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

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.

Keywords: GO enrichment; KEGG pathway analysis; differential expressed gene; glioblastoma; protein interaction network.

Figure 1.

Results of GO enrichment. Abscissa is the enriched GO, and ordinate is the number and ratio of the differentially expressed genes. Different colors represent different GO classes, namely Molecular function, Biological process, and Cellular component. GO, Gene Ontology.

Figure 2.

The diagram of protein interaction network. Circle represents the gene, and lines represent the protein interaction between the genes, and the information inside the circle describes protein structure: small nodes, protein of unknown 3D structure; large nodes, some 3D structure is known or predicted; a red line indicates the presence of fusion evidence; a green line, neighborhood evidence; a blue line, coocurrence evidence; a purple line, experimental evidence; a yellow line, text mining evidence; a light blue line, database evidence; a black line, coexpression evidence.

Figure 3.

Core protein histogram. The vertical coordinates is the gene name, and the horizontal coordinates is the number of adjacent genes, and the height represents the number of lines connected genes.