Fig 2: Reduced T cell TIGIT expression associates with increased level of acute phase reactants. Correlation of acute phase reactants in serum and the percentage of TIGIT-expressing T cells analyzed ex vivo in psoriasis (n = 7, blank symbol) and psoriatic arthritis (n = 7, filled symbol) patients, using flow cytometry. (A) Significant correlation of percentage TIGIT-positive CD4 T cells and ESR (rs = -0.7918 [95% CI -0.9457 to -0.3476], P = 0.0052). (B) Trend toward correlation of CD4 TIGIT-positive cells and CRP (rs = -0.792 [95% CI -0.8701 to 0.01175], P = 0.0521). (C) Significant correlation of percentage TIGIT-positive CD8 T cells and erythrocyte sedimentation rate (ESR) (Spearman’s Rank correlation coefficient [rs] = -0.705 [95% CI -0.920 to -0.162], P = 0.0189). (D) Significant correlation of CD8 TIGIT-positive CD8 T cells and C-reactive protein (CRP) (rs = -0.663 [95% CI -0.900 to -0.125], P = 0.022).

Fig 3: TIGIT blockade increases T cell proliferation, and DNAM1 blockade reduces T cell pro-inflammatory cytokine production. Flow cytometry analysis of PBMCs stimulated for 3 days with CD3/CD28 Dynabeads (PBMC:Dynabead 10:1), after either 10 µg/ml DNAM1 blocking antibody, 10 µg/ml TIGIT blocking antibody or 10 µg/ml DNAM1 and TIGIT blocking antibody isotypes. Pooled data of healthy controls, psoriasis, and psoriatic arthritis patients. Shown are percentages of proliferated T cells, stained with 2 µM CellTrace Violet reagent (A, B, G, and H) and percentages of TNF and IFN? producing T cells after 4 hours re-stimulation with 50 ng/ml PMA, 1 µg/ml ionomycin in the presence of Brefeldin A (1:1000) (C–F, H–K). (A) TIGIT block significantly increases CD4 T cell proliferation. (B) DNAM1 block has no significant effect on CD4 T cell proliferation. (C) No significant difference in CD4 T cell TNF production after TIGIT blockade (44.5% vs. 45.4%, P > 0.05). (D) No significant decrease in TNF production by CD4 T cells after DNAM1 block (44.5% vs. 39.7%, P > 0.05). (E) No significant increase in CD4 T cell IFN? production after TIGIT blockade (15.6% vs. 17.4%, P > 0.05). (F) Significantly decreased IFN? production by CD4 T cells after DNAM1 block (15.6% vs. 13.0%, P = 0.0015). (G) TIGIT block significantly increases CD8 T cell proliferation. (H) DNAM1 block has no significant effect on CD8 T cell proliferation. (I) No significant difference in CD8 T cell TNF production after TIGIT blockade (35.8% vs. 36.1%, P > 0.05). (J) Significant decrease in TNF production by CD8 T cells after DNAM1 block (36.1% vs. 29.6%, P = 0.0039). (K) Trend toward increased CD8 T cell IFN? production after TIGIT blockade (29.4% vs. 32.0%, P > 0.05). (L) Significant decrease in IFN? production by CD8 T cells after DNAM1 block (29.4% vs. 25.9%, P = 0.0140). *Significant P-value Wilcoxon-signed rank test.

Fig 4: Cell-to-cell communications between cancer cells and immune cells.A–F Heatmaps showing numbers of cell–cell interactions across cell types from variant sample origins. G, H NATMI networks showing ligand-receptor pairs among cells in lymph nodes with TNBC (G) and non-TNBC (H) cells. I Table showing impressive molecules and corresponding ligand-receptor pairs associated with breast cancer metastasis and the respective references. J Immunofluorescence staining of NECTIN2-TIGIT pair in lymph nodes with cancer cells.

Fig 5: Super resolution microscopy reveals the nanoscale proximity of TIGIT and TCR clusters.a Two-colour dSTORM imaging of TIGIT-GFP (magenta) in Jurkat cells that have interacted with PLBs loaded with ICAM-1 (100 molecules/µm2), the indicated nectin ligands (400 molecules/µm2) and directly labelled, mono-biotinylated stimulatory TCR antibody OKT3 (green) for the indicated timepoints. Cells pre-incubated with an antagonistic TIGIT antibody (aT) or an isotype-matched control (iso) are shown, as indicated. Representative TIRF and dSTORM images are shown in the top and middle rows, respectively. b–d Quantitative analysis of the colocalisation between TIGIT and TCR in Jurkat cells as shown in a; n = =15 cells per condition, representative of 3 independent experiments, with adjusted P values from a one-way ANOVA with Tukey’s multiple comparisons (b) or Kruskal-Wallis tests with Dunn’s multiple comparisons (c, d) are shown. Positive controls represent TIGIT labelled with both a GFP nanobody and a TIGIT antibody, with the negative control representing the same data but with the XY coordinates of one channel being swapped (Supplementary Fig. 12). Mean (±S.D.) Spearman rank correlations (b) and Mander’s coefficients (c) for TIGIT-OKT3 localisations across each cell. d Mean (±S.D.) fraction of localisations that have a score of >0.8 from a coordinate-based colocalisation analysis across single cells. e Two-colour dSTORM imaging of TIGIT (magenta) and PLB-bound OKT3 (green) in primary peripheral blood-isolated CD4+ and CD8 + T cells on PLBs, as in a. Representative TIRF and dSTORM images are shown in the top and middle rows, respectively. f–h Quantitative analysis of the colocalisation between TIGIT and TCR in primary T cells as shown in e; n = =15 cells (depicted in blue or orange) from 3 individual donors (as shown in black and matched by shape) with adjusted P values from one-way ANOVA with Holm-Šídák’s multiple corrections on the means of each donor displayed. Mean (±S.D.) Spearman rank correlations (f) and Mander’s coefficients (g) for TIGIT-OKT3 localisations across each cell. h Mean (±S.D.) fraction of localisations that have a score of >0.8 from a coordinate-based colocalisation analysis across single cells. In a and e, white scale bars = 5 µm, zoomed regions (5 µm x 5 µm; dashed yellow boxes) are displayed below with yellow scale bars = 1 µm. Source data are provided as a Source Data file.