DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management. Issue 13 (12th June 2020)

• Record Type: Journal Article
• Authors: Ma, Xianxiong; Cheng, Jiancheng; Zhao, Peng; Li, Lei; Tao, Kaixiong; Chen, Hengyu
• Is Part Of: Journal of cellular and molecular medicine. Volume 24:Issue 13(2020)
• Page Start: 7576
• Page End: 7589
• Publication Date: 2020-06-12
• Subjects: DNA methylation -- LUAD -- nomogram -- recurrence‐free survival -- signature; Cytology; Medicine; Molecular Biology; Cytologie -- Périodiques; Médecine -- Périodiques; Biologie moléculaire -- Périodiques; Cytology -- Periodicals; Medicine -- Periodicals; Molecular biology -- Periodicals; 611.01805
• DOI: 10.1111/jcmm.15393
• Languages: English
• ISSNs: 1582-1838

Abstract

Abstract: Increasing evidence suggested DNA methylation may serve as potential prognostic biomarkers; however, few related DNA methylation signatures have been established for prediction of lung cancer prognosis. We aimed at developing DNA methylation signature to improve prognosis prediction of stage I lung adenocarcinoma (LUAD). A total of 268 stage I LUAD patients from the Cancer Genome Atlas (TCGA) database were included. These patients were separated into training and internal validation datasets. GSE39279 was used as an external validation set. A 13‐DNA methylation signature was identified to be crucially relevant to the relapse‐free survival (RFS) of patients with stage I LUAD by the univariate Cox proportional hazard analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and multivariate Cox proportional hazard analysis in the training dataset. The Kaplan‐Meier analysis indicated that the 13‐DNA methylation signature could significantly distinguish the high‐ and low‐risk patients in entire TCGA dataset, internal validation and external validation datasets. The receiver operating characteristic (ROC) analysis further verified that the 13‐DNA methylation signature had a better value to predict the RFS of stage I LUAD patients in internal validation, external validation and entire TCGA datasets. In addition, a nomogram combining methylomic risk scores with other clinicopathological factors was performed and the result suggested the good predictive value of the nomogram. In conclusion, we successfully built a DNA methylation‐associated nomogram, enabling prediction of the RFS of patients with stage I LUAD.