Table_1_A prognostic model based on DNA methylation-related gene expression for predicting overall survival in hepatocellular carcinoma.docx

BackgroundHepatocellular carcinoma (HCC) continues to increase in morbidity and mortality among all types of cancer. DNA methylation, an important epigenetic modification, is associated with cancer occurrence and progression. The objective of this study was to establish a model based on DNA methylation risk scores for identifying new potential therapeutic targets in HCC and preventing cancer progression.
MethodsTranscriptomic, clinical, and DNA methylation data on 374 tumor tissues and 50 adjacent normal tissues were downloaded from The Cancer Genome Atlas–Liver Hepatocellular Carcinoma database. The gene expression profiles of the GSE54236 liver cancer dataset, which contains data on 161 liver tissue samples, were obtained from the Gene Expression Omnibus database. We analyzed the relationship between DNA methylation and gene expression levels after identifying the differentially methylated and expressed genes. Then, we developed and validated a risk score model based on the DNA methylation-driven genes. A tissue array consisting of 30 human hepatocellular carcinoma samples and adjacent normal tissues was used to assess the protein and mRNA expression levels of the marker genes by immunohistochemistry and qRT-PCR, respectively.
ResultsThree methylation-related differential genes were identified in our study: GLS, MEX3B, and GNA14. The results revealed that their DNA methylation levels were negatively correlated with local gene expression regulation. The gene methylation levels correlated strongly with the prognosis of patients with liver cancer. This was confirmed by qRT-PCR and immunohistochemical verification of the expression of these genes or proteins in tumors and adjacent tissues. These results revealed the relationship between the level of relevant gene methylation and the prognosis of patients with liver cancer as well as the underlying cellular and biological mechanisms. This allows our gene signature to provide more accurate and appropriate predictions for clinical applications.
ConclusionThrough bioinformatics analysis and experimental validation, we obtained three DNA methylation marker: GLS, MEX3B, and GNA14. This helps to predict the prognosis and may be a potential therapeutic target for HCC patients.

研究背景：肝细胞癌（Hepatocellular carcinoma, HCC）在各类癌症中的发病率与死亡率仍呈逐年上升趋势。DNA甲基化作为一种重要的表观遗传修饰，与癌症的发生及进展密切相关。本研究旨在构建基于DNA甲基化风险评分的模型，以识别肝细胞癌潜在的新型治疗靶点并阻断癌症进展。
研究方法：本研究从癌症基因组图谱-肝脏肝细胞癌（The Cancer Genome Atlas–Liver Hepatocellular Carcinoma, TCGA-LIHC）数据库下载了374份肿瘤组织与50份癌旁正常组织的转录组、临床及DNA甲基化数据；从基因表达综合（Gene Expression Omnibus, GEO）数据库获取包含161份肝脏组织样本的GSE54236肝癌数据集的基因表达谱数据。在筛选出差异甲基化基因与差异表达基因后，本研究分析了DNA甲基化水平与基因表达量之间的关联。随后，基于DNA甲基化驱动基因构建并验证了风险评分模型。本研究采用包含30份人肝细胞癌组织及对应癌旁正常组织的组织芯片，分别通过免疫组化（immunohistochemistry）与实时定量逆转录聚合酶链反应（qRT-PCR）检测标记基因的蛋白与mRNA表达水平。
研究结果：本研究共筛选得到3个与甲基化相关的差异基因：GLS、MEX3B及GNA14。结果显示，这些基因的DNA甲基化水平与局部基因表达调控呈负相关，且其甲基化水平与肝癌患者的预后显著相关。通过qRT-PCR与免疫组化验证这些基因/蛋白在肿瘤及癌旁组织中的表达水平，进一步证实了上述关联。本研究结果阐明了相关基因甲基化水平与肝癌患者预后的关联及其潜在的细胞与分子生物学机制，使得本研究所构建的基因特征可更为精准地应用于临床预后预测。
研究结论：通过生物信息学分析与实验验证，本研究确定了3个DNA甲基化标记物：GLS、MEX3B及GNA14。上述标记物可用于预测肝细胞癌患者的预后，或可成为该类患者潜在的治疗靶点。