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通过加权基因共表达网络分析鉴定 TNFAIP6 作为与胶质母细胞瘤进展相关的枢纽基因。

Identification of TNFAIP6 as a hub gene associated with the progression of glioblastoma by weighted gene co-expression network analysis.

机构信息

Department of Neurosurgery, The Second Affiliated Hospital-Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.

The Second School of Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, China.

出版信息

IET Syst Biol. 2022 Sep;16(5):145-156. doi: 10.1049/syb2.12046. Epub 2022 Jun 29.

DOI:10.1049/syb2.12046
PMID:35766985
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9469790/
Abstract

This study aims to discover the genetic modules that distinguish glioblastoma multiforme (GBM) from low-grade glioma (LGG) and identify hub genes. A co-expression network is constructed using the expression profiles of 28 GBM and LGG patients from the Gene Expression Omnibus database. The authors performed gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) analysis on these genes. The maximal clique centrality method was used to identify hub genes. Online tools were employed to confirm the link between hub gene expression and overall patient survival rate. The top 5000 genes with major variance were classified into 18 co-expression gene modules. GO analysis indicated that abnormal changes in 'cell migration' and 'collagen metabolic process' were involved in the development of GBM. KEGG analysis suggested that 'focal adhesion' and 'p53 signalling pathway' regulate the tumour progression. TNFAIP6 was identified as a hub gene, and the expression of TNFAIP6 was increased with the elevation of pathological grade. Survival analysis indicated that the higher the expression of TNFAIP6, the shorter the survival time of patients. The authors identified TNFAIP6 as the hub gene in the progression of GBM, and its high expression indicates the poor prognosis of the patients.

摘要

本研究旨在发现区分胶质母细胞瘤（GBM）和低级别胶质瘤（LGG）的遗传模块，并鉴定枢纽基因。使用来自基因表达综合数据库的 28 名 GBM 和 LGG 患者的表达谱构建共表达网络。作者对这些基因进行了基因本体论（GO）和京都基因与基因组百科全书（KEGG）分析。使用最大团中心度方法鉴定枢纽基因。在线工具用于确认枢纽基因表达与整体患者生存率之间的联系。具有主要方差的前 5000 个基因被分类为 18 个共表达基因模块。GO 分析表明，“细胞迁移”和“胶原代谢过程”的异常变化参与了 GBM 的发生。KEGG 分析表明，“粘着斑”和“p53 信号通路”调节肿瘤进展。TNFAIP6 被鉴定为枢纽基因，并且随着病理分级的升高，TNFAIP6 的表达增加。生存分析表明，TNFAIP6 的表达越高，患者的生存时间越短。作者确定 TNFAIP6 是 GBM 进展中的枢纽基因，其高表达表明患者预后不良。

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