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Five machine learning algorithms (LASSO, RSF, SVM\u2010RFE, Boruta, and XGBoost) were used to identify biomarkers for PCa using transcriptome data from multicenters (TCGA, MSKCC, DKFZ, and GSE70770) for constructing and validating the metastasis\u2010associated prognostic risk score (MAPRS), which revealed the molecular biological heterogeneity\u00a0and was confirmed with in\u2010house histopathological samples. The pathomics score (PSpc), derived from a machine learning framework (XGBoost, RSF, GBM, plsRCox, CoxBoost, Enet, Ridge, LASSO, SVM, and superPC) using hematoxylin and eosin (H&amp;E)\u2010stained digital pathology, quantified tumor morphological heterogeneity. The MAPRS correlated with poorer recurrence\u2010free survival (RFS) and was associated with the tumor microenvironment and pathogenic variants. A higher MAPRS may indicate sensitivity to treatments such as PARP inhibitors, docetaxel, and oxaliplatin. Pathology\u2010based evaluations of MAPRS, PSpc, and their combination effectively predicted RFS in patients who underwent RP. MAPRS also predicted progression\u2010free survival in patients receiving androgen deprivation therapy when combined with clinical indicators, whereas PSpc demonstrated limited efficacy. The digital pathology\u2010based signatures showed superior predictive efficacy compared to other tools.<\/jats:p><jats:p><jats:bold>Trial Registration:<\/jats:bold> Chinese Clinical Trial Registry number: ChiCTR2400085748 (June 18, 2024).<\/jats:p>","DOI":"10.1111\/cas.70149","type":"journal-article","created":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T03:44:42Z","timestamp":1752810282000},"page":"2893-2906","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Prognostic and Predictive Value of Machine Learning\u2010Based Biomarker and Pathomics Signatures in Patients With Prostate Cancer"],"prefix":"10.1111","volume":"116","author":[{"given":"Jianpeng","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Urology The First Affiliated Hospital of Guangzhou Medical University  Guangzhou China"},{"name":"Guangdong Provincial Key Laboratory of Urology  Guangzhou China"},{"name":"Guangdong 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