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Identification of Key Modules and Hub Genes in Glioblastoma Multiforme Based on Co-Expression Network Analysis

Long Gu  Jian Zhou  Jianhua Peng  Jinwei Pang  Lifang Zhang  Ligang Chen  Yong Jiang  
【摘要】:Purpose: Glioblastoma multiforme(GBM) is the most malignant primary tumor in the central nervous system. The molecular mechanism of its pathogenesis remains unclear. Our goal is to identify key modules and hub genes involved in the pathogenesis of GBM by constructing a gene co-expression network. Methods: Dataset GSE50161 was used to construct a co-expression network for Weighted Gene Co-Expression Network Analysis(WGCNA). Key modules were obtained by correlating module eigengenes and the disease status. Gene Oncology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis were performed. Hub genes were screened by survival analysis in The Cancer Genome Atlas(TCGA) and The Human Protein Atlas(HPA) database. The expression level and translational level of hub genes were also verified. Results: The brown and turquoise modules were found to have the strongest correlation with GBM. Functional enrichment analysis indicated that the brown module was involved with cell cycle, DNA replication and pyrimidine metabolism. The turquoise module is primarily related to circadian rhythm entrainment, glutamatergic synapses and axonal guidance. The eight hub genes(NUSAP1, SHCBP1, KNL1, SULT4 A1, SLC12 A5, NUF2, NAPB and GARNL3) were identified by survival analysis in TCGA, and verified at both expression and translational levels. Conclusion: In this study, we identified two modules and eight hub genes that are strongly related to GBM. These two modules provide new insights into the molecular mechanism of GBM. Meanwhile, the hub genes can be the potential biomarkers and therapeutic targets for the accurate diagnosis and management of GBM.

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