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Identification of a five m6A-relevant mRNAs signature and risk score for the prognostication of gastric cancer

BACKGROUND: N6-methyladenosine (m6A) is the most abundant form of methylation modification in eukaryotic cell messenger RNA (mRNA). However, the role of m6A in gastric cancer (GC), which is one of the most common gastrointestinal malignancies, is unclear. In this study, m6A-relevant mRNA signatures...

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Autores principales: Yin, Lei, Feng, Shichun, Sun, Yongqiang, Jiang, Yasu, Tang, Chong, Sun, Dongwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9660063/
https://www.ncbi.nlm.nih.gov/pubmed/36388685
http://dx.doi.org/10.21037/jgo-22-962
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author Yin, Lei
Feng, Shichun
Sun, Yongqiang
Jiang, Yasu
Tang, Chong
Sun, Dongwei
author_facet Yin, Lei
Feng, Shichun
Sun, Yongqiang
Jiang, Yasu
Tang, Chong
Sun, Dongwei
author_sort Yin, Lei
collection PubMed
description BACKGROUND: N6-methyladenosine (m6A) is the most abundant form of methylation modification in eukaryotic cell messenger RNA (mRNA). However, the role of m6A in gastric cancer (GC), which is one of the most common gastrointestinal malignancies, is unclear. In this study, m6A-relevant mRNA signatures and risk scores were determined to predict the prognosis of GC. METHODS: The expression profiles and clinical information of 367 patients were downloaded from The Cancer Genome Atlas (TCGA). Cluster analysis and univariate Cox analysis were performed to identify the regulatory factors of RNA methylation associated with GC prognosis. A co-expression network was constructed using the WGCNA package in R. The correlations between module eigengenes and clinical traits were then calculated to identify the relevant modules. We used univariate Cox analysis to screen for genes that are significantly associated with prognosis in the module. We identified hub genes by least absolute shrinkage and selection operator (LASSO) and multivariate analysis and developed a Cox prognostic model. Finally, the hub gene expression values weighted by the coefficients from the LASSO regression were applied to generate a risk score for each patient, and receiver operating characteristic (ROC) and Kaplan-Meier curves were used to assess the prognostic capacity of the risk scores. The asporin (ASPN) gene in GC cell lines was verified via quantitative polymerase chain reaction (qPCR) and Western blot. Moreover, 5-ethynyl-2'-deoxyuridine (EdU) and transwell assays were applied to evaluate the effects of the proliferation, migration, and invasion abilities in GC cells after ASPN knockdown. Western blot verified the effects of ASPN on the phosphoinositide 3-kinase (PI3K)/serine/threonine kinase (AKT)/mechanistic target of rapamycin kinase (mTOR) pathway and epithelial-mesenchymal transition (EMT) pathway-related gene expression. RESULTS: Our results indicated that AARD, ASPN, SLAMF9, MIR3117 and DUSP1 were hub genes affecting the prognosis of GC patients. Besides, we found that ASPN expression was upregulated in GC cells. The knockdown of ASPN expression suppressed GC cell proliferation, migration, and invasion by deactivating the PI3K/AKT/mTOR and EMT pathways, respectively. CONCLUSIONS: Our findings indicated that ASPN participates in the biological process of GC as an oncogene and may be a promising biomarker in GC.
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spelling pubmed-96600632022-11-15 Identification of a five m6A-relevant mRNAs signature and risk score for the prognostication of gastric cancer Yin, Lei Feng, Shichun Sun, Yongqiang Jiang, Yasu Tang, Chong Sun, Dongwei J Gastrointest Oncol Original Article BACKGROUND: N6-methyladenosine (m6A) is the most abundant form of methylation modification in eukaryotic cell messenger RNA (mRNA). However, the role of m6A in gastric cancer (GC), which is one of the most common gastrointestinal malignancies, is unclear. In this study, m6A-relevant mRNA signatures and risk scores were determined to predict the prognosis of GC. METHODS: The expression profiles and clinical information of 367 patients were downloaded from The Cancer Genome Atlas (TCGA). Cluster analysis and univariate Cox analysis were performed to identify the regulatory factors of RNA methylation associated with GC prognosis. A co-expression network was constructed using the WGCNA package in R. The correlations between module eigengenes and clinical traits were then calculated to identify the relevant modules. We used univariate Cox analysis to screen for genes that are significantly associated with prognosis in the module. We identified hub genes by least absolute shrinkage and selection operator (LASSO) and multivariate analysis and developed a Cox prognostic model. Finally, the hub gene expression values weighted by the coefficients from the LASSO regression were applied to generate a risk score for each patient, and receiver operating characteristic (ROC) and Kaplan-Meier curves were used to assess the prognostic capacity of the risk scores. The asporin (ASPN) gene in GC cell lines was verified via quantitative polymerase chain reaction (qPCR) and Western blot. Moreover, 5-ethynyl-2'-deoxyuridine (EdU) and transwell assays were applied to evaluate the effects of the proliferation, migration, and invasion abilities in GC cells after ASPN knockdown. Western blot verified the effects of ASPN on the phosphoinositide 3-kinase (PI3K)/serine/threonine kinase (AKT)/mechanistic target of rapamycin kinase (mTOR) pathway and epithelial-mesenchymal transition (EMT) pathway-related gene expression. RESULTS: Our results indicated that AARD, ASPN, SLAMF9, MIR3117 and DUSP1 were hub genes affecting the prognosis of GC patients. Besides, we found that ASPN expression was upregulated in GC cells. The knockdown of ASPN expression suppressed GC cell proliferation, migration, and invasion by deactivating the PI3K/AKT/mTOR and EMT pathways, respectively. CONCLUSIONS: Our findings indicated that ASPN participates in the biological process of GC as an oncogene and may be a promising biomarker in GC. AME Publishing Company 2022-10 /pmc/articles/PMC9660063/ /pubmed/36388685 http://dx.doi.org/10.21037/jgo-22-962 Text en 2022 Journal of Gastrointestinal Oncology. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Yin, Lei
Feng, Shichun
Sun, Yongqiang
Jiang, Yasu
Tang, Chong
Sun, Dongwei
Identification of a five m6A-relevant mRNAs signature and risk score for the prognostication of gastric cancer
title Identification of a five m6A-relevant mRNAs signature and risk score for the prognostication of gastric cancer
title_full Identification of a five m6A-relevant mRNAs signature and risk score for the prognostication of gastric cancer
title_fullStr Identification of a five m6A-relevant mRNAs signature and risk score for the prognostication of gastric cancer
title_full_unstemmed Identification of a five m6A-relevant mRNAs signature and risk score for the prognostication of gastric cancer
title_short Identification of a five m6A-relevant mRNAs signature and risk score for the prognostication of gastric cancer
title_sort identification of a five m6a-relevant mrnas signature and risk score for the prognostication of gastric cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9660063/
https://www.ncbi.nlm.nih.gov/pubmed/36388685
http://dx.doi.org/10.21037/jgo-22-962
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