Combined VEGF and PD-L1 Blockade Displays Synergistic Treatment Effects in an Autochthonous Mouse Model of Small Cell Lung Cancer

Small cell lung cancer (SCLC) accounts for 13% to 18% of primary lung cancer cases and is the most aggressive form of pulmonary carcinomas, mostly diagnosed at late stages with systemic metastases. Although current chemotherapies are initially effective in patients with SCLC, responses are typically transient and patients succumb to their disease within a few months after diagnosis (1, 2). Therefore, there is a critical need to convert therapy responses into durable remissions and to improve outcomes in patients with SCLC.

Immune checkpoint blockade using monoclonal antibodies targeting cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed cell-death receptor 1 (PD-1), and programmed cell-death ligand 1 (PD-L1) provided clinical activity in several cancer types including lung cancer (3, 4). Inhibitory immune checkpoint receptors including lymphocyte-activation gene 3 (LAG-3), T-cell immunoglobulin and mucin domain 3 (TIM-3), and T-cell immunoreceptor with Ig and ITIM (TIGIT) block T-cell effector functions and thereby the elimination of tumor cells (5), and their expression has been described as a prognostic factor in patients with SCLC (6). The limitation of immune checkpoint blockade in cancer therapy is the activation of different immunosuppressive mechanisms in the tumor microenvironment, which abrogate T-cell effector functions and inhibit the infiltration of tumor-educated T cells into the tumor (7). Because cross-talk between the tumor immune microenvironment and the tumor vasculature contributes to tumor immune evasion, combined therapy regimens targeting additional immune and/or vascular factors may provide sustained and potent antitumor immune responses (7).

As examples of dual immune checkpoint targeting, in advance melanomas, PD-1 blockade provided an overall response rate (ORR) of 33% (8), whereas combined PD-1/CTLA-4 blockade revealed 72% ORR, but with frequent adverse immune-related toxicities (9). In SCLC, treatment with nivolumab (anti–PD-1) alone provided an ORR of 11% and in combination with ipilimumab (anti–CTLA-4) an ORR of 25% (CheckMate032). In contrast to nonsquamous non–small cell lung cancer (NSCLC) PD-L1 expression on tumor cell membranes does not predict response to PD-1–targeted therapies in SCLC (10–12). Thus, SCLC still lacks a prediction marker for response to PD-1/PD-L1 blockade whereby more than 80% of SCLC did not respond to nivolumab (12).

The lack of broad responses to dual immune checkpoint blockade in SCLC (12) might refer to additional immunosuppressive mechanisms in the tumor microenvironment that are not directly triggered by T-cell effector functions. The infiltration of regulatory T cells (Treg; ref. 13), myeloid-derived suppressor cells (MDSC; ref. 14), and tumor-associated macrophages (TAM) may reduce the antitumor activity of immune checkpoint blockades and therefore present a valuable target for novel combined therapy approaches (15, 16).

Several studies indicated that anti-VEGF–targeted therapy transforms the tumor immune microenvironment toward an immunosupportive phenotype (17). Dendritic cells (DC) are antigen-presenting cells that take up antigens and present them to T cells. Recent studies showed that VEGF suppresses the maturation of DC precursors and that VEGF blockade improved DC function and thereby the efficacy of immunotherapy in cancer (18). In addition, high VEGF levels promote the proliferation of Tregs and the expansion of immature myeloid cells, which contribute to tumor-associated immunosuppression by suppressing antigen-specific T-cell responses (17). High intratumoral VEGF levels lead to an abnormal growth of tumor vessels that are characterized by hyperpermeable functionally insufficient vessels. This insufficient perfusion is associated with a hypoperfused, hypoxic tumor microenvironment with a high interstitial fluid pressure that impedes effector T-cell infiltration into the tumor and a shift of TAMs toward an immune inhibitory M2-like phenotype with suppressive effector T-cell function (7). Anti-VEGF treatment rescues the expression of adhesion proteins, such as E-selectin and ICAM-1, on endothelial cells in the tumor microenvironment and thereby enable effector T-cell migration into the tumor tissue (19–22).

Importantly, blocking VEGF/VEGFR signaling was described to directly regulate the expression of inhibitory immune checkpoint receptors on tumor educated T cells (23). Recent data showed that reduced VEGFA levels in patients with melanoma are associated with response to anti–PD-1-targeted treatment, suggesting that VEGFA expression might be associated with response to PD-1/PD-L1 blockade (24).

VEGFA, VEGF receptors (VEGFR), and PD-L1 are highly expressed in patients with SCLC (25, 26). Thus, we investigated the therapeutic efficacy of combined anti–PD-L1 and anti-VEGF–targeted therapy in a Cre-inducible autochthonous mouse model of SCLC (27).

This study was performed in accordance with FELASA recommendations. The protocol was approved by the local Ethics Committee of Animal experiments. The genetically engineered mouse model of SCLC is driven by a Cre-inducible conditional Rb1 and Tp53 knockout with flox out of exons 2 to 10 in Tp53 and exon 19 in Rb1, as previously described (27). Six-to-8-week-old male and female C57BL/6JxFVB/NJx129/Sv mice were anesthetized with Ketamin/Xylazin [100 mg/kg/body weight (BW) i.p./0.5 mg/kg/BW i.p.] and 2.5 × 10⁷ pfu Adeno-Cre was applied intratracheally (28). Viral vectors were provided by the University of Iowa Viral Vector Core (http://www.medicine.uiowa.edu/vectorcore). An initial cohort was used to determine survival from the time point of inhalation and estimate a starting point for monitoring initial tumor growth (Supplementary Fig. S1). Serial μCT to monitor tumor induction in the therapy groups were started from week 22 after Cre application and target lesions were correctly identified from isolated lung tissue (Supplementary Fig. S1). For μCT measurements (LaTheta mCT, Hitachi Alcoa Medical Ltd), mice were anesthetized using 2.5% isofluran. Histologically, SCLC primary tumors resembled human SCLC with regard to cell morphology determined by hematoxylin and eosin (H&E) stain, proliferation determined by Ki-67 stain and NE marker expression, here CD56. Moreover, SCLC tumors expressed PD-L1 and VEGF (Supplementary Fig. S1).

Upon a measurable target lesion, mice were randomly distributed into groups (Supplementary Fig. S1; Supplementary Table S1) and mice were imaged by μCT once a week. SCLC cohorts comprised five therapy groups, and all therapies were given every 3 days simultaneously: (i) vehicle (phosphate buffered saline; PBS); (ii) IgG (corresponding monotherapy IgGs; Southern Biotech; diluted in PBS); (iii) anti-mouse VEGFA monoclonal antibody (aVEGF, B20-4.1.1-PHAGE, kindly provided by Genentech) (5 mg/kg/BW i.p.); (iv) anti-mouse PD-L1 monoclonal antibody (aPD-L1, clone 6E11, kindly provided by Genentech) (5 mg/kg/BW i.p.); and (v) combined anti-VEGF/anti–PD-L1 (5 mg/kg/BW/5 mg/kg/BW i.p.), where both compounds were applied simultaneously. Reagents were diluted in PBS and obtained from Genentech, which specified the therapy regimen. As a reference group, SCLC-bearing mice were treated with cycles of a standard combined chemotherapy regimen comprising cisplatin (5 mg/kg/BW, 1× per week) and etoposide (10 mg/kg/BW, 3× per week) followed by 2 to 3 weeks of recovery depending on toxicity and weight loss (Supplementary Fig. S1). Tumor growth was monitored by serial μCT whereby the RECIST criteria v1.1 (29) were adapted to the SCLC model. The minimal measurable target lesion by μCT scans was adapted to 1 mm. Slice thickness was adapted to 0.3 mm. The first dose was given upon target lesion identification and baseline evaluation, maximally 1 day before. Response criteria to evaluate the target lesion were maintained with regard to diameter fold change. Complete response (CR) referred to a decrease of 100%, partial response (PR) was indicated upon a >30% reduction, progressive disease (PD) referred to an increase of >20% and/or new lung lesions, and stable disease (SD) was termed upon a diameter change that did not qualify for PR or PD. μCT data were analyzed using OsiriX-DICOM viewer (aycan Digitalsysteme GmbH). Progression-free survival (PFS) and overall survival (OS) of the therapy groups and the predictive additive probability of survival of both monotherapy-treated cohorts were analyzed as follows: Let |{p_A}\ ( t )$|⁠, |{p_B}\ ( t )$|⁠, |{p_{A,B}}\ ( t )$|⁠, and |{p_{{\rm{Cntrl}}}}\ ( t )$| denote the probability of survival for |t \in [ {0;\infty } )$| under therapy with compound |A$|⁠, |B$|⁠, their combination or vehicle solution, respectively. In order to determine whether the combination of two drugs |A$| and |B$| had a synergistic impact on survival, we calculated the expected additive curve as

where |{p_{A + B}}( t )$| denotes the expected probability of survival, assuming the combination effect of drugs |A$| and |B$| is additive, and |{| a |_{ \ge 0}}: = {\rm{max}}( {0,a} )$|⁠. Based on this definition, we calculated the expected number of events at each time point of |{p_{A + B}}( t )$| by inverting the Kaplan–Meier statistics, assuming equal cohort sizes between combination and single-agent cohorts. Based on these events, we finally compared the expected additive survival rate |{p_{A + B}}( t )$| and the observed survival rate |{p_{A,B}}\,( t )$| under drugs |A$| and |B$| in combination, using a Mantel–Cox test. Scripts are available upon request.

Organs of mice were harvested, and cells were isolated by mechanical dissociation using 40-μm cell strainers (BD Falcon). Red blood cells were lysed by ACK lysis buffer (Life Technologies), and cells were washed with PBS. Purified primary cells and T cells were stained for 30 minutes at 4°C for flow cytometry using antibodies against following targets and isotype controls, both obtained from BioLegend if not otherwise specified: LAG-3 (FITC, C9B7W, Thermo Scientific), CTLA-4 (PE, UC10-4B9), CXCR3 (FITC, CXCR3-173), CCR4 (PE-Cy7, 2G12), FOXP3 (PE, MF-14), IFNγ (Alexa Fluor 700, XMG1.2), TIM-3 (PE, RMT3-23; PerCP-Cy5.5, B8.2C12), CD4 (PE-Dazzle594, GK1.5), CD45 (PerCP-Cy5.5, Alexa Fluor 700, APC-Cy7, 30-F11), CD3 (PE-Cy7, Alexa Fluor 700, 17A2), PD-1 (APC, 29F.1A12), CD8a (FITC, Pacific Blue, 53-6.7), CD11c (PE-Dazzle594, N418), F4/80 (Alexa Fluor 700, BM8), PD-L1 (PE-Cy7, 10F.9G2), PD-L2 (eBioscience, FITC, 122), H-2Kb (Pacific Blue, AF6-88.5), galectin-9 (PE, 108A2), CD56 (R&D Systems, APC, 809220), Rat IgG2aΚ (FITC, PE, PerCP-Cy5.5, APC, Alexa Fluor 700), PE-Dazzle594 Armenian Hamster IgG (PE-Dazzle594), Rat IgG2bΚ (PE-Cy7), and mouse BALB/c IgG2aΚ (Pacific Blue). In addition, APC-Cy7-conjugated fixable viability dye (eBioscience) or the Zombie Aqua Fixable Viability Kit (BioLegend) was used.

Purified human T cells were stained in 50 μL volume for 20 minutes at 4°C for flow cytometry using antibodies against following targets, obtained from BioLegend if not otherwise specified: CD45 (FITC, HI30), TIM-3 (PE-Dazzle594, F38-2E2), CD3 (PerCP-Cy5.5, SK7), CD4 (PE-Cy7, SK3), PD-1 (APC, EH12.2H7), CD8a (Alexa Fluor 700, SK1), CD69 (APC-Fire 750, FN50). In addition, a Pacific Orange–conjugated fixable viability dye (Zombie Aqua) was used. Flow cytometry for murine and human cells was performed on a Gallios 10/3 (Beckman Coulter), and data were analyzed using FlowJo (TreeStar v7.6.1).

Murine T cells were isolated from harvested spleens of mice harboring SCLC using MojoSort Mouse CD3 T-cell Isolation (BioLegend) according to the manufacturer's protocol. T cells were cultured in 96-well flat bottom plates (Sarstedt) and stimulation was performed for 24 hours using 5 μg immobilized anti-CD3 (BD Pharmingen), 2 μg/mL soluble anti-CD28 (BD Pharmingen), 10 ng/mL murine IFNγ (PeproTech) and 50 ng/mL murine VEGF165 (PeproTech), also known as VEGFA. Human peripheral blood mononuclear cells (PBMC) were isolated from patients with SCLC blood between 2 and 4 weeks after the last dose received by density gradient centrifugation using Pancoll (Pan Biotech, density 1.077 g/L). T cells were purified by magnetic cell sorting using MojoSort Human CD3 T-cell isolation (BioLegend) according to the manufacturer's protocol for column-free isolation. T cells were cultured in 96-well flat bottom plates (Sarstedt) under humanized conditions and stimulated for 24 and 72 hours using 5 μg/mL immobilized anti-CD3 (BioLegend), 2 μg/mL soluble anti-CD28 (BioLegend), and 50 ng/mL human VEGF165 (PeproTech).

Murine organs were harvested and fixed in 4% PBS-buffered formalin for paraffin embedding. Three-micrometer tissue sections were deparaffinized and IHC was performed using the LabVision Autostainer-480S (Thermo Scientific) staining with H&E, primary antibodies against KI-67 (Cell Marque, SP6), CD31 (BD Pharmingen, MEC13.3), CD56 (Abcam, polyclonal, ab95153), PD-L1 (proteintech, polyclonal, 17952-1-AP), VEGF (Santa Cruz Biotechnology, A-20), CD4 (Abcam, EPR19514), CD8 (Abcam polyclonal, ab203035), FOXP3 (Novus Biologicals, polyclonal, NB100-39002), and the Secondary-Histofine-Simple-Stain (SHSS) antibody detection kit (Medac). Slides were scanned by the Panoramic-250 slide scanner (3D Histech). CD31 staining was used to determine microvessel density. Briefly, five representative 20× enlarged fields were extracted from each slide using the Panoramic Viewer Software. A customized script of ImageJ (National Institutes of Health) was used to identify CD31-positive structures. The number of structures with a minimum size of 30 pixels was counted per 20× enlarged field and averaged across all fields for each slide. Human SCLC was diagnosed based on histologic examination by trained lung pathologists. Pictures were acquired with a Leica-DM-5500 B microscope. Primary antibodies against PD-L1 (28-8, Abcam), TIM-3 (D5D5R, Cell Signaling Technology), galectin-9 (D9R4A, Cell Signaling Technology), CD56 (123C3, Zytomed), synaptophysin (SP11, Thermo Fisher Scientific), and chromogranin A (DAK-A3, Dako) were used. Secondary antibodies were purchased from ImmunoLogic (BrightVision+) and staining was performed using the LabVision Autostainer 480S (Thermo Scientific).

All human subject research was performed in strict accordance with approved protocols by the local ethics committee of the University Hospital Cologne and with the recognized ethical guidelines of the Declaration of Helsinki. Blood samples (reference number 17-130) and tumor tissue (reference number 10-242) were obtained during routine clinical procedures from patients diagnosed based on the World Health Organization classification of lung tumors (30) providing written informed consent for additional tissue collection.

Statistical analyses were done using Prism (GraphPad V5.0) and SPSS (IBM, V24.0). Error bars indicated standard error of the mean (SEM). P values <0.05 were regarded as significant and indicated in the figures: *, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001.

We performed a therapeutic study in an autochthonous mouse model of SCLC in which tumors are induced upon Cre-mediated biallelic deletion of Rb1 and Tp53. We recorded the clinicopathologic parameters of SCLC bearing mice listed according to the applied therapy regimens (Supplementary Table S1). Mice were randomized and systemically treated with vehicle, corresponding IgGs, anti-VEGF, anti–PD-L1, and with the combination of anti-VEGF and anti–PD-L1 targeting. Anti-VEGF monotherapy in SCLC-bearing mice did not improve PFS and OS (1 week, 3 weeks, respectively) in comparison with vehicle-treated mice (1 week, 3 weeks, respectively) and IgG-treated mice (1.5 weeks, 2.5 weeks, respectively; Fig. 1A and B). Treatment with anti–PD-L1 alone significantly improved PFS (2 weeks, P = 0.0061) and OS (4 weeks, P = 0.0008) compared with the vehicle group. Most strikingly, combined anti-VEGF/anti–PD-L1 inhibition led to a substantial improvement in median PFS (3 weeks) and OS (6 weeks) in comparison with anti–PD-L1 monotherapy (PFS: P = 0.0166, OS: P = 0.0231; Supplementary Tables S2–S5). To decipher whether the combination of anti-VEGF/anti-PD-L1–targeted therapy results in synergistic treatment effects, we calculated predicted additive PFS and OS curves as described in the Materials and Methods. Using Prism Mantel–Cox test (Supplementary Tables S2 and S3), we compared the predicted additive curves of OS and PFS with the observed survival curves of the anti-VEGF/anti–PD-L1 combined therapy group (PFS: 0.0119, OS: P = 0.0316; Fig. 1C and D). Because we determined a significant difference between the predicted additive and the combination therapy curves, the therapeutic effect on survival of anti-VEGF and anti–PD-L1-targeted therapy, which were administered simultaneously, was defined as synergistic effect. We further compared OS data of combined anti-VEGF/anti–PD-L1 treatment with standard combined cisplatin/etoposide chemotherapy. Of note, OS of the mice with SCLC treated with combined anti-VEGF/anti–PD-L1 therapy was better than the observed OS upon standard combined chemotherapy regiments (median OS: 5 weeks, 6 weeks, respectively, P = 0.1312; Supplementary Fig. S1).

We next assessed the change in target lesion diameter in all therapy groups after 1 and 2 weeks of treatment using μCT analysis. After 1 week of treatment, we found one SD in SCLC-bearing mice treated with anti-VEGF alone (20.0%, 2 of 10), while upon anti–PD-L1 monotherapy this was seen in 78.6% (11 of 14), and in 92.3% (12 of 13) with combined anti-VEGF/anti–PD-L1 treatment. A PR was found in 7.1% of mice (1 of 14) treated with anti–PD-L1 and 7.7% of mice (1 of 13) treated with combined anti-VEGF/anti–PD-L1. However, already after 1 week, 80.0% of mice (8 of 10) treated with anti-VEGF monotherapy, 50% of mice (3 of 6) treated with IgG controls and 100% of vehicle-treated mice (12 of 12) showed PD (Fig. 1E). After 2 weeks of treatment, SD was detected upon anti–PD-L1 monotherapy in 42.9% (6 of 14) and upon combined anti-VEGF/anti–PD-L1 in 46.2% (6 of 13). Of note, a PR was only determined in SCLC-bearing mice treated with combined anti-VEGF/anti–PD-L1 (15.4%; 2 of 13). PD was determined in all vehicle-treated (12 of 12), all IgG-treated (6 of 6), and all of the anti-VEGF–treated mice (10 of 10). Of anti–PD-L1 monotherapy-treated mice, 42.9% (6 of 14) showed a PD, while only 23.1% (3 of 13) of combined anti-VEGF/anti–PD-L1-treated mice showed progressive tumors (Fig. 1F). Representative serial μCT measurements indicated a PR upon combined anti-VEGF/anti–PD-L1 therapy followed by an SD at 4 weeks and a final PD after 7 weeks of treatment (Fig. 1G).

Taken together, treatment of SCLC-bearing mice with combined anti-VEGF and anti–PD-L1-targeted therapy synergistically improves PFS and OS compared with anti–PD-L1 and anti-VEGF alone.

We next analyzed the impact of anti–PD-L1, anti-VEGF, and combined anti-VEGF/anti–PD-L1 treatment on tumor-infiltrating T cells. First, the localization of CD4⁺, CD8⁺, and FOXP3⁺ T cells was examined using IHC (Fig. 2A). In vehicle-treated mice with SCLC, T cells did not accumulate in the pulmonary tissue around the tumor and did not infiltrate the tumor tissue. In anti–VEGF-treated mice, tumors were infiltrated by few CD4⁺ T cells, whereby CD8⁺ and FOXP3⁺ T cells remained at the tumor margin. In anti–PD-L1-treated mice, CD4⁺ and FOXP3⁺ T cells accumulated in the pulmonary tissue at the tumor margin but did not invade tumor tissue. In SCLC-bearing mice treated with combined anti-VEGF/anti–PD-L1 CD4⁺ T cells and few FOXP3⁺ and CD8⁺ T cells infiltrated tumor tissue. We also calculated CD31-positive tumor microvessels in progressed SCLC lesions upon therapy and did not detect significant differences in microvessel density (Supplementary Fig. S2).

Second, we generated single-cell suspensions from primary tumors and immunodetected tumor cells and immune cells, including T cells (CD45⁺ CD3⁺). We found a significantly increased ratio of pan-immune cells (CD45⁺) to tumor cells (CD45⁻ CD56⁺), but the fraction of T cells within the immune cell compartment, the CD4/CD8 ratio, and IFNγ expression were not significantly altered upon anti–PD-L1 and combined anti-VEGF/anti–PD-L1-targeted therapy compared with vehicle (Supplementary Figs. S3 and S4). However, we found a significant increase in the fraction of Tregs (CD4⁺ FOXP3⁺) in tumors that progressed upon combined anti-VEGF/anti–PD-L1 therapy (Supplementary Fig. S5). We further analyzed the fractions of Thelper1 (Th1) and Th2 CD4⁺ T cells using CXCR3 and CCR4 markers. The ratio of Th1 (CD4⁺ FOXP3⁻ CXCR3⁺) and Th2 (CD4⁺ FOXP3⁻ CCR4⁺) cells was not significantly affected using anti-VEGF and anti–PD-L1-targeted therapies (Supplementary Fig. S5).

With regard to CD8⁺ T cells, their assembly at the site of the tumor was significantly increased upon the initial response to combined anti-VEGF/anti–PD-L1 treatment (Supplementary Fig. S6), which disappeared upon PD.

To elucidate mechanisms of adaptive resistance, we analyzed immune checkpoint expression in tumor-infiltrating lymphocytes. Generally, the T-cell function is mediated by receptor–ligand interactions, which may have stimulatory or inhibitory effects. An exhausted T-cell phenotype is indicated by simultaneous upregulation of at least two inhibitory receptors, such as PD-1 and TIM-3 (3). Herein, we found upregulation of the immune checkpoints TIM-3, LAG-3, and PD-1 on CD4⁺ and CD8⁺ T cells in tumors with adaptive acquired resistance against anti–PD-L1 therapy (PD-1/TIM-3: CD4⁺ P = 0.0081 and CD8⁺ P = 0.0071; PD-1/LAG-3: CD4 P = 0.0082 and CD8 P = 0.0395; Fig. 2B–E). CTLA-4 and PD-1 double-positive T-cell fractions were not increased upon acquired anti–PD-L1 resistance (Supplementary Fig. S7). This exhausted T-cell phenotype was significantly increased in tumors that progressed during anti–PD-L1 treatment in comparison with anti–PD-L1-treated mice with PR and SD, which represents a true phenotype acquisition (CD4⁺ P = 0.0310 and CD8⁺ P = 0.0062; Supplementary Fig. S6). Moreover, we found that the exhausted T-cell phenotype was locally associated with the presence of tumor cells (Supplementary Fig. S8).

Interestingly, the PD-1/TIM-3–exhausted T-cell phenotype was significantly rescued by combining anti–PD-L1-targeted therapy with anti-VEGF therapy (CD4⁺ P = 0.0389; CD8⁺ P = 0.0411, respectively), whereas the PD-1/LAG-3–exhausted phenotype was not rescued (Fig. 2B–E). We also showed that the exhausted T-cell phenotype was not dependent on IFNγ (Supplementary Fig. S9). Moreover, VEGF knockout in SCLC tumors did not enhance response to aPD-L1 treatment (Supplementary Fig. S10).

As TIM-3 was upregulated upon progression during anti–PD-L1-targeted treatment, which was again abrogated by the addition of anti-VEGF therapy, we hypothesized that VEGF/VEGFR signaling induce TIM-3 expression on tumor-associated T cells. We found that VEGFR1 was upregulated on tumor-associated CD8⁺ T cells (Supplementary Fig. S11). Thus, these data might indicate that TIM-3 expression is regulated by VEGF-VEGFR1 in CD8 T cells. However, the VEGF-induced signaling pathway that regulates TIM-3 expression in CD-8 cells remains elusive.

Taken together, combining anti-VEGF to anti–PD-L1-targeted therapy rescued T-cell exhaustion, which was observed as an acquired resistance mechanism to PD-L1 blockade in SCLC.

We further investigated the expression of PD-L1 (31), PD-L2 (32), and galectin-9 (33) in the tumor microenvironment. They represent prominent ligands for PD-1 and TIM-3, respectively, and trigger immunotolerance and tumor immune evasion through the abrogation of IFNγ signaling and the induction of effector T-cell apoptosis (31–33).

We analyzed the expression of these ligands on tumor-associated DCs (TADC; CD45⁺ CD56⁻ F4/80⁻ CD11c⁺), tumor cells (CD45⁻ CD56⁺), and TAMs (CD45⁺ CD56⁻ F4/80⁺). The expression of galectin-9 was significantly increased on TAMs in SCLCs that progressed during anti–PD-L1 and combined anti-VEGF/anti–PD-L1 therapy (measured by mean fluorescence intensity compared with vehicle, anti–PD-L1: P = 0.0069, anti–PD-L1/anti-VEGF: P = 0.0212, respectively), but was not significantly altered on TADCs and tumor cells (Fig. 3A and B; Supplementary Fig. S12). In human SCLC patient samples without anti-PD-1/anti–PD-L1 treatment, galectin-9 was detected on tumor cells (3 of 18), TAMs and lymphocytes (8 of 18) and frequently coexpressed with TIM-3 (7 of 8) but not with PD-L1 (Supplementary Fig. S13; Supplementary Tables S6 and S7). PD-L1, which was shown to be significantly expressed on tumor cells and within the tumor microenvironment of SCLC (26), was significantly reduced on TADCs (anti–PD-L1: P > 0.001, anti–PD-L1/anti-VEGF: P = 0.002, respectively), tumor cells (anti–PD-L1: P = 0.0111, anti–PD-L1/anti-VEGF: P = 0.0220, respectively), and TAMs (anti–PD-L1: P = 0.0002, anti–PD-L1/anti-VEGF: P = 0.0009, respectively), upon anti–PD-L1 treatment in the monotherapy and combined anti-VEGF/anti–PD-L1 therapy cohort (Supplementary Fig. S12). PD-L2 was not expressed on TADCs and TAMs, but at low levels on tumor cells. However, PD-L2 was not differentially expressed in SCLC following the applied therapy regimens (Supplementary Fig. S12). Furthermore, we analyzed the expression of MHC class I on TADCs, TAMs, and tumor cells, as genomic aberrations in B2M resulting in MHC class I loss were identified as potential resistance mechanism to PD-1 blockade in melanoma (34). However, MHC class I was not differentially expressed between any of the cell types in our SCLC therapy cohorts (Supplementary Fig. S12). We also analyzed the ratio of TAMs and TADCs within the immune cells but did not identify significant alterations upon application of the different therapy regimens (Supplementary Fig. S3).

Because immune checkpoint receptors were recently discovered on TAMs, abrogating their antitumor function and directly contributing to the response to immune checkpoint blockade (35, 36), we investigated the expression of PD-1, TIM-3, LAG-3, and CTLA-4 on TAMs in mice with SCLC (Supplementary Fig. S14). We found that immune checkpoint receptor expression was induced on TAMs upon acquired resistance to PD-L1 blockade (PD-1 P < 0.0001; TIM-3 P = 0.1053; LAG-3 P = 0.0064; CTLA-4 P = 0.0015). Combining anti–PD-L1/anti–VEGF-targeted therapy reduced LAG-3 and CTLA-4 expression significantly (P = 0.0012; P = 0.0003, respectively) compared with anti–PD-L1 monotherapy. Taken together, TAMs might present an exhausted phenotype like T cells upon acquired resistance to PD-L1 blockade and may contribute to the prolonged survival of mice with SCLC achieved by combined anti-VEGF/anti–PD-L1 treatment.

To validate our preclinical findings in human patient samples, we isolated PBMCs from patients with SCLC that progressed during nivolumab (anti–PD-1) treatment. We investigated PBMCs of two cohorts of patients with SCLC: those treated with irradiation and chemotherapy alone (RC) or those treated with RC followed by the immune checkpoint inhibitor nivolumab (RCI). Confirming our preclinical data derived from mice with autochthonous SCLC, TIM-3 was significantly upregulated on CD8⁺ and CD4⁺ T cells of peripheral blood of patients with SCLC who progressed following response to anti–PD-1 therapy. As expected, PD-1 on these peripheral blood T cells was downregulated due to anti–PD-1 treatment (Fig. 4A–C).

Following our postulate that VEGF induces TIM-3 expression in tumor-associated T cells, we investigated the effect of VEGF stimulation on T cells derived from PBMCs of the above-mentioned patient cohorts. In line with our hypothesis, the fraction of PD-1/TIM-3 double-positive CD8⁺ T cells was significantly increased after 24 hours of VEGF costimulation of peripheral blood T cells from patients who progressed after an initial response to nivolumab (Fig. 4D–F; Supplementary Fig. S15). We found a similar, but not as prominent, effect in CD8⁺ T cells from patients treated with RC. However, comparing both patient cohorts, the fraction of PD-1/TIM-3 double-positive CD8⁺ T cells was more markedly increased in the RCI cohort (Fig. 4E and F). Similar results were obtained for CD4⁺ T cells (Supplementary Fig. S16).

We further analyzed activation markers on T cells isolated from lung, spleen, and blood of mice bearing SCLC. Interestingly, the expression of CD44 and CD69 on splenic T cells mimicked the activation pattern of T cells isolated from lungs harboring macroscopic tumors (Supplementary Fig. S17). In T-cell stimulations for 24 hours using anti-CD28 and VEGF, we observed increased fractions of splenic T cells expressing PD-1 and TIM-3 (Supplementary Fig. S18).

Our study demonstrates that combined inhibition of VEGF and PD-L1 improves PFS and OS in an autochthonous mouse model of SCLC in a synergistic manner. We observed limited and short-term response to anti–PD-L1 monotherapy in mice with SCLC, which is in accordance with the limited efficacy of anti–PD-1 treatment in patients with SCLC (37). Furthermore, we identified upregulated expression of the negative regulatory exhaustion markers TIM-3 and PD-1 on CD8⁺ and CD4⁺ T cells of SCLCs that acquired resistance to PD-1/PD-L1 blockade in mice and patients. We reproduced in vitro that this TIM-3–associated exhausted phenotype is regulated by VEGF signaling in CD4⁺ and CD8⁺ T cells.

TIM-3 has been described as a T-cell exhaustion marker that is coexpressed with PD-1 upon failure of antimicrobial and antitumor responses (38, 39). In line with our data, upregulation of TIM-3 upon resistance to PD-1/PD-L1 blockade has been described in colorectal cancer (23), head and neck cancer (40), NSCLC (41), and melanoma (42). However, sequential TIM-3 blockade overcame acquired resistance against anti–PD-1 therapy only for short term in a murine autochthonous NSCLC model (41).

Recent reports described a VEGF/VEGFR-mediated expression of TIM-3 upon resistance to PD-1 blockade (23, 40). In line with these findings, we found that the PD-1/TIM-3–exhausted T-cell phenotype is regulated by VEGF and rescued upon combined anti-VEGF/anti–PD-L1 treatment. Most strikingly, combined inhibition of VEGF and PD-L1 synergistically improves OS in mice with SCLC.

One has to consider that in the majority of patients with SCLC, tumors are induced by heavy and extended smoking (43). Therefore, SCLC in patients likely harbor an increased mutational load with higher immunogenicity compared with lung carcinomas occurring in autochthonous mouse models (44, 45). For this reason, patients with SCLC are probably more amendable to immunotherapies.

Allen and colleagues showed that combined antiangiogenic/anti–PD-L1 treatment facilitates the activation and infiltration of T cells into the tumor tissue (46). We observed an improved CD4⁺ T-cell infiltration in SCLCs of mice that received combined anti-VEGF/anti–PD-L1 therapy. In line with our data, in patients with renal cell carcinoma treated with atezolizumab (anti–PD-L1) and bevazizumab (anti-VEGF), a massive infiltration of cytotoxic T cells was found, as well (47).

Strikingly, Gordon and colleagues identified prolonged survival in tumor mouse models due to increase macrophage dependent antitumor immune responses and phagocytosis mediated by PD-1 blockade on TAMs (35). We found a significant upregulation of LAG-3 and CTLA-4 on TAMs upon resistance to PD-L1 treatment, which is rescued by combined VEGF/PD-L1 blockade. This might indicate that combined anti-VEGF/anti–PD-L1 therapy abrogates exhaustion of TAMs triggering prolonged survival of mice with SCLC.

We further observed that galectin-9 was upregulated in TAMs upon acquired resistance against PD-L1 blockade in mice and coexpressed with TIM-3 in patients with SCLC. In line with our findings, elevated galectin-9 expression had been detected in acquired resistance against PD-1 blockade in NSCLC (41) and is known to mediate apoptosis of CD4⁺ and CD8⁺ T cells via TIM-3 (33, 48). These findings indicate that galectin-9 expression on TAMs might contribute to T-cell exhaustion.

Upon resistance to immune checkpoint-targeted therapy, T cells become exhausted and lose their effector functions and the expression of TNFα and IFNγ (38, 40). We did not detect differential IFNy expression among the different therapy groups. However, we found a significantly increased fraction of Tregs upon resistance to combined anti-VEGF/anti–PD-L1 therapy. Other alternative resistance mechanisms to VEGF blockade might be initiated by macrophages that were attracted toward the tumor and generate an immunosuppressive tumor microenvironment (49, 50) or by incomplete DC maturation (18). Thereby tumor cell–derived VEGF abrogates expression of immune stimulatory molecules such as CD80, CD86, and MHC class II and thus DC maturation by interfering with the NFkB pathway (18, 51). Moreover, combined antiangiogenic/anti–PD-L1 treatment has been described to facilitate the activation and infiltration of DCs and T cells into the tumor tissue (46). However, we did not detect increased fractions of DCs associated with SCLCs treated with combined anti-VEGF/anti–PD-L1 therapy.

In summary, we identified an exhausted T-cell phenotype indicated by PD-1 and TIM-3 expression as a likely adaptive resistance mechanism to PD-1/PD-L1 blockade in mice and patients with SCLC. We show that the expression of the immunosuppressive receptor TIM-3 on tumor-educated T cells is regulated by VEGF signaling.

Strikingly, combined blockade of VEGF and PD-L1 results in synergistic treatment effects in an autochthonous mouse model of SCLC. These results strongly recommend simultaneous VEGF- and PD-L1 inhibition as a therapeutic strategy for the treatment of patients with SCLC.

R. Buettner is a consultant/advisory board member for BMS, MSD, Roche, Pfizer, Qiagen, AbbVie, and AstraZeneca. No potential conflicts of interest were disclosed by the other authors.

Conception and design: H.A. Schlößer, R. Buettner, J. Wolf, M. von Bergwelt-Baildon, R.T. Ullrich

Development of methodology: L. Meder, P. Schuldt, F. Dietlein, S. Borchmann, I. Vlasic, S. Oberbeck, K. Golfmann, M. Herling, H.C. Reinhardt, R.T. Ullrich

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): L. Meder, P. Schuldt, M. Thelen, A. Schmitt, S. Klein, K. Wennhold, I. Vlasic, S. Oberbeck, R. Riedel, K. Golfmann, H.A. Schlößer, R. Buettner, J. Wolf, M. Herling, R.T. Ullrich

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): L. Meder, P. Schuldt, M. Thelen, F. Dietlein, S. Klein, S. Borchmann, K. Wennhold, H.A. Schlößer, R. Buettner, J. Wolf, M. Hallek, M. von Bergwelt-Baildon, R.T. Ullrich

Writing, review, and/or revision of the manuscript: L. Meder, M. Thelen, F. Dietlein, S. Borchmann, K. Wennhold, H.A. Schlößer, R. Buettner, J. Wolf, M. Hallek, M. Herling, M. von Bergwelt-Baildon, H.C. Reinhardt, R.T. Ullrich

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): F. Dietlein, S. Klein, A. Florin, M. Odenthal, H.C. Reinhardt, R.T. Ullrich

Study supervision: R.T. Ullrich

This work was supported by the Deutsche Krebshilfe (grant no. 70113009, to R.T. Ullrich), the Thyssen Foundation (grant no. 10.16.1.028MN to R.T. Ullrich), the Nachwuchsforschungsgruppen-NRW (grant no. 1411ng005 to R.T. Ullrich), the Deutsche Forschungsgemeinschaft (DFG; grant no. UL379/1-1 to R.T. Ullrich and KFO-286 RP2/CP1 to H.C. Reinhardt), the Volkswagenstiftung (Lichtenberg Program; to H.C. Reinhardt), the Bundesministerium fuür Bildung und Forschung as part of the e:Med program (grant no. SMOOSE 01ZX1303A to H.C. Reinhardt), the German federal state North Rhine Westphalia (NRW) as part of the EFRE initiative (grant no. LS-1-1-030a to H.C. Reinhardt), the Else Kröner- Fresenius Stiftung (grant no. EKFS-2014-A06 to H.C. Reinhardt), the Deutsche Krebshilfe (grant no. 111724 to H.C. Reinhardt), and the Center for Molecular Medicine Cologne (CMMC; to R. Büttner, H.C. Reinhardt, and M. Odenthal).

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