Time to evolve: predicting engineered T cell-associated toxicity with next-generation models

Emmanuel Donnadieu, Maik Luu, Miriam Alb, Brigitte Anliker, Silvia Arcangeli, Chiara Bonini, Biagio de Angelis, Rashmi Choudhary, David Espie, Anne Galy, Cam Holland, Zoltán Ivics, Chahrazade Kantari-Mimoun, Marie Jose Kersten, Ulrike Köhl, Chantal Kuhn, Bruno Laugel, Franco Locatelli, Ibtissam Marchiq, Janet MarkmanMarta Angiola Moresco, Emma Morris, Helene Negre, Concetta Quintarelli, Michael Rade, Kristin Reiche, Matthias Renner, Eliana Ruggiero, Carmen Sanges, Hans Stauss, Maria Themeli, Jan van den Brulle, Michael Hudecek, Monica Casucci

Research output: Contribution to journalReview articleAcademicpeer-review

21 Citations (Scopus)

Abstract

Despite promising clinical results in a small subset of malignancies, therapies based on engineered chimeric antigen receptor and T-cell receptor T cells are associated with serious adverse events, including cytokine release syndrome and neurotoxicity. These toxicities are sometimes so severe that they significantly hinder the implementation of this therapeutic strategy. For a long time, existing preclinical models failed to predict severe toxicities seen in human clinical trials after engineered T-cell infusion. However, in recent years, there has been a concerted effort to develop models, including humanized mouse models, which can better recapitulate toxicities observed in patients. The Accelerating Development and Improving Access to CAR and TCR-engineered T cell therapy (T2EVOLVE) consortium is a public-private partnership directed at accelerating the preclinical development and increasing access to engineered T-cell therapy for patients with cancer. A key ambition in T2EVOLVE is to design new models and tools with higher predictive value for clinical safety and efficacy, in order to improve and accelerate the selection of lead T-cell products for clinical translation. Herein, we review existing preclinical models that are used to test the safety of engineered T cells. We will also highlight limitations of these models and propose potential measures to improve them.
Original languageEnglish
JournalJournal for Immunotherapy of Cancer
Volume10
Issue number5
DOIs
Publication statusPublished - 1 May 2022

Keywords

  • immunotherapy

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