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Identification of N6-Methylandenosine-Related lncRNAs for Subtype Identification and Risk Stratification in Gastric Adenocarcinoma
OBJECTIVES: The purpose of this study was to investigate the role of m(6)A-related lncRNAs in gastric adenocarcinoma (STAD) and to determine their prognostic value. METHODS: Gene expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) database. Correlation analysis...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504261/ https://www.ncbi.nlm.nih.gov/pubmed/34646770 http://dx.doi.org/10.3389/fonc.2021.725181 |
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author | Huang, Yuancheng Yang, Zehong Huang, Chaoyuan Jiang, Xiaotao Yan, Yanhua Zhuang, Kunhai Wen, Yi Liu, Fengbin Li, Peiwu |
author_facet | Huang, Yuancheng Yang, Zehong Huang, Chaoyuan Jiang, Xiaotao Yan, Yanhua Zhuang, Kunhai Wen, Yi Liu, Fengbin Li, Peiwu |
author_sort | Huang, Yuancheng |
collection | PubMed |
description | OBJECTIVES: The purpose of this study was to investigate the role of m(6)A-related lncRNAs in gastric adenocarcinoma (STAD) and to determine their prognostic value. METHODS: Gene expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) database. Correlation analysis and univariate Cox regression analysis were conducted to identify m(6)A-related prognostic lncRNAs. Subsequently, different clusters of patients with STAD were identified via consensus clustering analysis, and a prognostic signature was established by least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The clinicopathological characteristics, tumor microenvironment (TME), immune checkpoint genes (ICGs) expression, and the response to immune checkpoint inhibitors (ICIs) in different clusters and subgroups were explored. The prognostic value of the prognostic signature was evaluated using the Kaplan-Meier method, receiver operating characteristic curves, and univariate and multivariate regression analyses. Additionally, Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Ontology (GO) analysis were performed for biological functional analysis. RESULTS: Two clusters based on 19 m(6)A-related lncRNAs were identified, and a prognostic signature comprising 14 m(6)A-related lncRNAs was constructed, which had significant value in predicting the OS of patients with STAD, clinicopathological characteristics, TME, ICGs expression, and the response to ICIs. Biological processes and pathways associated with cancer and immune response were identified. CONCLUSIONS: We revealed the role and prognostic value of m(6)A-related lncRNAs in STAD. Together, our finding refreshed the understanding of m(6)A-related lncRNAs and provided novel insights to identify predictive biomarkers and immunotherapy targets for STAD. |
format | Online Article Text |
id | pubmed-8504261 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85042612021-10-12 Identification of N6-Methylandenosine-Related lncRNAs for Subtype Identification and Risk Stratification in Gastric Adenocarcinoma Huang, Yuancheng Yang, Zehong Huang, Chaoyuan Jiang, Xiaotao Yan, Yanhua Zhuang, Kunhai Wen, Yi Liu, Fengbin Li, Peiwu Front Oncol Oncology OBJECTIVES: The purpose of this study was to investigate the role of m(6)A-related lncRNAs in gastric adenocarcinoma (STAD) and to determine their prognostic value. METHODS: Gene expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) database. Correlation analysis and univariate Cox regression analysis were conducted to identify m(6)A-related prognostic lncRNAs. Subsequently, different clusters of patients with STAD were identified via consensus clustering analysis, and a prognostic signature was established by least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The clinicopathological characteristics, tumor microenvironment (TME), immune checkpoint genes (ICGs) expression, and the response to immune checkpoint inhibitors (ICIs) in different clusters and subgroups were explored. The prognostic value of the prognostic signature was evaluated using the Kaplan-Meier method, receiver operating characteristic curves, and univariate and multivariate regression analyses. Additionally, Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Ontology (GO) analysis were performed for biological functional analysis. RESULTS: Two clusters based on 19 m(6)A-related lncRNAs were identified, and a prognostic signature comprising 14 m(6)A-related lncRNAs was constructed, which had significant value in predicting the OS of patients with STAD, clinicopathological characteristics, TME, ICGs expression, and the response to ICIs. Biological processes and pathways associated with cancer and immune response were identified. CONCLUSIONS: We revealed the role and prognostic value of m(6)A-related lncRNAs in STAD. Together, our finding refreshed the understanding of m(6)A-related lncRNAs and provided novel insights to identify predictive biomarkers and immunotherapy targets for STAD. Frontiers Media S.A. 2021-09-27 /pmc/articles/PMC8504261/ /pubmed/34646770 http://dx.doi.org/10.3389/fonc.2021.725181 Text en Copyright © 2021 Huang, Yang, Huang, Jiang, Yan, Zhuang, Wen, Liu 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 Huang, Yuancheng Yang, Zehong Huang, Chaoyuan Jiang, Xiaotao Yan, Yanhua Zhuang, Kunhai Wen, Yi Liu, Fengbin Li, Peiwu Identification of N6-Methylandenosine-Related lncRNAs for Subtype Identification and Risk Stratification in Gastric Adenocarcinoma |
title | Identification of N6-Methylandenosine-Related lncRNAs for Subtype Identification and Risk Stratification in Gastric Adenocarcinoma |
title_full | Identification of N6-Methylandenosine-Related lncRNAs for Subtype Identification and Risk Stratification in Gastric Adenocarcinoma |
title_fullStr | Identification of N6-Methylandenosine-Related lncRNAs for Subtype Identification and Risk Stratification in Gastric Adenocarcinoma |
title_full_unstemmed | Identification of N6-Methylandenosine-Related lncRNAs for Subtype Identification and Risk Stratification in Gastric Adenocarcinoma |
title_short | Identification of N6-Methylandenosine-Related lncRNAs for Subtype Identification and Risk Stratification in Gastric Adenocarcinoma |
title_sort | identification of n6-methylandenosine-related lncrnas for subtype identification and risk stratification in gastric adenocarcinoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504261/ https://www.ncbi.nlm.nih.gov/pubmed/34646770 http://dx.doi.org/10.3389/fonc.2021.725181 |
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