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Chu, T.* ; Wu, M.* ; Höllbacher, B. ; de Almeida, G.P.* ; Wurmser, C.* ; Berner, J.* ; Donhauser, L.V.* ; Ann-Katrin, G.* ; Lin, S.* ; Cepeda-Mayorga, J.D.* ; Kilb, I.I.* ; Bongers, L.* ; Toppeta, F.* ; Strobl, P.* ; Youngblood, B.* ; Schulz, A.M.* ; Zippelius, A.* ; Knolle, P.A.* ; Heinig, M. ; Hackstein, C.P.* ; Zehn, D.*

Precursors of exhausted T cells are preemptively formed in acute infection.

Nature, DOI: 10.1038/s41586-024-08451-4 (2025)
Publ. Version/Full Text Research data DOI PMC
Open Access Gold (Paid Option)
Creative Commons Lizenzvertrag
T cell exhaustion limits effector T cell function in chronic infection and tumors1,2. The development of these hypofunctional T cells and of their precursors was considered to require stimulatory conditions met only upon persisting exposure to antigen and inflammation. In sharp contrast, we found similar T cell populations in the early phase of acute infections1,2. At that stage early developing TCF1+ precursor population shows an unexpected diversity, which includes precursors of normal memory T cells but also cells with a phenotype, gene-expression, and epigenetic profile that resembles precursors of exhausted T cells found in chronic infections. We demonstrate that high ligand affinity promotes, and PD-1 signaling restricts the development of these precursors. While these exhausted precursors are initially frequently found, they decline without being completely lost in infections the immune system resolves. We therefore concluded that precursor T cells with at least two distinct phenotypes are preemptively generated irrespectively of the outcome of the infection.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Differentiation; Quantification; Persistence; Dysfunction; Receptors; Phenotype; Cancer; States; Limits
ISSN (print) / ISBN 0028-0836
e-ISSN 1476-4687
Journal Nature
Publisher Nature Publishing Group
Publishing Place London
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Grants German Israeli Foundation (GIF)
German Research Foundation
European Research Council
San Salvatore Foundation
Helmholtz Association under the joint research school Munich School for Data Science (MUDS)