Journal article
T-cell-receptor cross-recognition and strategies to select safe T-cell receptors for clinical translation
T-Cells and Cancer, Experimental & Translational Immunology, Department of Health Technology, Technical University of Denmark1
Experimental & Translational Immunology, Department of Health Technology, Technical University of Denmark2
Department of Health Technology, Technical University of Denmark3
Adoptive transfer of T-cell-receptor (TCR)-transduced T cells has shown promising results for cancer treatment, but has also produced severe immunotoxicities caused by on-target as well as off-target TCR recognition. Off-target toxicities are related to the ability of a single T cell to cross-recognize and respond to several different peptide–major histocompatibility complex (pMHC) antigens; a property that is essential for providing broad antigenic coverage despite a confined number of unique TCRs in the human body.
However, this degeneracy makes it incredibly difficult to account for the range of targets that any TCR might recognize, which represents a major challenge for the clinical development of therapeutic TCRs. The prospect of using affinity-optimized TCRs has been impeded due to observations that affinity enhancement might alter the specificity of a TCR, thereby increasing the risk that it will cross-recognize endogenous tissue.
Strategies for selecting safe TCRs for the clinic have included functional assessment after individual incubations with tissue-derived primary cells or with peptides substituted with single amino acids. However, these strategies have not been able to predict cross-recognition sufficiently, leading to fatal cross-reactivity in clinical trials.
Novel technologies have emerged that enable extensive characterization of the exact interaction points of a TCR with pMHC, which provides a foundation from which to make predictions of the cross-recognition potential of individual TCRs. This review describes current advances in strategies for dissecting the molecular interaction points of TCRs, focusing on their potential as tools for predicting cross-recognition of TCRs in clinical development.
Language: | English |
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Publisher: | Elsevier Inc |
Year: | 2019 |
Pages: | 1-10 |
ISSN: | 25900188 |
Types: | Journal article |
DOI: | 10.1016/j.iotech.2019.06.003 |
ORCIDs: | Bentzen, Amalie Kai and Hadrup, Sine Reker |