A gene feature based on histone modifications can predict the prognosis of prostate cancer

Abstract

Abstract Background: Prostate cancer (PCa) is one of the most common malignant tumors in males, with a high recurrence rate and poor prognosis. Therefore, accurately predicting the prognosis of PCa patients and intervening as early as possible is of great significance. We aimed to establish a gene feature model based on histone modifications to predict the prognosis of patients with PCa after radical prostatectomy. Methods: Clinical data on PCa patients was obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) public databases and was comprehensively evaluated. Expression subtypes of histone-modifying factors were identified by unsupervised clustering, and the molecular characteristics and functions of each subtype were explored. Subsequently, a risk-scoring model was constructed to characterize its impact on the prognosis of PCapatients. Results: Combined with histone modification factor signatures, we identified four PCa subtypes with different prognoses, biological functions, and mutational characteristics. Based on a series of analysis and screening, 21 characteristic genes (MXD3, CCDC28B, COL11A2, SLC39A5, GPT, DNASE1L2, PIF1, KRTAP5-9, TTLL10, KRTAP5-1, KRTAP5-10, HAGHL, MSLNL, AMH, NKAIN4, CCDC114, SLC9A3, SULT1E1, SLC6A14, ALB, and RPE65) were used to establish a risk score model (HIS_score). Patients in the high-score group had worse outcomes than those in the low-score group. Additionally, we found that the HIS_score model can distinguish subgroups of PCa samples with different biological and immune characteristics. Conclusions: The HIS_score model with 21 genes as features is a promising tool that is of great significance for clinicians to predict the prognosis of PCa patients after radical prostatectomy and develop personalized treatment plans early.