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Identification of a novel m6A-related lncRNA pair signature for predicting the prognosis of gastric cancer patients

BACKGROUND: Accumulating studies have demonstrated that lncRNAs play vital roles in the prognosis of gastric cancer (GC); however, the prognostic value of N6-methyladenosine-related lncRNAs has not been fully reported in GC. This study aimed to construct and validate an m6A-related lncRNA pair signa...

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Autores principales: Wang, Jun-Mei, Li, Xuan, Yang, Peng, Geng, Wen-Bin, Wang, Xiao-Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8862389/
https://www.ncbi.nlm.nih.gov/pubmed/35189810
http://dx.doi.org/10.1186/s12876-022-02159-3
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author Wang, Jun-Mei
Li, Xuan
Yang, Peng
Geng, Wen-Bin
Wang, Xiao-Yong
author_facet Wang, Jun-Mei
Li, Xuan
Yang, Peng
Geng, Wen-Bin
Wang, Xiao-Yong
author_sort Wang, Jun-Mei
collection PubMed
description BACKGROUND: Accumulating studies have demonstrated that lncRNAs play vital roles in the prognosis of gastric cancer (GC); however, the prognostic value of N6-methyladenosine-related lncRNAs has not been fully reported in GC. This study aimed to construct and validate an m6A-related lncRNA pair signature (m6A-LPS) for predicting the prognosis of GC patients. METHODS: GC cohort primary data were downloaded from The Cancer Genome Atlas. We analysed the coexpression of m6A regulators and lncRNAs to identify m6A-related lncRNAs. Based on cyclical single pairing along with a 0-or-1 matrix and least absolute shrinkage and selection operator-penalized regression analyses, we constructed a novel prognostic signature of m6A-related lncRNA pairs with no dependence upon specific lncRNA expression levels. All patients were divided into high-risk and low-risk group based on the median risk score. The predictive reliability was evaluated in the testing dataset and whole dataset with receiver operating characteristic (ROC) curve analysis. Gene set enrichment analysis was used to identify potential pathways. RESULTS: Fourteen m6A-related lncRNA pairs consisting of 25 unique lncRNAs were used to construct the m6A-LPS. Kaplan–Meier analysis showed that the high-risk group had poor prognosis. The area under the curve for 5-year overall survival was 0.906, 0.827, and 0.882 in the training dataset, testing dataset, and whole dataset, respectively, meaning that the m6A-LPS was highly accurate in predicting GC patient prognosis. The m6A-LPS served as an independent prognostic factor for GC patients after adjusting for other clinical factors (p < 0.05). The m6A-LPS had more accuracy and a higher ROC value than other prognostic models for GC. Functional analysis revealed that high-risk group samples mainly showed enrichment of extracellular matrix receptor interactions and focal adhesion. Moreover, N-cadherin and vimentin, known biomarkers of epithelial–mesenchymal transition, were highly expressed in high-risk group samples. The immune infiltration analysis showed that resting dendritic cells, monocytes, and resting memory CD4 T cells were significantly positively related to the risk score. Thus, m6A-LPS reflected the infiltration of several types of immune cells. CONCLUSIONS: The signature established by pairing m6A-related lncRNAs regardless of expression levels showed high and independent clinical prediction value in GC patients.
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spelling pubmed-88623892022-02-23 Identification of a novel m6A-related lncRNA pair signature for predicting the prognosis of gastric cancer patients Wang, Jun-Mei Li, Xuan Yang, Peng Geng, Wen-Bin Wang, Xiao-Yong BMC Gastroenterol Research BACKGROUND: Accumulating studies have demonstrated that lncRNAs play vital roles in the prognosis of gastric cancer (GC); however, the prognostic value of N6-methyladenosine-related lncRNAs has not been fully reported in GC. This study aimed to construct and validate an m6A-related lncRNA pair signature (m6A-LPS) for predicting the prognosis of GC patients. METHODS: GC cohort primary data were downloaded from The Cancer Genome Atlas. We analysed the coexpression of m6A regulators and lncRNAs to identify m6A-related lncRNAs. Based on cyclical single pairing along with a 0-or-1 matrix and least absolute shrinkage and selection operator-penalized regression analyses, we constructed a novel prognostic signature of m6A-related lncRNA pairs with no dependence upon specific lncRNA expression levels. All patients were divided into high-risk and low-risk group based on the median risk score. The predictive reliability was evaluated in the testing dataset and whole dataset with receiver operating characteristic (ROC) curve analysis. Gene set enrichment analysis was used to identify potential pathways. RESULTS: Fourteen m6A-related lncRNA pairs consisting of 25 unique lncRNAs were used to construct the m6A-LPS. Kaplan–Meier analysis showed that the high-risk group had poor prognosis. The area under the curve for 5-year overall survival was 0.906, 0.827, and 0.882 in the training dataset, testing dataset, and whole dataset, respectively, meaning that the m6A-LPS was highly accurate in predicting GC patient prognosis. The m6A-LPS served as an independent prognostic factor for GC patients after adjusting for other clinical factors (p < 0.05). The m6A-LPS had more accuracy and a higher ROC value than other prognostic models for GC. Functional analysis revealed that high-risk group samples mainly showed enrichment of extracellular matrix receptor interactions and focal adhesion. Moreover, N-cadherin and vimentin, known biomarkers of epithelial–mesenchymal transition, were highly expressed in high-risk group samples. The immune infiltration analysis showed that resting dendritic cells, monocytes, and resting memory CD4 T cells were significantly positively related to the risk score. Thus, m6A-LPS reflected the infiltration of several types of immune cells. CONCLUSIONS: The signature established by pairing m6A-related lncRNAs regardless of expression levels showed high and independent clinical prediction value in GC patients. BioMed Central 2022-02-21 /pmc/articles/PMC8862389/ /pubmed/35189810 http://dx.doi.org/10.1186/s12876-022-02159-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wang, Jun-Mei
Li, Xuan
Yang, Peng
Geng, Wen-Bin
Wang, Xiao-Yong
Identification of a novel m6A-related lncRNA pair signature for predicting the prognosis of gastric cancer patients
title Identification of a novel m6A-related lncRNA pair signature for predicting the prognosis of gastric cancer patients
title_full Identification of a novel m6A-related lncRNA pair signature for predicting the prognosis of gastric cancer patients
title_fullStr Identification of a novel m6A-related lncRNA pair signature for predicting the prognosis of gastric cancer patients
title_full_unstemmed Identification of a novel m6A-related lncRNA pair signature for predicting the prognosis of gastric cancer patients
title_short Identification of a novel m6A-related lncRNA pair signature for predicting the prognosis of gastric cancer patients
title_sort identification of a novel m6a-related lncrna pair signature for predicting the prognosis of gastric cancer patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8862389/
https://www.ncbi.nlm.nih.gov/pubmed/35189810
http://dx.doi.org/10.1186/s12876-022-02159-3
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