Identification of TNFAIP6 as a hub gene associated with the progression of glioblastoma by weighted gene co‐expression network analysis. Issue 5 (29th June 2022)

• Record Type: Journal Article
• Authors: Lin, Dongdong; Li, Wei; Zhang, Nu; Cai, Ming
• Is Part Of: IET systems biology. Volume 16:Issue 5(2022)
• Page Start: 145
• Page End: 156
• Publication Date: 2022-06-29
• Subjects: Systems biology -- Periodicals; Cell physiology -- Periodicals; Biological systems -- Mathematical models -- Periodicals; Genetics -- Mathematical models -- Periodicals; Computational biology -- Periodicals; 573
• DOI: 10.1049/syb2.12046
• Languages: English
• ISSNs: 1751-8849

Abstract

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.