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Tetramer-aided sorting and single-cell RNA sequencing facilitate transcriptional profiling of antigen-specific CD8+ T cells
Affiliation:Genentech, 1 DNA way, South San Francisco, CA 94080, USA
Abstract:BackgroundRecent advances in single-cell technologies and an improved understanding of tumor antigens have empowered researchers to investigate tumor antigen-specific CD8+ T cells at the single-cell level. Peptide-MHC I tetramers are often utilized to enrich antigen-specific CD8+ T cells, which however, introduces the undesired risk of altering their clonal distribution or their transcriptional state. This study addresses the feasibility of utilizing tetramers to enrich antigen-specific CD8+ T cells for single-cell analysis.MethodsHLA-A*02:01-restricted human cytomegalovirus (CMV) pp65 peptide-specific CD8+ T cells were used as a model for analyzing antigen-specific CD8+ T cells. Single-cell RNA sequencing and TCR sequencing were performed to compare the frequency and gene expression profile of pp65-specific TCR clones between tetramer-sorted, unstimulated- and tetramer-stimulated total CD8+ T cells.ResultsThe relative frequency of pp65-specific TCR clones and their transcriptional profile remained largely unchanged following tetramer-based sorting. In contrast, tetramer-mediated stimulation of CD8+ T cells resulted in significant gene expression changes in pp65-specific CD8+ T cells. An Antigen-Specific Response (ASR) gene signature was derived from tetramer-stimulated pp65-specific CD8+ T cells. The ASR signature had a predictive value and was significantly associated with progression free survival in lung cancer patients treated with anti-PD-L1, anti-VEGF, chemotherapy combination (NCT02366143). The predictive power of the ASR signature was independent of the conventional CD8 effector signature.ConclusionsOur findings validate the approach of enriching antigen-specific CD8+ T cells through tetramer-aided Fluorescence-Activated Cell Sorting (FACS) sorting for single-cell analysis and also identifies an ASR gene signature that has value in predicting response to cancer immunotherapy.
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