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VISTA (PD-1H) is an immune regulatory molecule considered part of the next wave of immuno-oncology targets. VISTA is an immunoglobulin (Ig) superfamily cell surface molecule mainly expressed on myeloid cells, and to some extent on NK cells and T cells. In previous preclinical studies, some VISTA-targeting antibodies provided immune inhibitory signals, while other antibodies triggered immune stimulatory signals. Importantly, for therapeutic antibodies, the isotype backbone can have a strong impact on antibody function. To elucidate the mode of action of immune stimulatory anti-VISTA antibodies, we studied three different anti-human VISTA antibody clones, each on three different IgG isotypes currently used for therapeutic antibodies: unaltered IgG1 (IgG1-WT), IgG1-KO (IgG1-LL234,235AA-variant with reduced Fc-effector function), and IgG4-Pro (IgG4- S228P-variant with stabilized hinge region). Antibody functionality was analysed in mixed leukocyte reaction (MLR) of human peripheral blood mononuclear cells (PBMCs), as a model system for ongoing immune reactions, on unstimulated human PBMCs, as a model system for a resting immune system, and also on acute myeloid leukemia (AML) patient samples to evaluate anti-VISTA antibody effects on primary tumor material. The functions of three anti-human VISTA antibodies were determined by their IgG isotype backbones. An MLR of healthy donor PBMCs was effectively augmented by anti-VISTA-IgG4-Pro and anti-VISTA-IgG1-WT antibodies, as indicated by increased levels of cytokines, T cell activation markers and T cell proliferation. However, in a culture of unstimulated PBMCs of single healthy donors, only anti-VISTA-IgG1-WT antibodies increased the activation marker HLA-DR on resting myeloid cells, and chemokine levels. Interestingly, interactions with different Fc-receptors were required for these effects, namely CD64 for augmentation of MLR, and CD16 for activation of resting myeloid cells. Furthermore, anti-VISTA-IgG1-KO antibodies had nearly no impact in any model system. Similarly, in AML patient samples, anti-VISTA-antibody on IgG4-Pro backbone, but not on IgG1-KO backbone, increased interactions, as a novel readout of activity, between immune cells and CD34+ AML cancer cells. In conclusion, the immune stimulatory effects of antagonistic anti-VISTA antibodies are defined by the antibody isotype and interaction with different Fc-gamma-receptors, highlighting the importance of understanding these interactions when designing immune stimulatory antibody therapeutics for immuno-oncology applications.

CX3CR1 has been identified as a highly attractive target for several therapeutic interventions. Despite this potential, no potent antagonists, either small molecule or monoclonal antibody, have been identified. Here we describe the lead finding and engineering approach that lead to the identification of BI 655088, a potent biotherapeutic antagonist to CX3CR1. BI 655088 is a potent CX3CR1 antagonist that, upon therapeutic dosing, significantly inhibits plaque progression in the standard mouse model of atherosclerosis. BI 655088 represents a novel and highly selective biotherapeutic that could reduce inflammation in the atherosclerotic plaque when added to standard of care treatment including statins, which could result in a significant decrease in atherothrombotic events in patients with existing cardiovascular disease.

Here we provide data from a head-to-head comparison study using four biosensor platforms: GE Healthcare׳s Biacore T100, Bio-Rad׳s ProteOn XPR36, ForteBio׳s Octet RED384, and Wasatch Microfluidics׳s IBIS MX96. We used these instruments to analyze the binding interactions of a panel of ten high-affinity monoclonal antibodies with their antigen, human proprotein convertase subtilisin kexin type 9 (PCSK9). For each instrument, binding curves obtained at multiple densities of surface antibodies were fit to the 1:1 Langmuir kinetic model, and the association and dissociation rate constants and corresponding affinity constants were calculated. The data supplied in this article accompany the research article entitled, “Comparison of biosensor platforms in the evaluation of high affinity antibody–antigen binding kinetics” (Yang et al., 2016) [1], which further discusses the strengths and weaknesses of each biosensor platform with an emphasis on data consistency, comparability, and operational efficiency. Keywords: Biacore, ProteOn, Octet, MX96, Antibody–antigen interactions, Optical biosensor

Practically, IgG charge can contribute significantly to thermodynamic nonideality, and hence to solubility and viscosity. Biologically, IgG charge isomers exhibit differences in clearance and potency. It has been known since the 1930s that all immunoglobulins carry a weak negative charge in physiological solvents. However, there has been no systematic exploration of this fundamental property. Accurate charge measurements have been made using membrane confined electrophoresis in two solvents (pH 5.0 and pH 7.4) on a panel of twelve mAb IgGs, as well as their F(ab’)2 and Fc fragments. The following observations were made at pH 5.0: (1) the measured charge differs from the calculated charge by ~40 for the intact IgGs, and by ~20 for the Fcs; (2) the intact IgG charge depends on both Fv and Fc sequences, but does not equal the sum of the F(ab)’2 and Fc charge; (3) the Fc charge is consistent within a class. In phosphate buffered saline, pH 7.4: (1) the intact IgG charges ranged from 0 to −13; (2) the F(ab’)2 fragments are nearly neutral for IgG1s and IgG2s, and about −5 for some of the IgG4s; (3) all Fc fragments are weakly anionic, with IgG1 < IgG2 < IgG4; (4) the charge on the intact IgGs does not equal the sum of the F(ab’)2 and Fc charge. In no case is the calculated charge, based solely on H+ binding, remotely close to the measured charge. Some mAbs carried a charge in physiological salt that was outside the range observed for serum-purified human poly IgG. To best match physiological properties, a therapeutic mAb should have a measured charge that falls within the range observed for serum-derived human IgGs. A thermodynamically rigorous, concentration-dependent protein–protein interaction parameter is introduced. Based on readily measured properties, interaction curves may be generated to aid in the selection of proteins and solvent conditions. Example curves are provided.