Engineering a tumor-selective prodrug T-cell engager bispecific antibody for safer immunotherapy

Abstract

T-cell engaging (TCE) bispecific antibodies are potent drugs that trigger the immune system to eliminate cancer cells, but administration can be accompanied by toxic side effects that limit dosing. TCEs function by binding to cell surface receptors on T cells, frequently CD3, with one arm of the bispecific antibody while the other arm binds to cell surface antigens on cancer cells. On-target, off-tumor toxicity can arise when the target antigen is also present on healthy cells. The toxicity of TCEs may be ameliorated through the use of pro-drug forms of the TCE, which are not fully functional until recruited to the tumor microenvironment. This can be accomplished by masking the anti-CD3 arm of the TCE with an autoinhibitory motif that is released by tumor-enriched proteases. Here, we solve the crystal structure of the antigen-binding fragment of a novel anti-CD3 antibody, E10, in complex with its epitope from CD3 and use this information to engineer a masked form of the antibody that can activate by the tumor-enriched protease matrix metalloproteinase 2 (MMP-2). We demonstrate with binding experiments and in vitro T-cell activation and killing assays that our designed prodrug TCE is capable of tumor-selective T-cell activity that is dependent upon MMP-2. Furthermore, we demonstrate that a similar masking strategy can be used to create a pro-drug form of the frequently used anti-CD3 antibody SP34. This study showcases an approach to developing immune-modulating therapeutics that prioritizes safety and has the potential to advance cancer immunotherapy treatment strategies.

Keywords: Antibody engineering; CD3; HER2; T cell activation; T cell retargeting; bispecific antibody; cancer; cytokine release syndrome; x-ray structure.

Figure 1.

Crystal structure of E10 antibody with CD3ε peptide (PDB 8VY4) informs design of pro-TCE. (a) Top-down view of the isolated CDR loops (green) from anti-CD3 antibody E10 in contact with the CD3ε peptide antigen (pink). Key binding interaction features are highlighted from left to right respectively: N-terminal pyroglutamate, CDRH3 contacts with CD3ε, and CDRL3 contacts with CD3ε. (b) Fluorescence polarization binding data with WT and alanine mutant CD3ε peptides with anti-CD3 hE10 fab. The table below shows two K_D values for WT. “WT*” represents our best estimate for K_D and associated error from all replicates, while “WT*” and all other K_D values in the table are the fitted values and errors to the fit from the specific experiment shown in the figure. (c) PyRosetta Model of designed pro-TCE anti-CD3 antibody fragment and sequence of CD3ε peptide (pink) prepended with MMP-2 cleavage sites (blue). (d) Fluorescence polarization binding data with pro-TCE antibody fragment before and after MMP-2 proteolysis. K_D with reported standard deviation of the mean is shown for two replicate measurements. *Q undergoes cyclization to pyroglutamic acid (Pyr) under physiological conditions.

Figure 2.

Recombinant expression, assembly and biophysical characterization of pro-TCE. (a) Interface mutations across the antibody fab and Fc framework regions facilitate proper recombinant assembly of IgG bispecific antibodies. (b) SDS-PAGE gel electrophoresis showing recombinant MMP-2 before and after activation with APMA, and the pro-TCE before and after proteolysis with the active MMP-2. Protein samples treated with βMe. (c) Fluorescence polarization binding data with pro-TCE IgG before and after MMP-2 proteolysis. The reported K_D values are averages with errors reflecting the standard deviation of the mean for three replicates. (d) Biolayer interferometry data of the immobilized pro-TCE and parental anti-HER2 pertuzumab binding to HER2 extracellular domain before proteolysis. (e) Biolayer interferometry data of the immobilized pro-TCE and parental anti-CD3 hE10 mAb binding to CD3γε extracellular domain before and after proteolysis. In (d-e) the reported K_D values are averages along with the standard deviation of the mean for two replicates.

Figure 3.

Preclinical functional validation of pro-TCE with recombinant MMP-2 protease treatment. All experiments were performed at an effector cell to target cell ratio of 1:1. Each point represents the mean value of triplicates. (a) T cell activation induced by pro-TCE after proteolysis using a Jurkat NFAT-Luciferase T cell model. (b) HER2⁺ target cell killing by hPBMCs induced by pro-TCE after proteolysis after 48 hours. (c–d) IL-2 and IFN-γ secretion by hPBMCs induced by pro-TCE after 48 hours. The reported errors for the EC₅₀ values are the 95% confidence intervals from fitting each individual experiment.

Figure 4.

NCI-N87 tumor cell secreted proteases trigger pro-TCE activity. SDS-PAGE gel electrophoresis of pro-TCE before and after incubation with NCI-N87 cellular supernatant for 1 h (left). Jurkat NFAT-Luciferase T cell activation assay with NCI-N87 target cells (right). The reported EC₅₀ value is an average of three replicates with errors reflecting the 95% confidence intervals of the average measurements.

Figure 5.

Expanding the pro-TCE conditionally active T cell engager platform to clone SP34. (a) Anti-CD3 mAbs hE10 and SP34 both bind the N-terminus of CD3ε. (b) SDS-PAGE gel electrophoresis of SP34_Pertuzumab pro-TCE before and after proteolysis. (c) Designed pro-TCE using anti-CD3 mAb with SP34 CD3-binding arm activates Jurkat NFAT-Luciferase T cells when proteolyzed but not when masked. The reported EC₅₀ value is an average of three replicates with errors reflecting the 95% confidence intervals of the average measurements.