UCLA

Cytokine signaling a core mechanism by which immune activity is regulated in both health anddisease. Cytokine-mediated signaling regulates the proliferation, differentiation, and activity of cells in both the innate and adaptive immune systems. Due to their powerful regulatory capacity, cytokines have been leveraged as immunotherapies in a wide range of disease indications; for example, interleukin-2 (IL-2) has been explored as a potential immunostimulant for the treatment for cancer, as well as an immunosuppressant for the treatment of autoimmune diseases. However, in many such cases, the pleiotropic nature of cytokine signaling has stymied the development of efficacious and safe therapies due to the induction of signaling in off-target populations. To overcome this limitation and bias cytokines towards signaling in target populations, engineered cytokines with a variety of alterations, such as mutations affecting their binding interactions with their cognate receptors, fusion to antibody fragments, or co-formulation with antibodies to that cytokine have been developed. However, without a quantitative model of signaling the effects of such mutations and alterations are often difficult to anticipate, leading to inefficient cytokine engineering efforts. To address this lack of quantitative understanding, we conducted a battery of computational studies. First, using a mechanistic binding model, we developed a general, quantitative understanding of the landscape of cell-selective cytokine signaling, and found that affinity, valency, and multi-specificity must be simultaneously optimized to engineer optimally selective cytokines. We then specifically studied the IL-2 signaling pathway, and used both ordinary differential equation models and our mechanistic binding model to study the signaling characteristics of wild-type and engineered IL-2 mutants. Leveraging our newfound quantitative of how affinity and valency interact to determine a cytokine’s selectivity profile both generally and in the specific context of IL-2, we developed affinity-optimized tetravalent IL-2 mutants with superior regulatory cell selectivity. Using these models of IL-2 signaling, we also elucidated the mechanism by which engineered antibody-IL-2 fusions induced regulatory cell-selective signaling and conferred protection against autoimmunity. In total, this body of work demonstrates the critical role that computational modeling plays in potentiating the engineering of superior cytokine-based immunotherapies.