Project 2. A systems-metabolism approach to identify mitochondria-dependent vulnerabilities in colorectal cancer
Co-Leads and Co-Investigators
Harrison Distinguished Teaching Professor of Biomedical Engineering
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Research
Mutant KRAS is a potent oncogene that drives proliferation and adaptive cell-state changes in multiple cancer types. One direct consequence of active KRAS signaling is fragmentation of the normal mitochondrial network with concomitant decreases in oxidative phosphorylation and mitochondrial membrane potential. The impact of this organelle stress is unclear in colorectal cancer, where KRAS mutations are acquired late in the disease and only in about one-third of cases. Primary tumors develop amidst short-chain fatty acids (SCFAs) and other metabolites uniquely produced by the gut flora, creating carbon sources that may impact how mid-stage colorectal cancers (CRC) adapt to an acquired KRAS mutation. Non-obvious mechanisms exist at the systems level that may cause an even greater metabolic impairment than generic decreases in oxidative phosphorylation or mitochondrial membrane potential. The hypothesis of Project 2 is that mitochondrial fragmentation causes hyper-compartmentalization of key low-abundance metabolic enzymes that constrains how primary tumors evolve in the presence of SCFAs and colonize the liver where metabolic inputs are very different. The specific aims are to 1) curate a metabolic model of human CRC cells that incorporates the system-wide impact of mitochondrial fragmentation and the availability of microbe-derived SCFAs; 2) instantiate metabolic models of CRC with data characterizing in vivo metabolic states to assess impacts of gut microbiota metabolism and mitochondrial fragmentation; and 3) evaluate the impact of metabolic adaptations to mitochondrial organelle stress on CRC colonization and growth as liver metastases. Metabolic circuits isolated by mitochondrial fission could give rise to tumor cell biochemistry that is very different from the universal roadmap assumed in most standard genome-wide metabolic network reconstructions.
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