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Identification of Four Pathological Stage-Relevant Genes in Association with Progression and Prognosis in Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis
Joint Authors
Xu, Yuzi
Chen, Dake
Xu, Dengyong
Lv, Yiming
Wu, Fei
Liu, Yunlong
Zhu, Ming
Bai, Bingjun
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-28
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Clear cell renal cell carcinoma (ccRCC) is a major histological subtype of renal cell carcinoma and can be clinically divided into four stages according to the TNM criteria.
Identifying clinical stage-related genes is beneficial for improving the early diagnosis and prognosis of ccRCC.
By using bioinformatics analysis, we aim to identify clinical stage-relevant genes that are significantly associated with the development of ccRCC.
First, we analyzed the gene expression microarray data sets: GSE53757 and GSE73731.
We divided these data into five groups by staging information—normal tissue and ccRCC stages I, II, III, and IV—and eventually identified 500 differentially expressed genes (DEGs).
To obtain precise stage-relevant genes, we subsequently applied weighted gene coexpression network analysis (WGCNA) to the GSE73731 dataset and KIRC data from The Cancer Genome Atlas (TCGA).
Two modules from each dataset were identified to be related to the tumor TNM stage.
Several genes with high inner connection inside the modules were considered hub genes.
The intersection results between hub genes of key modules and 500 DEGs revealed UBE2C, BUB1B, RRM2, and TPX2 as highly associated with the stage of ccRCC.
In addition, the candidate genes were validated at both the RNA expression level and the protein level.
Survival analysis also showed that 4 genes were significantly correlated with overall survival.
In conclusion, our study affords a deeper understanding of the molecular mechanisms associated with the development of ccRCC and provides potential biomarkers for early diagnosis and individualized treatment for patients at different stages of ccRCC.
American Psychological Association (APA)
Xu, Dengyong& Xu, Yuzi& Lv, Yiming& Wu, Fei& Liu, Yunlong& Zhu, Ming…[et al.]. 2020. Identification of Four Pathological Stage-Relevant Genes in Association with Progression and Prognosis in Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis. BioMed Research International،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1132340
Modern Language Association (MLA)
Xu, Dengyong…[et al.]. Identification of Four Pathological Stage-Relevant Genes in Association with Progression and Prognosis in Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis. BioMed Research International No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1132340
American Medical Association (AMA)
Xu, Dengyong& Xu, Yuzi& Lv, Yiming& Wu, Fei& Liu, Yunlong& Zhu, Ming…[et al.]. Identification of Four Pathological Stage-Relevant Genes in Association with Progression and Prognosis in Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1132340
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132340