Open Access

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

  • Authors:
    • Ting Luo
    • Xiaoyi Chen
    • Shufei Zeng
    • Baozhang Guan
    • Bo Hu
    • Yu Meng
    • Fanna Liu
    • Taksui Wong
    • Yongpin Lu
    • Chen Yun
    • Berthold Hocher
    • Lianghong Yin
  • View Affiliations

  • Published online on: May 30, 2018     https://doi.org/10.3892/ol.2018.8842
  • Pages: 1747-1757
  • Copyright: © Luo et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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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 expression of enolase 2 (ENO2) was associated with short overall survival in ccRCC patients (P=0.023). High mRNA expression of cyclin D1 (CCND1) (P<0.001), fms related tyrosine kinase 1 (FLT1) (P=0.004), plasminogen (PLG) (P<0.001) and von Willebrand factor (VWF) (P=0.008) appeared to serve as favorable factors in survival. These findings indicate that the DEGs may be key genes in ccRCC pathogenesis and five genes, including ENO2, CCND1, PLT1, PLG and VWF, may serve as potential prognostic biomarkers in ccRCC.
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August-2018
Volume 16 Issue 2

Print ISSN: 1792-1074
Online ISSN:1792-1082

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Spandidos Publications style
Luo T, Chen X, Zeng S, Guan B, Hu B, Meng Y, Liu F, Wong T, Lu Y, Yun C, Yun C, et al: Bioinformatic identification of key genes and analysis of prognostic values in clear cell renal cell carcinoma. Oncol Lett 16: 1747-1757, 2018.
APA
Luo, T., Chen, X., Zeng, S., Guan, B., Hu, B., Meng, Y. ... Yin, L. (2018). Bioinformatic identification of key genes and analysis of prognostic values in clear cell renal cell carcinoma. Oncology Letters, 16, 1747-1757. https://doi.org/10.3892/ol.2018.8842
MLA
Luo, T., Chen, X., Zeng, S., Guan, B., Hu, B., Meng, Y., Liu, F., Wong, T., Lu, Y., Yun, C., Hocher, B., Yin, L."Bioinformatic identification of key genes and analysis of prognostic values in clear cell renal cell carcinoma". Oncology Letters 16.2 (2018): 1747-1757.
Chicago
Luo, T., Chen, X., Zeng, S., Guan, B., Hu, B., Meng, Y., Liu, F., Wong, T., Lu, Y., Yun, C., Hocher, B., Yin, L."Bioinformatic identification of key genes and analysis of prognostic values in clear cell renal cell carcinoma". Oncology Letters 16, no. 2 (2018): 1747-1757. https://doi.org/10.3892/ol.2018.8842