Identification of clinically relevant T cell receptors for personalized T cell therapy using combinatorial algorithms.
Journal
Nature biotechnology
ISSN: 1546-1696
Titre abrégé: Nat Biotechnol
Pays: United States
ID NLM: 9604648
Informations de publication
Date de publication:
07 May 2024
07 May 2024
Historique:
received:
07
11
2023
accepted:
02
04
2024
medline:
8
5
2024
pubmed:
8
5
2024
entrez:
7
5
2024
Statut:
aheadofprint
Résumé
A central challenge in developing personalized cancer cell immunotherapy is the identification of tumor-reactive T cell receptors (TCRs). By exploiting the distinct transcriptomic profile of tumor-reactive T cells relative to bystander cells, we build and benchmark TRTpred, an antigen-agnostic in silico predictor of tumor-reactive TCRs. We integrate TRTpred with an avidity predictor to derive a combinatorial algorithm of clinically relevant TCRs for personalized T cell therapy and benchmark it in patient-derived xenografts.
Identifiants
pubmed: 38714897
doi: 10.1038/s41587-024-02232-0
pii: 10.1038/s41587-024-02232-0
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s).
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