| Literature DB >> 36131208 |
Abhinav Achreja1,2,3,4, Tao Yu5, Anjali Mittal1,3,6, Srinadh Choppara1,2,3, Olamide Animasahun1,3,6, Minal Nenwani1,2,3, Fulei Wuchu1,2,3, Noah Meurs1,2,3, Aradhana Mohan1,2,3, Jin Heon Jeon1,2,3, Itisam Sarangi1,2,3, Anusha Jayaraman1,2,3, Sarah Owen3,6, Reva Kulkarni1,7, Michele Cusato4,8, Frank Weinberg9, Hye Kyong Kweon10, Chitra Subramanian3,4, Max S Wicha4,11, Sofia D Merajver4,11, Sunitha Nagrath3,4,6, Kathleen R Cho4,8,12, Analisa DiFeo4,8,12, Xiongbin Lu13,14,15, Deepak Nagrath16,17,18,19,20.
Abstract
Recurrent loss-of-function deletions cause frequent inactivation of tumour suppressor genes but often also involve the collateral deletion of essential genes in chromosomal proximity, engendering dependence on paralogues that maintain similar function. Although these paralogues are attractive anticancer targets, no methodology exists to uncover such collateral lethal genes. Here we report a framework for collateral lethal gene identification via metabolic fluxes, CLIM, and use it to reveal MTHFD2 as a collateral lethal gene in UQCR11-deleted ovarian tumours. We show that MTHFD2 has a non-canonical oxidative function to provide mitochondrial NAD+, and demonstrate the regulation of systemic metabolic activity by the paralogue metabolic pathway maintaining metabolic flux compensation. This UQCR11-MTHFD2 collateral lethality is confirmed in vivo, with MTHFD2 inhibition leading to complete remission of UQCR11-deleted ovarian tumours. Using CLIM's machine learning and genome-scale metabolic flux analysis, we elucidate the broad efficacy of targeting MTHFD2 despite distinct cancer genetic profiles co-occurring with UQCR11 deletion and irrespective of stromal compositions of tumours.Entities:
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Year: 2022 PMID： 36131208 DOI： 10.1038/s42255-022-00636-3
Source DB: PubMed Journal: Nat Metab ISSN： 2522-5812