Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning

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 ~5764 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.

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Publication Details

Journal
eLife
Published
2024-10-28
DOI
https://doi.org/10.7554/elife.101882
Citations
12
Primary Topic
Melanoma and MAPK Pathways
Type
article
Field-Weighted Citation Impact
2.81

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article

Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning

Edmond M. Linossi, John A. Capra, Natalia Jura, Eric A. Collisson et al.
12 citations
eLife
Melanoma and MAPK Pathways
2.81
article

Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning

Edmond M. Linossi, John A. Capra, Natalia Jura, Eric A. Collisson, Gabriella O. Estevam, Ashraya Ravikumar, James S. Fraser, Willow Coyote‐Maestas, Christian B. Macdonald, Harold Pimentel, J. N. K. Rao, Karson M Chrispens
article en
12 citations

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 ~5764 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.

eLifeVol. 13
Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa (ZA), University of California, Los Angeles (US), University of California, San Francisco (US), University of Washington (US), Fred Hutch Cancer Center (US), Quantitative BioSciences (US)
Howard Hughes Medical Institute, Sandler Foundation, National Institutes of Health, University of California, San Francisco, National Cancer Institute, National Institute of General Medical Sciences
Good health and well-being
Openalex Percentile: Top 9%
Melanoma and MAPK Pathways
2.81
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