Bioinformatics analysis of neuroblastoma miRNA based on GEO data

Abstract

Objective: To analyze the changes in downstream genes, signaling pathways, and proteins based on the difference of microRNA (miRNA) expression in neuroblastoma (NB). Methods: GSE128004 second-generation sequencing expression data were downloaded from GEO, and Limma package of R language was used to analyze differential expression, and a volcano map and heat map were drawn; the target genes corresponding to the differential miRNA were found using the miWalk web tool, and GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) were performed. The key genes were identified and verified in the TCGA database. Results: A total of 34 differentially expressed miRNAs were screened out. Among them, 22 up-regulated miRNAs predicted 1163 target genes and 12 down-regulated miRNAs predicted 1474 target genes. Target genes were enriched and analyzed by KEGG to find the FOXO signal pathway, mTOR signal pathway, AMPK signal pathway, and other signal pathways. After GO analysis, axon formation, regulation of chemical synaptic transmitters, regulation of nerve synapses, regulation of cross-synaptic signals, and other physiological processes were assessed. A total of 16 key genes were obtained by PPI analysis, and the survival analysis of TP53 and ATM genes verified in the TCGA database showed statistical significance. Conclusion: The 34 differential miRNAs may be related to the occurrence and development of NB. TP53 and ATM are related to the prognosis of NB. The role and mechanism of TP53 and ATM in NB need to be further verified.