Identification of clinically relevant T cell receptors for personalized T cell therapy using combinatorial algorithms.

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Accès restreint UNIL
Etat: Public
Version: de l'auteur⸱e
Licence: CC BY 4.0
ID Serval
serval:BIB_AF334A302D27
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Identification of clinically relevant T cell receptors for personalized T cell therapy using combinatorial algorithms.
Périodique
Nature biotechnology
Auteur⸱e⸱s
Pétremand R., Chiffelle J., Bobisse S., Perez MAS, Schmidt J., Arnaud M., Barras D., Lozano-Rabella M., Genolet R., Sauvage C., Saugy D., Michel A., Huguenin-Bergenat A.L., Capt C., Moore J.S., De Vito C., Labidi-Galy S.I., Kandalaft L.E., Dangaj Laniti D., Bassani-Sternberg M., Oliveira G., Wu C.J., Coukos G., Zoete V., Harari A.
ISSN
1546-1696 (Electronic)
ISSN-L
1087-0156
Statut éditorial
In Press
Peer-reviewed
Oui
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: 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.
Pubmed
Web of science
Open Access
Oui
Création de la notice
10/05/2024 13:37
Dernière modification de la notice
14/08/2024 6:17
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