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DNA Methylation-Based Panel Predicts Survival of Patients With Clear Cell Renal Cell Carcinoma and Its Correlations With Genomic Metrics and Tumor Immune Cell Infiltration.


ABSTRACT: DNA methylation based prognostic factor for patients with clear cell renal cell carcinoma (ccRCC) remains unclear. In the present study, we identified survival-related DNA methylation sites based on the differentially methylated DNA CpG sites between normal renal tissue and ccRCC. Then, these survival-related DNA methylation sites were included into an elastic net regularized Cox proportional hazards regression (CoxPH) model to build a DNA methylation-based panel, which could stratify patients into different survival groups with excellent accuracies in the training set and test set. External validation suggested that the DNA methylation-based panel could effectively distinguish normal controls from tumor samples and classify patients into metastasis group and non-metastasis group. The nomogram containing DNA methylation-based panel was reliable in clinical settings. Higher total mutation number, SCNA level, and MATH score were associated with higher methylation risk. The innate immune, ratio between CD8+T cell versus Treg cell as well as Th17 cell versus Th2 cell were significantly decreased in high methylation risk group. In inclusion, we developed a DNA methylation-based panel which might be independent prognostic factor in ccRCC. Patients with higher methylation risk were associated genomic alteration and poor immune microenvironment.

SUBMITTER: Liu XP 

PROVIDER: S-EPMC7593608 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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DNA Methylation-Based Panel Predicts Survival of Patients With Clear Cell Renal Cell Carcinoma and Its Correlations With Genomic Metrics and Tumor Immune Cell Infiltration.

Liu Xiao-Ping XP   Ju Lingao L   Chen Chen C   Liu Tongzu T   Li Sheng S   Wang Xinghuan X  

Frontiers in cell and developmental biology 20201015


DNA methylation based prognostic factor for patients with clear cell renal cell carcinoma (ccRCC) remains unclear. In the present study, we identified survival-related DNA methylation sites based on the differentially methylated DNA CpG sites between normal renal tissue and ccRCC. Then, these survival-related DNA methylation sites were included into an elastic net regularized Cox proportional hazards regression (CoxPH) model to build a DNA methylation-based panel, which could stratify patients i  ...[more]

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