Gene expression analyses to explore the biomarkers and therapeutic targets for gliomas

To improve treatment strategies of glioma, microarray data were applied to screen target molecules that were regulated by microRNAs (miRNAs). GSE31262 was downloaded from Gene Expression Omnibus, including five neural stem cells samples from normal human and nine stem cells samples from glioma patients. Differentially expressed genes (DEGs) were identified with Multtest package and Limma package of R language, and false discovery rate < 0.05 and |log2FC (fold change)| >1 were chosen as cut-off criterion. Hierarchical clustering and pathway enrichment analysis of DEGs were performed using pheatmap package of R language and KOBAS software, respectively. miRNAs related to up- and down-regulated DEGs were, respectively, predicted by WebGestalt software and its miRNAs-target DEGs interaction network were, respectively, constructed by STRING database. Bingo plug-in in Cytoscape software was applied to analyze Gene Ontology functional enrichment analysis for up- and down-regulated DEGs in network, respectively. A total of 428 DEGs were selected, including 331 down-regulated and 97 up-regulated DEGs. Hierarchical clustering analysis showed that glioma samples and normal samples were completely separated. Pathway analysis indicated that CDK2 and WEE1 participated in the cell cycle. miR-124 could simultaneously regulate up-regulated (ELAVL1 and EZH2) and down-regulated (BACE1) DEGs. The down-regulated genes (KIF23, WEE1 and CDK2) were associated with cell division, while the up-regulated genes (PLP1 and MBP) were related to myelination of neurons. miR-124 might participate in development of glioma by regulating BACE1, ELAVL1 and EZH2. The biomarkers (KIF23, WEE1, CDK2, PLP1 and MBP) were considered as therapeutic targets of glioma.