研究报告

DNA甲基化驱动的转录表达特征作为肝癌预后预测标志物的价值

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  • 1. 贵州大学医学院,贵阳 550025
    2. 军事科学院军事医学研究院辐射医学研究所,蛋白质组学国家重点实验室,国家蛋白质科学中心(北京),北京 100850;
骆红波,硕士研究生,专业方向:肝癌转录组学。E-mail: 965589073@qq.com

收稿日期: 2020-05-18

  修回日期: 2020-07-10

  网络出版日期: 2020-07-10

基金资助

国家科技重大专项艾滋病和病毒性肝炎等重大传染病防治专项项目资助编号(2018ZX10732202);国家科技重大专项艾滋病和病毒性肝炎等重大传染病防治专项项目资助编号(2017ZX10203205)

Prognostic and predictive value of a DNA methylation-driven transcriptional signature in hepatocellular carcinoma

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  • 1. Guizhou University School of Medicine, Guiyang 550025, China
    2. State Key Lab of Proteomics, National Center for Protein Sciences (Beijing), Institute of Radiation Medicine, Academy of Military Medical Sciences, Academy of Military Sciences, Beijing 100850, China;

Received date: 2020-05-18

  Revised date: 2020-07-10

  Online published: 2020-07-10

Supported by

Supported by the National S&T Major Project Nos(2018ZX10732202);Supported by the National S&T Major Project Nos(2017ZX10203205)

摘要

肝细胞癌(hepatocellular carcinoma,简称肝癌)是最常见的恶性肿瘤之一。DNA甲基化的异常是恶性肿瘤的特征之一,并被发现在肝癌等肿瘤的发生发展中发挥重要作用。为了能为肝癌患者提供新的临床预后预测标志物,本研究首先采用整合组学分析策略在全基因组范围内鉴定与肝癌患者预后相关的DNA甲基化驱动的差异表达基因;然后,采用LASSO (least absolute shrinkage and selection operator)分析建立了10个最优基因组合的预后预测模型。Cox比例风险回归分析显示,在校正临床特征参数后,此预测模型高风险评分与患者不良预后显著相关,表明该模型具有潜在的独立预后价值。受试者工作特征(receiver operating characteristic, ROC)曲线分析显示该风险评分模型在预测患者短期和长期预后方面优于其他已被报道的肝癌预后预测模型。基因集富集分析(gene set enrichment analysis, GSEA)表明,高风险评分与细胞周期和DNA损伤修复通路相关。以上结果表明,本研究构建了一个基于10个DNA甲基化驱动基因的预后风险评分模型,该模型可作为肝癌患者的潜在预后生物标志物,有助于肝癌患者的生存预后评估和治疗策略的指导。

本文引用格式

骆红波, 曹鹏博, 周钢桥 . DNA甲基化驱动的转录表达特征作为肝癌预后预测标志物的价值[J]. 遗传, 2020 , 42(8) : 775 -787 . DOI: 10.16288/j.yczz.20-139

Abstract

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. DNA methylation alterations are frequently observed in malignant tumours and play critical roles in the development of cancers, including HCC. To provide novel clinical prognosis biomarkers for HCC patients, we first performed a comprehensive analysis and identified a collection of prognosis-associated genes with DNA methylation-driven expression dysregulation in HCCs. Then, we optimally established a 10-gene prognostic risk score model using the least absolute shrinkage and selection operator (LASSO) analysis. Cox's proportional hazards regression analysis revealed that the high-risk score is significantly associated with poor prognosis after being adjusted by clinical parameters, indicating its potential prognostic value. The receiver operating characteristic curve (ROC) analysis showed that this 10-gene prognostic risk score model outperformed several other publicly available models in predicting both short- and long-term prognosis. Gene set enrichment analysis revealed that the high-risk score is relevantly associated with pathways involved in cell cycle and DNA damage repair. The above results indicate that we have constructed a 10-DNA-methylation-driven-gene prognostic risk score model, which might serve as a potential prognostic biomarker for HCC patients and guide treatment decisions for patients at high risk of tumour progression.

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