{"doi":"10.7554/elife.101882","title":"Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning","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.","journal":"eLife","year":2024,"id":484300,"datarank":0.3958585994422889,"base_score":2.639057329615259,"endowment":2.639057329615259,"self_citation_contribution":0.3958585994422889,"citation_network_contribution":0.0,"self_endowment_contribution":0.3958585994422889,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":13,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.92,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":755669,"name":"Edmond M. Linossi","orcid":"0000-0002-8039-573X","position":1,"is_corresponding":false},{"id":1186893,"name":"J. N. K. Rao","orcid":"0000-0002-4331-8786","position":2,"is_corresponding":false},{"id":347894,"name":"Christian B. Macdonald","orcid":"0000-0002-0201-8832","position":3,"is_corresponding":false},{"id":1042627,"name":"Ashraya Ravikumar","orcid":"0000-0002-4902-4025","position":4,"is_corresponding":false},{"id":1220484,"name":"Karson M Chrispens","orcid":"0000-0002-2115-3132","position":5,"is_corresponding":false},{"id":258343,"name":"John A. Capra","orcid":"0000-0001-9743-1795","position":6,"is_corresponding":false},{"id":690634,"name":"Willow Coyote‐Maestas","orcid":"0000-0001-9614-5340","position":7,"is_corresponding":false},{"id":78901,"name":"Harold Pimentel","orcid":"0000-0001-8556-2499","position":8,"is_corresponding":false},{"id":20519,"name":"Eric A. Collisson","orcid":"0000-0001-8037-9388","position":9,"is_corresponding":false},{"id":1485,"name":"Natalia Jura","orcid":"0000-0001-5129-641X","position":10,"is_corresponding":false},{"id":63530,"name":"James S. Fraser","orcid":"0000-0002-5080-2859","position":11,"is_corresponding":false},{"id":1071837,"name":"Gabriella O. Estevam","orcid":"0000-0002-9142-7805","position":0,"is_corresponding":true}],"reference_count":83,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:07:38.055693Z","pmid":"39960754","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}