Abstract 231: Evaluation of pharmacologic mechanisms to overcome IgG1 antibody (Ab) resistance via quantitative systems pharmacology (QSP) modeling of antibody-dependent cell mediated cytotoxicity (ADCC)

Abstract

Abstract Novel therapies that enhance ADCC have the potential to overcome Rituximab (RTX) resistance in lymphoma, which can occur due to e.g. CD20 loss, immunogenicity-induced reduction in RTX exposure, or SNPs resulting in lower CD16:Fc affinity. Nonlinear interactions between effector cells (ECs), drug, and target cell (TC) factors in ADCC, however, complicate the prediction of the net effect of potential therapeutic strategies that modulate one or more factors such as CD16 expression ([CD16]) on ECs, CD16:Fc binding affinity, or intrinsic killing propensity (g).We have developed a QSP model of the molecular-level binding reactions and cell-cell interactions governing ADCC using the anti-CD20 IgG1 antibody RTX in lymphoma as a case study. This model takes as inputs [CD16] on ECs, g, Ab Fc:CD16 binding affinity, [RTX], RTX:CD20 affinity, and [CD20] on TCs and predicts the degree of ADCC killing of tumor cells after RTX exposure. Simulations can then be used to estimate how much increase in an input parameter a potential RTX combination partner must provide to compensate for a given mechanism of RTX resistance (MoRR). The model has been successfully calibrated to ex vivo [RTX]-ADCC assays in SUDHL4 and Z138 cell lines (Herter, Mol Cancer Ther, 2013). The model and estimated parameter set well described the observed [RTX]-dependent %ADCC in both cell lines with ECs (PBMCs) from two donors with V158 and F158 CD16 SNP variants. The table below provides the model predictions of the fold increase in model parameters required to offset various MoRRs. For example, a 10-fold loss of [CD20] on TCs is predicted to cause a 100*(1 - 0.16) = 84% drop in ADCC activity, which can be overcome by a 7.8-fold increase in [CD16] on ECs. We have developed a mechanism-based simulation tool which can be used to predict the ability of novel ADCC-enhancing agents to overcome different mechanisms of IgG1 Ab resistance. Mechanism of RTX resistance (MoRR)ADCC fold change due to MoR(90% CI)Fold change in parameter required to restore ADCC (90% CI)CD16 expression on effector cells [CD16]CD16:Fc binding affinity kon16NK killing propensity g10x loss of CD20 on tumor0.16 (0.13,0.20)7.8 (6.3,9.2)10.6 (10.4,10.9)7.4 (6.1,8.7)10x loss of RTX exposure0.17(0.14,0.21)7.0(5.7,8.1)9.36(9.35,9.37)6.9(5.7,8.1)10x decrease in CD16:Fc affinity0.16(0.13,0.20)7.4(6.1,8.7)10(10,10)7.4(6.1,8.6) Citation Format: Kaitlyn E. Johnson, Maria Veronica Ciocanel, Josua Aponte, Nicolas Bajeux, Fanwang Meng, Dean Bottino. Evaluation of pharmacologic mechanisms to overcome IgG1 antibody (Ab) resistance via quantitative systems pharmacology (QSP) modeling of antibody-dependent cell mediated cytotoxicity (ADCC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 231.