{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T12:14:52Z","timestamp":1788524092637,"version":"build-2803163510"},"reference-count":37,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Pharmacol."],"abstract":"<jats:p>\n                    Lung adenocarcinoma (LUAD) remains molecularly heterogeneous, and many tumors lack clearly tractable vulnerabilities. We developed DepPrior, a computational framework that ranks candidate LUAD therapeutic targets by requiring concordant evidence of CRISPR dependency separability, molecular predictability, and cross-cohort expression\/protein reproducibility. DepMap dependency scores were modeled from matched expression and copy-number features using linear and non-linear learners, and gene-level AUROC and R\n                    <jats:sup>2<\/jats:sup>\n                    were combined into a heuristic DepScore. The final candidate set included FERMT2, CRKL, MYC, CHMP4B and related genes. The set formed a coherent tumor expression module in TCGA-LUAD, was strongly associated with proliferation-linked features, and showed rank-based concordance across GEO transcriptomic cohorts and CPTAC transcriptomic\/proteomic resources. Five-fold cross-validation supported the ranking of non-linear models, although performance gains were moderate and should be interpreted as model-ranking evidence rather than as large effect-size proof. Orthogonal experiments in HCC827 cells showed modest but reproducible protein-level reductions after FERMT2 and CRKL knockdown, accompanied by a directionally stronger apoptosis-associated protein shift after combined suppression than after single perturbation. These findings support DepPrior as a reproducibility-oriented, hypothesis-generating approach for target nomination. Because cross-cohort expression concordance does not prove patient-tumor dependency conservation, and experimental validation was restricted to selected genes and cell-line systems without rescue or proliferation\/clonogenic assays, the prioritized genes should be considered candidates for further perturbation, rescue, patient-derived model, and therapeutic tractability studies.\n                  <\/jats:p>","DOI":"10.3389\/fphar.2026.1859926","type":"journal-article","created":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T05:34:19Z","timestamp":1787808859000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["DepPrior: integrating CRISPR dependency predictability with multi-omics reproducibility to prioritize candidate LUAD therapeutic targets"],"prefix":"10.3389","volume":"17","author":[{"given":"Feng","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Thoracic Surgery, Changde First People\u2019s Hospital","place":["Changde, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, Changde First People\u2019s Hospital","place":["Changde, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lizhi","family":"Mo","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, Changde First People\u2019s Hospital","place":["Changde, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, Changde First People\u2019s Hospital","place":["Changde, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ji","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, Changde First People\u2019s Hospital","place":["Changde, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,27]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"920","DOI":"10.1016\/j.ccell.2022.08.011","article-title":"Clinical application of advanced multi-omics tumor profiling: shaping precision oncology of the future","volume":"40","author":"Akhoundova","year":"2022","journal-title":"Cancer Cell"},{"key":"B2","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1038\/s41586-018-0409-3","article-title":"Genetic and transcriptional evolution alters cancer cell line drug response","volume":"560","author":"Ben-David","year":"2018","journal-title":"Nature"},{"key":"B3","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate: a practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. R. Stat. Soc. Ser. B"},{"key":"B4","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/a:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"B5","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1145\/2939672.2939785","article-title":"XGBoost: a scalable tree boosting system","volume-title":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","author":"Chen","year":"2016"},{"key":"B6","doi-asserted-by":"publisher","first-page":"608","DOI":"10.1158\/2159-8290.CD-11-0046","article-title":"Amplification of CRKL induces transformation and epidermal growth factor receptor inhibitor resistance in human non\u2013small cell lung cancers","volume":"1","author":"Cheung","year":"2011","journal-title":"Cancer Discovery"},{"key":"B7","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/bf00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"B8","doi-asserted-by":"publisher","first-page":"1317","DOI":"10.21105\/joss.01317","article-title":"ifelines: survival analysis in Python","volume":"4","author":"Davidson-Pilon","year":"2019","journal-title":"J. Open Source Softw."},{"key":"B9","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1097\/JTO.0000000000000042","article-title":"Validation of a histology-independent prognostic gene signature for early-stage, non\u2013small-cell lung cancer including stage IA patients","volume":"9","author":"Der","year":"2014","journal-title":"J. Thoracic Oncology"},{"key":"B10","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1038\/s41586-023-06563-x","article-title":"Large-scale plasma proteomics comparisons through genetics and disease associations","volume":"622","author":"Eldjarn","year":"2023","journal-title":"Nature"},{"key":"B11","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy function approximation: a gradient boosting machine","volume":"29","author":"Friedman","year":"2001","journal-title":"Ann. Statistics"},{"key":"B12","first-page":"4193","article-title":"Inhibition of Myc effectively targets KRAS mutation-positive lung cancer expressing high levels of Myc","volume":"30","author":"Fukazawa","year":"2010","journal-title":"Anticancer Res."},{"key":"B13","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1186\/s13073-016-0333-9","article-title":"The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine","volume":"8","author":"Garofalo","year":"2016","journal-title":"Genome Medicine"},{"key":"B14","doi-asserted-by":"publisher","first-page":"762","DOI":"10.1038\/s41591-024-02805-1","article-title":"MYC targeting by OMO-103 in solid tumors: a phase 1 trial","volume":"30","author":"Garralda","year":"2024","journal-title":"Nat. Medicine"},{"key":"B15","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s10994-006-6226-1","article-title":"Extremely randomized trees","volume":"63","author":"Geurts","year":"2006","journal-title":"Mach. Learn."},{"key":"B16","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1038\/s41586-019-1186-3","article-title":"Next-generation characterization of the cancer cell line encyclopedia","volume":"569","author":"Ghandi","year":"2019","journal-title":"Nature"},{"key":"B17","doi-asserted-by":"publisher","first-page":"18708","DOI":"10.1073\/pnas.1111840108","article-title":"Redefining the relevance of established cancer cell lines to the study of mechanisms of clinical anti-cancer drug resistance","volume":"108","author":"Gillet","year":"2011","journal-title":"Proc. Natl. Acad. Sci."},{"key":"B18","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/j.cell.2020.06.013","article-title":"Proteogenomic characterization reveals therapeutic vulnerabilities in lung adenocarcinoma","volume":"182","author":"Gillette","year":"2020","journal-title":"Cell"},{"key":"B19","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1007\/s12022-014-9345-4","article-title":"The cancer genome atlas research network: a sight to behold","volume":"25","author":"Giordano","year":"2014","journal-title":"Endocr. Pathol."},{"key":"B20","doi-asserted-by":"publisher","first-page":"e3000999","DOI":"10.1371\/journal.pbio.3000999","article-title":"We need to keep a reproducible trace of facts, predictions, and hypotheses from gene to function in the era of big data","volume":"18","author":"Kasif","year":"2020","journal-title":"PLoS Biol."},{"key":"B21","doi-asserted-by":"publisher","first-page":"1397","DOI":"10.1016\/j.ccell.2023.06.009","article-title":"Proteogenomic data and resources for pan-cancer analysis","volume":"41","author":"Li","year":"2023","journal-title":"Cancer Cell"},{"key":"B22","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1038\/s41576-020-0247-7","article-title":"Discovering and validating cancer genetic dependencies: approaches and pitfalls","volume":"21","author":"Lin","year":"2020","journal-title":"Nat. Rev. Genet."},{"key":"B23","doi-asserted-by":"publisher","first-page":"e1006701","DOI":"10.1371\/journal.pcbi.1006701","article-title":"New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx","volume":"15","author":"Mounir","year":"2019","journal-title":"PLoS Computational Biology"},{"key":"B24","doi-asserted-by":"publisher","first-page":"1661","DOI":"10.1038\/s41467-021-21898-7","article-title":"Integrated cross-study datasets of genetic dependencies in cancer","volume":"12","author":"Pacini","year":"2021","journal-title":"Nat. Communications"},{"key":"B25","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1016\/j.ccell.2023.12.016","article-title":"A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization","volume":"42","author":"Pacini","year":"2024","journal-title":"Cancer Cell"},{"key":"B26","first-page":"2825","article-title":"Scikit-learn: machine learning in python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"B27","doi-asserted-by":"publisher","first-page":"829","DOI":"10.1056\/NEJMoa1704795","article-title":"Alectinib versus crizotinib in untreated ALK-positive non\u2013small-cell lung cancer","volume":"377","author":"Peters","year":"2017","journal-title":"N. Engl. J. Med."},{"key":"B28","doi-asserted-by":"publisher","first-page":"1900278","DOI":"10.1002\/pmic.201900278","article-title":"Comparison of proteomic assessment methods in multiple cohort studies","volume":"20","author":"Raffield","year":"2020","journal-title":"Proteomics"},{"key":"B29","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1056\/NEJMoa1913662","article-title":"Overall survival with osimertinib in untreated, EGFR-mutated advanced NSCLC","volume":"382","author":"Ramalingam","year":"2020","journal-title":"N. Engl. J. Med."},{"key":"B30","volume-title":"Lung-MAP (SWOG S1400): Design, Implementation, and Lessons Learned from a biomarker-driven Master Protocol (BDMP) for previously-treated Squamous Lung Cancer (sqNSCLC)","author":"Redman","year":"2020"},{"key":"B31","doi-asserted-by":"publisher","first-page":"3209","DOI":"10.1038\/onc.2015.375","article-title":"Differential association of STK11 and TP53 with KRAS mutation-associated gene expression, proliferation and immune surveillance in lung adenocarcinoma","volume":"35","author":"Schabath","year":"2016","journal-title":"Oncogene"},{"key":"B32","doi-asserted-by":"publisher","first-page":"1176","DOI":"10.1038\/s43018-024-00789-y","article-title":"Building a translational cancer dependency map for The Cancer Genome Atlas","volume":"5","author":"Shi","year":"2024","journal-title":"Nat. Cancer"},{"key":"B33","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1016\/j.ccm.2011.08.005","article-title":"Pathology of lung cancer","volume":"32","author":"Travis","year":"2011","journal-title":"Clin. Chest Medicine"},{"key":"B34","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1016\/j.cell.2017.06.010","article-title":"Defining a cancer dependency map","volume":"170","author":"Tsherniak","year":"2017","journal-title":"Cell"},{"key":"B35","doi-asserted-by":"publisher","first-page":"3574","DOI":"10.1038\/s41467-019-11415-2","article-title":"Comprehensive transcriptomic analysis of cell lines as models of primary tumors across 22 tumor types","volume":"10","author":"Yu","year":"2019","journal-title":"Nat. Communications"},{"key":"B36","doi-asserted-by":"publisher","first-page":"1226","DOI":"10.1038\/s41467-021-21254-9","article-title":"Uniform genomic data analysis in the NCI Genomic Data Commons","volume":"12","author":"Zhang","year":"2021","journal-title":"Nat. Communications"},{"key":"B37","doi-asserted-by":"publisher","first-page":"1206","DOI":"10.1016\/S1470-2045(23)00444-8","article-title":"Global variations in lung cancer incidence by histological subtype in 2020: a population-based study","volume":"24","author":"Zhang","year":"2023","journal-title":"Lancet Oncol."}],"container-title":["Frontiers in Pharmacology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fphar.2026.1859926\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T11:26:16Z","timestamp":1788521176000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fphar.2026.1859926\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,27]]},"references-count":37,"alternative-id":["10.3389\/fphar.2026.1859926"],"URL":"https:\/\/doi.org\/10.3389\/fphar.2026.1859926","relation":{},"ISSN":["1663-9812"],"issn-type":[{"value":"1663-9812","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,27]]},"article-number":"1859926"}}