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Increased NFATC4 Correlates With Poor Prognosis of AML Through Recruiting Regulatory T Cells
Despite that immune responses play important roles in acute myeloid leukemia (AML), immunotherapy is still not widely used in AML due to lack of an ideal target. Therefore, we identified key immune genes and cellular components in AML by an integrated bioinformatics analysis, trying to find potentia...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728998/ https://www.ncbi.nlm.nih.gov/pubmed/33329712 http://dx.doi.org/10.3389/fgene.2020.573124 |
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author | Zhao, Chong Yang, Shaoxin Lu, Wei Liu, Jiali Wei, Yanyu Guo, Hezhou Zhang, Yanjie Shi, Jun |
author_facet | Zhao, Chong Yang, Shaoxin Lu, Wei Liu, Jiali Wei, Yanyu Guo, Hezhou Zhang, Yanjie Shi, Jun |
author_sort | Zhao, Chong |
collection | PubMed |
description | Despite that immune responses play important roles in acute myeloid leukemia (AML), immunotherapy is still not widely used in AML due to lack of an ideal target. Therefore, we identified key immune genes and cellular components in AML by an integrated bioinformatics analysis, trying to find potential targets for AML. Eighty-six differentially expressed immune genes (DEIGs) were identified from 751 differentially expressed genes (DEGs) between AML patients with fair prognosis and poor prognosis from the TCGA database. Among them, nine prognostic immune genes, including NCR2, NPDC1, KIR2DL4, KLC3, TWIST1, SNORD3B-1, NFATC4, XCR1, and LEFTY1, were identified by univariate Cox regression analysis. A multivariable prediction model was established based on prognostic immune genes. Kaplan–Meier survival curve analysis indicated that patients in the high-risk group had a shorter survival rate and higher mortality than those in the low-risk group (P < 0.001), indicating good effectiveness of the model. Furthermore, nuclear factors of activated T cells-4 (NFATC4) was recognized as the key immune gene identified by co-expression of differentially expressed transcription factors (DETFs) and prognostic immune genes. ATP-binding cassette transporters (ABC transporters) were the downstream KEGG pathway of NFATC4, identified by gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA). To explore the immune responses NFATC4 was involved in, an immune gene set of T cell co-stimulation was identified by single-cell GSEA (ssGSEA) and Pearson correlation analysis, positively associated with NFATC4 in AML (R = 0.323, P < 0.001, positive). In order to find out the immune cell types affected by NFATC4, the CIBERSORT algorithm and Pearson correlation analysis were applied, and it was revealed that regulatory T cells (Tregs) have the highest correlation with NFATC4 (R = 0.526, P < 0.001, positive) in AML from 22 subsets of tumor-infiltrating immune cells. The results of this study were supported by multi-omics database validation. In all, our study indicated that NFATC4 was the key immune gene in AML poor prognosis through recruiting Tregs, suggesting that NFATC4 might serve as a new therapy target for AML. |
format | Online Article Text |
id | pubmed-7728998 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77289982020-12-15 Increased NFATC4 Correlates With Poor Prognosis of AML Through Recruiting Regulatory T Cells Zhao, Chong Yang, Shaoxin Lu, Wei Liu, Jiali Wei, Yanyu Guo, Hezhou Zhang, Yanjie Shi, Jun Front Genet Genetics Despite that immune responses play important roles in acute myeloid leukemia (AML), immunotherapy is still not widely used in AML due to lack of an ideal target. Therefore, we identified key immune genes and cellular components in AML by an integrated bioinformatics analysis, trying to find potential targets for AML. Eighty-six differentially expressed immune genes (DEIGs) were identified from 751 differentially expressed genes (DEGs) between AML patients with fair prognosis and poor prognosis from the TCGA database. Among them, nine prognostic immune genes, including NCR2, NPDC1, KIR2DL4, KLC3, TWIST1, SNORD3B-1, NFATC4, XCR1, and LEFTY1, were identified by univariate Cox regression analysis. A multivariable prediction model was established based on prognostic immune genes. Kaplan–Meier survival curve analysis indicated that patients in the high-risk group had a shorter survival rate and higher mortality than those in the low-risk group (P < 0.001), indicating good effectiveness of the model. Furthermore, nuclear factors of activated T cells-4 (NFATC4) was recognized as the key immune gene identified by co-expression of differentially expressed transcription factors (DETFs) and prognostic immune genes. ATP-binding cassette transporters (ABC transporters) were the downstream KEGG pathway of NFATC4, identified by gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA). To explore the immune responses NFATC4 was involved in, an immune gene set of T cell co-stimulation was identified by single-cell GSEA (ssGSEA) and Pearson correlation analysis, positively associated with NFATC4 in AML (R = 0.323, P < 0.001, positive). In order to find out the immune cell types affected by NFATC4, the CIBERSORT algorithm and Pearson correlation analysis were applied, and it was revealed that regulatory T cells (Tregs) have the highest correlation with NFATC4 (R = 0.526, P < 0.001, positive) in AML from 22 subsets of tumor-infiltrating immune cells. The results of this study were supported by multi-omics database validation. In all, our study indicated that NFATC4 was the key immune gene in AML poor prognosis through recruiting Tregs, suggesting that NFATC4 might serve as a new therapy target for AML. Frontiers Media S.A. 2020-11-27 /pmc/articles/PMC7728998/ /pubmed/33329712 http://dx.doi.org/10.3389/fgene.2020.573124 Text en Copyright © 2020 Zhao, Yang, Lu, Liu, Wei, Guo, Zhang and Shi. http://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 | Genetics Zhao, Chong Yang, Shaoxin Lu, Wei Liu, Jiali Wei, Yanyu Guo, Hezhou Zhang, Yanjie Shi, Jun Increased NFATC4 Correlates With Poor Prognosis of AML Through Recruiting Regulatory T Cells |
title | Increased NFATC4 Correlates With Poor Prognosis of AML Through Recruiting Regulatory T Cells |
title_full | Increased NFATC4 Correlates With Poor Prognosis of AML Through Recruiting Regulatory T Cells |
title_fullStr | Increased NFATC4 Correlates With Poor Prognosis of AML Through Recruiting Regulatory T Cells |
title_full_unstemmed | Increased NFATC4 Correlates With Poor Prognosis of AML Through Recruiting Regulatory T Cells |
title_short | Increased NFATC4 Correlates With Poor Prognosis of AML Through Recruiting Regulatory T Cells |
title_sort | increased nfatc4 correlates with poor prognosis of aml through recruiting regulatory t cells |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728998/ https://www.ncbi.nlm.nih.gov/pubmed/33329712 http://dx.doi.org/10.3389/fgene.2020.573124 |
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