In this study, to predict the BCR of PCa patients, we proposed to (1) construct a multi-protein-based signature and nomogram that combined clinicopathological variables to predict the prognosis of BCR for PCa patients, (2) validate predictive ability using time-dependent receiver operating characteristic (ROC) curves, calibration plots, concordance index (C-index), and decision curve analysis (DCA), (3) perform GO (Gene Ontology) pathway enrichment analyses and Gene Set Enrichment Analysis (GSEA) to investigate biological functions that are involved. The gene discussed is BCR; the disease is posterior cortical atrophy.