A novel CpG-based signature for survival prediction of lung adenocarcinoma patients

Lung adenocarcinoma (LACA) is the leading cause of cancer-associated death worldwide. The present study intended to identify DNA methylation patterns that may serve as diagnostic and prognostic biomarkers for LACA. Data on DNA methylation and the survival data of the patients of LACA were obtained f...

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Autores principales: Zheng, Rongjiong, Xu, Haiqi, Mao, Wenjie, Du, Zhennan, Wang, Mingming, Hu, Meiling, Gu, Xiaolong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909784/
https://www.ncbi.nlm.nih.gov/pubmed/31853300
http://dx.doi.org/10.3892/etm.2019.8200
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author Zheng, Rongjiong
Xu, Haiqi
Mao, Wenjie
Du, Zhennan
Wang, Mingming
Hu, Meiling
Gu, Xiaolong
author_facet Zheng, Rongjiong
Xu, Haiqi
Mao, Wenjie
Du, Zhennan
Wang, Mingming
Hu, Meiling
Gu, Xiaolong
author_sort Zheng, Rongjiong
collection PubMed
description Lung adenocarcinoma (LACA) is the leading cause of cancer-associated death worldwide. The present study intended to identify DNA methylation patterns that may serve as diagnostic and prognostic biomarkers for LACA. Data on DNA methylation and the survival data of the patients of LACA were obtained from The Cancer Genome Atlas. Kaplan-Meier curves and receiver operating characteristic curve analysis were utilized to build diagnostic and prognostic models. A total of 13 CpG sites were identified and validated as the optimal diagnostic and prognostic signature for overall survival. It was concluded that the CpG-based signature is a reliable predictor for the diagnosis and prognosis of patients with LACA.
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spelling pubmed-69097842019-12-18 A novel CpG-based signature for survival prediction of lung adenocarcinoma patients Zheng, Rongjiong Xu, Haiqi Mao, Wenjie Du, Zhennan Wang, Mingming Hu, Meiling Gu, Xiaolong Exp Ther Med Articles Lung adenocarcinoma (LACA) is the leading cause of cancer-associated death worldwide. The present study intended to identify DNA methylation patterns that may serve as diagnostic and prognostic biomarkers for LACA. Data on DNA methylation and the survival data of the patients of LACA were obtained from The Cancer Genome Atlas. Kaplan-Meier curves and receiver operating characteristic curve analysis were utilized to build diagnostic and prognostic models. A total of 13 CpG sites were identified and validated as the optimal diagnostic and prognostic signature for overall survival. It was concluded that the CpG-based signature is a reliable predictor for the diagnosis and prognosis of patients with LACA. D.A. Spandidos 2020-01 2019-11-15 /pmc/articles/PMC6909784/ /pubmed/31853300 http://dx.doi.org/10.3892/etm.2019.8200 Text en Copyright: © Zheng et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Zheng, Rongjiong
Xu, Haiqi
Mao, Wenjie
Du, Zhennan
Wang, Mingming
Hu, Meiling
Gu, Xiaolong
A novel CpG-based signature for survival prediction of lung adenocarcinoma patients
title A novel CpG-based signature for survival prediction of lung adenocarcinoma patients
title_full A novel CpG-based signature for survival prediction of lung adenocarcinoma patients
title_fullStr A novel CpG-based signature for survival prediction of lung adenocarcinoma patients
title_full_unstemmed A novel CpG-based signature for survival prediction of lung adenocarcinoma patients
title_short A novel CpG-based signature for survival prediction of lung adenocarcinoma patients
title_sort novel cpg-based signature for survival prediction of lung adenocarcinoma patients
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909784/
https://www.ncbi.nlm.nih.gov/pubmed/31853300
http://dx.doi.org/10.3892/etm.2019.8200
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