Abstract

Gliomas is the most common type of intracranial primary malignant tumor and it accounts for ∼80% of primary malignant tumors of the central nervous system. At present, surgical resection with adjuvant radiotherapy and temozolomide adjuvant chemotherapy combined with radiotherapy are the only standard treatments for glioma. However, but overall survival of patients is only 15 months. Glioma is resistant to radiotherapy and chemotherapy, and this malignant behavior leads to a high recurrence rate. Therefore, the use of therapeutics is usually ineffective. As a result, patients with glioma do not significantly benefit from standard treatment. There is therefore an urgent need to develop novel diagnostic approaches and, in particular, more effective treatment strategies. The application of gene expression microarrays provides a feasible and effective way to study gliomas. The present study therefore aimed to identify the key protein-coding genes of glioma using bioinformatics methods and thereby search, for novel biomarkers and therapeutic targets for the treatment of glioma. First, mRNA microarray datasets were selected and obtained from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) between gliomas and normal tissues. The DEGs were clarified using Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), Protein-Protein Interaction (PPI) network and statistical analysis. Subsequently, reverse transcription-quantitative PCR (RT-qPCR)and western blot were used to verify the results of the bioinformatics analysis. A total of 400 DEGs were identified in glioma and they were enriched in several cancer-related GO and KEGG pathways.