The molecular basis of cancer has advanced considerably over the past decade. There are now many drugs that benefit cancer patients by targeting specific, cancer promoting mutations. The clinical testing of patient tumors to detect which mutations are present is now a routine part of cancer patient care. Continued advances in this area will require extending the knowledge of which specific mutations promote cancer, and also which mutations are indicative of likely benefit from a cancer drug. The proposed research combines emerging computational and experimental approaches to address fundamental problems in the biology of cancer promoting mutations and their response to anti-cancer agents. This proposal builds upon graduate school and post-doctoral research that combined computational and experimental approaches to study oncogenic RAS GTPases, and it builds upon postdoctoral research that combines computational and experimental approaches to the study of EGFR and RAF kinases, genomic medicine, and targeted therapies.
Three specific aims will be pursued that build upon this foundation and will establish the applicant as an independent investigator working on cancer systems biology. These are: (1) The experimental testing of computational predictions for why colorectal cancer patients with different oncogenic KRAS mutations respond differently to anti-cancer agents. Modeling also suggests an approach for identifying which KRAS mutants indicate patients who will benefit from the treatment. (2) The experimental testing of novel computational predictions for the role of Kinase Suppressor of Ras in regulating RAS and RAF signals. (3) A combined computational and experimental approach to decipher mechanisms that regulate BRAF kinase activation and influence its response to anti-cancer BRAF inhibitors. I hypothesize that the mechanisms of RAF regulation are much better defined by existing data than traditional methods of analysis have revealed, and I will use a novel computational approach to reanalyze these data and elucidate mechanisms of RAF regulation. The model will also be experimentally validated for its ability to predict the behaviors of RAF mutants found in cancer. The candidate is an M.D., Ph.D. with residency training in Clinical Pathology. His goal is to obtain a position as a physician scientist with at least 80% of his effort dedicated to his research program in cancer systems biology and genomic medicine. These studies will help allow the applicant to transition to independent principal investigator in the field of cancer systems biology and genomic medicine and will provide the foundation for a continued research program in this important, emerging, area of cancer medicine.
Cancer develops from an accumulation of mutations to the DNA, some of which result in proteins with abnormal functions that promote cancer. Drugs that target cancer- promoting mutations have proven beneficial to cancer patients. The proposed research combines novel computational approaches with well-established experimental methods to investigate problems in how common, cancer-promoting, mutations promote cancer and influence the response to anti-cancer agents.