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

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 si...

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Published in:Nature biotechnology 2024-05
Main Authors: Pétremand, Rémy, Chiffelle, Johanna, Bobisse, Sara, Perez, Marta A S, Schmidt, Julien, Arnaud, Marion, Barras, David, Lozano-Rabella, Maria, Genolet, Raphael, Sauvage, Christophe, Saugy, Damien, Michel, Alexandra, Huguenin-Bergenat, Anne-Laure, Capt, Charlotte, Moore, Jonathan S, De Vito, Claudio, Labidi-Galy, S Intidhar, Kandalaft, Lana E, Dangaj Laniti, Denarda, Bassani-Sternberg, Michal, Oliveira, Giacomo, Wu, Catherine J, Coukos, George, Zoete, Vincent, Harari, Alexandre
Format: Article
Language:English
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Summary: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.
ISSN:1087-0156
1546-1696
1546-1696
DOI:10.1038/s41587-024-02232-0