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Identification of biological behavior HUB genes of glioblastoma by bioinformatics |
HE Xin, QIN Zhizhen, LI Xin, ZHAO Shuiqiang, CHENG Cheng, WANG Zhen, FENG Yaohui, QIU Xianjun, YANG Shuqin, WANG Jianzhen |
Department of Neurosurgery, the Third Medical Center, PLA General Hospital,Beijing 100039,China |
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Abstract Objective To analyze the chip data of multigroup glioblastoma (GBM) gene expression profiles in GEO database using bioinformatics, and to find the HUB genes closely related to the biological behavior of GBM.Methods GBM-related datasets were obtained from the GEO database, and the differentially expressed genes between GBM and normal brain tissue were analyzed via the R language. GO and KEGG databases were used for functional enrichment and functional annotation of differentially expressed genes. STRING database and Cytoscape software were used to construct protein-protein interaction (PPI) to analyze HUB genes, while TCGA database was used to analyze the survival of HUB genes.Results A total of 628 differentially expressed genes were identified, including 87 up-regulated genes and 541 down-regulated ones. Biological processes were concentrated in neurotransmitter secretion, extracellular secretion regulation and chemical synaptic transmission. Through the comparison of different algorithms, 19 HUB genes were finally obtained. The main signal pathways enriched by HUB genes included the signal pathways of retrograde nerves, synaptic vesicular circulation pathways and gaba-related pathways. The expression of GABRD genes was significantly correlated with tumor prognosis.Conclusions The differentially expressed genes found in this study can shed light on the molecular mechanism of GBM, and the HUB genes can be the focus of further research.
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Received: 11 February 2020
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