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Uncoupling protein 2 reprograms the tumor microenvironment to support the anti-tumor immune cycle

Nature Immunology volume 20, pages 206–217 (2019)Cite this article

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A Publisher Correction to this article was published on 12 March 2019

This article has been updated

Abstract

Immune checkpoint blockade therapy has shifted the paradigm for cancer treatment. However, the majority of patients lack effective responses due to insufficient T cell infiltration in tumors. Here we show that expression of mitochondrial uncoupling protein 2 (UCP2) in tumor cells determines the immunostimulatory feature of the tumor microenvironment (TME) and is positively associated with prolonged survival. UCP2 reprograms the immune state of the TME by altering its cytokine milieu in an interferon regulatory factor 5-dependent manner. Consequently, UCP2 boosts the conventional type 1 dendritic cell- and CD8+ T cell-dependent anti-tumor immune cycle and normalizes the tumor vasculature. Finally we show, using either a genetic or pharmacological approach, that induction of UCP2 sensitizes melanomas to programmed cell death protein-1 blockade treatment and elicits effective anti-tumor responses. Together, this study demonstrates that targeting the UCP2 pathway is a potent strategy for alleviating the immunosuppressive TME and overcoming the primary resistance of programmed cell death protein-1 blockade.

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Fig. 1: UCP2 expression is associated with elevated T cell infiltration and prolonged survival rates.
Fig. 2: UCP2 expression is associated with anti-tumor immune states and cDC1 and CD8+ T cell infiltration in tumors.
Fig. 3: UCP2 overexpression in melanoma cells induces anti-tumor responses and normalizes tumor vasculature.
Fig. 4: UCP2-induced anti-tumor responses are associated with the immune state and are dependent on CD103+ dendritic cells.
Fig. 5: UCP2-stimulated IRF5-CXCL10 axis supports engagement of the cDC1-CD8+ T cell anti-tumor cycle.
Fig. 6: UCP2-mediated tumor suppression is independent of the β-catenin-ATF3 pathway and PGE2 production.
Fig. 7: UCP2 induction sensitizes melanoma to PD-1 blockade therapy.

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Data availability

All other relevant data are available from the corresponding author on request.

Change history

  • 12 March 2019

    In the version of this article initially published, the bars were not aligned with the data points or horizontal axis labels in Fig. 5d, and the labels along each horizontal axis of Fig. 5j–l indicating the presence (+) or absence (–) of doxycycline (Dox) were incorrectly included with the labels below that axis. Also, the right vertical bar above Fig. 7b linking ‘P = 0.0001’ to the key was incorrect; the correct comparison is αPD-1 versus Dox + αPD-1. Similarly, the right vertical bar above Fig. 7e linking ‘P = 0.0002’ to the key was incorrect; the correct comparison is αPD-1 versus Rosig + αPD-1. The errors have been corrected in the HTML and PDF versions of the article.

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Acknowledgements

This study was supported in part by the Swiss Institute for Experimental Cancer Research (no. ISREC 26075483), the Swiss Cancer Foundation (no. KFS-3949-08-2016), a SNSF project grant (no. 31003A_163204), a Clinic and Laboratory Integration Program award from the Cancer Research Institute, a Harry J. Lloyd Charitable Trust Career Development Grant, a Roch-pRED grant and a SITC-MRA Young Investigator Award to P.-C.H. A.Z. and P.R. are supported by SNSF project grants (no. 320030_162575 to A.Z., nos. CRSII3_160708 and 31003A_156469 to P.R.). T.P. is supported by the MEDIC Foundation and Swiss Cancer League (no. KLS 3406-02-2016) and G.C. is supported by the Giorgi-Cavaglieri Foundation. We also thank Camilla Jandus for providing human melanoma cell lines.

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Authors and Affiliations

  1. Department of Fundamental Oncology, University of Lausanne, Lausanne, Switzerland

    Wan-Chen Cheng, Yao-Chen Tsui, Simone Ragusa, Fabien Franco, Benjamin Tschumi, Daniel Speiser, Pedro Romero, Tatiana V. Petrova & Ping-Chih Ho

  2. Ludwig Cancer Research, University of Lausanne, Epalinges, Switzerland

    Wan-Chen Cheng, Yao-Chen Tsui, Simone Ragusa, Fabien Franco, Benjamin Tschumi, Daniel Speiser, Pedro Romero, Tatiana V. Petrova & Ping-Chih Ho

  3. Division of Experimental Pathology, CHUV, Lausanne, Switzerland

    Simone Ragusa & Tatiana V. Petrova

  4. Institute of Pathology, Cantonal Hospital Baselland, Liestal, Switzerland

    Viktor H. Koelzer & Kirsten Mertz

  5. Department of Computational Biology, University of Lausanne, Lausanne, Switzerland

    Marco Mina & Giovanni Ciriello

  6. Swiss Institute of Bioinformatics, Lausanne, Switzerland

    Marco Mina & Giovanni Ciriello

  7. Department of Biomedicine, University Hospital Basel, Basel, Switzerland

    Heinz Läubli & Alfred Zippelius

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Contributions

W.-C.C. and P.-C.H. contributed to overall project design and wrote the manuscript. W.-C.C., Y.-C.T., S.R. and F.F. performed in vitro and in vivo animal experiments and data analysis. V.H.K., H.L., A.Z. and K.M. conducted the collection and immunohistochemical staining of human melanoma samples. V.H.K. and K.M. examined pathological sections. M.M. and G.C. performed computational analyses of TCGA datasets and single-cell RNA-seq. B.T., D.S. and P.R. provided essential materials and data analysis. S.R. and T.V.P. conducted and analyzed tumor blood vessel morphology and T cell infiltration.

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Correspondence to Ping-Chih Ho.

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Competing interests

W.-C.C., Y.-C.T., G.C. and P.-C.H. are inventors of patent application related to targeting of UCP2 in cancer immunotherapy. P.-C.H. received research grants from Roche and Idorsia. P.-C.H. also serves as a scientific advisory member for Elixiron Immunotherapeutics.

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Integrated supplementary information

Supplementary Figure 1 Functional enrichment analysis in patients characterized by computational separation of T cell anti-tumor immunity.

a, Gene ontology term enrichment analysis for top 20 biological process controlled by differentially expressed genes between of patients with either high or low combined score for T cell anti-tumor immunity. Top panel: top 20 up-regulated biological processes in patients with high T cell anti-immunity. Bottom panel: top-20 up-regulated biological processes genes in patients with low T cells anti-tumor immunity. b, Pearson correlation plots of expression of other members of UCP family, including UCP1, UCP3, UCP4 or UCP5, with transcripts of CD8A, IFNG, GZMB, TNF, LCK, and SYK. Data were analyzed form 472 melanoma patients in TCGA database (biologically independent melanoma tumor samples), and analyzed by Pearson correlation coefficient.

Supplementary Figure 2 Single-cell RNA-seq analysis and UCP2 signature identification.

Single-cell RNA sequencing analysis from Tirosh et al. dataset27. a, The violin plots of the complete distribution of UCP2 expression by cell type. Each dot represents a single cell. Minimum values: all group (0). Middle value: B cells (5.6588); CAF (0); Endothelial cell (0); Macrophage (5.4573); NK cells (5.75925), T cells (5.12575); Tumor (0), Unclear (3.7592). Maximum values: B cells (9.0913); CAF (4.5699); Endothelial cell (5.1351); Macrophage (8.8324); NK cells (8.2642), T cells (9.5713); Tumor (7.671), Unclear (9.5402). b, Gene association plot base on UCP2 expression. The association was determined by splitting the TCGA melanoma samples in low, mid, and high UCP2 expressing samples, and then computing a right-sided Wilcoxon Rank-sum test for each gene from the panel of genes specifically expressed in malignant cells according in the Tirosh et al. dataset27. The horizontal line corresponds to a P value of 0.05. The 49 genes with P value < 0.05 were selected as UCP2 signature. c, Heatmap of the average expression of the 49 genes in the UCP2 signature across the different cell populations. Data were analyzed form 472 melanoma patients in TCGA cohort and 19 melanoma patients form single cell RNA-seq dataset (biologically independent melanoma tumor samples).

Supplementary Figure 3 Immunohistochemical staining analysis of UCP2 expression with anti-tumor score in tumor sections from melanoma patients.

a, b, Quantitative results of IHC staining against UCP2, CD8A and PD-L1 in 66 melanoma patients. PD-L1 expression percentage in melanoma cells (a) and the combined scores of CD8A intensity and PD-L1 expression percentage and intensity (b) in sections with escalating UCP2 expression in melanoma cells. Each symbol represents an individual patient. (UCP2 expression level: 0, n = 33; 1, n = 25; 2, n = 8). c, Representative histology slides form 66 melanoma patients showing staining of haematocylin and eosin (H&E), UCP2 (stained in red), Melanine A (Melan A) (stained in red) and CD8 (stained in brown), and PD-L1 in patients with different UCP2 expression levels. Data are mean±s.e.m.; unpaired, two-tailed Student’s t-test.

Supplementary Figure 4 Characterization of immune infiltrates in B16-OVA melanomas upon UCP2 induction.

a, b, Percentage (a) and absolute number of NK cells per gram of tumor (b) from indicated tumor-bearing mice as illustrated in Figs. 3a. (a, 3F, n = 10; 3F+Dox, n = 13; 3F-UCP2, n = 11; 3F-UCP2+Dox, n = 9. b, 3F, n = 10; 3F+Dox, n = 13; 3F-UCP2, n = 10; 3F-UCP2+Dox, n = 9). c, d, Percentage (c) and absolute number of CD4+ T cells per gram of tumor (d) from indicated tumor-bearing mice. (c, 3F, n = 11); 3F+Dox, n = 13; 3F-UCP2, n = 11; 3F-UCP2+Dox, n = 9. d, 3F, n = 9; 3F+Dox, n = 12; 3F-UCP2, n = 10; 3F-UCP2+Dox, n = 9). e, f, Percentage of regulatory T cells (Tregs) (e) and B cells (f) among CD45+ cells in melanomas from indicated tumor-bearing mice. (e, 3F, n = 11; 3F+Dox, n = 13; 3F-UCP2, n = 11; 3F-UCP2+Dox, n = 9. f, 3F, n = 8; 3F+Dox, n = 9; 3F-UCP2, n = 7; 3F-UCP2+Dox, n = 5). g, h, Percentage of IFN-γ-producing (g) and TNF producing (h) CD8+ T cells among total tumor-infiltrating CD8+ T cells from indicated mice. (g, 3F, n = 15; 3F+Dox, n = 11; 3F-UCP2, n = 17; 3F-UCP2+Dox, n = 17. h, 3F, n = 8; 3F+Dox, n = 8; 3F-UCP2, n = 8; 3F-UCP2+Dox, n = 7). i, Quantitative result of MHC-I expression in indicated B16-OVA cell lines treated with or without Dox. (n = 9 in each group). j, Quantitative result of OT-I T cells interacting with indicated B16-OVA cell lines treated with control vehicle or Dox. (n = 6 in each group). k, Quantitative result (left panel) and representative FACS plot (right panel) of PD-L1 expression in B16-OVA 3F-UCP2 cell lines treated with control vehicle or Dox. (n = 9 in each group). l, Survival percentage of indicated B16 melanoma cells in the in vitro effector:target cell titration assay. (n = 9 in each group). All data are mean±s.e.m. Data are cumulative results from at least three independent experiments. n.s., not significant; unpaired, two-tailed Student’s t-test.

Supplementary Figure 5 Sustaining mTOR-HIF1 activity fails to prevent UCP2-induced anti- tumor responses.

a, b, Total reactive oxygen species, (a) and mitochondrial reactive oxygen species (b) in 3F and 3F-UCP2 B16-OVA melanoma cell lines treated with control vehicle or doxycycline were measured by CM-H2DCFDA and MitoSox Red (MitoSox), respectively. (n = 9 in each group). c, Immunoblot analysis of 3F-UCP2 B16-OVA cell and dual inducible B16-OVA cell, which simultaneously overexpress flag-tagged UCP2 and stabilized myc-tagged HIF-1α, treated with or without Dox. See also Supplementary Fig. 7a. d, e, Tumor growth (d) and tumor weight (e) of dual inducible B16-OVA melanoma from mice treated with or without Dox. (Ctrl, N = 6; Dox, n = 10). Data are mean±s.e.m. and analyzed by unpaired, two-tailed Student’s t-test. Data are cumulative results from at least three independent experiments (a-b, d-e), or representative images of three independent experiments (c). Each symbol represents one individual mouse.

Supplementary Figure 6 UCP2 induction enhances CD8+ T cell infiltration and normalizes tumor vessels.

a, Relative number of CD8a+ cells in tumor cores and margins of 3F and 3F-UCP2 B16-OVA melanomas from control or doxycycline treated co-engrafted mice. (ANOVA p values: Core, p<0.0001; Margins, p = 0.0202). b, Normalized individual vessel surface area in tumor cores and margins of indicated melanomas. (ANOVA p value: Core, p = 0.0028). c, relative mural SMA+ cell coverage of CD31+ tumor endothelial cells in the indicated melanomas. (ANOVA p value = 0.0001). Data are mean±s.e.m. and analyzed by one-way ANOVA with Tukey's Multiple Comparison test (a, b, c). d, Characterization of the tumor vasculature in the indicated tumors. Proportion of single VCAM-1+ or mural cell-covered (SMA+), double positive (SMA+VCAM-1+) and immature (SMAnegVCAM-1neg) vessels were quantified. Endothelial cells were identified by staining for pan-endothelial marker CD31, Data are mean±s.e.m. (a, 3F, n = 5; 3F = Dox, n = 6; 3F-UCP2, n = 6; 3F-UCP2+Dox, n = 7. b-d, 3F, n = 5; 3F = Dox, n = 6; 3F-UCP2, n = 6; 3F-UCP2+Dox, n = 6). e, Representative images of immunofluorescent staining for indicated proteins and DNA of YUMM1.7-OVA melanomas from wild type, Rag1-KO or CD8+ T cell-depleted mice. Scale bar, 50 µm. f-h, Quantification of the data shown in e. Relative number of tumor infiltrating CD8a+ cells (f); relative single tumor vessel area (g); and relative mural SMA+ cell coverage of VE-cadherin+ blood vessels (h). Data are mean±s.d. and analyzed by two-way ANOVA with Tukey's Multiple Comparison test (f, g, h). *p ≤0.05; **p ≤0.01; ***p ≤0.001; ****p ≤0.0001. Sample size: e-h, each group (n = 5). Data are cumulative results from two independent experiments (a-d, f-g) and representative images of two independent experiments (e). Each symbol represents one individual mouse.

Supplementary Figure 7 All raw and unprocessed immunoblots.

a, Immunoblots related to Supplementary Fig. 5c. b, Immunoblots related to Fig. 7c. c, Immunoblots related to Fig. 7g

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7, Supplementary Tables 2 and 3

Reporting Summary

Supplementary Table 1

T cell infiltration gene sets

Supplementary Table 4

Differentially expressed genes between UCP2hi and UCP2lo patients

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Cheng, WC., Tsui, YC., Ragusa, S. et al. Uncoupling protein 2 reprograms the tumor microenvironment to support the anti-tumor immune cycle. Nat Immunol 20, 206–217 (2019). https://doi.org/10.1038/s41590-018-0290-0

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