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

Wang,Xiaofu; Song,Pan; Huang,Chuiguo; Yuan,Naijun; Zhao,Xinghua; Xu,Changbao

doi:10.3892/mmr.2019.9881

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

Authors:
- Xiaofu Wang
- Pan Song
- Chuiguo Huang
- Naijun Yuan
- Xinghua Zhao
- Changbao Xu
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Affiliations: Department of Urology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450014, P.R. China, Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450014, P.R. China, College of Traditional Chinese Medicine, Institute of Integrated Traditional Chinese and Western Medicine, Jinan University, Guangzhou, Guangdong 510632, P.R. China
Published online on: January 21, 2019 https://doi.org/10.3892/mmr.2019.9881
Pages: 2041-2050
Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

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.

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