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DNA methylation regulator-based signature for predicting clear cell renal cell carcinoma prognosis.


ABSTRACT:

Objectives

To investigate the role of DNA methylation regulators in the prognosis of clear cell renal cell carcinoma (ccRCC) and to construct a DNA methylation regulator-based signature for predicting patient outcome.

Methods

Data from the TCGA dataset were downloaded and analyzed to identify differentially expressed DNA methylation regulators and their interaction as well as correlation. Consensus clustering was used to establish groups of ccRCC with distinct clinical outcomes. A prognostic signature based on two sets of DNA methylation regulators was established and validated in an independent cohort.

Results

Our analysis revealed that the expression levels of DNMT3B, MBD1, SMUG1, DNMT1, DNMT3A, TDG, TET3, MBD2, UHRF2, MBD3, UHRF1, and TET2 were significantly upregulated in ccRCC samples, while UNG, ZBTB4, TET1, ZBTB38, and MECP2 were markedly downregulated. UHRF1 was identified as a hub gene in the DNA methylation regulator interaction network. Significant differences were found regarding overall survival, gender, tumor status, and grade between ccRCC patients in the two risk groups. The prognostic signature, based on two sets of DNA methylation regulators, was an independent prognostic indicator, and these findings were validated in an external, independent cohort.

Conclusions

The study provides evidence that DNA methylation regulators play a significant role in the prognosis of ccRCC and the developed DNA methylation regulator-based signature could effectively predict patient outcome.

SUBMITTER: Gong W 

PROVIDER: S-EPMC10182479 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

DNA methylation regulator-based signature for predicting clear cell renal cell carcinoma prognosis.

Gong Wenliang W   Yang Runan R   Wang Zhenmeng Z  

American journal of translational research 20230415 4


<h4>Objectives</h4>To investigate the role of DNA methylation regulators in the prognosis of clear cell renal cell carcinoma (ccRCC) and to construct a DNA methylation regulator-based signature for predicting patient outcome.<h4>Methods</h4>Data from the TCGA dataset were downloaded and analyzed to identify differentially expressed DNA methylation regulators and their interaction as well as correlation. Consensus clustering was used to establish groups of ccRCC with distinct clinical outcomes. A  ...[more]

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