Abstract Currently approved T cell therapies fail to induce a durable remission for many of the patients who receive them, highlighting a pressing need to improve patient outcomes. To comprehensively explore genetic strategies to enhance function of engineered T cells, we have developed CRISPR-All, a combinatorial genetic perturbation language capable of simultaneously inducing natural gene overexpression, gene knockouts, and gene knockdowns, as well as new synthetic sequences such as chimeric antigen receptor (CAR) binders or signaling domains and synthetic gene sequences. Using CRISPR-All, we have created a T cell therapy “meta-library”, termed CRISPR-All Cell Therapy Universal Screening (CACTUS), collated from a comprehensive review of literature on effector function-enhancing genetic modifications in both native and engineered human T cells. In CACTUS2, we also included perturbations informed by clinical dataset analysis of patients receiving CD19-CAR or bispecific CD19/CD22-CAR therapy. We introduced the CACTUS2 library into primary human T cells along with a CD19-28Z CAR (axi-cel) and performed an in vitro assay in which edited CAR T cells are chronically stimulated over the course of 14 days via repetitive co-culture with target human leukemia or lymphoma cell lines (NALM6, Toledo, JeKo-1). Top hits across these screens emerged as synthetic chimeras of overexpressed genes. The large-scale analysis of perturbations relevant to T cell fitness in cancer models empowered by the CRISPR-All screening method is an important step in improving CAR T cell therapeutic designs for enhanced therapeutic outcomes. Citation Format: Alexander Eapen, Lujing Wu, Laura Moser, Boi Quach, Wael Gamal, Kameron Rodrigues, Kristin C. Tsui, Zinaida Good, Theodore Roth. Universal T cell therapy screening library in preclinical models of CAR T cell therapy abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4011.
Building similarity graph...
Analyzing shared references across papers
Loading...
Alexander Eapen
Lujing Wu
Laura M. Moser
Cancer Research
Stanford University
Building similarity graph...
Analyzing shared references across papers
Loading...
Eapen et al. (Fri,) studied this question.
www.synapsesocial.com/papers/69d1fde4a79560c99a0a446b — DOI: https://doi.org/10.1158/1538-7445.am2026-4011