Identification of Differently Expressed Genes and Pathways in Glioblastoma Multiforme Using Microarray

Abstract

Objective To identify the hub genes and signal pathways of glioblastoma multiforme(GBM) by microarray and bioinformatics analysis method, and to find out the potential markers for early diagnosis and targeted therapy of GBM. Methods The expression profiling data of GBM was obtained from the GEO database. R software was used to screen differentially expressed genes (DEGs), and DEGs was annotated using DAVID online tools for GO ontology and KEGG signaling pathway enrichment. Moreover, protein-protein interaction network(PPI) was constructed and from which the hub genes were selected. Finally, the TCGA database was used to validate the hub genes. Results Samples Pearson correlation analysis showed that the expression profiling was reliable. Totally 2142 DEGs including 968 up-regulated genes and 1174 down-regulated genes were screened. GO and KEGG enrichment showed that the DEGs mainly correlated with cell cycle, cell division and proliferation, synaptic transmission and other biological functions and pathways. Pathway network analysis indicated that MAPK signal pathway played a core regulatory role in the network. In addition, 9 hub genes most related to GBM were screened from PPI network, and further confirmed by TCGA database. Conclusion KEGG signaling pathways and hub genes may reveal the molecular mechanism of the development of GBM, and the hub genes may be used as the molecular marker for early diagnosis and therapeutic targets of GBM.

Keywords

• glioblastoma multiforme
• bioinformatics
• microarray
• differently expressed genes
• diagnosis marker