Single-cell transcriptome analysis of CAR T-cell products reveals subpopulations, stimulation, and exhaustion signatures

Autor: Berthold Göttgens, Fernando J Calero-Nieto, Carlotta Peticone, Xiaonan Wang, Ekaterini Kotsopoulou
Přispěvatelé: Wang, Xiaonan [0000-0003-3759-778X], Peticone, Carlotta [0000-0001-5665-6859], Göttgens, Berthold [0000-0001-6302-5705], Calero-Nieto, Fernando J [0000-0003-3358-8253], Apollo - University of Cambridge Repository
Rok vydání: 2021
Předmět:
Zdroj: OncoImmunology, Vol 10, Iss 1 (2021)
Oncoimmunology
article-version (VoR) Version of Record
Popis: Chimeric antigen receptor (CAR) T-cell adoptive therapy is set to transform the treatment of a rapidly expanding range of malignancies. Although the activation process of normal T cells is well characterized, comparatively little is known about the activation of cells via the CAR. Here we have used flow cytometry together with single-cell transcriptome profiling to characterize the starting material (peripheral blood mononuclear cells) and CAR therapeutic products of 3 healthy donors in the presence and absence of antigen-specific stimulation. Analysis of 53,191 single-cell transcriptomes showed APRIL-based CAR products to contain several subpopulations of cells, with cellular composition reproducible from donor to donor, and all major cellular subsets compatible with CAR expression. Only 50% of CAR-expressing cells displayed transcriptional changes upon CAR-specific antigen exposure. The resulting molecular signature for CAR T-cell activation provides a rich resource for future dissection of underlying mechanisms. Targeted data interrogation also revealed that a small proportion of antigen-responding CAR-expressing cells displayed an exhaustion signature, with both known markers and genes not previously associated with T-cell exhaustion. Comprehensive single-cell transcriptomic analysis thus represents a powerful way to guide the assessment and optimization of clinical-grade CAR-T-cells, and inform future research into the underlying molecular processes.
Databáze: OpenAIRE