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

Cheng Su; Jie Zheng; Siyu Chen; Jinwei Tuo; Jinxia Su; Xiuyi Ou; Shaohua Chen; Congjun Wang

doi:10.21037/atm-22-4477

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

Ann Transl Med. 2022 Nov;10(22):1204. doi: 10.21037/atm-22-4477.

Authors

Cheng Su^#¹, Jie Zheng^#², Siyu Chen¹, Jinwei Tuo¹, Jinxia Su¹, Xiuyi Ou¹, Shaohua Chen², Congjun Wang¹

Affiliations

¹ Department of Pediatric Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
² Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.

^# Contributed equally.

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.

Keywords: Cancer stem cell (CSC); Wilms’ tumor (WT); mRNAsi; protein interaction network; weighted gene co-expression network analysis (WGCNA).