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Identification of a Mitochondria-Related Gene Signature to Predict the Prognosis in AML

Mitochondria-related metabolic reprogramming plays a major role in the occurrence, development, drug resistance, and recurrence of acute myeloid leukemia (AML). However, the roles of mitochondria-related genes (MRGs) in the prognosis and immune microenvironment for AML patients remain largely unknow...

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Autores principales: Jiang, Nan, Zhang, Xinzhuo, Chen, Qi, Kantawong, Fahsai, Wan, Shengli, Liu, Jian, Li, Hua, Zhou, Jie, Lu, Bin, Wu, Jianming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8960857/
https://www.ncbi.nlm.nih.gov/pubmed/35359394
http://dx.doi.org/10.3389/fonc.2022.823831
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author Jiang, Nan
Zhang, Xinzhuo
Chen, Qi
Kantawong, Fahsai
Wan, Shengli
Liu, Jian
Li, Hua
Zhou, Jie
Lu, Bin
Wu, Jianming
author_facet Jiang, Nan
Zhang, Xinzhuo
Chen, Qi
Kantawong, Fahsai
Wan, Shengli
Liu, Jian
Li, Hua
Zhou, Jie
Lu, Bin
Wu, Jianming
author_sort Jiang, Nan
collection PubMed
description Mitochondria-related metabolic reprogramming plays a major role in the occurrence, development, drug resistance, and recurrence of acute myeloid leukemia (AML). However, the roles of mitochondria-related genes (MRGs) in the prognosis and immune microenvironment for AML patients remain largely unknown. In this study, by least absolute shrinkage and selection operator (LASSO) Cox regression analysis, 4 MRGs’ (HPDL, CPT1A, IDH3A, and ETFB) signature was established that demonstrated good robustness in TARGET AML datasets. The univariate and multivariate Cox regression analyses both demonstrated that the MRG signature was a robust independent prognostic factor in overall survival prediction with high accuracy for AML patients. Based on the risk score calculated by the signature, samples were divided into high- and low-risk groups. Gene set enrichment analysis (GSEA) suggested that the MRG signature is involved in the immune-related pathways. Via immune infiltration analysis and immunosuppressive genes analysis, we found that MRG risk of AML patients was strikingly positively correlated with an immune cell infiltration and expression of critical immune checkpoints, indicating that the poor prognosis might be caused by immunosuppressive tumor microenvironment (TME). In summary, the signature based on MRGs could act as an independent risk factor for predicting the clinical prognosis of AML and could also reflect an association with the immunosuppressive microenvironment, providing a novel method for AML metabolic and immune therapy based on the regulation of mitochondrial function.
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spelling pubmed-89608572022-03-30 Identification of a Mitochondria-Related Gene Signature to Predict the Prognosis in AML Jiang, Nan Zhang, Xinzhuo Chen, Qi Kantawong, Fahsai Wan, Shengli Liu, Jian Li, Hua Zhou, Jie Lu, Bin Wu, Jianming Front Oncol Oncology Mitochondria-related metabolic reprogramming plays a major role in the occurrence, development, drug resistance, and recurrence of acute myeloid leukemia (AML). However, the roles of mitochondria-related genes (MRGs) in the prognosis and immune microenvironment for AML patients remain largely unknown. In this study, by least absolute shrinkage and selection operator (LASSO) Cox regression analysis, 4 MRGs’ (HPDL, CPT1A, IDH3A, and ETFB) signature was established that demonstrated good robustness in TARGET AML datasets. The univariate and multivariate Cox regression analyses both demonstrated that the MRG signature was a robust independent prognostic factor in overall survival prediction with high accuracy for AML patients. Based on the risk score calculated by the signature, samples were divided into high- and low-risk groups. Gene set enrichment analysis (GSEA) suggested that the MRG signature is involved in the immune-related pathways. Via immune infiltration analysis and immunosuppressive genes analysis, we found that MRG risk of AML patients was strikingly positively correlated with an immune cell infiltration and expression of critical immune checkpoints, indicating that the poor prognosis might be caused by immunosuppressive tumor microenvironment (TME). In summary, the signature based on MRGs could act as an independent risk factor for predicting the clinical prognosis of AML and could also reflect an association with the immunosuppressive microenvironment, providing a novel method for AML metabolic and immune therapy based on the regulation of mitochondrial function. Frontiers Media S.A. 2022-03-10 /pmc/articles/PMC8960857/ /pubmed/35359394 http://dx.doi.org/10.3389/fonc.2022.823831 Text en Copyright © 2022 Jiang, Zhang, Chen, Kantawong, Wan, Liu, Li, Zhou, Lu and Wu 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
Jiang, Nan
Zhang, Xinzhuo
Chen, Qi
Kantawong, Fahsai
Wan, Shengli
Liu, Jian
Li, Hua
Zhou, Jie
Lu, Bin
Wu, Jianming
Identification of a Mitochondria-Related Gene Signature to Predict the Prognosis in AML
title Identification of a Mitochondria-Related Gene Signature to Predict the Prognosis in AML
title_full Identification of a Mitochondria-Related Gene Signature to Predict the Prognosis in AML
title_fullStr Identification of a Mitochondria-Related Gene Signature to Predict the Prognosis in AML
title_full_unstemmed Identification of a Mitochondria-Related Gene Signature to Predict the Prognosis in AML
title_short Identification of a Mitochondria-Related Gene Signature to Predict the Prognosis in AML
title_sort identification of a mitochondria-related gene signature to predict the prognosis in aml
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8960857/
https://www.ncbi.nlm.nih.gov/pubmed/35359394
http://dx.doi.org/10.3389/fonc.2022.823831
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