1. Academic Validation
  2. Metabolic collateral lethal target identification reveals MTHFD2 paralogue dependency in ovarian cancer

Metabolic collateral lethal target identification reveals MTHFD2 paralogue dependency in ovarian cancer

  • Nat Metab. 2022 Sep;4(9):1119-1137. doi: 10.1038/s42255-022-00636-3.
Abhinav Achreja  # 1 2 3 4 Tao Yu  # 5 Anjali Mittal 1 3 6 Srinadh Choppara 1 2 3 Olamide Animasahun 1 3 6 Minal Nenwani 1 2 3 Fulei Wuchu 1 2 3 Noah Meurs 1 2 3 Aradhana Mohan 1 2 3 Jin Heon Jeon 1 2 3 Itisam Sarangi 1 2 3 Anusha Jayaraman 1 2 3 Sarah Owen 3 6 Reva Kulkarni 1 7 Michele Cusato 4 8 Frank Weinberg 9 Hye Kyong Kweon 10 Chitra Subramanian 3 4 Max S Wicha 4 11 Sofia D Merajver 4 11 Sunitha Nagrath 3 4 6 Kathleen R Cho 4 8 12 Analisa DiFeo 4 8 12 Xiongbin Lu 13 14 15 Deepak Nagrath 16 17 18 19 20
Affiliations

Affiliations

  • 1 Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA.
  • 2 Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
  • 3 Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA.
  • 4 Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA.
  • 5 Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
  • 6 Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.
  • 7 Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, USA.
  • 8 Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
  • 9 Hematology and Oncology, University of Illinois, Chicago, IL, USA.
  • 10 Department of Biological Chemistry, University of Michigan, Ann Arbor, MI, USA.
  • 11 Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
  • 12 Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, USA.
  • 13 Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA. [email protected].
  • 14 Melvin & Bren Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA. [email protected].
  • 15 Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA. [email protected].
  • 16 Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA. [email protected].
  • 17 Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA. [email protected].
  • 18 Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA. [email protected].
  • 19 Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA. [email protected].
  • 20 Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA. [email protected].
  • # Contributed equally.
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.

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