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

Abhinav Achreja1,2,3,4, Tao Yu5, Anjali Mittal1,3,6

  • 1Laboratory for Systems Biology of Human Diseases, University of Michigan, Ann Arbor, MI, USA.

Nature Metabolism
|September 21, 2022
PubMed

Insights

Researchers identified a new method to find collateral lethal genes, revealing MTHFD2 as a target in ovarian tumors with UQCR11 deletions. Inhibiting MTHFD2 led to complete tumor remission, offering a promising new cancer therapy.

Area of Science:

  • Oncology
  • Metabolic Engineering
  • Genomics

Background:

  • Tumour suppressor gene deletions can co-occur with essential gene loss, creating dependencies on functional paralogues.
  • Identifying these collateral lethal genes is crucial for developing targeted cancer therapies, but no methodology currently exists.

Purpose of the Study:

  • To develop a novel framework for identifying collateral lethal genes using metabolic fluxes.
  • To uncover MTHFD2 as a collateral lethal gene in ovarian tumours with UQCR11 deletions.

Main Methods:

  • Developed the Collateral Lethal Gene Identification via Metabolic fluxes (CLIM) framework.
  • Utilized machine learning and genome-scale metabolic flux analysis.
  • Validated findings through in vivo experiments and MTHFD2 inhibition.

Main Results:

  • Identified MTHFD2 as a collateral lethal gene in UQCR11-deleted ovarian tumours.
  • Demonstrated MTHFD2's non-canonical oxidative function in providing mitochondrial NAD+.
  • Confirmed that MTHFD2 inhibition leads to complete remission of UQCR11-deleted ovarian tumours in vivo.

Conclusions:

  • The CLIM framework effectively identifies collateral lethal genes.
  • Targeting MTHFD2 shows broad efficacy in UQCR11-deleted ovarian cancers, regardless of genetic background or tumour stroma.
  • This discovery presents a promising new therapeutic strategy for ovarian cancer.

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