TIGIT contributes to the regulation of 4-1BB and does not define NK cell dysfunction in glioblastoma

Abstract

TIGIT is a receptor on human natural killer (NK) cells. Here, we report that TIGIT does not spontaneously induce inhibition of NK cells in glioblastoma (GBM), but rather acts as a decoy-like receptor, by usurping binding partners and regulating expression of NK activating ligands and receptors. Our data show that in GBM patients, one of the underpinnings of unresponsiveness to TIGIT blockade is that by targeting TIGIT, NK cells do not lose an inhibitory signal, but gains the potential for new interactions with other, shared, TIGIT ligands. Therefore, TIGIT does not define NK cell dysfunction in GBM. Further, in GBM, TIGIT⁺ NK cells are hyperfunctional. In addition, we discovered that 4-1BB correlates with TIGIT expression, the agonism of which contributes to TIGIT immunotherapy. Overall, our data suggest that in GBM, TIGIT acts as a regulator of a complex network, and provide new clues about its use as an immunotherapeutic target.

Keywords: Biological sciences; Cancer; Health sciences; Immunology.

Graphical abstract

Figure 1

Exhaustion markers PD-1 and LAG-3 are upregulated in GBM patients, but not TIGIT (A) Diagram depicting interactions between TIGIT, DNAM-1, CD96 and CD155, CD112, as well as intracellular cross-talk between TIGIT and other NK cell receptors (PD-1, 4-1BB, CD69, LAG-3. (B) TCGA Kaplan-Meier survival plot indicating that, together, CD155 and TIGIT are prognostic factors in GBM. High CD155 + TIGIT = 81 patients; Low CD155 + TIGIT = 81 patients. (C and D) Groups were compared by Kaplan-Meier survival analysis. Bar plots depicting (C) MFI (left) and (D) percentage (right) expression of NK cell activating (CD16, DNAM-1, NKG2D, CD69, NKp30, CD57, 4-1BB) and inhibitory (CD158e1, CD96, CD158b, TIGIT, NKG2A, PD-1, LAG-3, CD94) receptors on GBM patient cNK and tiNK cells, as well as NK cells from healthy donors (n = 8 patients). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (E) Histograms depicting differences in select NK ligands between healthy donors, GBM patient cNK, and GBM patient tiNK cells. (F and G) Correlation between TIGIT expression (Fold MFI) and 4-1BB expression (Fold MFI) on (F) cNK (R² = 0.9181) and (G) tiNK (R² = 0.9649) cells harvested from GBM patients (n = 6). R² was calculated by simple linear regression. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001.

Figure 2

TIGIT^high NK cells exhibit enhanced activation and maturity genotype over TIGIT^negative NK cells (A) Differential expression (log2CPM) of select NK cell genes related to maturity and activation TIGIT^high, TIGIT^medium, and TIGIT^negative NK cells (n = 3). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (B) Bubble chart of GSEA analysis NES and p value scores for select NK-relevant gene set from the Biocarta database. (C) Running enrichment score (ES) analysis of FAS, 4-1BB, Stress, and CXCR4 pathways for sorted TIGIT^high (left) and TIGIT^medium (right) NK cells. (D) Relative proportion of activation, inhibition, maturation, migration, and other NK genes up- and downregulated on sorted TIGIT^high (left) and TIGIT^medium (right) NK cells. (E) ClusterProfiler map of differentially expressed genes in for TIGIT^high NK cells FAS, 4-1BB, Stress, CXCR4, CTLA-4, and TGF-B pathways. Data are represented as mean ± SEM. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001.

Figure 3

TIGIT^high NK cells are more functional and overexpress activating receptors (A) Normalized percentage (left) and MFI (right) expression of NK cell receptors on sorted TIGIT^high, TIGIT^medium, and TIGIT^negative NK cells and (below) representative flow cytometric gating strategy for sorting these NK cell subsets (n = 3). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (B) Cytolysis of GBM43-WT cells by sorted TIGIT^high, TIGIT^medium, and TIGIT^negative NK cells at E:T ratios 2.5:1, 5:1, and 10:1 (n = 3). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (C) CD107a expression in response to GBM43-WT cells by sorted TIGIT^high, TIGIT^medium, and TIGIT^negative NK cells at E:T ratios 2.5:1, 5:1, and 10:1 (n = 3). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (D) IFN-γ expression in response to GBM43-WT cells by sorted TIGIT^high, TIGIT^medium, and TIGIT^negative NK cells at E:T ratios 2.5:1, 5:1, and 10:1 (n = 3). Data are shown for each individual donor. Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (E) Density plots depicting CD107a (top) and IFN-γ (bottom) expression in response to GBM43-WT cells by sorted TIGIT^high, TIGIT^medium, and TIGIT^negative NK cells at E:T ratios 2.5:1, 5:1, and 10:1. (F) Glycolysis levels (L-lactate concentration; mM) in cell culture supernatant of TIGIT^high, TIGIT^medium, and TIGIT^negative NK cells cultured for 24 or 48 h (n = 2). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. Data are represented as mean ± SEM. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001.

Figure 4

TIGIT blockade correlates with low CD16, high 4-1BB, and higher inflammatory cytokines (A) Heatmap depicting normalized MFI expression of NK cell activating (CD16, DNAM-1, NKG2D, CD69, NKp30, CD57, 4-1BB) and inhibitory (CD158e1, CD158b, NKG2A, PD-1, LAG-3, CD94, A2AR, TIM-3, KLRG1) receptors on NK cells cocultured with GBM43 cells, with or without CD155 and/or TIGIT mAb blockade (n = 3). (B) CD16, (C) 4-1BB, (D) and LAG-3 percentage (left) and MFI (right) expression on NK cells co-cultured with GBM43-WT cells, with or without CD155 and/or TIGIT mAb blockade (n = 3). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (E) Density plots depicting CD16, 4-1BB and LAG-3 expression on NK cells co-cultured with GBM43 cells, with or without CD155 and/or TIGIT mAb blockade. Levels of proinflammatory cytokines (F) IFN-γ, TNF-α, IL-8, IL-1β (G) IL-10, IL-5, GM-CSF, and IL-4 in cell supernatant of NK cells co-cultured with GBM43-WT cells, with or without CD155 and/or TIGIT mAb blockade (n = 3). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (H) Change in expression (measured as MFI fold over isotype control) of 4-1BB on TIGIT^KO and WT NK cells generated via CRISPR/Cas9 editing in the absence and presence of GBM43 cells (incubated as co-culture at an E:T 2.5:1). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. Data are represented as mean ± SEM. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001.

Figure 5

Loss of CD155 affects GBM tumor growth and results in NK cell hyperactivation in vivo (A) Relative proliferation of GBM43-WT and GBM43-CD155 KD cells (n = 3) measured via CCK-8 proliferation assay. Groups were compared using an unpaired Student’s t test at each timepoint indicated. (B) NK cell-induced cytolysis of GBM43-WT cells, with or without CD155 and/or TIGIT mAb blockade, at E:T ratios of 2.5:1, 5:1, and 10:1 (n = 3). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (C) In vivo study timeline. Timeline depicting tumor inoculation, tumor growth measurement, and tumor harvesting in GBM43 NRG and RAG1^−/− mouse xenografts. (D) Tumor volume measurements of NRG (left) or RAG1^−/−(right) mice bearing either GBM43-WT tumors, GBM43-CD155 KD tumors, or no tumors (n = 4). (E) Bodyweight measurements of NRG (left) or RAG1^−/−(right) mice bearing either GBM43-WT tumors, GBM43-CD155 KD tumors, or no tumors (n = 4). (F) MFI (top) and percentage (bottom) expression of NK cell receptors on cNK cells harvested from RAG1^−/− mice (n = 4). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (G) MFI (top) and percentage (bottom) expression of NK cell receptors on tiNK cells harvested from RAG1^−/− mice (n = 4). Groups were compared using unpaired Student’s t test for each ligand tested. (H) IHC staining of NKp46 and Granzyme B, in GBM43-WT and GBM43-CD155 KD tumor sections harvested from RAG1^−/− mice. Scale bar: 100 μm. Data are represented as mean ± SEM. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001.

Figure 6

TIGIT blockade relies on 4-1BB activity (A) Cytolysis of GBM43-WT cells by NK cells with or without TIGIT and/or 4-1BB (BBK-2) mAb blockade at E:T ratios 2.5:1, 5:1, and 10:1 (n = 4). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (B) Cytolysis of GBM43-WT cells by NK cells with or without TIGIT and/or 4-1BB agonistic (4B4-1) mAb treatment at E:T ratios 2.5:1, 5:1, and 10:1 (n = 4). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (C) In vivo study timeline. Timeline depicting tumor inoculation, NK cell adoptive transfer and mAb administration, tumor and bodyweight measurement, and tumor harvesting in GBM43 NRG mouse xenografts. (D) Final tumor volume, (E) final tumor weight, and (F) tumor-infiltrating NK cell number of NRG mice bearing GBM43-WT tumors, receiving NK cells with or without TIGIT and/or 4-1BB agonistic (4B4-1) mAb, or PBS (n = 5). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. (G) Bodyweight measurement of NRG mice bearing GBM43-WT tumors, receiving adoptively-transferred NK cells with or without TIGIT blocking and/or 4-1BB agonistic (4B4-1) mAb, or PBS (n = 5). (H) Heatmap depicting normalized MFI expression of NK cell receptors on NK cells harvested from NRG mice bearing GBM43-WT tumors, treated with adoptively-transferred NK cells with or without TIGIT blocking and/or 4-1BB agonistic (4B4-1) mAb (n = 5 per group). (I) Expression levels, on NK cells harvested from treated GBM43-bearing mice, of select NK cell receptors showing differential expression between NK cell adoptive transfer + mAb treatments and control NK cell groups (n = 5). Groups were compared using ordinary one-way ANOVA and Tukey’s post-hoc test. Data are represented as mean ± SEM. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001.