Department of Neurosurgery, The First Affiliated Hospital of Hainan Medical University, Haikou, China.
Department of General Medicine, The First Affiliated Hospital of Hainan Medical University, Haikou, China.
World Neurosurg. 2020 Jun;138:e492-e514. doi: 10.1016/j.wneu.2020.02.159. Epub 2020 Mar 5.
This study bioinformatically analyzed aberrant genes and pathways for associations with glioblastoma development and prognosis.
The Gene Expression Omnibus (GEO) database was searched and 4 GEO datasets (GSE4290, GSE50161, GSE116520, and GSE90598) were retrieved for limma and RobustRankAggreg package analyses of differentially expressed genes (DEGs) between glioblastoma and normal brain tissues. Functional enrichment analysis was conducted for the main biological functions of these DEGs, whereas the hub genes were identified using the protein-protein interaction network and confirmed for transcriptional and translational levels using the Cancer Genome Atlas, the Genotype-Tissue Expression, and the Human Protein Atlas data. The prognostic values of these hub genes were analyzed using the Chinese Glioma Genome Atlas. Their transcriptional factor regulation network was constructed to assess the roles in glioblastoma development and progression.
A total of 473 DEGs (182 upregulated and 291 downregulated) were identified and the hub genes (including CCNB1, CDC20, CCNB2, BUB1, and CCNA2) were shown in module 1 and enriched in the cell cycle or p53 signaling pathway. The highly expressed CCNB1, CDC20, BUB1, and CCNA2 in patients with glioblastoma were associated with poor overall survival, whereas TAF7 could upregulate expression of CCNB1 and CCNA2 and GTF2E2 could upregulate CDC20 expression in glioblastoma.
This study showed several DEGs in glioblastoma, and aberrant expression of their hub genes was associated with glioblastoma pathogenesis and poor prognosis, especially the signaling axes of TAF7/CCNB1, TAF7/CCNA2, and GTF2E2/CDC20.
本研究通过生物信息学分析,探讨与胶质母细胞瘤发生和预后相关的异常基因和通路。
检索基因表达综合数据库(GEO),并提取 4 个 GEO 数据集(GSE4290、GSE50161、GSE116520 和 GSE90598),通过 limma 和 RobustRankAggreg 包分析胶质母细胞瘤和正常脑组织之间差异表达基因(DEGs)。对这些 DEGs 的主要生物学功能进行功能富集分析,利用蛋白质-蛋白质相互作用网络识别枢纽基因,并使用癌症基因组图谱(TCGA)、基因型-组织表达(GTEx)和人类蛋白质图谱(HPA)数据在转录和翻译水平上进行验证。利用中国脑胶质瘤基因组图谱(CGGA)分析这些枢纽基因的预后价值。构建其转录因子调控网络,评估其在胶质母细胞瘤发生和进展中的作用。
共鉴定出 473 个 DEGs(182 个上调,291 个下调),其中枢纽基因(包括 CCNB1、CDC20、CCNB2、BUB1 和 CCNA2)位于模块 1 中,富集在细胞周期或 p53 信号通路中。胶质母细胞瘤患者中高表达的 CCNB1、CDC20、BUB1 和 CCNA2 与总生存期不良相关,而 TAF7 可上调 CCNB1 和 CCNA2 的表达,GTF2E2 可上调 CDC20 的表达。
本研究显示了胶质母细胞瘤中的几个 DEGs,其枢纽基因的异常表达与胶质母细胞瘤的发病机制和不良预后相关,特别是 TAF7/CCNB1、TAF7/CCNA2 和 GTF2E2/CDC20 信号轴。