Abstract A53: Mechanistic model predicts effects of altering CD3ζ immuno-tyrosine activating motif (ITAM) structure in chimeric antigen receptor- (CAR-) engineered T cells

Abstract

Chimeric antigen receptor- (CAR-) engineered T cells (CART cells) have emerged as a promising treatment for B cell lymphoma, but their success has not transferred to other cancer types. This is, in part, due to a fundamental lack of understanding of the mechanistic signaling events initiated by the CAR intracellular domains, which prevents us from being able to engineer an optimal CAR. Traditional CARs consist of intracellular signaling domains derived from CD3ζ, the main activating domain in the endogenous T cell receptor (TCR), and a co-stimulatory domain, such as CD28. The immuno-tyrosine activating motifs (ITAMs) on CD3ζ are able to induce T cell cytotoxicity on their own, while CD28 and other co-stimulatory signaling domains augment particular aspects of the response. To provide the quantitative insight needed to engineer a CAR structure that produces a desired level of T cell activation, we have developed a predictive mechanistic computational model that describes the signaling events that occur upon CAR activation. We are applying the model to improve our understanding of how CAR structure influences activation and to develop new hypotheses for the optimal design of CAR-engineered T cell systems. The computational model predicts T cell signaling mediated by CARs containing CD3ζ with and without the CD28 co-stimulatory domain, beginning with CAR activation and proceeding downstream to the activation of the transcription factors ERK and AKT. We include the key kinase, LCK, since it has been shown to play a significant role in the activation of the endogenous TCR and CD28. To account for the many species that emerge from phosphorylation of the six tyrosine sites on CD3ζ and four on CD28, we constructed the model in BioNetGen, a rule-based formalism that generates the ordinary differential equations (ODEs) for each phosphorylation permutation based on a minimal set of rules that describes the interactions between molecular species. The ODEs are implemented in MATLAB, where the different kinetic parameters can be fit to experimental data. We used phospho-proteomic mass spectrometry to quantify the site-specific phosphorylation kinetics of the CAR tyrosine sites. We expressed a variety of recombinant CAR proteins, with or without CD28 and with a series of tyrosine to phenylalanine mutations, and measured site specific phosphorylation by LCK over time. This data was used to fit a minimal model of CAR-specific phosphorylation mediated by LCK. We then extended the model to include ten additional proteins downstream of the CAR and validated it using data from the literature [1]. Our model is able to provide new insights into how the structure of the CAR intracellular signaling domains influences the rate of phosphorylation. For example, the model predicts that the order of CD28 and CD3ζ on the CAR greatly affects the overall phosphorylation rate of all sites by LCK. The model has also generated new hypotheses about how to control the overall level of CD3ζ phosphorylation in the system. The model predicts that the ability of a CD3ζ ITAM to propagate signal downstream is not controlled by how quickly the two sites get phosphorylated, but by the difference between the catalytic efficiency of LCK at each of the sites. We are currently testing these hypotheses experimentally. Once validated, these insights can be used to engineer the CD3ζ chain to control the extent of T cell activation and improve CAR therapies. Acknowledgments: This work was supported by the National Cancer Institute of the National Institutes of Health Award Number F31CA200242. Reference: 1. Hui E. et al. Science 2017;355(6332):1428-33. Citation Format: Jennifer A. Rohrs, Dongqing Zheng, Nicholas A. Graham, Pin Wang, Stacey D. Finley. Mechanistic model predicts effects of altering CD3ζ immuno-tyrosine activating motif (ITAM) structure in chimeric antigen receptor- (CAR-) engineered T cells [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2017 Oct 1-4; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2018;6(9 Suppl):Abstract nr A53.