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Background  Prostate cancer (PCa) is the most common malignant male neoplasm in the American male population. Our prior studies have demonstrated that protein phosphatase 1 regulatory subunit 12A (PPP1R12A) could be an efficient prognostic factor in patients with PCa, promoting further investigation. The present study attempted to construct a gene signature based on PPP1R12A and metabolism-related genes to predict the prognosis of PCa patients.    Methods  The mRNA expression profiles of 499 tumor and 52 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. We selected differentially expressed PPP1R12A-related genes among these mRNAs. Tandem affinity purification-mass spectrometry was used to identify the proteins that directly interact with PPP1R12A. Gene set enrichment analysis (GSEA) was used to extract metabolism-related genes. Univariate Cox regression analysis and a random survival forest algorithm were used to confirm optimal genes to build a prognostic risk model.    Results  We identified a five-gene signature ( PPP1R12A ,  PTGS2 ,  GGCT ,  AOX1 , and  NT5E ) that was associated with PPP1R12A and metabolism in PCa, which effectively predicted disease-free survival (DFS) and biochemical relapse-free survival (BRFS). Moreover, the signature was validated by two internal datasets from TCGA and one external dataset from the Gene Expression Omnibus (GEO).    Conclusion  The five-gene signature is an effective potential factor to predict the prognosis of PCa, classifying PCa patients into high- and low-risk groups, which might provide potential novel treatment strategies for these patients.

frontiers in genetics

Identification and Validation of a PPP1R12A-Related Five-Gene Signature Associated With Metabolism to Predict the Prognosis of Patients With Prostate Cancer