Abstract 4690: Next-generation screen for integrative subtyping and target discovery for KRAS-mutant cancer

Mutations in the small GTPase, KRAS, are found in ∼140,000 new cases of cancer every year in the United States. This heterogeneous class of cancers manifests primarily as adenocarcinomas of the lung, colon and pancreas. These cancers display a wide spectrum of KRAS-dependency and differentially activate downstream effector signaling. The tumors further diverge in their array of co-occurring secondary mutations, expression signatures and KRAS mutant allele. Ultimately, the sole trait these cancers share in common is an obstinate resistance to chemo- and targeted-therapies, making identification of effective treatments an urgent need. To identify treatments for such a heterogeneous class of cancers, we developed a strategy to stratify KRAS-mutant cell lines into subtypes by integrating next-generation RNAi screening and “Omics” database mining. Each subtype is characterized by unique biomarkers and distinct patterns of effector dependency, both of which represent potential targets for personalized therapeutic strategies. Our RNAi screen systematically evaluates sensitivity to siRNA-mediated knockdown of 40 KRAS effector nodes in a panel of 135 lung, colorectal and pancreatic cancer cell lines. Data is analyzed on the single cell level, through the simultaneous measurement of 5 functional parameters. This single-cell, multi-dimensional approach allows for a comprehensive assessment of cellular homeostasis, with unprecedented depth and dynamic range that allows robust classification of cell lines by similarity. We identify subtypes of KRAS-mutant cell lines that rely on particular effector pathways such as the RAL, RSK, MTOR and autophagy pathways, which are not engaged by all KRAS-mutant cell lines, and thus may represent targets for personalized treatment. We further identify widely shared dependencies such as on the RAF, glycolytic and cell cycle pathways. Through integrative data mining of exome, transcriptome and drug/siRNA sensitivity databases for each KRAS-mutant subtype, we can identify unique biomarkers that will serve to stratify patients in the clinic and recommend personalized treatment strategies. Citation Format: Tina L. Yuan, Rachel Bagni, Ming Yi, Arnaud Amzallag, Shervin Afghani, Katie Beam, William Burgan, Nicole Fer, Leslie Garvey, Brian Smith, Andrew Waters, Robert Stephens, Cyril Benes, Frank McCormick. Next-generation screen for integrative subtyping and target discovery for KRAS-mutant cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4690. doi:10.1158/1538-7445.AM2015-4690