Library-based single-cell analysis of CAR signaling reveals drivers of in vivo persistence

The anti-tumor function of engineered T cells expressing chimeric antigen receptors (CARs) is dependent on signals transduced through intracellular signaling domains (ICDs). Different ICDs are known to drive distinct phenotypes, but systematic investigations into how ICD architectures direct T cell function—particularly at the molecular level—are lacking. Here, we use single-cell sequencing to map diverse signaling inputs to transcriptional outputs, focusing on a defined library of clinically relevant ICD architectures. Informed by these observations, we functionally characterize transcriptionally distinct ICD variants across various contexts to build comprehensive maps from ICD composition to phenotypic output. We identify a unique tonic signaling signature associated with a subset of ICD architectures that drives durable in vivo persistence and efficacy in liquid, but not solid, tumors. Our findings work toward decoding CAR signaling design principles, with implications for the rational design of next-generation ICD architectures optimized for in vivo function. Overall design: CD3+ T cells expressing a library of 35 distinct ICD architectures following various tumor perturbations were single-cell sequenced via Chromium Next GEM Single Cell 5' Kit v2, generating gene expression libraries, CAR BC libraries (see below), and, for samples stained with CITE-seq antibodies, feature barcoding libraries. Each CAR variant is barcoded by a unique 8bp sequence in the 5'UTR, allowing deconvolution of the ICD architecture expressed by each cell. The resulting libraries were pooled to achieve approximately 30000, 5000, and 1000 reads per cell, respectively. Reads were aligned to the Genome Reference Consortium Human Build 38 (GRCh38), and a cell–feature matrix was generated using the CellRanger pipeline (10X Genomics; v6.1.2–7.0.1). Downstream analysis was performed using the Seurat package (v4.3.0.1). Several different scRNA-seq datasets are presented, with sample-specific treatments given in the description for each sample.