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Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma

The m7G modification has been proven to play an important role in RNA post-transcriptional modification and protein translation. However, the potential role of m7G modification patterns in assessing the prognosis of Skin cutaneous melanoma (SKCM) and tumor microenvironment (TME) has not been well st...

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Autores principales: Zhang, Xin, Miao, Ying, Sun, Hao-Wen, Wang, Yi-Xiao, Zhao, Wen-Min, Pang, A-Ying, Wu, Xiao-Yan, Shen, Cong-Cong, Chen, Xiao-Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751814/
https://www.ncbi.nlm.nih.gov/pubmed/36532001
http://dx.doi.org/10.3389/fimmu.2022.1034516
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author Zhang, Xin
Miao, Ying
Sun, Hao-Wen
Wang, Yi-Xiao
Zhao, Wen-Min
Pang, A-Ying
Wu, Xiao-Yan
Shen, Cong-Cong
Chen, Xiao-Dong
author_facet Zhang, Xin
Miao, Ying
Sun, Hao-Wen
Wang, Yi-Xiao
Zhao, Wen-Min
Pang, A-Ying
Wu, Xiao-Yan
Shen, Cong-Cong
Chen, Xiao-Dong
author_sort Zhang, Xin
collection PubMed
description The m7G modification has been proven to play an important role in RNA post-transcriptional modification and protein translation. However, the potential role of m7G modification patterns in assessing the prognosis of Skin cutaneous melanoma (SKCM) and tumor microenvironment (TME) has not been well studied. In this study, we investigated and finally identified 21 available m7G-related genes. We used hierarchical clustering (K-means) to classify 743 SKCM patients into three m7G-modified subtypes named m7G/gene cluster-A, B, C. We found that both m7G cluster B and gene cluster B exhibited higher prognosis and higher immune cell infiltration in TME compared to other subtypes. EIF4E3 and IFIT5, two m7G related genes, were both markedly elevated in Cluster B. Then, we constructed an m7G score system utilizing principal component analysis (PCA) in order to evaluate the patients' prognosis. High m7G score subtype was associated with better survival prognosis and active immune response. Overall, this article revealed that m7G modification patterns were involved in the development of the tumor microenvironment. Evaluating patients' m7G modification patterns will enhance our understanding of TME characteristics and help to guide personal treatment in clinics in the future.
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spelling pubmed-97518142022-12-16 Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma Zhang, Xin Miao, Ying Sun, Hao-Wen Wang, Yi-Xiao Zhao, Wen-Min Pang, A-Ying Wu, Xiao-Yan Shen, Cong-Cong Chen, Xiao-Dong Front Immunol Immunology The m7G modification has been proven to play an important role in RNA post-transcriptional modification and protein translation. However, the potential role of m7G modification patterns in assessing the prognosis of Skin cutaneous melanoma (SKCM) and tumor microenvironment (TME) has not been well studied. In this study, we investigated and finally identified 21 available m7G-related genes. We used hierarchical clustering (K-means) to classify 743 SKCM patients into three m7G-modified subtypes named m7G/gene cluster-A, B, C. We found that both m7G cluster B and gene cluster B exhibited higher prognosis and higher immune cell infiltration in TME compared to other subtypes. EIF4E3 and IFIT5, two m7G related genes, were both markedly elevated in Cluster B. Then, we constructed an m7G score system utilizing principal component analysis (PCA) in order to evaluate the patients' prognosis. High m7G score subtype was associated with better survival prognosis and active immune response. Overall, this article revealed that m7G modification patterns were involved in the development of the tumor microenvironment. Evaluating patients' m7G modification patterns will enhance our understanding of TME characteristics and help to guide personal treatment in clinics in the future. Frontiers Media S.A. 2022-12-01 /pmc/articles/PMC9751814/ /pubmed/36532001 http://dx.doi.org/10.3389/fimmu.2022.1034516 Text en Copyright © 2022 Zhang, Miao, Sun, Wang, Zhao, Pang, Wu, Shen and Chen 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 Immunology
Zhang, Xin
Miao, Ying
Sun, Hao-Wen
Wang, Yi-Xiao
Zhao, Wen-Min
Pang, A-Ying
Wu, Xiao-Yan
Shen, Cong-Cong
Chen, Xiao-Dong
Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma
title Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma
title_full Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma
title_fullStr Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma
title_full_unstemmed Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma
title_short Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma
title_sort integrated analysis from multi-center studies identities m7g-derived modification pattern and risk stratification system in skin cutaneous melanoma
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751814/
https://www.ncbi.nlm.nih.gov/pubmed/36532001
http://dx.doi.org/10.3389/fimmu.2022.1034516
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