Research Papers:

Identifying prognostic biomarkers based on aberrant DNA methylation in kidney renal clear cell carcinoma

Guang Chen _, Yihan Wang, Lu Wang and Wanhai Xu

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Oncotarget. 2017; 8:5268-5280. https://doi.org/10.18632/oncotarget.14134

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Guang Chen1,*, Yihan Wang2,*, Lu Wang1, Wanhai Xu1

1Department of Urology, The 4th Affiliated Hospital of Harbin Medical University, Harbin 150001, China

2College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China

*These authors have contributed equally to this work

Correspondence to:

Wanhai Xu, email: [email protected]

Keywords: kidney renal clear cell carcinoma, DNA methylation, prognosis, network, gene expression

Received: July 28, 2016     Accepted: November 22, 2016     Published: December 24, 2016


The outcome of kidney renal clear cell carcinoma (KIRC) differs even among individuals with similar clinical characteristics. DNA methylation is regarded as a regulator of gene expression in cancers, which may be a molecular marker of prognosis. In this study, we aimed to mine novel methylation markers of the prognosis of KIRC. We revealed a total of 2793 genes differentially methylated in their promoter regions (DMGs) and 2979 differentially expressed genes (DEGs) in KIRC tissues compared with normal tissues using The Cancer Genome Atlas datasets. Then, we detected 57 and 34 subpathways enriched among the DMGs and DEGs, respectively, using the R package iSubpathwayMiner. We retained 56 subpathways related to both aberrant methylation and expression based on a hypergeometric test for further analysis. An integrated gene regulatory network was constructed using the regulatory relationships between genes in the subpathways. Using the top 15% of the nodes from the network ranked by degree, survival analysis was performed. We validated four DNA methylation signatures (RAC2, PLCB2, VAV1, and PARVG) as being highly correlated with prognosis in KIRC. These findings suggest that DNA methylation might become a prognostic predictor in KIRC and could supplement histological prognostic prediction.

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