has allowed us to address questions about the landscape of breast cancer cell lines such as: Where do the patient-derived lines lay relative to the conventional cell lines? How consistent are the landscapes defined by each dataset? How does integration across datasets provide mechanistic insight into signaling pathways that are active in each cancer subtypes? The measured and inferred baseline data were used to build predictors of the observed drug responses with the goal of identifying the biological processes responsible for the differences in sensitivity across drugs and cell lines. Overall the dataset that has been collected is a valuable resource for understanding drug response in triple negative breast cancer, and the molecular mechanisms that influence it. Citation Format: Mills CE, Subramanian K, Hafner M, Chung M, Boswell SA, Everley RA, Juric D, Sorger PK. Systematic characterization of kinase inhibitors reveals heterogeneity in responses by class and cell line [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-07-03.