Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung Adenocarcinoma

BackgroundN6-methyladenosine (m6A) RNA modification is vital for cancers because methylation can alter gene expression and even affect some functional modification. Our study aimed to analyze m6A RNA methylation regulators and m6A-related genes to understand the prognosis of early lung adenocarcinom...

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Main Authors: Bingzhou Guo, Hongliang Zhang, Jinliang Wang, Rilige Wu, Junyan Zhang, Qiqin Zhang, Lu Xu, Ming Shen, Zhibo Zhang, Fangyan Gu, Weiliang Zeng, Xiaodong Jia, Chengliang Yin
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Genetics
Subjects:
m6A
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2021.656114/full
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spelling doaj-67a9026d4aeb4378959b85e4db694b602021-06-11T08:32:17ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-06-011210.3389/fgene.2021.656114656114Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung AdenocarcinomaBingzhou Guo0Hongliang Zhang1Jinliang Wang2Rilige Wu3Rilige Wu4Junyan Zhang5Junyan Zhang6Qiqin Zhang7Lu Xu8Ming Shen9Zhibo Zhang10Fangyan Gu11Weiliang Zeng12Xiaodong Jia13Chengliang Yin14School of Mathematical Sciences, Harbin Normal University, Harbin, ChinaDepartment of Emergency, The First Medical Center of Chinese PLA General Hospital, Beijing, ChinaDepartment of Oncology, The Second Medical Center of Chinese PLA General Hospital, Beijing, ChinaNational Engineering Laboratory for Medical Big Data Application Technology, Chinese PLA General Hospital, Beijing, ChinaMedical Big Data Research Center, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing, ChinaNational Engineering Laboratory for Medical Big Data Application Technology, Chinese PLA General Hospital, Beijing, ChinaMedical Big Data Research Center, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing, ChinaDepartment of Orthopedics, Weifang Traditional Chinese Hospital, Weifang, ChinaLaboratory of Translational Medicine, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing, ChinaLaboratory of Translational Medicine, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing, ChinaThe 78th Group Army Hospital of Chinese PLA, Mudanjiang, ChinaClinical Biobank Center, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing, ChinaSchool of Mathematical Sciences, Harbin Normal University, Harbin, China0Department of Liver Disease, Fifth Medical Center of Chinese PLA General Hospital, Beijing, China1Faculty of Medicine, Macau University of Science and Technology, Macau, ChinaBackgroundN6-methyladenosine (m6A) RNA modification is vital for cancers because methylation can alter gene expression and even affect some functional modification. Our study aimed to analyze m6A RNA methylation regulators and m6A-related genes to understand the prognosis of early lung adenocarcinoma.MethodsThe relevant datasets were utilized to analyze 21 m6A RNA methylation regulators and 5,486 m6A-related genes in m6Avar. Univariate Cox regression analysis, random survival forest analysis, Kaplan–Meier analysis, Chi-square analysis, and multivariate cox analysis were carried out on the datasets, and a risk prognostic model based on three feature genes was constructed.ResultsRespectively, we treated GSE31210 (n = 226) as the training set, GSE50081 (n = 128) and TCGA data (n = 400) as the test set. By performing univariable cox regression analysis and random survival forest algorithm in the training group, 218 genes were significant and three prognosis-related genes (ZCRB1, ADH1C, and YTHDC2) were screened out, which could divide LUAD patients into low and high-risk group (P < 0.0001). The predictive efficacy of the model was confirmed in the test group GSE50081 (P = 0.0018) and the TCGA datasets (P = 0.014). Multivariable cox manifested that the three-gene signature was an independent risk factor in LUAD. Furthermore, genes in the signature were also externally validated using the online database. Moreover, YTHDC2 was the important gene in the risk score model and played a vital role in readers of m6A methylation.ConclusionThe findings of this study suggested that associated with m6A RNA methylation regulators and m6A-related genes, the three-gene signature was a reliable prognostic indicator for LUAD patients, indicating a clinical application prospect to serve as a potential therapeutic target.https://www.frontiersin.org/articles/10.3389/fgene.2021.656114/fulllung adenocarcinomam6Aprognostic signaturem6A-related genesRNA methylation regulators
collection DOAJ
language English
format Article
sources DOAJ
author Bingzhou Guo
Hongliang Zhang
Jinliang Wang
Rilige Wu
Rilige Wu
Junyan Zhang
Junyan Zhang
Qiqin Zhang
Lu Xu
Ming Shen
Zhibo Zhang
Fangyan Gu
Weiliang Zeng
Xiaodong Jia
Chengliang Yin
spellingShingle Bingzhou Guo
Hongliang Zhang
Jinliang Wang
Rilige Wu
Rilige Wu
Junyan Zhang
Junyan Zhang
Qiqin Zhang
Lu Xu
Ming Shen
Zhibo Zhang
Fangyan Gu
Weiliang Zeng
Xiaodong Jia
Chengliang Yin
Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung Adenocarcinoma
Frontiers in Genetics
lung adenocarcinoma
m6A
prognostic signature
m6A-related genes
RNA methylation regulators
author_facet Bingzhou Guo
Hongliang Zhang
Jinliang Wang
Rilige Wu
Rilige Wu
Junyan Zhang
Junyan Zhang
Qiqin Zhang
Lu Xu
Ming Shen
Zhibo Zhang
Fangyan Gu
Weiliang Zeng
Xiaodong Jia
Chengliang Yin
author_sort Bingzhou Guo
title Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung Adenocarcinoma
title_short Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung Adenocarcinoma
title_full Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung Adenocarcinoma
title_fullStr Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung Adenocarcinoma
title_full_unstemmed Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung Adenocarcinoma
title_sort identification of the signature associated with m6a rna methylation regulators and m6a-related genes and construction of the risk score for prognostication in early-stage lung adenocarcinoma
publisher Frontiers Media S.A.
series Frontiers in Genetics
issn 1664-8021
publishDate 2021-06-01
description BackgroundN6-methyladenosine (m6A) RNA modification is vital for cancers because methylation can alter gene expression and even affect some functional modification. Our study aimed to analyze m6A RNA methylation regulators and m6A-related genes to understand the prognosis of early lung adenocarcinoma.MethodsThe relevant datasets were utilized to analyze 21 m6A RNA methylation regulators and 5,486 m6A-related genes in m6Avar. Univariate Cox regression analysis, random survival forest analysis, Kaplan–Meier analysis, Chi-square analysis, and multivariate cox analysis were carried out on the datasets, and a risk prognostic model based on three feature genes was constructed.ResultsRespectively, we treated GSE31210 (n = 226) as the training set, GSE50081 (n = 128) and TCGA data (n = 400) as the test set. By performing univariable cox regression analysis and random survival forest algorithm in the training group, 218 genes were significant and three prognosis-related genes (ZCRB1, ADH1C, and YTHDC2) were screened out, which could divide LUAD patients into low and high-risk group (P < 0.0001). The predictive efficacy of the model was confirmed in the test group GSE50081 (P = 0.0018) and the TCGA datasets (P = 0.014). Multivariable cox manifested that the three-gene signature was an independent risk factor in LUAD. Furthermore, genes in the signature were also externally validated using the online database. Moreover, YTHDC2 was the important gene in the risk score model and played a vital role in readers of m6A methylation.ConclusionThe findings of this study suggested that associated with m6A RNA methylation regulators and m6A-related genes, the three-gene signature was a reliable prognostic indicator for LUAD patients, indicating a clinical application prospect to serve as a potential therapeutic target.
topic lung adenocarcinoma
m6A
prognostic signature
m6A-related genes
RNA methylation regulators
url https://www.frontiersin.org/articles/10.3389/fgene.2021.656114/full
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