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An integrative analysis of DNA methylation and gene expression to predict lung adenocarcinoma prognosis

Background: Abnormal DNA methylation of gene promoters is an important feature in lung adenocarcinoma (LUAD). However, the prognostic value of DNA methylation remains to be further explored. Objectives. We sought to explore DNA methylation characteristics and develop a quantifiable criterion related...

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Autores principales: Xu, Liexi, Huang, Zhengrong, Zeng, Zihang, Li, Jiali, Xie, Hongxin, Xie, Conghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9465336/
https://www.ncbi.nlm.nih.gov/pubmed/36105089
http://dx.doi.org/10.3389/fgene.2022.970507
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author Xu, Liexi
Huang, Zhengrong
Zeng, Zihang
Li, Jiali
Xie, Hongxin
Xie, Conghua
author_facet Xu, Liexi
Huang, Zhengrong
Zeng, Zihang
Li, Jiali
Xie, Hongxin
Xie, Conghua
author_sort Xu, Liexi
collection PubMed
description Background: Abnormal DNA methylation of gene promoters is an important feature in lung adenocarcinoma (LUAD). However, the prognostic value of DNA methylation remains to be further explored. Objectives. We sought to explore DNA methylation characteristics and develop a quantifiable criterion related to DNA methylation to improve survival prediction for LUAD patients. Methods: Illumina Human Methylation450K array data, level 3 RNA-seq data and corresponding clinical information were obtained from TCGA. Cox regression analysis and the Akaike information criterion were used to construct the best-prognosis methylation signature. Receiver operating characteristic curve analysis was used to validate the prognostic ability of the DNA methylation-related feature score. qPCR was used to measure the transcription levels of the identified genes upon methylation. Results: We identified a set of DNA methylation features composed of 11 genes (MYEOV, KCNU1, SLC27A6, NEUROD4, HMGB4, TACR3, GABRA5, TRPM8, NLRP13, EDN3 and SLC34A1). The feature score, calculated based on DNA methylation features, was independent of tumor recurrence and TNM stage in predicting overall survival. Of note, the combination of this feature score and TNM stage provided a better overall survival prediction than either of them individually. The transcription levels of all the hypermethylated genes were significantly increased after demethylation, and the expression levels of 3 hypomethylated proteins were significantly higher in tumor tissues than in normal tissues, as indicated by immunohistochemistry data from the Human Protein Atlas. Our results suggested that these identified genes with prognostic features were regulated by DNA methylation of their promoters. Conclusion: Our studies demonstrated the potential application of DNA methylation markers in the prognosis of LUAD.
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spelling pubmed-94653362022-09-13 An integrative analysis of DNA methylation and gene expression to predict lung adenocarcinoma prognosis Xu, Liexi Huang, Zhengrong Zeng, Zihang Li, Jiali Xie, Hongxin Xie, Conghua Front Genet Genetics Background: Abnormal DNA methylation of gene promoters is an important feature in lung adenocarcinoma (LUAD). However, the prognostic value of DNA methylation remains to be further explored. Objectives. We sought to explore DNA methylation characteristics and develop a quantifiable criterion related to DNA methylation to improve survival prediction for LUAD patients. Methods: Illumina Human Methylation450K array data, level 3 RNA-seq data and corresponding clinical information were obtained from TCGA. Cox regression analysis and the Akaike information criterion were used to construct the best-prognosis methylation signature. Receiver operating characteristic curve analysis was used to validate the prognostic ability of the DNA methylation-related feature score. qPCR was used to measure the transcription levels of the identified genes upon methylation. Results: We identified a set of DNA methylation features composed of 11 genes (MYEOV, KCNU1, SLC27A6, NEUROD4, HMGB4, TACR3, GABRA5, TRPM8, NLRP13, EDN3 and SLC34A1). The feature score, calculated based on DNA methylation features, was independent of tumor recurrence and TNM stage in predicting overall survival. Of note, the combination of this feature score and TNM stage provided a better overall survival prediction than either of them individually. The transcription levels of all the hypermethylated genes were significantly increased after demethylation, and the expression levels of 3 hypomethylated proteins were significantly higher in tumor tissues than in normal tissues, as indicated by immunohistochemistry data from the Human Protein Atlas. Our results suggested that these identified genes with prognostic features were regulated by DNA methylation of their promoters. Conclusion: Our studies demonstrated the potential application of DNA methylation markers in the prognosis of LUAD. Frontiers Media S.A. 2022-08-29 /pmc/articles/PMC9465336/ /pubmed/36105089 http://dx.doi.org/10.3389/fgene.2022.970507 Text en Copyright © 2022 Xu, Huang, Zeng, Li, Xie and Xie. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Xu, Liexi
Huang, Zhengrong
Zeng, Zihang
Li, Jiali
Xie, Hongxin
Xie, Conghua
An integrative analysis of DNA methylation and gene expression to predict lung adenocarcinoma prognosis
title An integrative analysis of DNA methylation and gene expression to predict lung adenocarcinoma prognosis
title_full An integrative analysis of DNA methylation and gene expression to predict lung adenocarcinoma prognosis
title_fullStr An integrative analysis of DNA methylation and gene expression to predict lung adenocarcinoma prognosis
title_full_unstemmed An integrative analysis of DNA methylation and gene expression to predict lung adenocarcinoma prognosis
title_short An integrative analysis of DNA methylation and gene expression to predict lung adenocarcinoma prognosis
title_sort integrative analysis of dna methylation and gene expression to predict lung adenocarcinoma prognosis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9465336/
https://www.ncbi.nlm.nih.gov/pubmed/36105089
http://dx.doi.org/10.3389/fgene.2022.970507
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