Cell GenomicsCancer BiologyPeer-reviewed journal article
Single-cell meta-analysis of T cells reveals clonal dynamics of response to checkpoint immunotherapy
Abstract
Despite the crucial role of T cell clones in the anti-tumor activity, their characterization and association with clinical outcome following immune checkpoint inhibitors (ICI) is lacking. Here we analyzed paired single-cell RNA-sequencing/T-cell receptor sequencing of 767,606 T cells from 460 samples spanning 6 cancer types. We found a robust signature of response based on expanded CD8+ clones that differentiates between responders and non-responders. Analysis of persistent clones showed transcriptional changes that are differentially induced by therapy in the different response groups, suggesting an improved reinvigoration capacity in responding patients. Moreover, a gene trajectory analysis revealed changes in the pseudo-temporal state of de-novo clones that are associated with response to therapy. Lastly, we found that clones shared between tumor and blood are more abundant in non-responders and execute distinct transcriptional programs. Overall, our results highlight differences in clonal transcriptional states that are linked to patient response, offering valuable insights into the mechanisms driving effective anti-tumor immunity. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/614877v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@176f326org.highwire.dtl.DTLVardef@5573baorg.highwire.dtl.DTLVardef@20cf13org.highwire.dtl.DTLVardef@1faf7d8_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: deep learning
- approach: statistical model
- Citations
- 21
- FWCI
- 2.42
- Field percentile
- top 9%
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