A predictive analysis approach for paediatric and adult high-grade glioma: miRNAs and network insight.

Background: Brain tumours are the most common solid tumour in children and are a cause of mortality in adults. Most cases of brain tumour-related death are attributed to glioblastoma (GBM), with an elevated rate for high-grade glioma (HGG). Showing strong heterogeneity, the lesion location, molecule expression and type of HGG differ between adults and children. However, with regard to pathogenesis, brain tumours are expected to have the same underlying molecular processes.

Methods: In this study, we obtained data from the Gene Expression Omnibus (GEO) database to analyse molecular expression in HGG between adults and children. The same and different mutations were identified in these groups, and the genes involved were compared using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Molecular analysis revealed the same trend of differences between children and adults, which was verified in The Cancer Genome Atlas (TCGA).

Results: A total of 12 microarrays including 455 HGG patients were screened. Through a rigorous intersecting process, we identified miR-10a, miR-10b, and miR-139 as having common differences, as well as 6 target genes, such as and , etc. And 12 long noncoding RNAs (lncRNAs).

Conclusions: We identified that these key molecules are involved in development and progression of HGG between adults and children. The findings provide a comprehensive description of the similarities in advanced diseases between adults and children and molecular diagnostic directions for precision small-molecule medicine to treat HGG in different age populations.