Sitravatinib potentiates immune checkpoint blockade in refractory cancer models

Abstract

Immune checkpoint blockade has achieved significant therapeutic success for a subset of cancer patients; however, a large portion of cancer patients do not respond. Unresponsive tumors are characterized as being immunologically "cold," indicating that these tumors lack tumor antigen-specific primed cytotoxic T cells. Sitravatinib is a spectrum-selective tyrosine kinase inhibitor targeting TAM (TYRO3, AXL, MerTK) and split tyrosine-kinase domain-containing receptors (VEGFR and PDGFR families and KIT) plus RET and MET, targets that contribute to the immunosuppressive tumor microenvironment. We report that sitravatinib has potent antitumor activity by targeting the tumor microenvironment, resulting in innate and adaptive immune cell changes that augment immune checkpoint blockade. These results suggest that sitravatinib has the potential to combat resistance to immune checkpoint blockade and expand the number of cancer patients that are responsive to immune therapy.

Keywords: Cancer immunotherapy; Drug therapy; Macrophages; Oncology; Therapeutics.

Figure 1. MerTK inhibition with sitravatinib directly affects macrophage phenotype.

The expression of M1-type macrophage markers Tnfα, Il-6, and Il-12 (A) and M2-type macrophage markers Arg1, Ym-1, and Fizz-1 (B) in bone marrow–derived macrophages (BMDMs). BMDMs were harvested from WT C57BL/6 or MerTK^–/– (green) mice, stimulated with 20 ng/ml LPS for 2 hours (A) or 40 ng/ml IL-4 for 18 hours (B). Each stimulation was performed with or without sitravatinib (12.5, 50, 200, and 800 nM) in the presence (red and green) or absence (blue) of KLN205 conditioned media (CM). The expression level of TNF-α, IL-6, IL-12, arginase 1, YM-1, and Fizz-1 was determined by q-PCR. Three independent experiments using duplicate samples were performed. Data are displayed as fold change normalized to control in each condition (mean ± SD). For each marker, the top graph is the basal expression change in each stimulation condition, and the bottom graph is expression change caused by different concentrations of sitravatinib in each condition. *P < 0.05, **P < 0.01, ***P < 0.005, ****P < 0.001 vs. the control (WT macrophages without stimulation) or DMSO (0 nM) in each condition by ANOVA.

Figure 2. Sitravatinib has potent antitumor activity in vivo.

(A–C) In vivo assessment of treatment response of subcutaneously or orthotopically implanted tumors. We injected 0.5 × 10⁶ KLN205 cells (A, n = 11/group) subcutaneously into 6-week-old DBA/2 mice, 1 × 10⁶ CT1B-A5 cells (B, n = 5/group) subcutaneously into 6-week-old C57BL/6 mice, and 0.5 × 10⁶ E0771 cells (C, n = 5/group) orthotopically into the mammary fat pads of 6-week-old female C57BL/6 mice. Mice with established tumors (500–700 mm³) were treated with control (Ctrl, vehicle, once per day) or sitravatinib (sitrav, p.o. 20 mg/kg, once per day). Effects on tumor growth are shown after 6 days of treatment. Tumor and spleen weight were determined in each mouse (mean ± SD). *P < 0.05, **P < 0.01, ***P < 0.005, ****P < 0.001 vs. control by t test. (D) Colony formation for KLN205 and E0771 cell lines grown in normal growth performed with or without sitravatinib at the indicated doses for 14 days. Two independent experiments using triplicate samples were performed. Mean ± SD colonies/hpf are shown. (E) Cell growth assays were performed in a 96-well format for 5 days using MTS. Three independent experiments using two 96-well plates/cell line were performed. Drug-sensitivity curves are displayed.

Figure 3. Sitravatinib potently inhibits MerTK activity and reduces angiogenesis.

(A) Lysates of tumors from KLN205 tumor-bearing animals treated with control (Ctrl), sitravatinib, or glesatinib were probed for the indicated targets by Western blotting. (B) KLN205 tumor–bearing animals treated with control, sitravatinib (sitra), or glesatinib (gles) were evaluated by immunohistochemistry for the expression level of the indicated markers. Images were taken by Nanozoomer and analyzed using ImageJ. Quantification of percentage of the area analyzed positive for staining (% area fraction) is shown. Data are displayed as mean ± SD and represent images covering the whole tumor, with 4–5 animals per group analyzed. Original magnification, ×20. **P < 0.01, ****P < 0.001 vs. control by ANOVA.

Figure 4. Transcriptome analysis of the immune landscape of KLN205 tumors treated with sitravatinib.

RNA was isolated from KLN205 tumors treated for 6 days with sitravatinib (sitra) or glesatinib (gles) and was analyzed using a preassembled nCounter PanCancer Immune Profiling Panel (mouse) and the nCounter system (NanoString Technologies). Samples were then normalized based on the geometric means of the supplied positive controls and the panel of housekeeping genes, as recommended by the manufacturer. Only genes that were significantly different (P < 0.05; t test, false discover rate adjusted) and at least 1.5-fold differentially expressed between groups were considered. The most downregulated (A) and upregulated genes (B) from the gene expression analysis (NanoString Technologies) were displayed (mean ± SD). (C) Upregulated and downregulated gene program/pathways.

Figure 5. Sitravatinib alters the immune landscape of KLN205 tumors to favor immune checkpoint blockade.

Flow cytometry of tumor-associated myeloid (A) and lymphoid cells (B) from mice bearing KLN205 tumors treated for 6 days with sitravatinib (sitra, n = 9–10/group). Monocytic myeloid-derived suppressor cells (M-MDSCs; CD11b⁺Ly6G^–Ly6C⁺), PD-L1⁺ M-MDSCs, polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs; CD11b⁺Ly6G⁺Ly6C⁺), PD-L1⁺ PMN-MDSC, neutrophils (CD11b⁺Ly6G⁺Ly6C^–), macrophages (CD11b⁺Ly6G^–Ly6C^–F4/80⁺CD11c⁺MHCII⁺), Arg1⁺ macrophages (Macs), iNOS⁺ macrophages, CD3⁺ T cells, CD4⁺ T cells, CD8⁺ T cells, and PD-1⁺CTLA4⁺CD8⁺ T cells were analyzed. *P < 0.05, **P < 0.01 vs. control (Ctrl) by t test. (C) Flow cytometry of splenocytes from mice bearing KLN205 tumors treated with sitravatinib for 6 days (n = 9–10/group). CD3⁺ T cells, CD4⁺ T cells, CD8⁺ T cells, and Ki67⁺ CD8⁺ T cells were analyzed. *P < 0.05, **P < 0.01 vs. control by t test.

Figure 6. Sitravatinib enhances the efficacy of PD-1 blockade.

(A and B) In vivo assessment of treatment response of subcutaneously or orthotopically implanted tumors (n = 12–14/group) in combination with PD-1 blockade. We injected 0.5 × 10⁶ KLN205 cells (A) subcutaneously into 6-week-old DBA/2 mice, and 0.5 × 10⁶ E0771 cells (B) were injected orthotopically into the mammary fat pads of 6-week-old female C57BL/6 mice. Therapy was initiated in mice with a tumor volume of 300 mm³ (KLN205) or 500 mm³ (E0771) and included control (Ctrl, vehicle, once per day), anti–PD-1 (PD-1, i.p. 10 mg/kg, every 3 days), sitravatinib (sitra, p.o. 20 mg/kg, once per day), or anti–PD-1 in combination with sitravatinib at the indicated dose. Mice were treated for 2.5 weeks. **P < 0.01 anti–PD-1 in combination with sitravatinib vs. sitravatinib alone by t test. Two of fourteen mice bearing E0771 tumors treated with the combination therapy showed complete remission and stayed tumor free for 50 days. (C) Rechallenge growth curve of the 2 tumor-free animals from B. We injected 0.5 × 10⁶ E0771 cells orthotopically into the mammary fat pads of 6-week-old female C57BL/6 mice (Ctrl, n = 4) and on the contralateral side from the original injection of the 2 tumor-free animals.