{"doi":"10.1038/s42003-021-02636-7","title":"Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets","abstract":"Identifying genomic alterations of cancer proteins has guided the development of targeted therapies, but proteomic analyses are required to validate and reveal new treatment opportunities. Herein, we develop a new algorithm, OPPTI, to discover overexpressed kinase proteins across 10 cancer types using global mass spectrometry proteomics data of 1,071 cases. OPPTI outperforms existing methods by leveraging multiple co-expressed markers to identify targets overexpressed in a subset of tumors. OPPTI-identified overexpression of ERBB2 and EGFR proteins correlates with genomic amplifications, while CDK4/6, PDK1, and MET protein overexpression frequently occur without corresponding DNA- and RNA-level alterations. Analyzing CRISPR screen data, we confirm expression-driven dependencies of multiple currently-druggable and new target kinases whose expressions are validated by immunochemistry. Identified kinases are further associated with up-regulated phosphorylation levels of corresponding signaling pathways. Collectively, our results reveal protein-level aberrations-sometimes not observed by genomics-represent cancer vulnerabilities that may be targeted in precision oncology.","journal":"Communications Biology","year":2021,"id":7234,"datarank":0.517639902917994,"base_score":2.8903717578961645,"endowment":2.8903717578961645,"self_citation_contribution":0.4335557636844247,"citation_network_contribution":0.08408413923356926,"self_endowment_contribution":0.4335557636844247,"citer_contribution":0.08408413923356926,"corpus_percentile":null,"corpus_rank":null,"citation_count":17,"citer_count":8,"citers_with_citation_signal":4,"citers_with_endowment":4,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0455,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-09-22","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":39897,"name":"Serena Tharakan","orcid":"0000-0001-5188-2099","position":1,"is_corresponding":false},{"id":16367,"name":"Suraj K. Jaladanki","orcid":"0000-0003-0406-2973","position":2,"is_corresponding":false},{"id":65065,"name":"Matthew D. Galsky","orcid":"0000-0001-7655-9378","position":3,"is_corresponding":false},{"id":23356,"name":"Tao Liu","orcid":"0000-0002-8818-8313","position":4,"is_corresponding":false},{"id":1998,"name":"Kuan-lin Huang","orcid":"0000-0002-3237-4248","position":5,"is_corresponding":false},{"id":2334,"name":"Abdülkadir Elmas","orcid":"0000-0002-7999-5770","position":0,"is_corresponding":true}],"reference_count":45,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"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":[]}