KRAS mutation is enormous problem in oncology and results in hundreds of thousands of deaths from cancer each year. It plays a particularly relevant role in pancreatic ductal adenocarcinoma (PDA), where mutation of the KRAS gene is the cardinal genomic event in the vast majority of cases. The classical approach to developing a KRas drug, by outcompeting GTP in the active site, has failed, likely due to the high affinity of mutant KRas for GTP combined with mM GTP concentrations in the cell. Thus, new ideas, novel approaches and synergistic collaborations from lab bench to clinic are required to imagine the means by which we address KRAS mutant cancers therapeutically. The goal of this proposal is to discover, and eventually exploit genetic dependencies unique to KRAS mutant cancer cells. This goal builds on recently developed genetically defined mouse models of PDA, and cancer cell lines derived from them.
Our specific aims utilize strategically coupled steps, integrating an innovative use of murine shRNA libraries in cell lines from genetically engineered mice followed by validation in both human cell lines and in mouse models. Significantly, we anticipate the results will provide key mechanistic insights into KRas processing and signaling, and provide new targets molecules that mutant KRas requires for its oncogenic program.
KRas plays a key role in the development and progression of pancreatic cancer, meets all criteria as the central driver of the disease, but is not druggable by current medicinal chemistry techniques. Thus, this R21 looks to discover and describe genes that are required specifically for KRas (but not other driver oncogenes) to maintain pancreatic cancer growth and survival.
|Torphy, Robert J; Wang, Zhen; True-Yasaki, Aisha et al. (2018) Stromal Content Is Correlated With Tissue Site, Contrast Retention, and Survival in Pancreatic Adenocarcinoma. JCO Precis Oncol 2018:|
|Lu, Xinyuan; Peled, Nir; Greer, John et al. (2017) MET Exon 14 Mutation Encodes an Actionable Therapeutic Target in Lung Adenocarcinoma. Cancer Res 77:4498-4505|
|Hoadley, Katherine A; Yau, Christina; Wolf, Denise M et al. (2014) Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell 158:929-944|