Identification of key genes and validation of key gene aquaporin 1 on Wilms’ tumor metastasis

Abstract

Background Wilms’ tumor (WT) is one of the most common solid tumors in children with unsatisfactory prognosis, but few molecular prognostic markers have been discovered for it. Many genes are associated with the occurrence and prognosis of WT. This study aimed to explore the key genes and potential molecular mechanisms through bioinformatics and to verify the effects of aquaporin 1 (AQP1) on WT metastasis. Methods Differentially expressed genes (DEGs) were generated from WT gene expression data sets from the Gene Expression Omnibus (GEO) database. Gene functional enrichment analysis was carried out with the Database for Annotation, Visualization and Integrated Discovery (DAVID). A protein–protein interaction network (PPI) was constructed and visualized by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and Cytoscape software. Minimal Common Oncology Data Elements (MCODE) was used to detect the important modules in the PPI network, and the important nodes (genes) in the PPI module were sorted by CytoHubba. RT-qPCR was performed to validate the expression of the key genes in WT. Wound healing and Transwell assays were used to detect the cell migration and invasion abilities of AQP1-overexpressing cells. Phalloidin-iFlour 488 was used to stain the cytoskeleton to observe how AQP1 overexpression affects cytoskeletal microfilament structure. Results A total of 73 co-expressed DEGs were chosen for further investigation. The importance of homeostasis and transmembrane transport of ions and water were highlighted by functional analysis. Gene regulatory network and PPI network were predicted. MCODE plug identified two important modules. Finally, top five key genes were identified using CytoHubba, including Renin (REN), nephrosis 2 (NPHS2), Solute Carrier Family 12 Member 3 (SLC12A3), Solute Carrier Family 12 Member 1 (SLC12A1) and AQP1. The five key genes were mainly enriched in cell volume and ion homeostasis. RT-qPCR confirmed the expression of the five key genes in WT. AQP1 was validated to be expressed at significantly lower levels in WT than in normal tissue. AQP1 overexpression significantly reduced the migratory and invasive capacity of Wit-49 cells, as evidenced by reducing the scratch healing rate and the number of perforated control cells by Wit-49 cells. AQP1 overexpression also reduced the expression of biomarkers of epithelial-mesenchymal transformation, decreased levels of vimentin and N-cadherin and increased expression of E-cadherin, resulting in decreased formation of conspicuous lamellipodial protrusions, characteristic of diminished WT cell invasion and migration. Conclusion Our study reveals the key genes of WT. These key genes may provide novel insight for the mechanism and diagnosis of WT. AQP1 overexpression inhibited invasion, migration, EMT, and cytoskeletal rearrangement of WT cells, indicating that AQP1 plays a role in the pathogenesis of WT.