Protein kinases represent a most effective class of therapeutic targets in cancer cells, and potent inhibitors of oncogenic kinases including ABL, AKT, ALK, AURKs, BRAF, CDKs, EGFR, ERBB2, FGFRs, KIT, MAPKs, MET, PIK3CA, PLKs, RET, SRC, S6Ks, and VEGFR are in clinical use, trials, or development. Presence of activating mutations, gene fusions or copy number amplification of many of these kinases predict responsiveness to specific inhibitors, for example, imatinib for BCR-ABL-positive chronic myeloid leukemia, trastuzumab and lapatinib for ERBB2-amplified breast cancers, gefitinib for lung cancers with kinase domain mutations in EGFR, and crizotinib for lung cancers with ALK gene fusions. However, tumors with defined kinase aberrations represent a very small proportion of all cancers, and we hypothesize that potentially most, if not all, cancers are dependent on specific kinases, and that “Outlier Expression” of specific kinases in individual samples may be indicative of selection during clonal evolution, and thus may represent a therapeutic avenue. To explore this hypothesis, we analyzed RNA-sequencing data from a compendium of 482 cancer and benign samples belonging to 25 different tissue types to define sample-specific ‘kinome’ expression profiles. Comparing the expression of kinases within a sample and across sample sets, we identified distinct ‘outlier kinases’ in individual samples, defined as genes showing the highest statistically significant levels of absolute and differential expression. Frequently observed outlier kinases included known therapeutic targets like ERBB2 and FGFR4 in breast cancer, distinct from MET, AKT2, and PLK2 in pancreatic cancer. Outlier kinases imparted sample-specific dependencies in various cell lines as assessed by siRNA knockdown or pharmacologic inhibition in vitro and in vivo. Outlier expression of polo-like kinases (PLKs) observed in a subset of KRAS-dependent pancreatic cancer cell lines conferred increased sensitivity to the PLK inhibitor BI 6727. Together, our results suggest that outlier kinases represent effective personalized therapeutic targets that are readily identifiable through RNA-sequencing of tumors. Next, to help translate these observations into treatment options, we are attempting to establish 3D tumoroid cultures from tumor samples that can be used to optimize combinations of therapeutics including outlier kinase inhibitors.

Citation Format: Chandan Kumar-Sinha, Vishal Kothari, Iris Wei, Sunita Shankar, Shanker Kalyana-Sundaram, Lidong Wang, Linda W. Ma, Pankaj Vats, Catherine Grasso, Dan Robinson, Yi-Mi Wu, Xuhong Cao, Diane M. Simeone, Arul M. Chinnaiyan. Sample specific outlier kinase expression identified by RNA-Seq provide targets for precision therapy. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3136. doi:10.1158/1538-7445.AM2013-3136