通过共表达分析比较肿瘤细胞、常氧和低氧胶质母细胞瘤干细胞样细胞系筛选胶质母细胞瘤中的重要枢纽基因。

Screening the Significant Hub Genes by Comparing Tumor Cells, Normoxic and Hypoxic Glioblastoma Stem-like Cell Lines Using Co-Expression Analysis in Glioblastoma.

机构信息

Department of Biomedical Engineering, Düzce University, Düzce 81620, Turkey.

Department of Pharmacology, College of Pharmacy, Jouf University, Sakaka 72341, Al Jouf, Saudi Arabia.

出版信息

Genes (Basel). 2022 Mar 15;13(3):518. doi: 10.3390/genes13030518.

DOI:10.3390/genes13030518

PMID:35328072

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8951270/

Abstract

Glioblastoma multiforme (GBM) is categorized by rapid malignant cellular growth in the central nervous system (CNS) tumors. It is one of the most prevailing primary brain tumors, particularly in human male adults. Even though the combination therapy comprises surgery, chemotherapy, and adjuvant therapies, the survival rate is on average 14.6 months. Glioma stem cells (GSCs) have key roles in tumorigenesis, progression, and counteracting chemotherapy and radiotherapy. In our study, firstly, the gene expression dataset GSE45117 was retrieved and differentially expressed genes (DEGs) were spotted. The co-expression network analysis was employed on DEGs to find the significant modules. The most significant module resulting from co-expression analysis was the turquoise module. The turquoise module related to the tumor cells, hypoxia, normoxic treatments of glioblastoma tumor (GBT), and GSCs were screened. Sixty-one common genes in the turquoise module were selected generated through the co-expression analysis and protein-protein interaction (PPI) network. Moreover, the GO and KEGG pathway enrichment results were studied. Twenty common hub genes were screened by the NetworkAnalyst web instrument constructed on the PPI network through the STRING database. After survival analysis via the Kaplan-Meier (KM) plotter from The Cancer Genome Atlas (TCGA) database, we identified the five most significant hub genes strongly related to the progression of GBM. We further observed these five most significant hub genes also up-regulated in another GBM gene expression dataset. The protein-protein interaction (PPI) network of the turquoise module genes was constructed and a KEGG pathway enrichments study of the turquoise module genes was performed. The VEGF signaling pathway was emphasized because of the strong link with GBM. A gene-disease association network was further constructed to demonstrate the information of the progression of GBM and other related brain neoplasms. All hub genes assessed through this study would be potential markers for the prognosis and diagnosis of GBM.

摘要

胶质母细胞瘤（GBM）是中枢神经系统（CNS）肿瘤中快速恶性细胞生长的分类。它是最常见的原发性脑肿瘤之一，特别是在人类成年男性中。尽管联合治疗包括手术、化疗和辅助治疗，但平均存活率为 14.6 个月。神经胶质瘤干细胞（GSCs）在肿瘤发生、进展以及对抗化疗和放疗方面起着关键作用。在我们的研究中，首先，我们检索了基因表达数据集 GSE45117，并发现了差异表达基因（DEGs）。我们对 DEGs 进行了共表达网络分析，以找到显著的模块。共表达分析产生的最显著模块是绿松石模块。我们筛选了与肿瘤细胞、缺氧、胶质母细胞瘤肿瘤（GBT）和 GSCs 的常氧处理相关的绿松石模块。通过共表达分析和蛋白质-蛋白质相互作用（PPI）网络选择了绿松石模块中的 61 个共同基因。此外，我们还研究了 GO 和 KEGG 通路的富集结果。通过 STRING 数据库构建的 NetworkAnalyst 网络工具，我们从 PPI 网络中筛选了 20 个共同枢纽基因。通过从癌症基因组图谱（TCGA）数据库中的 Kaplan-Meier（KM）绘图器进行生存分析，我们确定了与 GBM 进展密切相关的五个最重要的枢纽基因。我们进一步观察到，另一个 GBM 基因表达数据集中这五个最重要的枢纽基因也上调了。构建了绿松石模块基因的蛋白质-蛋白质相互作用（PPI）网络，并对绿松石模块基因进行了 KEGG 途径富集研究。由于与 GBM 有很强的联系，我们强调了血管内皮生长因子（VEGF）信号通路。进一步构建了基因-疾病关联网络，以展示 GBM 及其他相关脑肿瘤的进展信息。通过本研究评估的所有枢纽基因都可能成为 GBM 预后和诊断的潜在标志物。