Abstract

BackgroundRecently, increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC).MethodsWe used the DNA methylation dataset of The Cancer Genome Atlas (TCGA) database to construct a 31-CpG-based signature which could accurately predict the overall survival of ccRCC. Meanwhile, we constructed a nomogram to predict the prognosis of patients with ccRCC.ResultThrough LASSO Cox regression analysis, we obtained the 31-CpG-based epigenetic signature which were significantly related to the prognosis of ccRCC. According to the epigenetic signature, patients were divided into two groups with high and low risk, and the predictive value of the epigenetic signature was verified by other two sets. In the training set, hazard ratio (HR) = 13.0, 95% confidence interval (CI) 8.0–21.2, P < 0.0001; testing set: HR = 4.1, CI 2.2–7.7, P < 0.0001; entire set: HR = 7.2, CI 4.9–10.6, P < 0.0001, Moreover, combined with clinical indicators, the prediction of 5-year survival of ccRCC reached an AUC of 0.871.ConclusionsOur study constructed a 31-CpG-based epigenetic signature that could accurately predicted overall survival of ccRCC and staging progression of ccRCC. At the same time, we constructed a nomogram, which may facilitate the prediction of prognosis for patients with ccRCC.

Highlights

  • Increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma

  • We constructed a nomogram, which may facilitate the prediction of prognosis for patients with clear cell renal cell carcinoma (ccRCC)

  • Our results identified a new 31-CpG-based epigenetic marker that may be a new target for predicting overall survival of ccRCC

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Summary

Introduction

Increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC). Renal cell carcinoma (RCC) is a cancer that originates in the renal epithelial cells and accounts for more than 90% of renal cancer, of which clear cell RCC (ccRCC) is most common subtype and causes the most deaths [1]. Rather than using only one marker to construct a prognostic model, will make the results more stable and reliable, and improve its predictive value [8]. Many studies have used multiple targets to construct the prognostic model of ccRCC [9, 10]. We used the methylation data of the ccRCC of TCGA database to construct a 31-CpG-based signature

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