Fig. 4: Single-cell RNA-seq defines T-cell states in CLL LNs.

A UMAP plot of 61,040 cells from paired LNs and PB samples of 5 CLL patients analyzed by scRNA-seq identifying 16 clusters, 6 CD4⁺ T-cell clusters, 5 CD8⁺ T-cell clusters, 1 cluster of proliferating CD4⁺ and CD8⁺ T cells, 1 cluster of MAIT cells, 1 cluster of NK-like cells, and 2 clusters of CLL cells which were spiked in. B Dot plot of the expression of marker genes in the 16 cell clusters. C Frequency of cell subset out of total T cells, from PB (n = 5) and LN (n = 5) samples of CLL patients. A box plot represents the 25th to 75th percentiles and the mean, with dots corresponding to samples. D-I) LN samples were clustered and analyzed separately, identifying 13 clusters of T cells and CLL cells (see Supplementary Fig. 6A, B). D, E Violin plot of average expression levels in LN T-cell subsets of the slightly adapted exhaustion gene signature derived from Zheng et al.²² (D), and the precursor exhaustion gene signature derived from Guo et al.²³ (E). Stars indicate that the CD8 T_EX (D) and CD8 T_PEX (E) subsets have statistically significantly higher signature scores compared to all other subsets (see Supplementary Data 5). F Pseudotime trajectory across the 4 CD8⁺ T-cell subsets identified in LNs. G, H Heatmap showing genes with significant expression changes along the trajectory from CD8 T_N to CD8 T_EM (G), and from CD8 T_N to CD8 T_EX (H). Color represents z-scores. I Pseudotime trajectory across the 6 CD4⁺ T-cell subsets identified in LNs. J Heatmap showing genes with significant expression changes along the trajectory from CD4 T_N to CD4 T_FH. Color represents z-scores. Statistical significance was tested by two-sided unpaired t test (C) and two-sided Wilcoxon rank sum test (D, E). Only significant p-values (p < 0.05) are shown. Source data are provided as a Source Data file Fig4.