We then used the candidate genes in conjunction with an external dataset [The Cancer Genome Atlas prostate adenocarcinoma (TCGA-PRAD)] to produce a minimal 5-gene expression signature (PCBP1, PABPN1, PTPRF, DANCR, and MYC) using the least absolute shrinkage and selection operator (LASSO) and Cox regression methods to predict PFS. The gene discussed is PABPN1; the disease is prostate adenocarcinoma.