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

Rémy Pétremand; Johanna Chiffelle; Sara Bobisse; Marta A S Perez; Julien Schmidt; Marion Arnaud; David Barras; Maria Lozano-Rabella; Raphael Genolet; Christophe Sauvage; Damien Saugy; Alexandra Michel; Anne-Laure Huguenin-Bergenat; Charlotte Capt; Jonathan S Moore; Claudio De Vito; S Intidhar Labidi-Galy; Lana E Kandalaft; Denarda Dangaj Laniti; Michal Bassani-Sternberg; Giacomo Oliveira; Catherine J Wu; George Coukos; Vincent Zoete; Alexandre Harari

doi:10.1038/s41587-024-02232-0

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

Nat Biotechnol. 2024 May 7. doi: 10.1038/s41587-024-02232-0. Online ahead of print.

Authors

Rémy Pétremand^{1

2}, Johanna Chiffelle^{1

2}, Sara Bobisse^{1

2}, Marta A S Perez^{1

3}, Julien Schmidt^{1

2

4}, Marion Arnaud^{1

2}, David Barras^{1

2}, Maria Lozano-Rabella^{1

2}, Raphael Genolet^{1

2}, Christophe Sauvage^{1

2}, Damien Saugy^{1

2}, Alexandra Michel^{1

2}, Anne-Laure Huguenin-Bergenat^{1

2}, Charlotte Capt^{1

2}, Jonathan S Moore⁵, Claudio De Vito⁶, S Intidhar Labidi-Galy^{5

7}, Lana E Kandalaft^{1

2

4}, Denarda Dangaj Laniti^{1

2}, Michal Bassani-Sternberg^{1

2

4}, Giacomo Oliveira^{8

9

10}, Catherine J Wu^{8

9

10}, George Coukos^{1

2

11}, Vincent Zoete^{1

3}, Alexandre Harari^{12

13}

Affiliations

¹ Ludwig Institute for Cancer Research, Lausanne Branch, Department of Oncology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Agora Cancer Research Center, Lausanne, Switzerland.
² Center for Cell Therapy, CHUV-Ludwig Institute, Lausanne, Switzerland.
³ Molecular Modelling Group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
⁴ Center of Experimental Therapeutics, Lausanne University Hospital (CHUV), Lausanne, Switzerland.
⁵ Department of Medicine and Center of Translational Research in Onco-Hematology, Faculty of Medicine, University of Geneva, Swiss Cancer Center Leman, Geneva, Switzerland.
⁶ Division of Clinical Pathology, Department of Diagnostics, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
⁷ Department of Oncology, Hôpitaux Universitaires de Genève, Geneva, Switzerland.
⁸ Dana-Farber Cancer Institute, Boston, MA, USA.
⁹ Harvard Medical School, Boston, MA, USA.
¹⁰ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹¹ Immuno-oncology Service, Department of Oncology, Lausanne University Hospital, Lausanne, Switzerland.
¹² Ludwig Institute for Cancer Research, Lausanne Branch, Department of Oncology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Agora Cancer Research Center, Lausanne, Switzerland. [email protected].
¹³ Center for Cell Therapy, CHUV-Ludwig Institute, Lausanne, Switzerland. [email protected].

PMID: 38714897
DOI: 10.1038/s41587-024-02232-0

Abstract

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.