One size does not fit all: navigating the multi-dimensional space to optimize T-cell engaging protein therapeutics

Abstract

T-cell engaging biologics is a class of novel and promising immune-oncology compounds that leverage the immune system to eradicate cancer. Here, we compared and contrasted a bispecific diabody-Fc format, which displays a relatively short antigen-binding arm distance, with our bispecific IgG platform. By generating diverse panels of antigen-expressing cells where B cell maturation antigen is either tethered to the cell membrane or located to the juxtamembrane region and masked by elongated structural spacer units, we presented a systematic approach to investigate the role of antigen epitope location and molecular formats in immunological synapse formation and cytotoxicity. We demonstrated that diabody-Fc is more potent for antigen epitopes located in the membrane distal region, while bispecific IgG is more efficient for membrane-proximal epitopes. Additionally, we explored other parameters, including receptor density, antigen-binding affinity, and kinetics. Our results show that molecular format and antigen epitope location, which jointly determine the intermembrane distance between target cells and T cells, allow decoupling of cytotoxicity and cytokine release, while antigen-binding affinities appear to be positively correlated with both readouts. Our work offers new insight that could potentially lead to a wider therapeutic window for T-cell engaging biologics in general.

Keywords: Bispecific engineering; cd3; t-cell engager; therapeutic window.

Figure 1.

Generation and optimization of diabody-Fc (DbFc) fusion for T-cell redirection. (a) Schematic diagram of DbFc construct after optimization of the hinge and linker sequences between the variable domains; (b) Relative geometric configurations of bispecific IgG2, DbFc, diabody (Db), and BiTE

Figure 2.

Differential cytotoxicity profiles of bispecific anti-BCMA/anti-CD3 IgG2, DbFc, and Db on engineered cell lines where BCMA is tethered to the cell surface with increasing distance from the membrane. (a) Schematic diagram of T0-T7 cell lines, with P-cadherin ectodomain structure depicted alongside to show relative dimensions; (b) Cytotoxicity of aforementioned four bispecific molecules on the eight cell lines at 24-hour timepoint; (c) EC₅₀ values as a function of the number of EGF-like domains; (d) Maximal killing (E_max) values as a function of the number of EGF-like domains

Figure 3.

Differential cytotoxicity profiles of bispecific anti-BCMA/anti-CD3 IgG2 and DbFc engineered cell lines where BCMA is located at the membrane proximal region and masked by increasing number of EGF-like domains. (a) Schematic diagram of the M0, M2, M4, and M7 cell lines depicting how BCMA and the masking EGF-like domains may potentially orient on the cell surface; (b) Dose-dependent cytotoxicity of the IgG2 and DbFc on the four cell lines at 15-hour timepoint; (c) Dose-dependent cytotoxicity of the IgG2 and DbFc on the four cell lines at 24-hour timepoint

Figure 4.

Case study using the multi-domain FTL3 as antigen demonstrating that DbFc more potently targets membrane-distal epitopes while IgG2 bispecific is more potent for membrane-proximal epitopes. (a) Crystal structure of the FLT3 extracellular region (PDB ID: 3QS9); (b) Binding of DbFc and bispecific IgG (derived from the same pairs of anti-FLT3 and anti-CD3 variable domains) to cells expressing FLT3 is equivalent over the concentration ranges tested here; (c-g) T-cell redirected lysis of the FLT3-overexpressing AML cell line EoL-1 in the presence of increasing concentrations of DbFc and IgG2-based anti-FLT3/anti-CD3 targeting domains 1, 2, 3, 4, 5 of the FLT3, respectively; (h) Schematic diagram illustrating why IgG format gives rise to more effective bridging between the epitopes located at domains 4 or 5 of FLT3 on target cell and CD3 on T cell

Figure 5.

The influence of receptor density, antigen-binding affinities, molecular format, and cytotoxicity kinetics, as represented by AUC (raw data in Supplementary Figure 5). Dashed lines represent y = x.(a-b) Pair-wise comparison of cytotoxicity of DbFc versus IgG (with the same antigen-binding arms) on cell lines with low, medium, and high receptor expression at 24 and 48 h timepoints; (c–d) Pair-wise comparison of cytotoxicity of CD3 affinity variants at 24 and 48 h timepoints, with all other parameters (cell line, affinity to BCMA, molecular format, receptor density) being the same; (e–f) Pair-wise comparison of cytotoxicity of BCMA affinity variants at 24 and 48 h timepoints, with all other parameters (cell line, affinity to CD3, molecular format, receptor density) being the same

Figure 6.

Deconvolution of cytotoxicity and cytokine release is achievable through a combination of molecular format and antigen epitope location. (a-c) Correlation of cytotoxicity versus the release of cytokines TNFα, IL-2, and IFNγ shown as AUC scatter plots, with data sets grouped based on molecular format; (d-f) Correlation of cytotoxicity versus the release of cytokines TNFα, IL-2, and IFNγ shown as AUC scatter plots, with data sets grouped based on CD3 binding affinity

Figure 7.

Exemplary cytotoxicity and cytokine release profiles for different scenarios. (a) Same cell line (T0) and same antibody clone with the only difference in therapeutic modality suggest that it is possible to decouple cytotoxicity and cytokine secretion by modulating therapeutic modality; (b) T0, IgG2 and T2, DbFc demonstrated similar potency and cytokine secretion, indicating that the optimal intermembrane distance can be achieved by a combination of modality and antigen epitope location

Figure 8.

Mathematical model of Trimer-based CD3-bispecific cytotoxicity explains dependence of potency on receptor density and Tumor antigen/CD3 affinities. (a) Structure of mathematical model for TAA-Drug-CD3 Trimer formation and tumor cell in vitro cytotoxicity. (b) Model fits for BCMA-CD3 bispecifics with different combinations of CD3 and BCMA affinities. Lines and symbols show model fits and observations respectively. Colors indicate DbFc vs IgG2 formats. (c) Model explains observed potency [Drug]_50% (= concentration to reach 50% cytotoxicity) dependence on BCMA density and Tumor antigen/CD3 affinities. Lines and symbols represent model predictions and observations respectively. (d) Model-predicted scaling relationship of (gray surface) explains the observed sensitivity of potency to these parameters

Figure 9.

Model of CD3-bispecific pharmacokinetics (PK) shows the benefit of low CD3-affinity on potential efficacy/toxicity tradeoff. (a) Structure of in vivo PK model to explain CD3-affinity dependent PK of bispecifics. In this model, typical values of linear two-compartment parameters (V1, V2, CL and Q) are used together with physiological/measured values of T-cell number, CD3/T-cell, and CD3 internalization rate are used to predict the effect of different KDCD3 on bispecific PK. (b) Validation of model of CD3-bispecific pharmacokinetics (PK) using PK data for CLL1-CD3 bispecifics in humanized CD3 mice (hCD3-Mouse) from Leong et al., Blood 2012. Time-concentration profiles predicted by the model are consistent with the observations of CD3 bispecific PK in mice reported by Leong. Lines and circles show model predictions and reported data. (c) CD3 internalization driven elimination adversely affects the in vivo therapeutic dose of high CD3 affinity bispecifics. Despite the better in vitro CTL assay potency for CD3-H (reported CLL1-CD3 EC₅₀ for CD3-H = 0.1 nM, EC₅₀ for CD3-M = 1 nM), the PK model predicts that due to CD3-M’s better in vivo half-life at the same 50ug/kg IV-weekly dose, this lower affinity bispecific is better able to maintain serum concentrations high enough (i.e. >EC₅₀) to ensure efficient killing