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Engineering potent chimeric antigen receptor T cells by programming signaling during T-cell activation [RNA-seq]

GSE269134 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2024/08/12 Platform GPL24676
Summary
Programming cell signaling during T-cell activation represents a simple strategy for improving the potency of therapeutic T-cell products. Stim-R™ technology (Lyell Immunopharma) is a customizable, degradable synthetic cell biomimetic that emulates physiologic, cell-like presentation of signal molecules to control T-cell activation. A breadth of Stim-R formulations with different anti-CD3/anti-CD28 (αCD3/αCD28) antibody densities and stoichiometries were screened for their effects on multiple metrics of T-cell function. We identified an optimized formulation that produced receptor tyrosine kinase-like orphan receptor 1 (ROR1)-targeted chimeric antigen receptor (CAR) T cells with enhanced persistence and polyfunctionality in vitro, as assessed in repeat-stimulation assays, compared with a benchmark product generated using a conventional T-cell–activating reagent. In transcriptomic analyses, CAR T cells activated with Stim-R technology showed downregulation of exhaustion-associated gene sets and retained a unique subset of stem-like cells with effector-associated gene signatures following repeated exposure to tumor cells. Compared with the benchmark product, CAR T cells activated using the optimized Stim-R technology formulation exhibited higher peak expansion, prolonged persistence, and improved tumor control in a solid tumor xenograft model. Enhancing T-cell products with Stim-R technology during T-cell activation may help improve therapeutic efficacy against solid tumors.
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Direct links to NCBI, no account and no request form: the whole study as GSE269134_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1120384 and SRA study SRP511955. Searching any of these in the dataset finder brings you back here.

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