Specific glioblastoma multiforme prognostic-subtype distinctions based on DNA methylation patterns
Specific glioblastoma multiforme prognostic-subtype distinctions based on DNA methylation patterns
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基于 DNA 甲基化模式的特定多形性胶质母细胞瘤预后亚型区别
DOI：
10.1038/s41417-019-0142-6
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发表时间：
2020-09-01
影响因子：
6.4
通讯作者：
Chen, Xueran
中科院分区：
文献类型：
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作者：
Ma, Huihui;Zhao, Chenggang;Chen, Xueran
DNA甲基化是基因表达的重要调控因子，在脑癌变过程中起重要作用。在这里，我们利用来自癌症基因组图谱（TCGA）数据库的138个多形性胶质母细胞瘤（GBM）样本，探讨了基于DNA甲基化状态的特定预后亚型。在训练集中，11,637个与生存显著相关的CpG位点的甲基化谱被用于一致性聚类。我们确定了三种GBM分子亚型，它们的生存曲线彼此不同。此外，通过对CpG位点进行加权基因共表达网络分析（WGCNA），获得了10个特征CpG位点。我们能够将样本分为高甲基化组和低甲基化组，并使用分层聚类算法对训练集样本进行聚类分析后对样本的预后信息进行分类。在试验组和临床GBM标本中也得到了类似的结果。最后，我们发现甲基化水平与替莫唑胺（或放疗）敏感性或GBM细胞抗迁移能力呈正相关。综上所述，本研究构建的模型有助于解释GBM先前分子亚群的异质性，并可为临床医生对GBM的预后提供指导。
DNA methylation is an important regulator of gene expression, and plays a significant role in carcinogenesis in the brain. Here, we explored specific prognosis-subtypes based on DNA methylation status using 138 Glioblastoma Multiforme (GBM) samples from The Cancer Genome Atlas (TCGA) database. The methylation profiles of 11,637 CpG sites that significantly correlated with survival in the training set were employed for consensus clustering. We identified three GBM molecular subtypes, and their survival curves were distinct from each other. Furthermore, ten feature CpG sites were obtained on conducting a weighted gene co-expression network analysis (WGCNA) of the CpG sites. We were able to classify the samples into high- and low-methylation groups, and classified the prognosis information of the samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained in the test set and clinical GBM specimens. Finally, we found that a positive relationship existed between methylation level and sensitivity to temozolomide (or radiotherapy) or anti-migration ability of GBM cells. Taken together, these results suggest that the model constructed in this study could help explain the heterogeneity of previous molecular subgroups in GBM and can provide guidance to clinicians regarding the prognosis of GBM.