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Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis
BACKGROUND: Evidence has suggested that cytokine storms may be associated with T cell exhaustion (TEX) in COVID-19. However, the interaction mechanism between cytokine storms and TEX remains unclear. METHODS: With the aim of dissecting the molecular relationship of cytokine storms and TEX through si...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9172646/ https://www.ncbi.nlm.nih.gov/pubmed/35694714 http://dx.doi.org/10.1093/pcmedi/pbac014 |
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author | Yang, Minglei Lin, Chenghao Wang, Yanni Chen, Kang Han, Yutong Zhang, Haiyue Li, Weizhong |
author_facet | Yang, Minglei Lin, Chenghao Wang, Yanni Chen, Kang Han, Yutong Zhang, Haiyue Li, Weizhong |
author_sort | Yang, Minglei |
collection | PubMed |
description | BACKGROUND: Evidence has suggested that cytokine storms may be associated with T cell exhaustion (TEX) in COVID-19. However, the interaction mechanism between cytokine storms and TEX remains unclear. METHODS: With the aim of dissecting the molecular relationship of cytokine storms and TEX through single-cell RNA sequencing data analysis, we identified 14 cell types from bronchoalveolar lavage fluid of COVID-19 patients and healthy people. We observed a novel subset of severely exhausted CD8 T cells (Exh T_CD8) that co-expressed multiple inhibitory receptors, and two macrophage subclasses that were the main source of cytokine storms in bronchoalveolar. RESULTS: Correlation analysis between cytokine storm level and TEX level suggested that cytokine storms likely promoted TEX in severe COVID-19. Cell–cell communication analysis indicated that cytokines (e.g. CXCL10, CXCL11, CXCL2, CCL2, and CCL3) released by macrophages acted as ligands and significantly interacted with inhibitory receptors (e.g. CXCR3, DPP4, CCR1, CCR2, and CCR5) expressed by Exh T_CD8. These interactions formed the cytokine–receptor axes, which were also verified to be significantly correlated with cytokine storms and TEX in lung squamous cell carcinoma. CONCLUSIONS: Cytokine storms may promote TEX through cytokine-receptor axes and be associated with poor prognosis in COVID-19. Blocking cytokine-receptor axes may reverse TEX. Our finding provides novel insights into TEX in COVID-19 and new clues for cytokine-targeted immunotherapy development. |
format | Online Article Text |
id | pubmed-9172646 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-91726462022-06-10 Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis Yang, Minglei Lin, Chenghao Wang, Yanni Chen, Kang Han, Yutong Zhang, Haiyue Li, Weizhong Precis Clin Med Research Article BACKGROUND: Evidence has suggested that cytokine storms may be associated with T cell exhaustion (TEX) in COVID-19. However, the interaction mechanism between cytokine storms and TEX remains unclear. METHODS: With the aim of dissecting the molecular relationship of cytokine storms and TEX through single-cell RNA sequencing data analysis, we identified 14 cell types from bronchoalveolar lavage fluid of COVID-19 patients and healthy people. We observed a novel subset of severely exhausted CD8 T cells (Exh T_CD8) that co-expressed multiple inhibitory receptors, and two macrophage subclasses that were the main source of cytokine storms in bronchoalveolar. RESULTS: Correlation analysis between cytokine storm level and TEX level suggested that cytokine storms likely promoted TEX in severe COVID-19. Cell–cell communication analysis indicated that cytokines (e.g. CXCL10, CXCL11, CXCL2, CCL2, and CCL3) released by macrophages acted as ligands and significantly interacted with inhibitory receptors (e.g. CXCR3, DPP4, CCR1, CCR2, and CCR5) expressed by Exh T_CD8. These interactions formed the cytokine–receptor axes, which were also verified to be significantly correlated with cytokine storms and TEX in lung squamous cell carcinoma. CONCLUSIONS: Cytokine storms may promote TEX through cytokine-receptor axes and be associated with poor prognosis in COVID-19. Blocking cytokine-receptor axes may reverse TEX. Our finding provides novel insights into TEX in COVID-19 and new clues for cytokine-targeted immunotherapy development. Oxford University Press 2022-05-23 /pmc/articles/PMC9172646/ /pubmed/35694714 http://dx.doi.org/10.1093/pcmedi/pbac014 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the West China School of Medicine & West China Hospital of Sichuan University. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Yang, Minglei Lin, Chenghao Wang, Yanni Chen, Kang Han, Yutong Zhang, Haiyue Li, Weizhong Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis |
title | Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis |
title_full | Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis |
title_fullStr | Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis |
title_full_unstemmed | Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis |
title_short | Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis |
title_sort | cytokine storm promoting t cell exhaustion in severe covid-19 revealed by single cell sequencing data analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9172646/ https://www.ncbi.nlm.nih.gov/pubmed/35694714 http://dx.doi.org/10.1093/pcmedi/pbac014 |
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