Luo Hong Bo, Cao Peng Bo, Zhou Gang Qiao
Guizhou University School of Medicine, Guiyang 550025, China.
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.
Yi Chuan. 2020 Aug 20;42(8):775-787. doi: 10.16288/j.yczz.20-139.
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.
肝细胞癌（HCC）是全球最常见的癌症之一。DNA甲基化改变在恶性肿瘤中经常被观察到，并且在包括HCC在内的癌症发展中起关键作用。为了为HCC患者提供新的临床预后生物标志物，我们首先进行了全面分析，并鉴定了一组在HCC中具有DNA甲基化驱动的表达失调的预后相关基因。然后，我们使用最小绝对收缩和选择算子（LASSO）分析最优地建立了一个10基因预后风险评分模型。Cox比例风险回归分析显示，在经临床参数调整后，高风险评分与不良预后显著相关，表明其潜在的预后价值。受试者工作特征曲线（ROC）分析表明，这个10基因预后风险评分模型在预测短期和长期预后方面优于其他几个公开可用的模型。基因集富集分析显示，高风险评分与细胞周期和DNA损伤修复相关的通路有关。上述结果表明，我们构建了一个由10个DNA甲基化驱动基因组成的预后风险评分模型，它可能作为HCC患者潜在的预后生物标志物，并指导肿瘤进展高风险患者的治疗决策。
