Prediction and analysis of hub genes between glioblastoma and low-grade glioma using bioinformatics analysis.

Gliomas are an intractable tumor in the central nervous system. The present study aimed to identify the differentially expressed genes (DEGs) between glioblastoma multiforme (GBM) and low-grade gliomas (LGG) in order to investigate the mechanisms of different grades of gliomas. The Cancer Genome Atlas (TCGA) database was used to identify DEGs between GBM and LGG, and 2641 genes have been found differentially expressed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to determine the related functions and pathways of DEGs. Protein-protein interaction (PPI) network extracted a total of 444 nodes and 1953 interactions, and identified the top 6 hub genes in gliomas. The microarray data of the datasets GSE52009 and GSE4412, which were obtained from Gene Expression Omnibus (GEO) database, were used to externally validate DEGs expression levels. Gene Expression Profiling Interactive Analysis (GEPIA) database which was based on TCGA was used to explore the survival of hub genes in LGG and GBM. Additionally, the Oncomine database and Chinese Glioma Genome Atlas (CGGA) database were used to validate the mRNA expression level and prognostic value of hub genes. Gene Set Enrichment Analysis (GSEA) identified further hub genes-related pathways. In summary, through biological information and survival analysis, 6 hub genes may be new biomarkers for diagnosis and for guiding the choice of treatment strategies for different grades of gliomas.