Screening function enrichment and related signaling pathways bioinformatics analysis of differentially expressed gene in glioma

Abstract

Objective: To screen the differentially expressed genes, functional enrichment and related signaling pathways in glioma by bioinformatics analysis. Methods: Microarray data of glioma related gene expression profiles were selected in GEO database, and differentially expressed genes in glioma patients and normal brain tissues were screened by R statistical software of lima package. Functional enrichment of differentially expressed genes (GO and KEGG) was performed. The protein-protein interaction database (STRING) was used to analyze the interaction between the screened differentially expressed genes and the related signaling pathways. Results: Two gene expression profiles, GSE15824 and GSE66354, were selected for analysis, and 158 genes with differential expression more than 2 times and P<0.05 were screened. Molecular function (MF) of 158 differentially expressed genes was integrin binding, cell adhesion molecule binding, calcium binding and AMPA glutamate receptor activity. Cell component localization (CC) was located in cell membrane, neuron cell body, axon of nerve cell and so on, while biological process (BP) was mainly cell adhesion and nervous system. Development, cell proliferation, GTPase activity, apoptosis and angiogenesis; KEGG signaling pathways were mainly cAMP signaling pathway, purine metabolism pathway, MAPK signaling pathway and cGMP-PKG signaling pathway. There were 177 interaction connections in 158 differential expression gene-protein interaction networks, with an average interaction of 2.39 between each node and an aggregation coefficient of 0.37. Cytohubb screened the key genes (hub genes) in the signaling pathway. The results indicated that SLC6A1,SLC1A2,BDNF,GAP43,NRXN1,GAD1,OLIG2, PLP1,S100B and GRIA3 were the key genes in the signaling pathway of the interacting protein network. All the 10 key genes were related to the prognosis of patients (P<0.05). Conclusions: There are differentially expressed genes profile in glioma tissues and normal tissues. SLC6A1, SLC1A2, BDNF, GAP43, NRXN1, GAD1, OLIG2, PLP1, S100B and GRIA3 are key genes for glioma development and are related to the prognosis of patients.