Abstract IA006: Reverse-engineering discovery of targets, involved cell types, and compounds for liver cancer chemoprevention


 Hepatocellular carcinoma (HCC) is a cancer type with clinically unequivocal and well-defined predisposing conditions, namely chronic fibrotic liver diseases caused by viral hepatitis and metabolic disorders. By following up the at-risk patient cohort, natural history of HCC development can be captured over the timeframe of one to two decades. Archived biospecimens are often available from the time of initial liver disease diagnosis, and unbiased molecular profiling of the specimens provides unique opportunities to interrogate molecular dysregulations confidently correlated with the real long-term clinical outcome, i.e., HCC development from early-stage liver diseases. This “reverse-engineering” strategy helps increase the likelihood of identifying clinically relevant therapeutic targets without solely relying on data from experimental preclinical models. This is particularly useful in cancer chemoprevention target discovery given the the requirement of overwhelmingly lengthy and costly clinical validation of experimentally derived candidate targets, which is often practically infeasible. Utilizing this strategy, we could successfully identify HCC chemoprevention targets (e.g., cellular signaling such as EGFR pathway, circulating bioactive lipids), involved cell types (e.g., hepatic myofibroblasts, conventional dendritic cells), and compounds (e.g., small molecular signaling pathway inhibitors, generic agents), streamline the process of their clinical validation, and facilitate translation of promising chemoprevention agents to the care of liver disease patients.
 Citation Format: Yujin Hoshida. Reverse-engineering discovery of targets, involved cell types, and compounds for liver cancer chemoprevention [abstract]. In: Proceedings of the Second Biennial NCI Meeting: Translational Advances in Cancer Prevention Agent Development (TACPAD); 2022 Sep 7-9. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_2): Abstract nr IA006.