Background: Prostate cancer recurrence following radical prostatectomy (RP) affects 30-50% of men within 10 years, yet existing biomarkers show variable prognostic performance.Pathway-level approaches may offer additional prognostic insight by capturing coordinated biological processes.We applied Reactome-based pathway enrichment to tumor transcriptomes to identify biological processes associated with time to biochemical recurrence (BCR).Methods: This retrospective cohort study included 55 patients with intermediate-to high-risk prostate cancer who underwent RP at a tertiary academic medical center with available postoperative PSA follow-up (minimum 5 years unless BCR or death occurred earlier).RNA sequencing was performed on prostatectomy-derived tumor specimens.Reactome pathway enrichment analysis was conducted using ReactomePA (version 1.50.0)within the clusterProfiler framework.Cox proportional hazards-derived gene statistics, adjusted for age, sample batch, and grade group, were used as ranked input.Pathways were evaluated by normalized enrichment score (NES) with false discovery rate (FDR) adjustment.Results: BCR occurred in 30 of 55 patients (55%).Positively enriched pathways associated with shorter time to BCR included epigenetic silencing (PRC2-mediated histone methylation, DNA methylation), extracellular matrix (ECM) organization, neutrophil degranulation, and defective pyroptosis.Negatively enriched pathways associated with longer recurrence-free intervals included RNA processing, nonsense-mediated decay, and peptide elongation.Pathway clustering revealed distinct functional modules corresponding to epigenetic regulation, innate immune signaling, and translational control.Conclusions: Reactome-based pathway enrichment identifies coordinated programs involving epigenetic regulation, innate immune signaling, extracellular matrix organization, and RNA/translational processes associated with biochemical recurrence following radical prostatectomy.These findings support the potential utility of pathway-level transcriptomic analysis for identifying biologically relevant processes and provide a framework for future validation studies in prostate cancer.
Davis et al. (Thu,) studied this question.