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Wilms tumor (WT) is one of the most common types of pediatric solid tumors; however, its molecular mechanisms remain unclear. The present study aimed to identify key genes and microRNAs (miRNAs), and to predict the underlying molecular mechanisms of WT using integrated bioinformatics analysis. Original gene expression profiles were downloaded from the Gene Expression Omnibus (GEO; accession, GSE66405) and The Cancer Genome Atlas (TCGA) databases. Similarly, miRNA expression patterns were downloaded from GEO (accession, GSE57370) and TCGA. R version 3.5.0 software was used to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) using the limma and edgeR packages. Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses were performed to examine the biological functions of the DEGs. Additionally, a protein-protein interaction (PPI) network was constructed to screen hub gene modules using Cytoscape software. By predicting target genes of the DEMs and integrating them with DEGs, the present study constructed a miRNA-mRNA regulatory network to predict the possible molecular mechanism of WT. Expression of hub genes was validated using the Oncomine database. A total of 613 genes and 29 miRNAs were identified to be differentially expressed in WT. By constructing a PPI network and screening hub gene modules, 5 upregulated genes, including BUB1 mitotic checkpoint serine/threonine kinase, BUB1B mitotic checkpoint serine/threonine kinase B, cell division cycle protein 45, cyclin B2 and pituitary tumor-transforming 1. These genes were identified to be associated with the cell cycle pathway, which suggested that these genes may serve important roles in WT. In addition, a miRNA-mRNA regulatory network was constructed and comprised 16 DEMs and 19 DEGs. In conclusion, key genes, miRNAs and the mRNA-miRNA regulatory network identified in the present study may improve understanding of the underlying molecular mechanisms in the occurrence and development of WT, and may aid the identification of potential biomarkers and therapeutic targets.

Identification of key genes and microRNAs involved in kidney Wilms tumor by integrated bioinformatics analysis