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Glioma is the most common type of primary brain tumor, which is associated with a poor prognosis due to its aggressive growth behavior and highly invasive nature. Research regarding glioma pathogenesis is expected to provide novel methods of adjuvant therapy for the treatment of glioma. The use of bioinformatics to identify candidate genes is commonly used to understand the genetic basis of disease. The present study used bioinformatics to mine the disease-related genes using gene expression profiles (GSE50021) and dual-channel DNA methylation data (GSE50022). The results identified 17 methylation sites located on 33 transcription factor binding sites, which may be responsible for downregulation of 17 target genes. glutamate metabotropic receptor 2 was one of the 17 downregulated target genes. Furthermore, inositol-trisphosphate 3-kinase A (ITPKA) was revealed to be the gene most associated with the risk of glioma in children. The protein coded by the ITPKA gene appeared in all risk sub-pathways, thus suggesting that ITPKA was the gene most associated with the risk of glioma, and inositol phosphate metabolism may be a key pathway associated with glioma in children. The identification of specific genes helps to determine the pathogenesis and possible therapeutic targets for the treatment of glioma in children.

Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database