Litcius/Paper detail

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

Anqi Liu, Hengyu Zhao, Banghao Sun, Xue Han, Danyang Zhou, Zhongqi Cui, Xiaoyu Ma, Jianan Zhang, Lijie Yuan

2020Annals of Translational Medicine16 citationsDOIOpen Access PDF

Abstract

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: , 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.

Topics & Concepts

KEGGGliomamicroRNAGeneDNA microarrayComputational biologyBiologyBioinformaticsGene expression profilingMedicineGene expressionOncologyCancer researchGeneticsTranscriptomeGlioma Diagnosis and TreatmentCancer-related molecular mechanisms researchFerroptosis and cancer prognosis
A predictive analysis approach for paediatric and adult high-grade glioma: miRNAs and network insight | Litcius