Weighted gene co‑expression network analysis for identifying hub genes in association with prognosis in Wilms tumor

Wilms tumor (WT) is the most common type of renal malignancy in children. Survival rates are low and high‑risk WT generally still carries a poor prognosis. To better elucidate the pathogenesis and tumorigenic pathways of high‑risk WT, the present study presents an integrated analysis of RNA expression profiles of high‑risk WT to identify predictive molecular biomarkers, for the improvement of therapeutic decision‑making. mRNA sequence data from high‑risk WT and adjacent normal samples were downloaded from The Cancer Genome Atlas to screen for differentially expressed genes (DEGs) using R software. From 132 Wilms tumor samples and six normal samples, 2,089 downregulated and 941 upregulated DEGs were identified. In order to identify hub DEGs that regulate target genes, weighted gene co‑expression network analysis (WGCNA) was used to identify 11 free‑scale gene co‑expressed clusters. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were annotated using KEGG Orthology Based Annotation System annotation of different module genes. The Search Tool for the Retrieval of Interacting Genes was used to construct a protein‑protein interaction network for the identified DEGs, and the hub genes of WGCNA modules were identified using the Cytohubb plugin with Cytoscape software. Survival analysis was subsequently performed to highlight hub genes with a clinical signature. The present results suggest that epidermal growth factor, cyclin dependent kinase 1, endothelin receptor type A, nerve growth factor receptor, opa‑interacting protein 5, NDC80 kinetochore complex component and cell division cycle associated 8 are essential to high‑risk WT pathogenesis, and they are closely associated with clinical prognosis.