期刊
MATHEMATICAL BIOSCIENCES AND ENGINEERING
卷 18, 期 6, 页码 8559-8576出版社
AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/mbe.2021424
关键词
signature; DNA methylation; kidney renal clear cell carcinoma; recurrence free survival; nomogram
资金
- National Nature Science Foundation of China [82073324]
The study successfully identified a 9-DNA methylation signature for predicting recurrence free survival in kidney renal clear cell carcinoma patients. The robustness of the methylation signature was validated through ROC analysis in internal and external datasets. Additionally, a nomogram combining methylation risk score with clinic-related covariates showed good performance in improving prognostic predictive ability for KIRC patients.
Background: Various studies have suggested that the DNA methylation signatures were promising to identify novel hallmarks for predicting prognosis of cancer. However, few studies have explored the capacity of DNA methylation for prognostic prediction in patients with kidney renal clear cell carcinoma (KIRC). It's very promising to develop a methylomics-related signature for predicting prognosis of KIRC. Methods: The 282 patients with complete DNA methylation data and corresponding clinical information were selected to construct the prognostic model. The 282 patients were grouped into a training set (70%, n = 198 samples) to determine a prognostic predictor by univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. The internal validation set (30%, n = 84) and an external validation set (E-MTAB-3274) were used to validate the predictive value of the predictor by receiver operating characteristic (ROC) analysis and Kaplan-Meier survival analysis. Results: We successfully identified a 9-DNA methylation signature for recurrence free survival (RFS) of KIRC patients. We proved the strong robustness of the 9-DNA methylation signature for predicting RFS through ROC analysis (AUC at 1, 3, 5 years in internal dataset (0.859, 0.840, 0.817, respectively), external validation dataset (0.674, 0.739, 0.793, respectively), entire TCGA dataset (0.834, 0.862, 0.842, respectively)). In addition, a nomogram combining methylation risk score with the conventional clinic-related covariates was constructed to improve the prognostic predicted ability for KIRC patients. The result implied a good performance of the nomogram. Conclusions: we successfully identified a DNA methylation-associated nomogram, which was helpful in improving the prognostic predictive ability of KIRC patients.
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