Identification of key genes associated with cancer stem cell characteristics in Wilms’ tumor based on bioinformatics analysis

Abstract

Background: Nephroblastoma, also known as Wilms' tumor (WT), remains one of the major causes of tumor-related deaths worldwide in children. Cancer stem cells (CSCs) are considered to be the main culprits in cancer resistance and disease recurrence, which are reported in multiple types of tumors. However, the research on CSCs in WT is limited. Therefore, our study aimed to identify the key genes related to CSCs in WT to provide new ideas for treating WT. Methods:The RNA-seq and clinical data of WT samples were obtained from the University of California Santa Cruz (UCSC) Xena database, which included 120 WT and six para-cancerous tissues.The mRNA stemness index (mRNAsi) based on mRNA expression was calculated to evaluate tumor stem cell characteristics in WT patients. A Kaplan-Meier (KM) analysis was performed to explore the clinical characteristics of the mRNAsi in WT. A weighted gene co-expression network analysis (WGCNA) was used to identify the key modules and genes related to the mRNAsi. A Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was performed to explore the signaling pathways based on the key genes. The expression levels of the key genes were validated by the Gene Expression Omnibus (GEO) database. Further, the important upstream genes were identified by DisNor and gene co-expression analyses. Results:The mRNAsi was significantly upregulated in WT (P=7.2e-05) and showed an upward trend in line with the pathological stage. Patients with lower mRNAsi scores had better overall survival (OS) than those with higher mRNAsi scores (P=0.0087). Eleven genes were defined as the key genes associated with the mRNAsi based on our WGCNA analysis [cor.MM (correlation. Module membership) >0.8 and cor. GS (correlation. Gene significance) >0.45] and were closely related to cell proliferation-related signaling pathways (P<0.05). Moreover, using protein interaction analysis, we identified ATM and CDKN1A as the key upstream regulatory genes of the 11 key genes.Conclusions: Our study showed that the mRNAsi score was a potential prognostic factors in WT and identified the upstream genes ATM and CDKN1A and 11 genes closely related to the mRNAsi, which may provide new insights for CSC-targeted therapy in WT and improve clinical outcomes for WT patients.

Cancer predisposition signaling in Beckwith-Wiedemann Syndrome drives Wilms tumor development

“…Modules enriched for altered-11p15 nonBWS-WT trait mainly showed enrichment of cell cycle and metabolic processes. Many other studies on WT using the WGCNA approach have showed enrichment of cell cycle related processes, indicating it as a major molecular signature for WT [ 77 – 79 ]. Along with metabolic pathway enrichment, Wang et al have also shown enrichment of PI3K-Akt, FoxO, p53, and TNF signaling pathways, along with many other cancer related pathways in WT, using the WGCNA approach [ 78 ].…”

Nephroblastoma-specific dysregulated gene SNHG15 with prognostic significance: scRNA-Seq with bulk RNA-Seq data and experimental validation

“…The uniformly normalized pan-cancer dataset was downloaded from the UCSC database ( https://xenabrowser.net/ ) (Access date: September 15, 2022). The GSE66405 dataset in the GEO database can be employed to verify whether there are differences in the expression of SNHG15 [ 13 , 14 ].…”

Bioinformatical analysis of the key differentially expressed genes for screening potential biomarkers in Wilms tumor

“…Identification of differentially expressed genes. In this study, we searched the GEO database and selected two gene expression profiles (GSE66405 and GSE11024) [29][30][31] . These GSE datasets were downloaded from the NCBI database and all GSE datasets consisted of two groups: WT and normal tissue.…”