Targeting the Immune Microenvironment in the Treatment of Head and Neck Squamous Cell Carcinoma

Hypoxia is a common feature of solid tumors (Semenza, 2011). Hypoxic zones in tumors attract immunosuppressive cells such as myeloid-derived suppressor cells (MDSCs; Corzo et al., 2010), tumor-associated macrophages (TAMs; Doedens et al., 2010; Imtiyaz et al., 2010), and regulatory T cells (T reg cells; Clambey et al., 2012). MDSCs are a heterogeneous group of relatively immature myeloid cells and several studies have described mechanisms of MDSC-mediated immune suppression (Gabrilovich et al., 2012). A large body of preclinical and clinical data indicates that antibody blockade of immune checkpoints can significantly enhance antitumor immunity (Pardoll, 2012; West et al., 2013). Recently, antibody-mediated blockade of preprogrammed death 1 (PD-1; Topalian et al., 2012) and its ligand, PD-L1 (Brahmer et al., 2012), was shown to result in durable tumor regression and prolonged stabilization of disease in patients with advanced cancers. PD-1, a cell surface glycoprotein with a structure similar to cytotoxic T lymphocyte antigen 4 (CTLA-4), belongs to the B7 family of co-stimulatory/co-inhibitory molecules and plays a key part in immune regulation (Greenwald et al., 2005). PD-1 has two known ligands, PD-L1 (B7-H1) and PD-L2 (B7-DC). Although hypoxia has been shown to regulate the function and differentiation of MDSCs (Corzo et al., 2010), several major questions remain unresolved. The influence of hypoxia on the regulation of immune checkpoint receptors (PD-1 and CTLA-4) and their respective ligands (PD-L1, PD-L2, CD80, and CD86) on MDSCs remains largely obscure. Furthermore, the potential contribution of these immune checkpoint receptors and their respective ligands on MDSC function under hypoxia is still unknown. In the present study, we showed that hypoxia via hypoxia-inducible factor-1α (HIF-1α) selectively up-regulated PD-L1 on MDSCs, but not other B7 family members, by binding directly to the HRE in the PD-L1 proximal promoter. Blockade of PD-L1 under hypoxia abrogated MDSC-mediated T cell suppression by modulating MDSCs cytokine production. RESULTS AND DISCUSSION Differential expression of PD-L1 on tumor-infiltrating MDSCs versus splenic MDSCs and selective up-regulation of PD-L1 in splenic MDSCs under hypoxic stress We first compared the level of expression of PD-L1 and PD-L2 between splenic MDSCs and tumor-infiltrating MDSCs from tumor-bearing mice. We found that the percentage of PD-L1+ cells was significantly higher on tumor-infiltrating MDSCs as compared with splenic MDSC in B16-F10, LLC (Fig. 1 A), CT26, and 4T1 (Fig. 1 B) tumor models. No significant difference was found in the percentage of PD-L2+ cells in splenic MDSCs as compared with tumor-infiltrating MDSCs in four tumor models tested (Fig. 1 C). We did not observe any significant difference in the expression levels of other members of the B7 family such as CD80, CD86, PD-1, and CTLA-4 on MDSCs from spleen and tumor (unpublished data). Youn et al. (2008) previously observed no significant differences in the percentage of PD-L1+ or CD80+ cells within the splenic MDSCs from tumor-bearing mice and immature myeloid cells from naive tumor-free mice. However, by comparing the expression of immune checkpoint inhibitors between splenic and tumor-infiltrating MDSCs, we showed that there is a differential expression of PD-L1 on tumor-infiltrating MDSCs. Figure 1. Tumor-infiltrating MDSCs differentially express PD-L1 as compared with splenic MDSCs, and hypoxia selectively up-regulates PD-L1 on splenic MDSCs in tumor-bearing mice. Surface expression level of PD-L1 and PD-L2 on Gr1+ CD11b+ cells (MDSCs) from (B16-F10 and LLC; A; CT26 and 4T1; B) in spleens (black dotted line histogram) and tumor (black line histogram) as compared with isotype control (gray-shaded histogram) was analyzed by flow cytometry. (C) Statistically significant differences (indicated by asterisks) between tumor-infiltrating MDSCs and splenic MDSCs are shown (*, P 20 fold for HRE-4), comparable to their binding to an established HRE in VEGF, LDHA, and Glut1 genes. To determine whether this HIF-1α site (HRE-4) was a transcriptionally active HRE, MSC-1 cells were co-transfected with pGL4-hRluc/SV40 vector and pGL3 EV, pGL3 HRE-4, or pGL3 HRE-4 MUT vectors (Fig. 3 M) and grown under normoxia or hypoxia. After 48 h, firefly and renilla luciferase activities were measured. As shown in Fig. 3 N, hypoxia significantly increased the luciferase activity of HRE-4 reporter by more than threefold as compared with normoxia. More interestingly, the luciferase activity of HRE-4 MUT was significantly decreased (>50%) as compared with HRE-4 under hypoxia (Fig. 3 N). The results presented in Figs. 3 (H–N) demonstrate that PD-L1 is a direct HIF-1α target gene in MSC-1 cells. Thus, we provide evidence here that HIF-1α is a major regulator of PD-L1 mRNA and protein expression, and that HIF-1α regulates the expression of PD-L1 by binding directly to the HRE-4 in the PD-L1 proximal promoter. Blocking PD-L1 decreases MDSC-mediated T cell suppression under hypoxia by down-regulating MDSC IL-6 and IL-10 To directly test the functional consequences of hypoxia-induced up-regulation of PD-L1 in MDSC-mediated T cell suppression, the expression of PD-L1 was blocked on ex vivo MDSCs by using anti–PD-L1 monoclonal antibody. Hypoxia increased the ability of MDSCs to suppress both specific and nonspecific stimuli-mediated T cell proliferation (Fig. 4, A and B). Interestingly, blockade of PD-L1 under hypoxia significantly abrogated the suppressive activity of MDSCs in response to both nonspecific stimuli (anti-CD3/CD28 antibody; Fig. 4 A) and specific stimuli (TRP-2(180–88) peptide; Fig. 4 B). Under hypoxia, MDSCs acquired the ability to inhibit T cell function (Fig. 4, C and D) by decreasing the percentage of IFN-γ+ CD8+ and CD4+ T cells; whereas the percentage of IFN-γ+ CD8+ (Fig. 4 C) and IFN-γ+ CD4+ T cells (Fig. 4 D) significantly increased after PD-L1 blockade under hypoxic conditions. Thus, the immune suppressive function of MDSCs enhanced under hypoxia was abrogated after blocking PD-L1, and hypoxic up-regulation of PD-L1 on MDSCs is involved in mediating the suppressive action of MDSCs, at least in part, as we were not able to completely restore T cell proliferation and function after PD-L1 blockade on MDSCs under hypoxia. Figure 4. Blockade of PD-L1 under hypoxia down-regulates MDSC IL-6 and IL-10 and enhances T cell proliferation and function. MDSCs isolated from spleens of B16-F10 tumor-bearing mice were pretreated for 30 min on ice with 5 µg/ml control antibody (IgG) or antibody against PD-L1 (PDL1 Block) and co-cultured with splenocytes under normoxia and hypoxia for 72 h. (A and B) Effect of MDSC on proliferation of splenocytes stimulated with (A) anti-CD3/CD28 coated beads or (B) TRP-2(180–88) peptide under the indicated conditions. Cell proliferation was measured in triplicates by [3H]thymidine incorporation and expressed as counts per minute (CPM). (C and D) MDSCs were cultured with splenocytes from B16-F10 mice stimulated with anti-CD3/CD28. Intracellular IFN-γ production was evaluated by flow cytometry by gating on (C) CD3+CD8+ IFN-γ+ and (D) CD3+CD4+ IFN-γ+ populations. Statistically significant differences (indicated by asterisks) are shown (**, P 95% as evaluated by FACS analysis. MDSC functional assays. For evaluation of T cell proliferation, splenocytes from B16-F10 mice were plated into U-bottom 96-well plates along with MDSCs at different ratios (50,000 MDSC:200,000 splenocytes/well). Plates were stimulated with either anti-CD3/CD28 beads (Miltenyi Biotec) or TRP-2 180–88 peptide for 72 h at 37°C. Co-cultures were pulsed with thymidine (1 µCi/well; Promega) for 16–18 h before harvesting, and [3H]thymidine uptake was counted using Packard’s TopCount NXT liquid scintillation counter and expressed as counts per minute (CPM). For assessment of T cell functions, MDSCs co-cultured with splenocytes from B16-F10 mice were stimulated with anti-CD3/CD28 beads. After 72 h, intracellular IFN-γ production was evaluated by flow cytometry by gating on CD3+CD8+ IFN-γ+ and CD3+CD4+ IFN-γ+ populations. MDSCs cytokine production (ELISA). MDSCs isolated from spleens of B16-F10 tumor-bearing mice were pretreated for 30 min on ice with 5 μg/ml control antibody (IgG) or Anti-Mouse PD-L1 (B7-H1) Functional Grade Purified antibody 5 µg/ml (clone MIH5; eBioscience; PDL1 Block) and cultured under normoxia and hypoxia for 72 h. Supernatants were collected and the secretion of IL-6, IL-10, and IL-12p70 (eBioscience) was determined by ELISA. ChIP assay. ChIP was performed with lysates prepared from MSC-1 by using SimpleChIP Enzymatic Chromatin IP kit (Cell Signaling Technology). SYBR Green RT-qPCR was performed using the primers detailed in Table S1. Arginase enzymatic activity and NO (nitric oxide) production. Arginase activity was measured in MDSC cell lysates, and for NO production, culture supernatants were mixed with Greiss reagent and nitrite concentrations were determined as described earlier (Youn et al., 2008). Luciferase reporter assay. A 653-bp section corresponding to mouse PD-L1 promoter containing HRE4 sequence was inserted into the NheI–XhoI sites of pGL3-Basic vector (Promega). Mutation of HRE4 was performed by site-directed mutagenesis and verified by sequencing. A 56-bp mouse PD-L1 gene sequence was inserted into the Bgl II site of pGL3-Promoter (Promega). MSC-1 cells were co-transfected with 0.2 µg of pGL4-hRluc/SV40 vector (which contains renilla luciferase sequences downstream of the SV40 promoter) and 1 µg of pGL3 empty vector, pGL3 HRE-4, or pGL3 HRE-4 MUT vectors in 6-well plates with Lipofectamine 2000 (Invitrogen) in OPTIMEM (Invitrogen) medium and grown under normoxia or hypoxia. After 48 h, firefly and Renilla luciferase activities were measured using the Dual-Luciferase Reporter assay (Promega) and the ratio of firefly/Renilla luciferase was determined. Statistics. Data were analyzed with GraphPad Prism. Student’s t test was used for single comparisons. Online supplemental material. Table S1 shows genomic oligonucleotide primers used for amplification of immunoprecipitated DNA samples from ChIP assays. Online supplemental material is available at http://www.jem.org/cgi/content/full/jem.20131916/DC1. Supplementary Material Supplemental Material

Despite compelling antitumour activity of antibodies targeting the programmed death 1 (PD-1): programmed death ligand 1 (PD-L1) immune checkpoint in lung cancer, resistance to these therapies has increasingly been observed. In this study, to elucidate mechanisms of adaptive resistance, we analyse the tumour immune microenvironment in the context of anti-PD-1 therapy in two fully immunocompetent mouse models of lung adenocarcinoma. In tumours progressing following response to anti-PD-1 therapy, we observe upregulation of alternative immune checkpoints, notably T-cell immunoglobulin mucin-3 (TIM-3), in PD-1 antibody bound T cells and demonstrate a survival advantage with addition of a TIM-3 blocking antibody following failure of PD-1 blockade. Two patients who developed adaptive resistance to anti-PD-1 treatment also show a similar TIM-3 upregulation in blocking antibody-bound T cells at treatment failure. These data suggest that upregulation of TIM-3 and other immune checkpoints may be targetable biomarkers associated with adaptive resistance to PD-1 blockade.

Immune checkpoint inhibitors (ICI) targeting CTLA-4 and the PD-1/PD-L1 axis have shown unprecedented clinical activity in several types of cancer and are rapidly transforming the practice of medical oncology. Whereas cytotoxic chemotherapy and small molecule inhibitors (‘targeted therapies’) largely act on cancer cells directly, immune checkpoint inhibitors reinvigorate anti-tumour immune responses by disrupting co-inhibitory T-cell signalling. While resistance routinely develops in patients treated with conventional cancer therapies and targeted therapies, durable responses suggestive of long-lasting immunologic memory are commonly seen in large subsets of patients treated with ICI. However, initial response appears to be a binary event, with most non-responders to single-agent ICI therapy progressing at a rate consistent with the natural history of disease. In addition, late relapses are now emerging with longer follow-up of clinical trial populations, suggesting the emergence of acquired resistance. As robust biomarkers to predict clinical response and/or resistance remain elusive, the mechanisms underlying innate (primary) and acquired (secondary) resistance are largely inferred from pre-clinical studies and correlative clinical data. Improved understanding of molecular and immunologic mechanisms of ICI response (and resistance) may not only identify novel predictive and/or prognostic biomarkers, but also ultimately guide optimal combination/sequencing of ICI therapy in the clinic. Here we review the emerging clinical and pre-clinical data identifying novel mechanisms of innate and acquired resistance to immune checkpoint inhibition.