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Updated: Jan 26, 2026

An In Vitro Approach to Study Mitochondrial Dysfunction: A Cybrid Model
Published on: March 9, 2022
Metabolomics reveals tepotinib-related mitochondrial dysfunction in MET-activating mutations-driven models
Michaela Poliaková1,2, Andrea Felser3, Katarzyna Pierzchala4
1Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Switzerland.
MET signaling drives cancer metabolism. Inhibiting MET with tepotinib alters metabolites and mitochondrial function, indicating efficacy in sensitive cancer cells and suggesting new biomarkers for anti-MET therapies.
Area of Science:
- Oncology
- Molecular Biology
- Cancer Metabolism
Background:
- Genetic aberrations in the MET receptor tyrosine kinase drive oncogenic addiction in various human cancers.
- MET is a viable target for anticancer therapies.
- MET signaling influences cellular metabolic phenotypes.
Purpose of the Study:
- To investigate the role of MET signaling in cancer cell metabolism.
- To characterize the metabolic alterations induced by MET inhibition.
- To identify potential early biomarkers for MET-targeted therapy efficacy.
Main Methods:
- Utilized cellular models with MET-activating mutations (sensitive and resistant to inhibitors).
- Administered the MET inhibitor tepotinib and assessed cell viability, apoptosis, and metabolic profiles via metabolite ion analysis.
- Performed functional assays including oxygen consumption rate, citrate synthase activity, and mitochondrial membrane potential measurements.
Main Results:
- Tepotinib treatment decreased viability and increased apoptosis in sensitive cells.
- MET inhibition led to significant reductions in amino sugar, gluconeogenesis, glycine/serine, and TCA cycle metabolites.
- Sensitive cells exhibited decreased oxygen consumption, reduced citrate synthase activity, and impaired mitochondrial function.
Conclusions:
- MET signaling significantly impacts cancer cell metabolism.
- Altered metabolic signatures and mitochondrial dysfunction are early indicators of effective MET inhibition.
- Metabolic changes observed could serve as predictive biomarkers for anti-MET therapies.
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