Impacts of Antibody Structure and Mixtures on Receptor Signaling for Antibody-Dependent Cellular Cytotoxicity

Antibody-Dependent Cellular Cytotoxicity (ADCC) is a key mechanism of action for humoral immune response, which is important for clinical antibodies such as trastuzumab and cetuximab. The level of ADCC is dependent on multiple properties such as antibody isotype, Fab affinity, epitope, and geometry in the immune synapse. Here, we integrated computational simulations with experiments to analyze the impacts of several key factors on ADCC, including binding affinity, target expression, hinge flexibility, and antibody valency. The kinetic model was adapted to simulate antibody cross-linking between tumor and immune-reporter cells, followed by signal activation. Given the complexity of the interactions between cells and the formation of the immunological synapse, we fitted the effective on-rates within the synapse that are hard to determine a priori. With minimal fitting, the model successfully replicated the trends of immune activation for a series of trastuzumab structural mutants. The simulations demonstrated that antibody variants with a higher likelihood of monovalent target binding, such as single-arm antibodies, as well as those with low Fab affinity and reduced hinge flexibility, increased signaling. The model was able to capture the efficacy of mixtures of antibodies with different Fc domains, which are relevant for combination treatments such as trastuzumab and pertuzumab. Interestingly, the fraction of receptors blocked with antibody combinations was more important than total receptor expression, implying restrictions on diffusion of free receptors in the synapse. Overall, the simulations showed close agreement with experimental observations, providing a tool to interpret the ADCC results and guide the design of antibody therapeutics.