Glioma is the most common primary brain tumor in humans and the most deadly. Stem cells, which are characterized by therapeutic resistance and self-renewal, play a critical role in glioma, and therefore the identification of stem cell-related genes in glioma is important. In this study, we collected and evaluated the epigenetically regulated-mRNA expression-based stemness index (EREG-mRNAsi) of The Cancer Genome Atlas (TCGA, http://www.ncbi.nlm.nih.gov/) for glioma patient samples, corrected through tumor purity. After EREG-mRNAsi correction, glioma pathological grade and survival were analyzed. The differentially expressed gene (DEG) co-expression network was constructed by weighted gene co-expression network analysis (WGCNA) in TCGA glioma samples to find modules of interest and key genes. Gene ontology (GO) and pathway-enrichment analysis were performed to identify the function of significant genetic modules. Protein–protein interaction (PPI) and co-expression network analysis of key genes was performed for further analysis. In this experiment, we found that corrected EREG-mRNAsi was significantly up-regulated in glioma samples and increased with glioma grade, with G4 having the highest stemness index. Patients with higher corrected EREG-mRNAsi scores had worse overall survival. Fifty-one DEGs in the brown gene module were found to be positively related to EREG-mRNAsi via WGCNA. GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that chromosome segregation and cell cycle molecular function were the major functions in key DEGs. Among these key DEGs, BUB1 showed high connectivity and co-expression, and also high connectivity in PPI. Fifty-one key genes were verified to play a critical role in glioma stem cells. These genes may serve as primary therapeutic targets to inhibit the activity of glioma stem cells.

胶质瘤是人类最常见的原发性脑肿瘤，也是最致命的。干细胞具有治疗抗性和自我更新的特点，在胶质瘤中起着关键作用，因此鉴定胶质瘤中的干细胞相关基因很重要。在这项研究中，我们收集并评估了胶质瘤患者样本的癌症基因组图谱（TCGA，http://www.ncbi.nlm.nih.gov/）的基于表观遗传调节的 mRNA 表达的干性指数（EREG-mRNAsi） ，通过肿瘤纯度纠正。EREG-mRNAsi校正后，分析胶质瘤病理分级和存活率。通过TCGA神经胶质瘤样本中的加权基因共表达网络分析（WGCNA）构建差异表达基因（DEG）共表达网络，以寻找感兴趣的模块和关键基因。进行基因本体论 (GO) 和通路富集分析，以确定重要遗传模块的功能。对关键基因进行蛋白质-蛋白质相互作用（PPI）和共表达网络分析以进行进一步分析。在本实验中，我们发现校正后的 EREG-mRNAsi 在神经胶质瘤样本中显着上调，并随着神经胶质瘤等级的增加而增加，其中 G4 具有最高的干性指数。具有较高校正 EREG-mRNAsi 评分的患者总生存期较差。通过 WGCNA，发现棕色基因模块中的 51 个 DEG 与 EREG-mRNAsi 呈正相关。GO 和京都基因和基因组百科全书 (KEGG) 富集分析表明，染色体分离和细胞周期分子功能是关键 DEG 的主要功能。在这些关键的 DEG 中，BUB1 表现出高连接性和共表达，以及 PPI 中的高连接性。51 个关键基因被证实在胶质瘤干细胞中发挥关键作用。这些基因可以作为主要治疗靶点来抑制胶质瘤干细胞的活性。