Lenvatinib plus anti-PD-1 antibody combination treatment activates CD8+ T cells through reduction of tumor-associated macrophage and activation of the interferon pathway

Abstract

Lenvatinib is a multiple receptor tyrosine kinase inhibitor targeting mainly vascular endothelial growth factor (VEGF) and fibroblast growth factor (FGF) receptors. We investigated the immunomodulatory activities of lenvatinib in the tumor microenvironment and its mechanisms of enhanced antitumor activity when combined with a programmed cell death-1 (PD-1) blockade. Antitumor activity was examined in immunodeficient and immunocompetent mouse tumor models. Single-cell analysis, flow cytometric analysis, and immunohistochemistry were used to analyze immune cell populations and their activation. Gene co-expression network analysis and pathway analysis using RNA sequencing data were used to identify lenvatinib-driven combined activity with anti-PD-1 antibody (anti-PD-1). Lenvatinib showed potent antitumor activity in the immunocompetent tumor microenvironment compared with the immunodeficient tumor microenvironment. Antitumor activity of lenvatinib plus anti-PD-1 was greater than that of either single treatment. Flow cytometric analysis revealed that lenvatinib reduced tumor-associated macrophages (TAMs) and increased the percentage of activated CD8+ T cells secreting interferon (IFN)-γ+ and granzyme B (GzmB). Combination treatment further increased the percentage of T cells, especially CD8+ T cells, among CD45+ cells and increased IFN-γ+ and GzmB+ CD8+ T cells. Transcriptome analyses of tumors resected from treated mice showed that genes specifically regulated by the combination were significantly enriched for type-I IFN signaling. Pretreatment with lenvatinib followed by anti-PD-1 treatment induced significant antitumor activity compared with anti-PD-1 treatment alone. Our findings show that lenvatinib modulates cancer immunity in the tumor microenvironment by reducing TAMs and, when combined with PD-1 blockade, shows enhanced antitumor activity via the IFN signaling pathway. These findings provide a scientific rationale for combination therapy of lenvatinib with PD-1 blockade to improve cancer immunotherapy.

Fig 1. Antitumor activity of lenvatinib in immunocompetent and immunodeficient mice in the CT26 model.

A. Immunodeficient mice (Balb/c^nu/nu) and immunocompetent mice (Balb/c^wt/wt) inoculated with the CT26 cells were randomized into groups of 6 mice with an average tumor volume size (Day 1 mean TV: Balb/c^nu/nu mice, 76.7 mm³; Balb/c^wt/wt mice, 80.0 mm³), and were then treated with vehicle (blue circles) or 10 mg/kg lenvatinib (red squares) once daily (black arrows). Error bars indicate the SEM. B. The values of ΔT/C (%) were plotted for Balb/c^nu/nu mice (red-filled squares) and Balb/c^wt/wt mice (red-open squares). ****, P<0.0001; ***, P<0.001; Dunnett’s test vs vehicle, ***P<0.001, Dunnett’s test vs. Balb/c^nu/nu mouse (n = 6). C. Mice, inoculated with CT26 cells, were randomized on Day 9 after CT26 inoculation with an average tumor volume size (Day 1 mean TV, 138 mm³) into groups of 6 or 7 mice, and were then treated with vehicle (blue bar) or 10 mg/kg lenvatinib (red bar). TILs were isolated on Day 8 after the start of treatment, and the percentage of TAMs gated by using Ly6C⁻ F4/80⁺ (black square) in the CD11b⁺ Ly6G⁻ population was analyzed and plotted. ****, P<0.0001, unpaired t-test vs. vehicle (n = 6 or 7). D. Immunohistochemical analysis of the TAM population in CT26 tumor tissues. CD11b is stained red, F4/80 is green, and DAPI is blue.

Fig 2. Antitumor activity of lenvatinib under CD8⁺ T cell-depleted conditions in the CT26 model.

Mice, inoculated with CT26 cells, were treated with anti-CD8 antibody or control IgG on Day 6 and twice weekly thereafter. A. For flow cytometric analysis, the percentage of CD8⁺ T cells in the blood was determined. B. Two days after the first injection of anti-CD8 antibody or control IgG, mice were randomized into groups of 8 or 9 with an average tumor volume size (Day 1 mean TV: anti-CD8 antibody, 65.9 mm³; control IgG, 49.3 mm³), and then treated with vehicle (blue circles) or 10 mg/kg lenvatinib (red squares), indicated by the black arrow. Error bars represent the SEM. C. The percentage of ΔT/C (tumor size of each mouse treated with lenvatinib divided by the average tumor size of vehicle-treated mice) is shown for the control IgG (red-filled squares) and anti-CD8 antibody (red-open squares) treatment groups. **, P<0.01, Dunnett’s test vs. vehicle or control IgG (n = 8 or 9).

Fig 3. Antitumor effects of lenvatinib treatment alone or in combination with anti-PD-1 in the CT26 model.

A. Mice were inoculated with CT26 cells and randomized into groups of 8 with an average tumor volume size (Day 1 mean TV, 32.6 mm³) and were then treated with vehicle (blue circles), 10 mg/kg lenvatinib (red squares) once daily, anti-PD-1 at 200 μg/mouse (green triangles) once every 3 days, or a combination of lenvatinib plus anti-PD-1 (purple circles). Lenvatinib treatment is indicated by the black arrow; anti-PD-1 treatment is indicated by black triangles. B. Tumor volumes for individual mice are shown for each treatment group. Error bars represent the SEM. **** P<0.0001, Dunnett’s test vs. vehicle on Day 19; ## P<0.01, #### P<0.0001 vs. combination.

Fig 4. Immune cell population analysis of lymphocytes in the CT26 tumor tissues.

A, Percentages of myeloid and TAM cell populations. Upper panel: TAMs, pDCs, granulocytes, and monocytes. Lower panel: M1, M2 in CD45⁺ cells, and the M1/M2 ratio. B. Upper panel: T cells, CD4⁺ T cells, and CD8⁺ T cells. Lower panel: PD-1⁺ Tim3⁺ CD8⁺ T cells, IFN-γ⁺ CD8⁺ T cells, and GzmB⁺CD8⁺ T cells. The gating strategy is shown in S1 Fig. *P <0.05, **P <0.01, ***P<0.001, unpaired t-test vs. vehicle; #P<0.05, unpaired t-test vs. combination (n = 6).

Fig 5. Weighted gene co-expression network analysis (WGCNA) to identify gene subsets modulated by combination treatment.

RNA-Seq analysis of tumor tissues followed by WGCNA was performed by using CT26 tumor tissues. A. Defined sample traits, each of which reflects a pattern of expression as indicated in the text. Gene subsets that correlate with one of traits (6) through (9) are considered to be possible target gene sets of the ‘potentiating effect’ of the two drugs. B. Modules from the WGCNA selected for trait correlation analysis. The modules highly correlated with one of the modules in A (r>0.65 and P<0.01) are shown with the number of genes included in each module in parentheses. The correlation strength of each module with each trait is shown in the heatmap where the most highly correlated trait is indicated by an asterisk. The significance (FDR-adjusted P value) of the top over-represented pathway in each module is shown in the bar graph, and the significantly enriched pathway is indicated (FDR-adjusted P value <0.05). The genes in the antiquewhite2 module represented in the type-I IFN signaling pathway are shown in the arrow box to the right. C. Eigengene expression pattern for the antiquewhite2 module.

Fig 6. Antitumor activity of lenvatinib under IFN-γ-inhibited conditions in the CT26 model.

A. Mice, inoculated with CT26 cells, were treated with anti-IFN-γ antibody or control IgG on Day 8 after CT26 inoculation and twice weekly thereafter. The mice were randomized into groups of 7 with an average tumor volume size (Day 1 mean TV 71.1 mm³). The day after the first injection of anti-IFN-γ antibody or control IgG, mice were treated with vehicle (control IgG, dark blue; anti-IFN-γ antibody, light blue), 10 mg/kg lenvatinib (control IgG, dark red; anti-IFN-γ antibody, light red), anti-PD-1 (control IgG, dark green; anti-IFN-γ antibody, light green) or combination (control IgG, dark purple; anti-IFN-γ antibody, light purple). Lenvatinib treatment is indicated by the black arrow, and anti-PD-1 treatment is indicated as black triangles. Error bars represent the SEM. **P<0.01, ****P<0.0001, Dunnett’s test vs. control IgG (n = 7).