Data analysis of high-throughput sequencing and microarray to identify key signatures of microribonucleic acids in glioblastoma

Abstract

Purpose of the study. This research was devoted to study of mRNA and miRNA expression patterns in glioglastomas using The Cancer Genome Atlas (TCGA) data, to search for genetic determinants that determine the prognosis of patient survival and to create of interaction networks for glioblastomas.Materials and methods. Based on the data of the open TCGA database groups of glioblastomas and conventionally normal brain tissue samples were formed. Survival gene and miRNA expression data were extracted for each sample. After the data stratification by groups the differential expression analysis and search the genes affecting patient survival was carried out. The enrichment analysis by functional affiliation and an interactome analysis were performed.Results. A total of 156 glioblastoma samples with mRNA sequencing data, 571 samples with microarray microRNA analysis data, and 15 control samples were analyzed. Networks of mRNA-miRNA interactions were built and expression profiles of genes and miRNAs characteristic of glioblastomas were developed. We have determined the genes which aberrant level is associated with survival and shown the pairwise DEG and DE of microRNA correlations.Conclusion. The microRNA-mRNA regulatory pairs identified for glioblastomas can stimulate the development of new therapeutic approaches based on subtype-specific regulatory mechanisms of oncogenesis.

Keywords

• glioblastoma
• the cancer genome atlas
• expression patterns
• mrna-microrna interactions
• prognosis of survival