Four plasma proteins associated with mortality in UK Biobank prostate cancer cohort

Four circulating plasma proteins—growth differentiation factor 15 (GDF15), tenascin C (TNC), tumor necrosis factor receptor superfamily member 10B (TNFRSF10B) and ribonucleotide reductase regulatory subunit M2 (RRM2)—were most strongly associated with post-baseline all-cause mortality among 353 men with prostate cancer in a UK Biobank analysis. The study abstract reports 113 all-cause deaths, including 36 deaths attributed to prostate cancer, during follow-up. These findings identify candidate mortality-associated protein signals; they do not establish that the proteins cause death or are ready for clinical use.

Researchers selected participants with available baseline plasma proteomic data and identified candidate proteins using multivariable Cox regression with adjustment across multiple models, Bonferroni correction and bootstrap stability assessment. The criterion for bootstrap stability was a coefficient of variation below 20%. Robustness testing included 200 bootstrap resampling iterations, with full proteome-wide screening and Bonferroni correction repeated in each resample; proteins were then prioritized by their final reselection frequency. Restricted cubic spline, landmark, time-window and cross-sectional analyses of post-baseline residual survival were used to examine the key protein–mortality associations. Exploratory risk-estimation models were assessed with internal validation and bootstrap optimism correction, while all preprocessing and model-fitting steps were conducted within each bootstrap training sample.

The composite model combined the four proteins with available clinical and selected covariates and produced the highest internally validated discrimination. Its area under the curve for predicting 15-year all-cause mortality was 0.7835 (95% confidence interval, 0.7303–0.8265). This represented a 6.77-percentage-point increase over the baseline covariate model; the difference had a 95% confidence interval of 1.84 to 10.63 percentage points and a reported P value of 0.01. The abstract also states that the model had acceptable calibration and a higher estimated net benefit in decision-curve analysis. Those internal performance results require confirmation in external cohorts before the model’s clinical usefulness can be evaluated.

Exploratory competing-risk analyses identified galanin (GAL), prokineticin 1 (PROK1) and guanylate-binding protein 2 (GBP2) as proteins associated with prostate-cancer-specific mortality. Their relationships with death varied in nonlinearity and in cross-sectional baseline patterns by the time from baseline to prostate-cancer-specific death. The authors characterized these findings as hypothesis-generating because only 36 prostate-cancer-specific deaths were recorded. Mechanistic analyses in the study included protein–protein interaction networks, pathway enrichment, module construction, mediation analysis, module interaction and module-combination survival analysis. The investigators proposed that death receptor–mediated immune apoptosis, extracellular-matrix remodeling and replication-stress-related mechanisms may be involved, but the evidence presented in the abstract supports associations rather than causal effects. Overall, the analysis concerns prevalent prostate cancer in a UK Biobank cohort and requires external validation; it is not evidence that measuring these proteins can currently improve patient care.

Subject of Research: Plasma protein associations with mortality in men with prostate cancer

Article Title: Candidate plasma proteins associated with all-cause mortality among patients with prostate cancer: a UK biobank analysis

Article References: Gao, L., Chen, Y., Feng, P., Zhang, C., Hu, J., Zheng, Z., Shi, G., Li, S., Wang, L., Yan, X., Wu, B., & Cao, X. (2026). Candidate plasma proteins associated with all-cause mortality among patients with prostate cancer: a UK biobank analysis. BMC Cancer. https://doi.org/10.1186/s12885-026-16972-6

Image Credits: AI Generated

DOI: 10.1186/s12885-026-16972-6

Keywords: prostate cancer, plasma proteomics, all-cause mortality, UK Biobank, GDF15, TNC, TNFRSF10B, RRM2, prognostic modeling, Candidate, plasma, proteins