RT Journal Article
SR Electronic
T1 Mapping CAR T-cell design space using agent-based models
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.04.07.487561
DO 10.1101/2022.04.07.487561
A1 Alexis N. Prybutok
A1 Jessica S. Yu
A1 Joshua N. Leonard
A1 Neda Bagheri
YR 2022
UL http://biorxiv.org/content/early/2022/04/09/2022.04.07.487561.abstract
AB Chimeric antigen receptor (CAR) T-cell therapy shows promise for treating liquid cancers and increasingly for solid tumors as well. While potential design strategies exist to address translational challenges, including the lack of unique tumor antigens and the presence of an immunosuppressive tumor microenvironment, testing all possible design choices in vitro and in vivo is prohibitively expensive, time consuming, and laborious. To address this gap, we extended the modeling framework ARCADE (Agent-based Representation of Cells And Dynamic Environments) to include CAR T-cell agents (CAR T-cell ARCADE, or CARCADE). We conducted in silico experiments to investigate how clinically relevant design choices and inherent tumor features—CAR T-cell dose, CD4+:CD8+ CAR T-cell ratio, CAR-antigen affinity, cancer and healthy cell antigen expression—individually and collectively impact treatment outcomes. Our analysis revealed that tuning CAR affinity modulates IL-2 production by balancing CAR T-cell proliferation and effector function. It also identified a novel multi-feature tuned treatment strategy for balancing selectivity and efficacy and provided insights into how spatial effects can impact relative treatment performance in different contexts. CARCADE facilitates deeper biological understanding of treatment design and could ultimately enable identification of promising treatment strategies to accelerate solid tumor CAR T-cell design-build-test cycles.Competing Interest StatementThe authors have declared no competing interest.