CRISPR-based gene disruption and integration of high-avidity, WT1-specific T cell receptors improve antitumor T cell function.

T cell receptor (TCR)-based therapy has the potential to induce durable clinical responses in patients with cancer by targeting intracellular tumor antigens with high sensitivity and by promoting T cell survival. However, the need for TCRs specific for shared oncogenic antigens and the need for manufacturing protocols able to redirect T cell specificity while preserving T cell fitness remain limiting factors. By longitudinal monitoring of T cell functionality and dynamics in 15 healthy donors, we isolated 19 TCRs specific for Wilms' tumor antigen 1 (WT1), which is overexpressed by several tumor types. TCRs recognized several peptides restricted by common human leukocyte antigen (HLA) alleles and displayed a wide range of functional avidities. We selected five high-avidity HLA-A*02:01-restricted TCRs, three that were specific to the less explored immunodominant WT137-45 and two that were specific to the noncanonical WT1-78-64 epitopes, both naturally processed by primary acute myeloid leukemia (AML) blasts. With CRISPR-Cas9 genome editing tools, we combined TCR-targeted integration into the TCR α constant (TRAC) locus with TCR ß constant (TRBC) knockout, thus avoiding TCRαß mispairing and maximizing TCR expression and function. The engineered lymphocytes were enriched in memory stem T cells. A unique WT137-45-specific TCR showed antigen-specific responses and efficiently killed AML blasts, acute lymphoblastic leukemia blasts, and glioblastoma cells in vitro and in vivo in the absence of off-tumor toxicity. T cells engineered to express this receptor are being advanced into clinical development for AML immunotherapy and represent a candidate therapy for other WT1-expressing tumors.

Flow cytometry data mining by cytoChain identifies determinants of exhaustion and stemness in TCR-engineered T cells.

The phenotype of infused cells is a major determinant of Adoptive T-cell therapy (ACT) efficacy. Yet, the difficulty in deciphering multiparametric cytometry data limited the fine characterization of cellular products. To allow the analysis of dynamic and complex flow cytometry samples, we developed cytoChain, a novel dataset mining tool and a new analytical workflow. CytoChain was challenged to compare state-of-the-art and innovative culture conditions to generate stem-like memory cells (TSCM ) suitable for ACT. Noticeably, the combination of IL-7/15 and superoxides scavenging sustained the emergence of a previously unidentified nonexhausted Fit-TSCM signature, overlooked by manual gating and endowed with superior expansion potential. CytoChain proficiently traced back this population in independent datasets, and in T-cell receptor engineered lymphocytes. CytoChain flexibility and function were then further validated on a published dataset from circulating T cells in COVID-19 patients. Collectively, our results support the use of cytoChain to identify novel, functionally critical immunophenotypes for ACT and patients immunomonitoring.