{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T22:28:59Z","timestamp":1773786539563,"version":"3.50.1"},"reference-count":32,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T00:00:00Z","timestamp":1764201600000},"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. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Prostate cancer (PCa) ranks as the second most common malignancy in men worldwide. While serum prostate-specific antigen (PSA) is routinely monitored, its low specificity frequently leads to overdiagnosis. Cytokines within the tumor microenvironment (TME) demonstrate strong tumor-progression associations, but their combined predictive utility with PSA for metastasis and chemotherapy response remains undetermined. This study aimed to quantify cross-sectional differences in pre-treatment cytokine levels based on metastatic status, assess their prognostic value for biochemical progression-free survival in metastatic patients, and characterize cytokine profiles from baseline to biochemical recurrence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We retrospectively analyzed 328 PCa patients (175 metastatic, 153 non-metastatic), collecting data on age, smoking history, Gleason score, total PSA (TPSA), and cytokines. Metastasis-associated factors were identified by Spearman correlation and logistic regression. Prognostic models were evaluated using ROC curves\/AUC analysis. Multi index combination was used to find the best prognostic group.Survival analysis employed Kaplan-Meier methodology, while Cox regression assessed post-chemotherapy PSA rebound predictors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>We find that smoking, TPSA, and IL-8 emerged as independent metastasis risk factors. Prognostic indices PRE1 (smoking, TPSA, IL-8) and PRE2 (all significant factors) achieved AUCs of 0.788 and 0.787 respectively, with PRE1 demonstrating superior calibration. The AUC of TPSA+IL-6+IL-8+IL-10 four factor combination was 0.753, and this combination yielded high prognostic performance, and the proportion of metastasis group was significantly higher than that of non-metastasis group. Univariate Cox analysis associated age, TPSA, IL-6, IL-8, and TNF-\u03b1 with PSA rebound, though multivariate analysis identified no independent predictors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>These results underscore the immunological relevance of specific cytokines in PCa progression and their potential as complementary biomarkers to PSA for improving risk stratification.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2025.1686570","type":"journal-article","created":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T07:06:01Z","timestamp":1764227161000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Pre\u2212treatment cytokines plus TPSA predict biochemical progression\u2212free survival in prostate cancer metastasis and discriminate metastatic status: a retrospective 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