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Correlation of m6A methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of RNA expression profiles

BACKGROUND: Non-small cell lung cancer (NSCLC) is a common type of lung cancer with a poor prognosis. N6-methyladenosine (m6A) methylation, which is a reversible ribonucleic acid (RNA) modification, plays an important role in the occurrence and development of NSCLC. However, the potential effect of...

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Autores principales: Dong, Bo, Wu, Chunli, Li, Shi-Hao, Huang, Lan, Zhang, Chunyang, Wu, Bin, Sheng, Yinliang, Liu, Yafei, Ye, Guanchao, Qi, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506701/
https://www.ncbi.nlm.nih.gov/pubmed/34734017
http://dx.doi.org/10.21037/atm-21-4248
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author Dong, Bo
Wu, Chunli
Li, Shi-Hao
Huang, Lan
Zhang, Chunyang
Wu, Bin
Sheng, Yinliang
Liu, Yafei
Ye, Guanchao
Qi, Yu
author_facet Dong, Bo
Wu, Chunli
Li, Shi-Hao
Huang, Lan
Zhang, Chunyang
Wu, Bin
Sheng, Yinliang
Liu, Yafei
Ye, Guanchao
Qi, Yu
author_sort Dong, Bo
collection PubMed
description BACKGROUND: Non-small cell lung cancer (NSCLC) is a common type of lung cancer with a poor prognosis. N6-methyladenosine (m6A) methylation, which is a reversible ribonucleic acid (RNA) modification, plays an important role in the occurrence and development of NSCLC. However, the potential effect of m6A methylation on immune infiltrates and prognosis remains unclear. METHODS: In this study, a weighted gene co-expression network analysis was used to screen out messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) that were co-expressed with m6A regulators. Additionally, 2 molecular subtypes (Clusters 1 and 2) were determined via consensus clustering. Subsequently, a prognostic risk model was constructed using both co-expressed mRNAs and ncRNAs. Based on the risk scores calculated by the prognostic model, the patients were divided into the high-risk group or low-risk group. Finally, the altered patterns of the tumor immune microenvironments (TIMEs) between the 2 stratification methods were thoroughly investigated, and a gene set enrichment analysis was conducted to further examine the potential mechanism. RESULTS: Patients in Cluster 1 had lower immunoscores, higher programmed death-ligand 1 (PD-L1) expression, and shorter overall survival (OS) compared to patients in Cluster 2. A further investigation based on the prognostic model revealed that the PD-L1 expression levels of patients in the high-risk group were significantly upregulated, and the immunoscores were lower than those in the low-risk group. The immune cells with a high infiltration in Cluster 1 showed a significant positive correlation with the risk score; those with low infiltration showed a significant negative correlation. The hallmarks of the Myelocytomatosis viral oncogene (MYC) targets, the second Gap/Mitosis (G2/M) checkpoint, E2 transcription Factor (E2F) targets, glycolysis, deoxyribonucleic acid (DNA) repair, and unfolded protein response were significantly enriched in Cluster 1, the low-immunoscore group, and the high-risk group. CONCLUSIONS: This study revealed that m6A methylation is closely related to the poor prognosis of NSCLC patients via interference with the TIME, which suggests that m6A may play a role in optimizing individualized immunotherapy management and improving prognosis.
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spelling pubmed-85067012021-11-02 Correlation of m6A methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of RNA expression profiles Dong, Bo Wu, Chunli Li, Shi-Hao Huang, Lan Zhang, Chunyang Wu, Bin Sheng, Yinliang Liu, Yafei Ye, Guanchao Qi, Yu Ann Transl Med Original Article BACKGROUND: Non-small cell lung cancer (NSCLC) is a common type of lung cancer with a poor prognosis. N6-methyladenosine (m6A) methylation, which is a reversible ribonucleic acid (RNA) modification, plays an important role in the occurrence and development of NSCLC. However, the potential effect of m6A methylation on immune infiltrates and prognosis remains unclear. METHODS: In this study, a weighted gene co-expression network analysis was used to screen out messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) that were co-expressed with m6A regulators. Additionally, 2 molecular subtypes (Clusters 1 and 2) were determined via consensus clustering. Subsequently, a prognostic risk model was constructed using both co-expressed mRNAs and ncRNAs. Based on the risk scores calculated by the prognostic model, the patients were divided into the high-risk group or low-risk group. Finally, the altered patterns of the tumor immune microenvironments (TIMEs) between the 2 stratification methods were thoroughly investigated, and a gene set enrichment analysis was conducted to further examine the potential mechanism. RESULTS: Patients in Cluster 1 had lower immunoscores, higher programmed death-ligand 1 (PD-L1) expression, and shorter overall survival (OS) compared to patients in Cluster 2. A further investigation based on the prognostic model revealed that the PD-L1 expression levels of patients in the high-risk group were significantly upregulated, and the immunoscores were lower than those in the low-risk group. The immune cells with a high infiltration in Cluster 1 showed a significant positive correlation with the risk score; those with low infiltration showed a significant negative correlation. The hallmarks of the Myelocytomatosis viral oncogene (MYC) targets, the second Gap/Mitosis (G2/M) checkpoint, E2 transcription Factor (E2F) targets, glycolysis, deoxyribonucleic acid (DNA) repair, and unfolded protein response were significantly enriched in Cluster 1, the low-immunoscore group, and the high-risk group. CONCLUSIONS: This study revealed that m6A methylation is closely related to the poor prognosis of NSCLC patients via interference with the TIME, which suggests that m6A may play a role in optimizing individualized immunotherapy management and improving prognosis. AME Publishing Company 2021-09 /pmc/articles/PMC8506701/ /pubmed/34734017 http://dx.doi.org/10.21037/atm-21-4248 Text en 2021 Annals of Translational Medicine. 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
Dong, Bo
Wu, Chunli
Li, Shi-Hao
Huang, Lan
Zhang, Chunyang
Wu, Bin
Sheng, Yinliang
Liu, Yafei
Ye, Guanchao
Qi, Yu
Correlation of m6A methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of RNA expression profiles
title Correlation of m6A methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of RNA expression profiles
title_full Correlation of m6A methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of RNA expression profiles
title_fullStr Correlation of m6A methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of RNA expression profiles
title_full_unstemmed Correlation of m6A methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of RNA expression profiles
title_short Correlation of m6A methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of RNA expression profiles
title_sort correlation of m6a methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of rna expression profiles
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506701/
https://www.ncbi.nlm.nih.gov/pubmed/34734017
http://dx.doi.org/10.21037/atm-21-4248
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