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Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures

Increasing evidence has implicated the modification of 7-methylguanosine (m(7)G), a type of RNA modification, in tumor progression. However, no comprehensive analysis to date has summarized the predicted role of m(7)G-related gene signatures in lung adenocarcinoma (LUAD). Herein, we aimed to develop...

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Autores principales: Lu, Fei, Gao, Jingyan, Hou, Yu, Cao, Ke, Xia, Yaoxiong, Chen, Zhengting, Yu, Hui, Chang, Li, Li, Wenhui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243265/
https://www.ncbi.nlm.nih.gov/pubmed/35785179
http://dx.doi.org/10.3389/fonc.2022.876360
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author Lu, Fei
Gao, Jingyan
Hou, Yu
Cao, Ke
Xia, Yaoxiong
Chen, Zhengting
Yu, Hui
Chang, Li
Li, Wenhui
author_facet Lu, Fei
Gao, Jingyan
Hou, Yu
Cao, Ke
Xia, Yaoxiong
Chen, Zhengting
Yu, Hui
Chang, Li
Li, Wenhui
author_sort Lu, Fei
collection PubMed
description Increasing evidence has implicated the modification of 7-methylguanosine (m(7)G), a type of RNA modification, in tumor progression. However, no comprehensive analysis to date has summarized the predicted role of m(7)G-related gene signatures in lung adenocarcinoma (LUAD). Herein, we aimed to develop a novel prognostic model in LUAD based on m(7)G-related gene signatures. The LUAD transcriptome profiling data and corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus datasets. After screening, we first obtained 29 m(7)G-related genes, most of which were upregulated in tumor tissues and negatively associated with overall survival (OS). According to the expression similarity of m(7)G-related genes, the combined samples from the TCGA-LUAD and GSE68465 datasets were further classified as two clusters that exhibit distinct OS rates and genetic heterogeneity. Then, we constructed a novel prognostic model involving four genes by using 130 differentially expressed genes among the two clusters. The combined samples were randomly divided into a training cohort and an internal validation cohort in a 1:1 ratio, and the GSE72094 dataset was used as an external validation cohort. The samples were divided into high- and low-risk groups. We demonstrated that a higher risk score was an independent negative prognostic factor and predicted poor OS. A nomogram was further constructed to better predict the survival of LUAD patients. Functional enrichment analyses indicated that cell cycle and DNA replication-related biological processes and pathways were enriched in the high-risk group. More importantly, the low-risk group had greater infiltration and enrichment of most immune cells, as well as higher ESTIMATE, immune, and stromal scores. In addition, the high-risk group had a lower TIDE score and higher expressions of most immune checkpoint-related genes. We finally noticed that patients in the high-risk group were more sensitive to chemotherapeutic agents commonly used in LUAD. In conclusion, we herein summarized for the first time the alterations and prognostic role of m(7)G-related genes in LUAD and then constructed a prognostic model based on m(7)G-related gene signatures that could accurately and stably predict survival and guide individualized treatment decision-making in LUAD patients.
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spelling pubmed-92432652022-07-01 Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures Lu, Fei Gao, Jingyan Hou, Yu Cao, Ke Xia, Yaoxiong Chen, Zhengting Yu, Hui Chang, Li Li, Wenhui Front Oncol Oncology Increasing evidence has implicated the modification of 7-methylguanosine (m(7)G), a type of RNA modification, in tumor progression. However, no comprehensive analysis to date has summarized the predicted role of m(7)G-related gene signatures in lung adenocarcinoma (LUAD). Herein, we aimed to develop a novel prognostic model in LUAD based on m(7)G-related gene signatures. The LUAD transcriptome profiling data and corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus datasets. After screening, we first obtained 29 m(7)G-related genes, most of which were upregulated in tumor tissues and negatively associated with overall survival (OS). According to the expression similarity of m(7)G-related genes, the combined samples from the TCGA-LUAD and GSE68465 datasets were further classified as two clusters that exhibit distinct OS rates and genetic heterogeneity. Then, we constructed a novel prognostic model involving four genes by using 130 differentially expressed genes among the two clusters. The combined samples were randomly divided into a training cohort and an internal validation cohort in a 1:1 ratio, and the GSE72094 dataset was used as an external validation cohort. The samples were divided into high- and low-risk groups. We demonstrated that a higher risk score was an independent negative prognostic factor and predicted poor OS. A nomogram was further constructed to better predict the survival of LUAD patients. Functional enrichment analyses indicated that cell cycle and DNA replication-related biological processes and pathways were enriched in the high-risk group. More importantly, the low-risk group had greater infiltration and enrichment of most immune cells, as well as higher ESTIMATE, immune, and stromal scores. In addition, the high-risk group had a lower TIDE score and higher expressions of most immune checkpoint-related genes. We finally noticed that patients in the high-risk group were more sensitive to chemotherapeutic agents commonly used in LUAD. In conclusion, we herein summarized for the first time the alterations and prognostic role of m(7)G-related genes in LUAD and then constructed a prognostic model based on m(7)G-related gene signatures that could accurately and stably predict survival and guide individualized treatment decision-making in LUAD patients. Frontiers Media S.A. 2022-06-16 /pmc/articles/PMC9243265/ /pubmed/35785179 http://dx.doi.org/10.3389/fonc.2022.876360 Text en Copyright © 2022 Lu, Gao, Hou, Cao, Xia, Chen, Yu, Chang and Li 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 Oncology
Lu, Fei
Gao, Jingyan
Hou, Yu
Cao, Ke
Xia, Yaoxiong
Chen, Zhengting
Yu, Hui
Chang, Li
Li, Wenhui
Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures
title Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures
title_full Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures
title_fullStr Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures
title_full_unstemmed Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures
title_short Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures
title_sort construction of a novel prognostic model in lung adenocarcinoma based on 7-methylguanosine-related gene signatures
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243265/
https://www.ncbi.nlm.nih.gov/pubmed/35785179
http://dx.doi.org/10.3389/fonc.2022.876360
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