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Gege, C.

Publications and source records attributed to Gege, C..

2 recordsLinked to original sources

KDM6 Enzymes are the Mechanistic Targets of Mutant IDH that Dictate Replication Stress Sensitivity

Cancer-associated isocitrate dehydrogenase (IDH) mutations sensitize gliomas to replication stress, although the underlying mechanisms are unclear. IDH-mutant enzymes synthesize (R)-2-hydroxyglutarate (R2HG), which broadly inhibits 2-oxoglutarate-dependent enzymes. We performed forward genetic screens targeting all 2-oxoglutarate-dependent enzymes and discovered that KDM6 histone demethylases play a vital role in protecting cells from replication stress. Genetic or R2HG-mediated repression of KDM6 catalytic activity sensitized glioma cells to disparate replication stress-inducing drugs, including Ataxia-telangiectasia and Rad3-related (ATR) and dihydroorotate dehydrogenase (DHODH) inhibitors. This liability is generalizable because KDM6A loss-of-function mutations commonly observed in urothelial carcinomas sensitized bladder cancer cells to DHODH inhibition, thereby phenocopying IDH mutations in glioma. To exploit these oncogene-induced replication stress vulnerabilities, we developed an effective, on-target, and well-tolerated DHODH inhibitor, GLIO-1, that is poised for clinical translation. Collectively, we reveal KDM6 activity as a fundamental determinant of replication stress sensitivity and nominate pan-cancer, mechanism-based biomarkers of ATR and DHODH inhibitor efficacy. STATEMENT OF SIGNIFICANCEWe discovered that the KDM6 enzymes are the mechanistic targets of R2HG that mediate mutant IDH-induced replication stress hypersensitivity. We report a promising new DHODH inhibitor, GLIO-1, and nominate KDM6 and IDH mutations as predictive biomarkers for the antitumor effects of GLIO-1 and other replication stress inducers.

cancer biology↗

Finding New Molecular Targets of Familiar Natural Products Using In Silico Target Prediction

Natural products comprise a rich reservoir for innovative drug leads and are a constant source of bioactive compounds. To find pharmacological targets for new or already known natural products using modern computer-aided methods is a current endeavor in drug discovery. Natures treasures, however, could be used more effectively. Yet, reliable pipelines for large scale target prediction of natural products are still rare. We have developed an in silico workflow consisting of four independent, stand-alone target prediction tools and evaluated its performance on dihydrochalcones (DHCs) - a well-known class of natural products. Thereby, we revealed four previously unreported protein targets for DHCs, namely 5-lipoxygenase, cyclooxygenase-1, 17{beta}-hydroxysteroid dehydrogenase 3, and aldo-keto reductase 1C3. Moreover, we provide a thorough strategy on how to perform computational target prediction and guidance on using the respective tools.

bioinformatics↗