Cargando…

DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Ma, Xianxiong, Cheng, Jiancheng, Zhao, Peng, Li, Lei, Tao, Kaixiong, Chen, Hengyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7339160/
https://www.ncbi.nlm.nih.gov/pubmed/32530136
http://dx.doi.org/10.1111/jcmm.15393
_version_ 1783554833197826048
author Ma, Xianxiong
Cheng, Jiancheng
Zhao, Peng
Li, Lei
Tao, Kaixiong
Chen, Hengyu
author_facet Ma, Xianxiong
Cheng, Jiancheng
Zhao, Peng
Li, Lei
Tao, Kaixiong
Chen, Hengyu
author_sort Ma, Xianxiong
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7339160
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-73391602020-07-13 DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management Ma, Xianxiong Cheng, Jiancheng Zhao, Peng Li, Lei Tao, Kaixiong Chen, Hengyu J Cell Mol Med Original Articles 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. John Wiley and Sons Inc. 2020-06-12 2020-07 /pmc/articles/PMC7339160/ /pubmed/32530136 http://dx.doi.org/10.1111/jcmm.15393 Text en © 2020 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Ma, Xianxiong
Cheng, Jiancheng
Zhao, Peng
Li, Lei
Tao, Kaixiong
Chen, Hengyu
DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management
title DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management
title_full DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management
title_fullStr DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management
title_full_unstemmed DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management
title_short DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management
title_sort dna methylation profiling to predict recurrence risk in stage ι lung adenocarcinoma: development and validation of a nomogram to clinical management
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7339160/
https://www.ncbi.nlm.nih.gov/pubmed/32530136
http://dx.doi.org/10.1111/jcmm.15393
work_keys_str_mv AT maxianxiong dnamethylationprofilingtopredictrecurrenceriskinstageilungadenocarcinomadevelopmentandvalidationofanomogramtoclinicalmanagement
AT chengjiancheng dnamethylationprofilingtopredictrecurrenceriskinstageilungadenocarcinomadevelopmentandvalidationofanomogramtoclinicalmanagement
AT zhaopeng dnamethylationprofilingtopredictrecurrenceriskinstageilungadenocarcinomadevelopmentandvalidationofanomogramtoclinicalmanagement
AT lilei dnamethylationprofilingtopredictrecurrenceriskinstageilungadenocarcinomadevelopmentandvalidationofanomogramtoclinicalmanagement
AT taokaixiong dnamethylationprofilingtopredictrecurrenceriskinstageilungadenocarcinomadevelopmentandvalidationofanomogramtoclinicalmanagement
AT chenhengyu dnamethylationprofilingtopredictrecurrenceriskinstageilungadenocarcinomadevelopmentandvalidationofanomogramtoclinicalmanagement