Related Experiment Video
Updated: Jun 18, 2025
A Method for Screening and Validation of Resistant Mutations Against Kinase Inhibitors
Published on: December 7, 2014
Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning
Gabriella O Estevam1,2, Edmond M Linossi3,4, Jingyou Rao5
1Department of Bioengineering and Therapeutic Sciences, UCSF, San Francisco, CA, United States.
Abstract:
Mutations in the kinase and juxtamembrane domains of the MET Receptor Tyrosine Kinase are responsible for oncogenesis in various cancers and can drive resistance to MET-directed treatments. Determining the most effective inhibitor for each mutational profile is a major challenge for MET-driven cancer treatment in precision medicine. Here, we used a deep mutational scan (DMS) of ~5,764 MET kinase domain variants to profile the growth of each mutation against a panel of 11 inhibitors that are reported to target the MET kinase domain. We validate previously identified resistance mutations, pinpoint common resistance sites across type I, type II, and type I ½ inhibitors, unveil unique resistance and sensitizing mutations for each inhibitor, and verify non-cross-resistant sensitivities for type I and type II inhibitor pairs. We augment a protein language model with biophysical and chemical features to improve the predictive performance for inhibitor-treated datasets. Together, our study demonstrates a pooled experimental pipeline for identifying resistance mutations, provides a reference dictionary for mutations that are sensitized to specific therapies, and offers insights for future drug development.
Insights
This study profiles MET kinase domain mutations against 11 inhibitors to identify resistance and sensitivity patterns. Findings aid precision medicine by guiding targeted therapy selection for MET-driven cancers.
Area of Science:
- Oncology
- Molecular Biology
- Pharmacology
Background:
- Mutations in the MET Receptor Tyrosine Kinase (MET) drive oncogenesis and treatment resistance in various cancers.
- Identifying optimal MET-directed therapies based on specific mutation profiles is crucial for precision medicine.
Purpose of the Study:
- To comprehensively profile MET kinase domain variants against a panel of MET inhibitors.
- To identify resistance and sensitizing mutations for different inhibitor classes.
- To improve predictive models for inhibitor response in MET-driven cancers.
Main Methods:
- Deep mutational scanning (DMS) of ~5,764 MET kinase domain variants.
- Assessing mutation growth against 11 MET kinase domain inhibitors.
- Augmenting a protein language model with biophysical and chemical features for enhanced prediction.
Main Results:
- Validated known MET resistance mutations and identified common resistance sites across inhibitor types.
- Discovered unique resistance and sensitizing mutations specific to individual inhibitors.
- Verified non-cross-resistant sensitivities between type I and type II MET inhibitors.
- Improved predictive performance of a protein language model for inhibitor-treated datasets.
Conclusions:
- Established a pooled experimental pipeline for identifying MET resistance mutations.
- Generated a reference dictionary of mutations sensitive to specific MET-targeted therapies.
- Provided insights for developing next-generation MET inhibitors and personalized cancer treatments.
Related Concept Videos
02:56Treatment Resistant Cancers
01:20Mismatch Repair
The Mutator Protein Family Plays a Key Role in DNA Mismatch Repair
The human genome has more than 3 billion base pairs of DNA per cell. Prior to cell division, that vast amount of genetic...
02:30Metastasis
Epithelial-to-Mesenchymal Transition
The epithelial-to-mesenchymal transition or EMT is a developmental process commonly observed in wound healing, embryogenesis, and cancer metastasis. EMT is induced by transforming growth factor-beta (TGF-β) or receptor tyrosine kinase (RTK) ligands, which further...