Open Access

Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database

  • Authors:
    • Anping Wang
    • Guibin Zhang
  • View Affiliations

  • Published online on: September 12, 2017     https://doi.org/10.3892/ol.2017.6922
  • Pages:6040-6044
  • Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The ‘limma’ data packet in ‘R’ software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using ‘RobustRankAggreg’ package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in ‘neurotransmitter:sodium symporter activity’ and ‘neurotransmitter transporter activity’, which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in ‘protein processing in endoplasmic reticulum’, which can affect protein proce­ssing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.

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November 2017
Volume 14 Issue 5

Print ISSN: 1792-1074
Online ISSN:1792-1082

2016 Impact Factor: 1.39
Ranked #68/217 Oncology
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APA
Wang, A., & Wang, A. (2017). Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database. Oncology Letters, 14, 6040-6044. https://doi.org/10.3892/ol.2017.6922
MLA
Wang, A., Zhang, G."Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database". Oncology Letters 14.5 (2017): 6040-6044.
Chicago
Wang, A., Zhang, G."Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database". Oncology Letters 14, no. 5 (2017): 6040-6044. https://doi.org/10.3892/ol.2017.6922