Mapping the effector response space of antibody combinations

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Antibodies are crucial, central regulators of the immune response. They are particularly versatile therapeutic agents due to their ability to both bind to a target with high affinity and direct the immune system. Indeed, antibodies comprise a broad range of approved therapies across disease indications, many of which are known to rely in large part on effector cell (immune) response. Antibodies of the IgG isotype interact with FcγRs on effector cells and elicit effector function through multiple cell types (e.g., macrophages, monocytes) and through multiple processes, including phagocytosis and killing of diseased cells. The many possible design parameters—constant region composition, FcγRs, cell populations, and antigen binding in combination—have made precisely understanding, measuring, and manipulating effector function an elusive goal. Our proposed work is centered around the hypothesis that two IgGs can elicit distinct responses when present in combination from what would be suggested by the response to either on its own. Using a computational model of antibody-FcγR interaction, we will identify predicted cases of this emergent behavior. These combinations will be tested for their binding and effector response in vitro and then in two models of antibody-targeted cell killing. Finally, we will use the computational model of effector regulation to map how human and mouse IgGs are related according to their effector response. In total, these efforts will provide critical information for designing more effective antibodies with the goal of targeted cell killing and provide a clearer view of how existing therapeutic antibodies function.