Bioinformatic identification of key genes and analysis of prognostic values in clear cell renal cell carcinoma

Oncology Letters
Ting LuoLianghong Yin

Abstract

The present study aimed to identify new key genes as potential biomarkers for the diagnosis, prognosis or targeted therapy of clear cell renal cell carcinoma (ccRCC). Three expression profiles (GSE36895, GSE46699 and GSE71963) were collected from Gene Expression Omnibus. GEO2R was used to identify differentially expressed genes (DEGs) in ccRCC tissues and normal samples. The Database for Annotation, Visualization and Integrated Discovery was utilized for functional and pathway enrichment analysis. STRING v10.5 and Molecular Complex Detection were used for protein-protein interaction (PPI) network construction and module analysis, respectively. Regulation network analyses were performed with the WebGestal tool. UALCAN web-portal was used for expression validation and survival analysis of hub genes in ccRCC patients from The Cancer Genome Atlas (TCGA). A total of 65 up- and 164 downregulated genes were identified as DEGs. DEGs were enriched with functional terms and pathways compactly related to ccRCC pathogenesis. Seventeen hub genes and one significant module were filtered out and selected from the PPI network. The differential expression of hub genes was verified in TCGA patients. Kaplan-Meier plot showed that high mRNA expres...Continue Reading

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Citations

Feb 11, 2020·Molecular Carcinogenesis·Takashi TsuyukuboTamotsu Sugai
Nov 27, 2020·Frontiers in Genetics·Jose María Zamora-FuentesJesús Espinal-Enríquez
May 29, 2021·Frontiers in Oncology·Natalya ApanovichAlexander Karpukhin

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Datasets Mentioned

BETA
GSE46699
GSE71963

Software Mentioned

Overrepresentation Enrichment Analysis ( ORA )
Cytoscape
STRING
GEO2R
DAVID
WebGestal
The Database for Annotation , Visualization and Integrated Dis...
Cytoscape Complex Detection (
MCODE
UALCAN

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