CAR-J cells for antibody discovery and lead optimization of TCR-like immunoglobulins

Abstract

T-cell bispecific antibodies (TCBs) are a novel class of engineered immunoglobulins that unite monovalent binding to the T-cell receptor (TCR) CD3e chain and bivalent binding to tumor-associated antigens in order to recruit and activate T-cells for tumor cell killing. In vivo, T-cell activation is usually initiated via the interaction of the TCR with the peptide-HLA complex formed by the human leukocyte antigen (HLA) and peptides derived from intracellular proteins. TCR-like antibodies (TCRLs) that recognize pHLA-epitopes extend the target space of TCBs to peptides derived from intracellular proteins, such as those overexpressed during oncogenesis or created via mutations found in cancer. One challenge during lead identification of TCRL-TCBs is to identify TCRLs that specifically, and ideally exclusively, recognize the desired pHLA, but not unrelated pHLAs. In order to identify TCRLs suitable for TCRL-TCBs, large numbers of TCRLs have to be tested in the TCB format. Here, we propose a novel approach using chimeric antigen receptors (CARs) to facilitate the identification of highly selective TCRLs. In this new so-called TCRL-CAR-J approach, TCRL-candidates are transduced as CARs into Jurkat reporter-cells, and subsequently assessed for their specificity profile. This work demonstrates that the CAR-J reporter-cell assay can be applied to predict the profile of TCRL-TCBs without the need to produce each candidate in the final TCB format. It is therefore useful in streamlining the identification of TCRL-TCBs.

A de-risking experimental framework defines the physiological interactome of TCR-based therapeutics in human tissues

“…In the absence of a human relevant cross-reactive toxicology species, the non-clinical safety evaluation of TCRlike molecules is generally supported by new alternative methods. At an early stage of development, in silico strategies integrating peptide binding prediction and TCR contact profile elucidation through structural computational modeling are leveraged to predict potential off-targets (7). In silico strategies interrogating TCR repertoires rely on interactome data obtained from large peptide or HLA peptide complex libraries that enable the estimation of the TCR specificity (8)(9)(10)(11)(12)(13)(14).…”

The physiological interactome of TCR-like antibody therapeutics in human tissues

“…In the absence of a human relevant cross-reactive toxicology species, the non-clinical safety evaluation of TCR-like molecules is generally supported by new alternative methods. At an early stage of development, in silico strategies integrating peptide binding prediction and TCR/antibody contact profile elucidation through structural computational modeling are leveraged to predict potential off-targets 7 . In silico strategies interrogating TCR repertoires rely on interactome data obtained from large peptide or HLA peptide complex libraries that enable the determination of the TCR or TCR-like antibody specificity profile [8][9][10][11][12][13][14][15] .…”