Fig. 3: The T-cell composition of CLL LNs is distinct and enriched in regulatory and exhausted subsets. | Nature Communications

Fig. 3: The T-cell composition of CLL LNs is distinct and enriched in regulatory and exhausted subsets.

From: Integrative multi-omics reveals a regulatory and exhausted T-cell landscape in CLL and identifies galectin-9 as an immunotherapy target

Fig. 3

A Principal component analysis of all samples analyzed by mass cytometry based on cell subset frequencies. B UMAP plots of T cells from rLNs, CLL PB, CLL LNs, and CLL BM overlaid with a contour plot indicating the cell density. A UMAP plot indicating the main T-cell clusters is provided on the left. C Boxplot showing cell subset abundances out of total T cells in LNs (n = 20), PB (n = 7), and BM (n = 3) of CLL patients. D Boxplot showing cell subset abundances out of total T cells in CLL LNs (n = 20) and rLNs (n = 13). E Median expression of PD1, TIGIT, CD39, CD38, CTLA4, OX40, EOMES, and TOX markers in CD8 TEM cells per sample in LNs (n = 20), PB (n = 7), BM (n = 3) samples of CLL patients and rLN samples (n = 13) of healthy individuals. Boxplots represent the 25th to 75th percentiles with the median as the central line, whiskers indicate minimal and maximal value. Each symbol represents an individual patient sample. Statistical significance was tested using limma on normalized cell counts, with p-values adjusted for multiple comparisons using the Benjamini–Hochberg method (C, D), or the Kruskal–Wallis test with Bonferroni correction (E). Only significant p-values (p < 0.05) are shown. Source data are provided as a Source Data file Fig3.

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