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Existing approaches often rely on cohort-specific model fitting, limiting cross-dataset comparability and downstream biological interpretation. We developed a cross-cohort projection framework that maps baseline clinical variables to a clinically anchored latent risk coordinate, $\\mu$, enabling application across external datasets without refitting. The fixed projector was trained in a local imaging cohort and applied unchanged to independent cohorts. Projected $\\mu$ was evaluated across multiple molecular layers, including bulk transcriptomics, single-cell-guided deconvolution, spatial transcriptomics, and circulating cell-free DNA (cfDNA). In an independent external cohort, projected $\\mu$ preserved separation of time to castration resistance across predefined strata (P\u00a0=\u2009.002), with 30-month risk increasing from 0.13 to 0.86 across ordered $\\mu$ bins. In bulk transcriptomics, higher projected $\\mu$ was associated with increased proliferation-related signaling and reduced androgen receptor\/lineage programs ($\\rho$ = 0.40 and \u22120.26; both P\u00a0&amp;lt;\u2009.001). Deconvolution analyses linked higher projected $\\mu$ to reduced AR-high epithelial cell fractions ($\\rho$ = \u22120.17, P\u00a0=\u2009.001). Spatial transcriptomics demonstrated organized tissue-level structure of prespecified molecular programs. In cfDNA, higher projected $\\mu$ was associated with a more negative RB1 copy-number signal in the detectable subset ($\\rho$ = \u22120.49, P\u00a0=\u2009.0278). This study presents a projection-based framework for cross-cohort translation of clinically anchored latent risk into interpretable multi-omics context. By enabling reuse of a fixed coordinate without refitting, the approach provides a practical strategy for linking clinical risk to molecular programs and blood-based readouts across datasets.<\/jats:p>","DOI":"10.1093\/bib\/bbag423","type":"journal-article","created":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T11:51:41Z","timestamp":1784116301000},"source":"Crossref","is-referenced-by-count":0,"title":["Cross-cohort projection of clinically anchored latent risk enables multi-omics interpretation without refitting"],"prefix":"10.1093","volume":"27","author":[{"given":"Zhongfu","family":"Huang","sequence":"first","affiliation":[{"name":"Department of Urology, Disorders of Prostate Cancer Multidisciplinary Team, National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University , No. 87 Xiangya Road, Kaifu District, Changsha, Hunan 410008 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\u00a0","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0998-8943","authenticated-orcid":false,"given":"Shuo","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of PET Center, National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University , No. 87 Xiangya Road, Kaifu District, Changsha, Hunan 410008 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongxiang","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of PET Center, National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University , No. 87 Xiangya Road, Kaifu District, Changsha, Hunan 410008 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