Abstract
Single-cell RNA sequencing in principle offers unique opportunities to improve the efficacy of contemporary T-cell based immunotherapy against cancer. The use of high-quality single-cell data will aid our incomplete understanding of molecular programs determining the differentiation and functional heterogeneity of cytotoxic T lymphocytes (CTLs), allowing for optimal therapeutic design. So far, a major obstacle to high depth single-cell analysis of CTLs is the minute amount of RNA available, leading to low capturing efficacy. Here, to overcome this, we tailor a droplet-based approach for high-throughput analysis (tDrop-seq) and a plate-based method for high-performance in-depth CTL analysis (tSCRB-seq). The latter gives, on average, a 15-fold higher number of captured transcripts per gene compared to droplet-based technologies. The improved dynamic range of gene detection gives tSCRB-seq an edge in resolution sensitive downstream applications such as graded high confidence gene expression measurements and cluster characterization. We demonstrate the power of tSCRB-seq by revealing the subpopulation-specific expression of co-inhibitory and co-stimulatory receptor targets of key importance for immunotherapy.
Highlights
Single-cell RNA sequencing in principle offers unique opportunities to improve the efficacy of contemporary T-cell based immunotherapy against cancer
We establish T cell-tailored variants of both protocols designated as tDrop-seq and tSCBRseq (t from T cell). tDrop-seq is a tool for cost-effective highthroughput but shallow single-cell transcriptome profiling of cytotoxic T cells, which is highly valuable for initial exploratory analysis. tSCBR-seq is a tool with superior power to delineate fine transcriptomic differences between transcriptionally similar cytotoxic T lymphocyte (CTL) populations
The former is cost efficient and high throughput. The latter has a high power to detect differentially expressed genes, due to the high number of captured transcripts per gene[18]. Both methods incorporate unique molecular identifiers (UMIs), which allows for absolute quantification of gene expression by effectively eliminating the bias introduced by PCR (Supplementary Fig. 1C)[19–21]
Summary
Single-cell RNA sequencing in principle offers unique opportunities to improve the efficacy of contemporary T-cell based immunotherapy against cancer. We use a well-established relevant experimental system to obtain naive or differentiated T cell populations and perform a series of optimizations of the classical droplet sequencing (Drop-seq)[16] and single-cell RNA barcoding and sequencing (SCRB-seq)[17].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
