Extended Data Fig. 3: Effect of TBK1 inhibition on the tumour immune microenvironment.
From: Targeting TBK1 to overcome resistance to cancer immunotherapy
a–b, tSNE plot of 11 clusters of CD45+ cells (a) from patients with metastatic melanoma responsive (R) or non-responsive (NR) to immune checkpoint blockade (ref. Sade-Feldman et al. 2018), and t-SNE plots of RNA-sequenced single cells with colouring of CD3E (T cells), CD14 (myeloid cells), and CD19 (B cells) TBK1 and IKBKE expression (b). c–d, broad cluster proportions (c) and percent cells per cluster across indicated treatment groups (d). e–f, UMAP (c) and density (d) plots of reclustered lymphoid (T/NK) cells. g, cluster proportions of lymphoid (T/NK) cells. Means (bars) and individual values (circles) are shown +/− s.e.m (error bars). Multiple unpaired t-test, *P < 0.05; **P < 0.01; ***P < 0.001; **** P < 0.0001; ns, not significant. h, percentage of activated (CD69+CD25+) mouse CD8+ splenocytes pre-treated with TBK1i (1 μM) or DMSO (0.1%) with/without restimulation; n = 3 biologically independent samples, 2-way ANOVA, Sidak’s multiple comparisons test; *P < 0.05; ***P < 0.001. i–k, intracellular cytokine staining for TNF (i), IL-2 (j), and IFNγ (k) of mouse CD3+CD8+ splenocytes pre-treated with TBK1i (1 μM) or DMSO (0.1%) with/without restimulation with data shown as % CD69+CD25+ cells and MFI); n = 3 biologically independent samples, 2-way ANOVA, Sidak’s multiple comparisons test; **P < 0.01; **** P < 0.0001; ns, not significant.
