Specific Glioma Prognostic Subtype Distinctions Based on DNA Methylation Patterns

DNA methylation is an important regulator of gene expression and may provide an important basis for effective glioma diagnosis and therapy. Here, we explored specific prognosis subtypes based on DNA methylation status using 653 gliomas from The Cancer Genome Atlas (TCGA) database. Five subgroups were distinguished by consensus clustering using 11,637 cytosines preceding a guanosine (CpGs) that significantly influenced survival. The specific DNA methylation patterns were correlated with age, tumor stage, and prognosis. Additionally, weighted gene co-expression network analysis (WGCNA) analysis of CpG sites revealed that 11 of them could distinguish the samples into high- and low-methylation groups and could classify the prognostic information of samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained from the test set and 12 glioma patients. Moreover, in vitro experiments revealed an inverse relationship between methylation level and migration ability or insensitivity to temozolomide (or radiotherapy) of glioma cells based on the final prognostic predictor. Thus, these results suggested that the model constructed in this study could provide guidance for clinicians regarding the prognosis of various epigenetic subtypes.

DNA甲基化是基因表达的重要调控因子，可为胶质瘤的有效诊断与治疗提供重要依据。本研究利用癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据库中的653例胶质瘤样本，基于DNA甲基化状态探索特定的预后亚型。通过共识聚类方法，利用11,637个对生存有显著影响的鸟嘌呤前胞嘧啶（CpGs）位点，将样本分为5个亚组。这些特定的DNA甲基化模式与年龄、肿瘤分期及预后相关。此外，对CpG位点的加权基因共表达网络分析（weighted gene co-expression network analysis, WGCNA）显示，其中11个位点可将样本分为高甲基化组与低甲基化组，并能在训练集样本经层次聚类算法分析后对样本的预后信息进行分类。测试集及12例胶质瘤患者样本也得到了类似结果。此外，基于最终的预后预测因子开展的体外实验表明，胶质瘤细胞的甲基化水平与其迁移能力或对替莫唑胺（或放疗）的不敏感性呈负相关。因此，本研究构建的模型可为临床医生判断不同表观遗传亚型的预后提供指导。