{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T12:32:13Z","timestamp":1763123533310,"version":"3.45.0"},"reference-count":61,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T00:00:00Z","timestamp":1763078400000},"content-version":"vor","delay-in-days":317,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81902617","82272896"],"award-info":[{"award-number":["81902617","82272896"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2021A1515012322"],"award-info":[{"award-number":["2021A1515012322"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Human Mutation"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Prostate cancer (PCa) ranks among the most prevalent malignancies, with prognosis heavily influenced by diagnostic stage. The role of PANoptosis in T cell\u2010based immunotherapy has garnered growing attention recently. This study is aimed at establishing a T cell\u2010specific PANoptosis signature (TSPS) to predict prognosis and immunotherapy response in patients with PCa.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Single\u2010cell RNA sequencing (scRNA\u2010seq) data from the GSE185344 dataset were used to identify T cell\u2010specific genes. A comprehensive machine learning pipeline incorporating 10 distinct algorithms was employed to construct a consensus prognostic TSPS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The scRNA\u2010seq analysis identified T cells as the predominant cell type, and cell\u2013cell communication analysis indicated heightened activation of specific immune\u2010related signaling pathways in PCa. A consensus prognostic signature comprising nine key genes was developed, demonstrating superior predictive accuracy for clinical outcomes compared to conventional clinical variables. A TSPS\u2010based nomogram was also constructed, displaying strong predictive capability for survival outcomes in patients with PCa. Patients in the high\u2010risk group exhibited greater intratumor heterogeneity, increased immune infiltration, and higher immunosuppression scores, suggesting reduced immunotherapy benefits. Validation with four independent immunotherapy cohorts verified that patients in the low\u2010risk group exhibited more favorable immunotherapy responses. Additionally, 18 compounds were determined as therapeutic options for high\u2010risk patients with PCa. In vitro experiments demonstrated that\n                      <jats:italic>UBB<\/jats:italic>\n                      expression was upregulated in PCa, and\n                      <jats:italic>UBB<\/jats:italic>\n                      knockdown significantly inhibited PCa cell proliferation and invasion.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We established a consensus prognostic TSPS for PCa, offering a potential foundation for future personalized approaches in risk stratification, prognostic evaluation, and treatment selection for patients with PCa.<\/jats:p>\n                  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