Deep phenotypical characterization of human CD3
CD56
T cells
allergy
human
mass cytometry
Journal
European journal of immunology
ISSN: 1521-4141
Titre abrégé: Eur J Immunol
Pays: Germany
ID NLM: 1273201
Informations de publication
Date de publication:
03 2021
03 2021
Historique:
received:
26
08
2020
revised:
25
09
2020
accepted:
19
11
2020
pubmed:
25
11
2020
medline:
21
8
2021
entrez:
24
11
2020
Statut:
ppublish
Résumé
CD56
Identifiants
pubmed: 33231295
doi: 10.1002/eji.202048941
doi:
Substances chimiques
Antigens, Differentiation, T-Lymphocyte
0
CD3 Complex
0
CD56 Antigen
0
Receptors, Antigen, T-Cell, gamma-delta
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
672-681Informations de copyright
© 2020 The Authors. European Journal of Immunology published by Wiley-VCH GmbH.
Références
Van Acker, H. H., Capsomidis, A., Smits, E. L. and Van Tendeloo, V. F., CD56 in the immune system: more than a marker for cytotoxicity? Front. Immunol. 2017. 8: 892.
Almehmadi, M., Flanagan, B. F., Khan, N., Alomar, S. and Christmas, S. E., Increased numbers and functional activity of CD56+ T cells in healthy cytomegalovirus positive subjects. Immunology 2014. 142: 258-268.
Peng, L., Mao, F., Zhao, Y., Wang, T., Chen, N., Zhang, J., Cheng, P. et al., Altered phenotypic and functional characteristics of CD3+CD56+ NKT-like cells in human gastric cancer. Oncotarget 2016. 34: 55222-55230.
Montoya, C. J., Pollar, D., Martinson, J., Kumari, K., Wasserfall, C., Mulder, C., Rugeles, M. T. et al., Characterization of human invariant natural killer T subsets in health and disease using a novel invariant natural killer T cell-clonotypic monoclonal antibody, 6B11. Immunology 2007. 122: 1-14.
Norris, S., Doherty, D. G., Collins, C., McEntee, G., Traynor, O., Hegarty, J. E., and O'Farrelly, C., Natural T cells in the human liver: cytotoxic lymphocytes with dual T cell function are phenotypically heterogeneous and include Vα24-JαQ and γδ T cell receptor bearing cells. Hum. Immunol. 1999. 60: 20-31.
Dias, J., Leeansyah, E., and Sandberg, J. K., Multiple layers of heterogeneity and subset diversity in human MAIT cell responses to distinct microorganisms and to innate cytokines. Proc. Natl. Acad. Sci. USA 2017. 114: E5434-E5443.
Slauenwhite, D., and Johnston, B., Regulation of NKT cell localization in homeostasis and infection. Front. Immunol. 2015. 6: 255.
Akbari, O., Stock, P., Meyer, E., Kronenber, M., Sidobre, S., Nakayama, T., Taniguchi, M. et al., Essential role of NKT cells producing IL-4 and IL-3 in the development of allergen-induced airway hyperreactivity. Nat. Med. 2003. 9: 582-588.
Schulz, A. R., and Mei, H. E., Surface barcoding of live PBMC for multiplexed mass cytometry. Methods Mol. Biol. 2019. 1989: 93-108.
Mei, H. E., Leipold, M. D., Schulz, A. R., Chester, C. and Maecker, H. T., Barcoding of live human PBMC for multiplexed mass cytometry. J. Immunol. 2015. 194: 2022-2031.
Maaten, L. V. D., and Hinton, G., Visualizing data using t-SNE. J. Mach. Learn. 2008. 9: 2579-2605.
Edwards, M. R., Strong, K., Cameron, A., Walton, R. P., Jackson, D. J., and Johnston, S. L., Viral infections in allergy and immunology: how allergic inflammation influences viral infections and illness. J. Allergy Clin. Immunol. 2017. 140: 909-920.
Van Gassen, S., Callebaut, B., Van Helden, M. J., Lambrecht, B. N., Demeester, P., Dhaene, T., and Saeys, Y., FlowSOM: using self-organizing maps for visualization and interpretation of mass cytometry data. Cytometry A 2015. 87: 636-645.
Nowicka, M., Krieg, C., Crowell, H. L., Weber, L. M., Hartmann, F. J., Guglietta, S., Becher, B. et al., CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets. F1000Res. 2017. 6: 748.
Stikvoort, A., Chen, Y., Rådestad, E., Törlén, J., Lakshmikanth, T., Björklund, A., Mikes, J. et al., Combining flow and mass cytometry in the search for biomarkers in chronic graft-versus-host disease. Front. Immunol. 2017. 8: 717.
Yu, H. T., Youn, J., Lee, J., Park, S., Chi, H., Lee, J., Choi, C. et al., Characterization of CD8+CD57+ T cells in patients with acute myocardial infarction. Cell. Mol. Immunol. 2015. 12: 466-473.
Kadivar, M., Petersson, J., Svensson, L., and Marsal, J., CD8αβ+ γδ T cells: a novel T cell subset with a potential role in inflammatory bowel disease. J. Immunol. 2016. 197: 4584-4592.
Kared, H., Martelli, S., Ng, T. P., Pender, S. L. F., and Larbi, A., CD57 in human natural killer cells and T-lymphocytes. Cancer Immunol. Immunother. 2016. 65: 441-452.
Bengsch, B., Ohtani, T., Herati, R. S., Bovenschen, N., Chang, K. and Wherry, E. J., Deep immune profiling by mass cytometry links human T and NK cell differentiation and cytotoxic molecule expression patterns. J. Immunol. Methods 2018. 453: 3-10.
Yang, Z., Kim, H. J., Villasboas, J. C., Price-Troska, T., Shahrzad, J., Wu, H., Luchtel, R. A. et al., Mass cytometry analysis reveals that specific intratumoral CD4+ T cell subsets correlate with patient survival in follicular lymphoma. Cell. Rep. 2019. 26: 2178-2193.
Hlongwane, P., Mungra, N., Madheswaran, S., Akinrinmade, O. A., Chetty, S., and Barth, S., Human granzyme B based targeted cytolytic fusion proteins. Biomedicines. 2018. 6: 72.
Fergusson, J. R., Fleming, V. M., and Klenerman, P., CD161-expressing human T cells. Front. Immunol. 2011. 2: 36.
Billerbeck, E., Kang, Y., Walker, L., Lockstone, H., Grafmueller, S., Fleming, V., Flint, J. et al., Analysis of CD161 expression on human CD8+ T cells defines a distinct functional subset with tissue-homing properties. Proc. Natl. Acad. Sci. USA 2010. 107: 3006-3011.
Northfiel, J. W., Kasprowicz, V., Lucas, M., Kersting, N., Bengsch, B., Kim, A., Phillips, R. E. et al., CD161 expressing on hepatitis C virus-specific CD8+ T cells suggest a distinct pathway of T cell differentiation. Hepatology 2008. 47: 396-406.
Takahashi, T., Dejbakhsh-Jones, S., and Strober, S., Expression of CD161 (NKR-P1A) defines subsets of CD4 and CD8 T cells with different functional activities. J. Immunol. 2006. 176: 211-216.
Annunziato, F., Cosmi, L., Santarlasci, V., Maggi, L., Liotta, F., Mazzinghi, B., Parente, E. et al., Phenotypic and functional features of human Th17 cells. J. Exp. Med. 2007. 204: 1849-1861.
Cosmi, L., De Palma, R., Santarlasci, V., Maggi, L., Capone, M., Frosali, F., Rodolico, G. et al., Human interleukin 17-producing cells originate from a CD161+CD4+ T cell precursor. J. Exp. Med. 2008. 205: 1903-1916.
Kleinschek, M. A., Boniface, K., Sadekova, S., Grein, J., Murphy, E. E., Turner, S. P., Raskin, L. et al., Circulating and gut-resident human Th17 cells express CD161 and promote intestinal inflammation. J. Exp. Med. 2009. 206: 525-534.
Maggi, L., Santarlasci, V., Capone, M., Peired, A., Frosali, F., Crome, S., Querci, V. et al., CD161 is a marker of all human IL-17-producing T-cell subsets and is induced by RORC. Eur. J. Immunol. 2010. 40: 2174-2181.
Tian, Y., Babor, M., Lane, J., Schulten, V., Patil, V. S., Seumois, G., Rosales, S. L. et al., Unique phenotypes and clonal expansions of human CD4 effector memory T cells re-expressing CD45RA. Nat. Commun. 2017. 8: 1473.
Sallusto, F., Geginat, J., Lanzavecchia, A., Central memory and effector memory T cell subsets: function, generation, and maintenance. Annu. Rev. Immunol. 2004. 22: 745-763.
Champagne, P., Ogg, G. S., King, A. S., Knabenhans, C., Ellefsen, K., Nobile, M., Appay, V. et al., Skewed maturation of memory HIV-specific CD8 T lymphocytes. Nature 2001. 410: 106-111.
Sallusto, F., Lenig, D., Förster, R., Lipp, M., and Lanzavecchia, A., Two subsets of memory T lymphocytes with distinct homing potentials and effector functions. Nature 1999. 401: 708-712.
Mittrücker, H., Visekruna, A., and Huber, M., Heterogeneity in the differentiation and function of CD8+ T cells. Arch. Immunol. Ther. Exp. (Warsz) 2014. 62: 449-458.
Mei, H. E., Leipold, M. D., and Maecker, H. T., Platinum-conjugated antibodies for application in mass cytometry. Cytometry A 2016. 89: 292-300.
Schulz, A. R., Baumgart, S., Schulze, J., Urbicht, M., Grützau, A., and Mei, H. E., Stabilizing antibody cocktails for mass cytometry. Cytometry A 2019. 95: 910-916.
Leipold, M. D., Newell, E. W., and Maecker, H. T., Multiparameter phenotyping of human PBMC using mass cytometry. Methods Mol. Biol. 2015. 1343: 81-95.
Chevrier, S., Crowell, H. L., Zaanotelli, V. R. T., Engler, S., Robinson, M. D., and Bodenmiller, B., Compensation of signal spillover in suspension and imaging mass cytometry. Cell Syst. 2018. 6: 612-620.
Budzinski, L., Schulz, A. R., Baumgart, S., Burns, T., Rose, T., Hirseland, H., and Mei, H. E., Osmium-labeled microspheres for bead-based assays in mass cytometry. J. Immunol. 2019. 202: 3103-3112.
Amir, E. D., Davis, K. L., Tadmor, M. D., Simonds, E. F., Levine, J. H., Bendall, S. C., Shenfeld, D. K. et al., viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat. Biotechnol. 2013. 31: 545-552.
Chen, T. J., and Kotecha, N. Cytobank: providing an analytics platform for community cytometry data analysis and collaboration. Curr. Top. Microbiol. Immunol. 2014. 377: 127-157.
Belkina, A. C., Ciccolella, C. O., Anno, R., Halpert, R., Spidlen, J., and Snyder-Cappione, J. E., Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets. Nat. Commun. 2019. 10: 5415.