Abstract PR16: Targeting cancer-specific kinase dependency for precision therapy

Abstract

Abstract Precision/ personalized cancer therapy based on clinical sequencing is premised on the identification of genomic aberrations in actionable therapeutic targets. Protein kinases represent the most accessible therapeutic targets across cancers, albeit only very small subsets of cancers harbor canonical targetable aberrations in kinases. Considering that kinases represent the predominant drivers of oncogenesis, functioning directly or downstream of other oncogenic aberrations, we hypothesize that most cancers harbor distinct “kinase dependencies” and thus provide a potent therapeutic avenue in individual cancers. Here, we test the hypothesis that the kinase(s) that display an “off the chart” Outlier Expression in individual cancer samples, impart a dependency on growth and survival that can be exploited therapeutically. Analyzing RNA-Seq data from a compendium of 482 cancer and benign samples belonging to 25 different tissue types we defined 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 in breast cancer included known therapeutic targets like ERBB2 and FGFR4, 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 optimizing ex vivo culture of tumor tissues from surgical resections that will be used to test combinations of therapeutics including outlier kinase inhibitors. This abstract is also presented as Poster B21. Citation Format: Vishal Kothari, Wei Iris, Sunita Shankar, Shanker Kalyana-Sundaram, Lidong Wang, Linda W. Ma, Pankaj Vats, Catherine S. Grasso, Dan R. Robinson, Yi-Mi Wu, Xuhong Cao, Diane M. Simeone, Arul M. Chinnaiyan, Chandan Kumar-Sinha. Targeting cancer-specific kinase dependency for precision therapy. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Synthetic Lethal Approaches to Cancer Vulnerabilities; May 17-20, 2013; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(5 Suppl):Abstract nr PR16.