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通过综合生物信息学分析鉴定多形性胶质母细胞瘤的核心基因并筛选潜在靶点

Identification of Core Genes and Screening of Potential Targets in Glioblastoma Multiforme by Integrated Bioinformatic Analysis.

作者信息

Yang Ji'an, Yang Qian

机构信息

Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China.

Division of Nephrology, Renmin Hospital of Wuhan University, Wuhan, China.

出版信息

Front Oncol. 2021 Feb 24;10:615976. doi: 10.3389/fonc.2020.615976. eCollection 2020.

Abstract

Glioblastoma multiforme is the most common primary intracranial malignancy, but its etiology and pathogenesis are still unclear. With the deepening of human genome research, the research of glioma subtype screening based on core molecules has become more in-depth. In the present study, we screened out differentially expressed genes (DEGs) through reanalyzing the glioblastoma multiforme (GBM) datasets GSE90598 from the Gene Expression Omnibus (GEO), the GBM dataset TCGA-GBM and the low-grade glioma (LGG) dataset TCGA-LGG from the Cancer Genome Atlas (TCGA). A total of 150 intersecting DEGs were found, of which 48 were upregulated and 102 were downregulated. These DEGs from GSE90598 dataset were enriched using the overrepresentation method, and multiple enriched gene ontology (GO) function terms were significantly correlated with neural cell signal transduction. DEGs between GBM and LGG were analyzed by gene set enrichment analysis (GSEA), and the significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in synapse signaling and oxytocin signaling pathways. Then, a protein-protein interaction (PPI) network was constructed to assess the interaction of proteins encoded by the DEGs. MCODE identified 2 modules from the PPI network. The 11 genes with the highest degrees in module 1 were designated as core molecules, namely, GABRD, KCNC1, KCNA1, SYT1, CACNG3, OPALIN, CD163, HPCAL4, ANK3, KIF5A, and MS4A6A, which were mainly enriched in ionic signaling-related pathways. Survival analysis of the GSE83300 dataset verified the significant relationship between expression levels of the 11 core genes and survival. Finally, the core molecules of GBM and the DrugBank database were assessed by a hypergeometric test to identify 10 drugs included tetrachlorodecaoxide related to cancer and neuropsychiatric diseases. Further studies are required to explore these core genes for their potentiality in diagnosis, prognosis, and targeted therapy and explain the relationship among ionic signaling-related pathways, neuropsychiatric diseases and neurological tumors.

摘要

多形性胶质母细胞瘤是最常见的原发性颅内恶性肿瘤,但其病因和发病机制仍不清楚。随着人类基因组研究的深入,基于核心分子的胶质瘤亚型筛查研究也更加深入。在本研究中,我们通过重新分析来自基因表达综合数据库(GEO)的多形性胶质母细胞瘤(GBM)数据集GSE90598、癌症基因组图谱(TCGA)的GBM数据集TCGA-GBM和低级别胶质瘤(LGG)数据集TCGA-LGG,筛选出差异表达基因(DEG)。共发现150个交集DEG,其中48个上调,102个下调。使用超几何方法对来自GSE90598数据集的这些DEG进行富集,多个富集的基因本体(GO)功能术语与神经细胞信号转导显著相关。通过基因集富集分析(GSEA)分析GBM和LGG之间的DEG,显著富集的京都基因与基因组百科全书(KEGG)通路涉及突触信号通路和催产素信号通路。然后,构建蛋白质-蛋白质相互作用(PPI)网络以评估DEG编码的蛋白质之间的相互作用。MCODE从PPI网络中识别出2个模块。模块1中度数最高的11个基因被指定为核心分子,即GABRD、KCNC1、KCNA1、SYT1、CACNG3、OPALIN、CD163、HPCAL4、ANK3、KIF5A和MS4A6A,它们主要富集在离子信号相关通路中。对GSE83300数据集的生存分析验证了11个核心基因的表达水平与生存之间的显著关系。最后,通过超几何检验评估GBM的核心分子与药物银行数据库,以鉴定出10种与癌症和神经精神疾病相关的药物,包括四氯癸氧化物。需要进一步研究来探索这些核心基因在诊断、预后和靶向治疗方面的潜力,并解释离子信号相关通路、神经精神疾病和神经肿瘤之间的关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6edf/7943725/98688a84ad37/fonc-10-615976-g001.jpg

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