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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...

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Detalles Bibliográficos
Autores principales: Huang, Yuancheng, Yang, Zehong, Huang, Chaoyuan, Jiang, Xiaotao, Yan, Yanhua, Zhuang, Kunhai, Wen, Yi, Liu, Fengbin, Li, Peiwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
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
Descripción
Sumario: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.