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Comprehensive Analysis of m6A RNA Methylation Regulators in the Prognosis and Immune Microenvironment of Multiple Myeloma

BACKGROUND: N6-methyladenosine is the most abundant RNA modification, which plays a prominent role in various biology processes, including tumorigenesis and immune regulation. Multiple myeloma (MM) is the second most frequent hematological malignancy. MATERIALS AND METHODS: Twenty-two m6A RNA methyl...

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Autores principales: Liu, Rui, Shen, Ying, Hu, Jinsong, Wang, Xiaman, Wu, Dong, Zhai, Meng, Bai, Ju, He, Aili
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8599583/
https://www.ncbi.nlm.nih.gov/pubmed/34804925
http://dx.doi.org/10.3389/fonc.2021.731957
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author Liu, Rui
Shen, Ying
Hu, Jinsong
Wang, Xiaman
Wu, Dong
Zhai, Meng
Bai, Ju
He, Aili
author_facet Liu, Rui
Shen, Ying
Hu, Jinsong
Wang, Xiaman
Wu, Dong
Zhai, Meng
Bai, Ju
He, Aili
author_sort Liu, Rui
collection PubMed
description BACKGROUND: N6-methyladenosine is the most abundant RNA modification, which plays a prominent role in various biology processes, including tumorigenesis and immune regulation. Multiple myeloma (MM) is the second most frequent hematological malignancy. MATERIALS AND METHODS: Twenty-two m6A RNA methylation regulators were analyzed between MM patients and normal samples. Kaplan–Meier survival analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were employed to construct the risk signature model. Receiver operation characteristic (ROC) curves were used to verify the prognostic and diagnostic efficiency. Immune infiltration level was evaluated by ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA). RESULTS: High expression of HNRNPC, HNRNPA2B1, and YTHDF2 and low expression of ZC3H13 were associated with poor survival. Based on these four genes, a prognostic risk signature model was established. Multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic factor of MM. Enrichment analysis showed that cell cycle, immune response, MYC, proteasome, and unfold protein reaction were enriched in high-risk MM patients. Furthermore, patients with higher risk score exhibited lower immune scores and lower immune infiltration level. CONCLUSION: The m6A-based prognostic risk score accurately and robustly predicts the survival of MM patients and is associated with the immune infiltration level, which complements current prediction models and enhances our cognition of immune infiltration.
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spelling pubmed-85995832021-11-19 Comprehensive Analysis of m6A RNA Methylation Regulators in the Prognosis and Immune Microenvironment of Multiple Myeloma Liu, Rui Shen, Ying Hu, Jinsong Wang, Xiaman Wu, Dong Zhai, Meng Bai, Ju He, Aili Front Oncol Oncology BACKGROUND: N6-methyladenosine is the most abundant RNA modification, which plays a prominent role in various biology processes, including tumorigenesis and immune regulation. Multiple myeloma (MM) is the second most frequent hematological malignancy. MATERIALS AND METHODS: Twenty-two m6A RNA methylation regulators were analyzed between MM patients and normal samples. Kaplan–Meier survival analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were employed to construct the risk signature model. Receiver operation characteristic (ROC) curves were used to verify the prognostic and diagnostic efficiency. Immune infiltration level was evaluated by ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA). RESULTS: High expression of HNRNPC, HNRNPA2B1, and YTHDF2 and low expression of ZC3H13 were associated with poor survival. Based on these four genes, a prognostic risk signature model was established. Multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic factor of MM. Enrichment analysis showed that cell cycle, immune response, MYC, proteasome, and unfold protein reaction were enriched in high-risk MM patients. Furthermore, patients with higher risk score exhibited lower immune scores and lower immune infiltration level. CONCLUSION: The m6A-based prognostic risk score accurately and robustly predicts the survival of MM patients and is associated with the immune infiltration level, which complements current prediction models and enhances our cognition of immune infiltration. Frontiers Media S.A. 2021-11-04 /pmc/articles/PMC8599583/ /pubmed/34804925 http://dx.doi.org/10.3389/fonc.2021.731957 Text en Copyright © 2021 Liu, Shen, Hu, Wang, Wu, Zhai, Bai and He 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 Oncology
Liu, Rui
Shen, Ying
Hu, Jinsong
Wang, Xiaman
Wu, Dong
Zhai, Meng
Bai, Ju
He, Aili
Comprehensive Analysis of m6A RNA Methylation Regulators in the Prognosis and Immune Microenvironment of Multiple Myeloma
title Comprehensive Analysis of m6A RNA Methylation Regulators in the Prognosis and Immune Microenvironment of Multiple Myeloma
title_full Comprehensive Analysis of m6A RNA Methylation Regulators in the Prognosis and Immune Microenvironment of Multiple Myeloma
title_fullStr Comprehensive Analysis of m6A RNA Methylation Regulators in the Prognosis and Immune Microenvironment of Multiple Myeloma
title_full_unstemmed Comprehensive Analysis of m6A RNA Methylation Regulators in the Prognosis and Immune Microenvironment of Multiple Myeloma
title_short Comprehensive Analysis of m6A RNA Methylation Regulators in the Prognosis and Immune Microenvironment of Multiple Myeloma
title_sort comprehensive analysis of m6a rna methylation regulators in the prognosis and immune microenvironment of multiple myeloma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8599583/
https://www.ncbi.nlm.nih.gov/pubmed/34804925
http://dx.doi.org/10.3389/fonc.2021.731957
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