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      The tumor microenvironment as a metabolic barrier to effector T cells and immunotherapy

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          Abstract

          Breakthroughs in anti-tumor immunity have led to unprecedented advances in immunotherapy, yet it is now clear that the tumor microenvironment (TME) restrains immunity. T cells must substantially increase nutrient uptake to mount a proper immune response and failure to obtain sufficient nutrients or engage the appropriate metabolic pathways can alter or prevent effector T cell differentiation and function. The TME, however, can be metabolically hostile due to insufficient vascular exchange and cancer cell metabolism that leads to hypoxia, depletion of nutrients, and accumulation of waste products. Further, inhibitory receptors present in the TME can inhibit T cell metabolism and alter T cell signaling both directly and through release of extracellular vesicles such as exosomes. This review will discuss the metabolic changes that drive T cells into different stages of their development and how the TME imposes barriers to the metabolism and activity of tumor infiltrating lymphocytes.

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          Hallmarks of Cancer: The Next Generation

          The hallmarks of cancer comprise six biological capabilities acquired during the multistep development of human tumors. The hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis. Underlying these hallmarks are genome instability, which generates the genetic diversity that expedites their acquisition, and inflammation, which fosters multiple hallmark functions. Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list-reprogramming of energy metabolism and evading immune destruction. In addition to cancer cells, tumors exhibit another dimension of complexity: they contain a repertoire of recruited, ostensibly normal cells that contribute to the acquisition of hallmark traits by creating the "tumor microenvironment." Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer. Copyright © 2011 Elsevier Inc. All rights reserved.
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            The Emerging Hallmarks of Cancer Metabolism.

            Tumorigenesis is dependent on the reprogramming of cellular metabolism as both direct and indirect consequence of oncogenic mutations. A common feature of cancer cell metabolism is the ability to acquire necessary nutrients from a frequently nutrient-poor environment and utilize these nutrients to both maintain viability and build new biomass. The alterations in intracellular and extracellular metabolites that can accompany cancer-associated metabolic reprogramming have profound effects on gene expression, cellular differentiation, and the tumor microenvironment. In this Perspective, we have organized known cancer-associated metabolic changes into six hallmarks: (1) deregulated uptake of glucose and amino acids, (2) use of opportunistic modes of nutrient acquisition, (3) use of glycolysis/TCA cycle intermediates for biosynthesis and NADPH production, (4) increased demand for nitrogen, (5) alterations in metabolite-driven gene regulation, and (6) metabolic interactions with the microenvironment. While few tumors display all six hallmarks, most display several. The specific hallmarks exhibited by an individual tumor may ultimately contribute to better tumor classification and aid in directing treatment.
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              PD-L1 is a novel direct target of HIF-1α, and its blockade under hypoxia enhanced MDSC-mediated T cell activation

              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
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                05 May 2020
                2020
                : 9
                : e55185
                Affiliations
                [1 ]Department of Medicine, Division of Hematology and Oncology, Vanderbilt University Medical Center NashvilleUnited States
                [2 ]Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center NashvilleUnited States
                [3 ]Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center NashvilleUnited States
                [4 ]Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center NashvilleUnited States
                University of Paris Descartes France
                Pfizer United States
                Author information
                https://orcid.org/0000-0002-4106-3396
                Article
                55185
                10.7554/eLife.55185
                7200151
                32367803
                d29cd683-299c-4ac3-8717-65b3d4090f99
                © 2020, Lim et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 15 January 2020
                : 22 April 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: R01 CA217987
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: T32GM007347
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Review Article
                Cancer Biology
                Immunology and Inflammation
                Custom metadata
                Diverse components of the tumor microenvironment affect T cell metabolism in ways that are crucial to improving immunotherapy.

                Life sciences
                immunometabolism,tumor microenvironment,tumor-infiltrating lymphocytes,t cells,immunotherapy,cancer

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