DNA methylation is a common chemical modification of DNA in the carcinogenesis of hepatocellular carcinoma (HCC). In this bioinformatics analysis, 348 liver cancer samples were collected from the Cancer Genome Atlas (TCGA) database to analyse specific DNA methylation sites that affect the prognosis of HCC patients. 10,699 CpG sites (CpGs) that were significantly related to the prognosis of patients were clustered into 7 subgroups, and the samples of each subgroup were significantly different in various clinical pathological data. In addition, by calculating the level of methylation sites in each subgroup, 119 methylation sites (corresponding to 105 genes) were selected as specific methylation sites within the subgroups. Moreover, genes in the corresponding promoter regions in which the above specific methylation sites were located were subjected to signalling pathway enrichment analysis, and it was discovered that these genes were enriched in the biological pathways that were reported to be closely correlated with HCC. Additionally, the transcription factor enrichment analysis revealed that these genes were mainly enriched in the transcription factor KROX. A naive Bayesian classification model was used to construct a prognostic model for HCC, and the training and test data sets were used for independent verification and testing. This classification method can well reflect the heterogeneity of HCC samples and help to develop personalized treatment and accurately predict the prognosis of patients.

中文翻译：

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基于HDNA甲基化数据的分子亚型分类与肝细胞癌患者的预后有关。

DNA甲基化是肝细胞癌（HCC）癌变中DNA的常见化学修饰。在这项生物信息学分析中，从癌症基因组图谱（TCGA）数据库中收集了348个肝癌样本，以分析影响HCC患者预后的特定DNA甲基化位点。与患者预后显着相关的10,699个CpG位点（CpGs）分为7个亚组，每个亚组的样本在各种临床病理数据中均存在显着差异。另外，通过计算每个亚组中甲基化位点的水平，选择了119个甲基化位点（对应于105个基因）作为亚组内的特定甲基化位点。此外，对上述特定甲基化位点所在的相应启动子区域中的基因进行信号传导途径富集分析，发现这些基因在据报道与肝癌密切相关的生物学途径中富集。另外，转录因子富集分析表明这些基因主要富集在转录因子KROX中。使用朴素的贝叶斯分类模型构建肝癌的预后模型，训练和测试数据集用于独立验证和测试。这种分类方法可以很好地反映出肝癌样本的异质性，有助于开展个性化治疗并准确预测患者的预后。并且发现这些基因丰富了据报道与肝癌密切相关的生物学途径。另外，转录因子富集分析表明这些基因主要富集在转录因子KROX中。使用朴素的贝叶斯分类模型构建肝癌的预后模型，训练和测试数据集用于独立验证和测试。这种分类方法可以很好地反映HCC样本的异质性，有助于开展个性化治疗并准确预测患者的预后。并且发现这些基因丰富了据报道与肝癌密切相关的生物学途径。另外，转录因子富集分析表明这些基因主要富集在转录因子KROX中。使用朴素的贝叶斯分类模型构建肝癌的预后模型，训练和测试数据集用于独立验证和测试。这种分类方法可以很好地反映HCC样本的异质性，有助于开展个性化治疗并准确预测患者的预后。使用朴素的贝叶斯分类模型构建肝癌的预后模型，训练和测试数据集用于独立验证和测试。这种分类方法可以很好地反映HCC样本的异质性，有助于开展个性化治疗并准确预测患者的预后。使用朴素的贝叶斯分类模型构建肝癌的预后模型，训练和测试数据集用于独立验证和测试。这种分类方法可以很好地反映HCC样本的异质性，有助于开展个性化治疗并准确预测患者的预后。