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In this study, we propose CPCG (Cancer Prognosis\u2019s Causal Gene), a two-stage framework identifying gene sets causally associated with patient prognosis across diverse cancer types using transcriptomic data. Initially, an ensemble approach models gene expression\u2019s impact on survival with parametric and semiparametric hazard models. Subsequently, an iterative conditional independence test combined with graph pruning is utilized to infer the causal skeleton, thereby pinpointing prognosis-related genes. Experiments on transcriptomic data from 18 cancer types sourced from The Cancer Genome Atlas Project demonstrate CPCG\u2019s effectiveness in predicting prognosis under four evaluation metrics. Validations on 24 additional datasets covering 12 cancer types from the Gene Expression Omnibus and the Chinese Glioma Genome Atlas Project further demonstrate CPCG\u2019s robustness and generalizability. CPCG identifies a concise but reliable set of genes, obviating the need for gene combination enumeration for survival time estimation. These genes are also proved closely linked to crucial biological processes in cancer. Moreover, CPCG constructs a stable causal skeleton and exhibits insensitivity to the order of data shuffling. Overall, CPCG is a powerful tool for extracting cancer prognostic biomarkers, offering interpretability, generalizability, and robustness. CPCG holds promise for facilitating targeted interventions in clinical treatment strategies.<\/jats:p>","DOI":"10.1093\/bib\/bbae721","type":"journal-article","created":{"date-parts":[[2025,1,14]],"date-time":"2025-01-14T13:45:01Z","timestamp":1736862301000},"source":"Crossref","is-referenced-by-count":1,"title":["Identifying cancer prognosis genes through causal learning"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-4737-0774","authenticated-orcid":false,"given":"Siwei","family":"Wu","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Jilin University , 3003 Qianjin Street, 130012 Changchun ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaoyi","family":"Yin","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Jilin University , 3003 Qianjin Street, 130012 Changchun 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