A Gene Feature Based on Histone Modifications Can Predict the Prognosis of Prostate Cancer

Background/Objectives: Prostate cancer (PCa) remains a prevalent malignancy among men, often complicated by recurrence and unfavorable clinical outcomes. Consequently, precise risk stratification and timely clinical intervention are paramount. Initially, we delineated distinct expression profiles of histone modification regulators via unsupervised clustering, identifying PCa subtypes with divergent survival probabilities and biological phenotypes. Subsequently, we sought to develop a prognostic gene signature, derived from the transcriptomic variations among these regulator-defined subtypes, to predict outcomes in PCa patients following radical prostatectomy (RP). Methods: Clinical and transcriptomic data from PCa cohorts were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories for comprehensive analysis. Subtypes driven by histone modification regulators were established using unsupervised consensus clustering, followed by in-depth characterization of their molecular features and associated pathways. A risk-scoring model was then developed to evaluate its prognostic efficacy in this patient population. Results: Stratification based on histone modification regulators yielded four distinct PCa subtypes exhibiting heterogeneous survival outcomes, functional pathways, and genomic mutational landscapes. Following rigorous feature selection, a 21-gene risk signature (HIS_score)—comprising MXD3, CCDC28B, COL11A2, SLC39A5, GPT, DNASE1L2, PIF1, KRTAP5-9, TTLL10, KRTAP5-1, KRTAP5-10, HAGHL, MSLNL, AMH, NKAIN4, CCDC114, SLC9A3, SULT1E1, ALB, SLC6A14, and RPE65—was constructed. Survival analyses demonstrated that patients assigned to the high HIS_score cohort experienced significantly worse clinical outcomes compared to their low-score counterparts. Furthermore, we integrated this signature into a novel clinical nomogram to facilitate individualized prognostic assessments. Conclusions: Derived from transcriptomic disparities between extreme epigenetic subtypes, the HIS_score and its associated nomogram serve as robust prognostic instruments. These tools effectively encapsulate the downstream transcriptional sequelae of histone modification dysregulation, offering clinicians a valuable framework to accurately predict post-RP outcomes and expedite the formulation of personalized therapeutic strategies.

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Publication Details

Journal
Biomedicines
Published
2026-05-28
DOI
https://doi.org/10.3390/biomedicines14061219
Primary Topic
Prostate Cancer Treatment and Research
Type
article
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0.00
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article

A Gene Feature Based on Histone Modifications Can Predict the Prognosis of Prostate Cancer

Jialin Gao, Xuee Zhou, Xiaoxiang Rong, Jiahong Hong et al.
Biomedicines
Prostate Cancer Treatment and Research
article

A Gene Feature Based on Histone Modifications Can Predict the Prognosis of Prostate Cancer

Jialin Gao, Xuee Zhou, Xiaoxiang Rong, Jiahong Hong, Yan Tan, Rui Zhou, Zetao Zuo, Zhenhua Huang
article en

Abstract

Background/Objectives: Prostate cancer (PCa) remains a prevalent malignancy among men, often complicated by recurrence and unfavorable clinical outcomes. Consequently, precise risk stratification and timely clinical intervention are paramount. Initially, we delineated distinct expression profiles of histone modification regulators via unsupervised clustering, identifying PCa subtypes with divergent survival probabilities and biological phenotypes. Subsequently, we sought to develop a prognostic gene signature, derived from the transcriptomic variations among these regulator-defined subtypes, to predict outcomes in PCa patients following radical prostatectomy (RP). Methods: Clinical and transcriptomic data from PCa cohorts were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories for comprehensive analysis. Subtypes driven by histone modification regulators were established using unsupervised consensus clustering, followed by in-depth characterization of their molecular features and associated pathways. A risk-scoring model was then developed to evaluate its prognostic efficacy in this patient population. Results: Stratification based on histone modification regulators yielded four distinct PCa subtypes exhibiting heterogeneous survival outcomes, functional pathways, and genomic mutational landscapes. Following rigorous feature selection, a 21-gene risk signature (HIS_score)—comprising MXD3, CCDC28B, COL11A2, SLC39A5, GPT, DNASE1L2, PIF1, KRTAP5-9, TTLL10, KRTAP5-1, KRTAP5-10, HAGHL, MSLNL, AMH, NKAIN4, CCDC114, SLC9A3, SULT1E1, ALB, SLC6A14, and RPE65—was constructed. Survival analyses demonstrated that patients assigned to the high HIS_score cohort experienced significantly worse clinical outcomes compared to their low-score counterparts. Furthermore, we integrated this signature into a novel clinical nomogram to facilitate individualized prognostic assessments. Conclusions: Derived from transcriptomic disparities between extreme epigenetic subtypes, the HIS_score and its associated nomogram serve as robust prognostic instruments. These tools effectively encapsulate the downstream transcriptional sequelae of histone modification dysregulation, offering clinicians a valuable framework to accurately predict post-RP outcomes and expedite the formulation of personalized therapeutic strategies.

BiomedicinesVol. 14(6)
Nanfang Hospital (CN), Southern Medical University (CN)
Good health and well-being
Openalex Percentile: Top 6%
Prostate Cancer Treatment and Research
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