Mao Yu Kun, Liu Zhi Bo, Cai Lin
Department of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China.
Oncol Lett. 2020 Aug;20(2):1619-1628. doi: 10.3892/ol.2020.11729. Epub 2020 Jun 11.
Glioblastoma (GBM) is the most aggressive and lethal tumor of the central nervous system. The present study set out to identify reliable prognostic and predictive biomarkers for patients with GBM. RNA-sequencing data were obtained from The Cancer Genome Atlas database and DNA methylation data were downloaded using the University of California Santa Cruz-Xena database. The expression and methylation differences between patients with GBM, and survival times <1 and ≥1 year were investigated. A protein-protein interaction network was constructed and functional enrichment analyses of differentially expressed and methylated genes were performed. Hub genes were identified using the Cytoscape plug-in cytoHubba software. Survival analysis was performed using the survminer package, in order to determine the prognostic values of the hub genes. The present study identified 71 genes that were hypomethylated and expressed at high levels, and four genes that were hypermethylated and expressed at low levels in GBM. These genes were predominantly enriched in the 'JAK-STAT signaling pathway', 'transcriptional misregulation in cancer' and the 'ECM-receptor interaction', which are associated with GBM development. Among the 24 hub genes identified, 15 possessed potential prognostic value. An integrative analysis approach was implemented in order to analyze the association of DNA methylation with changes in gene expression and to assess the association of gene expression changes with GBM survival time. The results of the present study suggest that these 15 CpG-based genes may be useful and practical tools in predicting the prognosis of patients with GBM. However, future research on gene methylation and/or expression is required in order to develop personalized treatments for patients with GBM.
胶质母细胞瘤（GBM）是中枢神经系统中最具侵袭性和致命性的肿瘤。本研究旨在为GBM患者确定可靠的预后和预测生物标志物。从癌症基因组图谱数据库中获取RNA测序数据，并使用加利福尼亚大学圣克鲁兹分校的Xena数据库下载DNA甲基化数据。研究了GBM患者与生存时间<1年和≥1年患者之间的表达和甲基化差异。构建了蛋白质-蛋白质相互作用网络，并对差异表达和甲基化基因进行了功能富集分析。使用Cytoscape插件cytoHubba软件鉴定枢纽基因。使用survminer软件包进行生存分析，以确定枢纽基因的预后价值。本研究在GBM中鉴定出71个低甲基化且高表达的基因，以及4个高甲基化且低表达的基因。这些基因主要富集于与GBM发展相关的“JAK-STAT信号通路”、“癌症中的转录失调”和“细胞外基质-受体相互作用”。在鉴定出的24个枢纽基因中，15个具有潜在的预后价值。采用综合分析方法来分析DNA甲基化与基因表达变化之间的关联，并评估基因表达变化与GBM生存时间之间的关联。本研究结果表明，这15个基于CpG的基因可能是预测GBM患者预后的有用且实用的工具。然而，为了开发针对GBM患者的个性化治疗方法，未来还需要对基因甲基化和/或表达进行研究。
