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Epigenetic silencing of TH1-type chemokines shapes tumour immunity and immunotherapy

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Abstract

Epigenetic silencing including histone modifications and DNA methylation is an important tumorigenic mechanism1. However, its role in cancer immunopathology and immunotherapy is poorly understood. Using human ovarian cancers as our model, here we show that enhancer of zeste homologue 2 (EZH2)-mediated histone H3 lysine 27 trimethylation (H3K27me3) and DNA methyltransferase 1 (DNMT1)-mediated DNA methylation repress the tumour production of T helper 1 (TH1)-type chemokines CXCL9 and CXCL10, and subsequently determine effector T-cell trafficking to the tumour microenvironment. Treatment with epigenetic modulators removes the repression and increases effector T-cell tumour infiltration, slows down tumour progression, and improves the therapeutic efficacy of programmed death-ligand 1 (PD-L1; also known as B7-H1) checkpoint blockade2,3,4 and adoptive T-cell transfusion5 in tumour-bearing mice. Moreover, tumour EZH2 and DNMT1 are negatively associated with tumour-infiltrating CD8+ T cells and patient outcome. Thus, epigenetic silencing of TH1-type chemokines is a novel immune-evasion mechanism of tumours. Selective epigenetic reprogramming alters the T-cell landscape6 in cancer and may enhance the clinical efficacy of cancer therapy.

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Figure 1: Epigenetic reprogramming alters cancer T-cell immunotherapy.
Figure 2: Histone methyltransferase represses TH1-type chemokines.
Figure 3: DNA methylation regulates TH1-type chemokine expression.
Figure 4: EZH2/H3K27 and DNMT1 interaction and its impact on clinical outcome.

Change history

  • 11 November 2015

    A sentence in the Methods that included an incorrect citation to the Supplementary Information was removed.

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Acknowledgements

This work is supported (in part) by the NIH grants (CA190176; CA123088; CA099985; CA156685; CA193136; CA152470; CA171306; 5P30CA46592), the Rivkin Ovarian Cancer Center, and the Ovarian Cancer Research Fund. We appreciate discussion with B. Richardson. We thank L. Cabrera, D. Postiff, M. Vinco, R. Craig and J. Barikdar for their technical assistance. We are grateful for the professional help from W. Wu and C. Johnson in our Microarray Core and Bioinformatics Core. We particularly appreciate the support of B. Leclair and D. Leclair.

Author information

Authors and Affiliations

Authors

Contributions

D.P. and W.Z. initiated and designed the research. D.P., I.K. and W.Z. wrote the manuscript. D.P., I.K., N.N., S.W., E.Z., L.V., W.W. and W.S. performed experiments. L.Z., I.K. and D.P. analysed data. J.K., R.T., Y.D., S.H.-A., A.M., K.C. and R.L. provided intellectual and technical support, clinical specimens, and clinical and pathological information.

Corresponding author

Correspondence to Weiping Zou.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Epigenetic reprogramming alters immunotherapy.

ac, Effects of DZNep and 5-AZA-dC on ID8 mouse ovarian cancer progression. The ID8 tumour-bearing mice (C57BL/6) were treated with DZNep and 5-AZA-dC. a, Tumour growth was recorded by bioluminescence imaging and quantified by calculating the total flux (photons per second). The representative images and tumour volume at day 24 are shown. Day 0, tumour inoculation. b, Tumour-infiltrating CD8+ T cells were quantified by immunohistochemistry staining (IHC) and expressed as the mean ± s.e.m. per high-power field. c, Tumour Cxcl9 mRNA was quantified by real-time PCR. Mean ± s.e.m.; n = 5 per group, *P < 0.05, Mann–Whitney U-test as compared to the control group or the group treated with DZNep or 5-AZA-dC. d, e, Effects of EPZ6438 and 5-AZA-dC on ID8 mouse ovarian cancer progression. The ID8 tumour-bearing mice (C57BL/6) were treated with EPZ6438 and 5-AZA-dC. d, Tumour growth was recorded by bioluminescence imaging and quantified by calculating the total flux (photons per second). The representative images and tumour volume at day 22 are shown. Day 0, tumour inoculation. Mean ± s.e.m.; *P < 0.05; one-way ANOVA. e, Tumour Cxcl9 mRNA was quantified by real-time PCR. Mean ± s.e.m.; *P < 0.05; one-way ANOVA. f, Effects of DZNep and 5-AZA-dC on ovarian tumour progression in NSG mice. Mouse ID8-luc ovarian cancer cells were intraperitoneally inoculated into NSG mice. Tumour-bearing mice were treated with DZNep and 5-AZA dC. Tumour growth was recorded and quantified by bioluminescence imaging. The representative bioluminescence images on day 15 (days after tumour inoculation) are shown. n = 4 per group; mean ± s.e.m. g–i, Effects of DZNep and 5-AZA-dC on anti-PD-L1 immunotherapy. Anti-PD-L1 (10 mg/kg) was given to ID8 tumour-bearing mice (C57BL/6) with or without DZNep and 5-AZA-dC (5-Aza). g, Tumour growth was recorded. The representative images and tumour volume at day 18 are shown. h, Tumour-infiltrating CD8+ T cells were assessed and expressed as the mean ± s.e.m. per high-power field. i, Tumour Cxcl9 gene expression was quantified and expressed as the mean values ± s.e.m. n = 5 per group; *P < 0.05; Mann–Whitney U-test). jl, Effects of DZNep and 5-AZA-dC on T-cell immunotherapy. Autologous tumour-specific human CD8+ T cells were tranfused into ovarian-cancer-bearing NSG mice with or without DZNep and 5-AZA-dC treatment. The mice were treated with anti-CXCR3. j, Tumour volume was monitored. k, TH1-type chemokine expression was quantified by real-time PCR. l, Tumour-infiltrating T cells were determined by FACS. Mean ± s.e.m.; n = 5 per group; *P < 0.05 Mann–Whitney U-test. mq, Effects of GSK126 and 5-AZA-dC on T-cell immunotherapy. Ovarian-cancer-bearing NSG mice were treated with or without GSK126 and 5-AZA-dC, and received autologous human ovarian-cancer-specific CD8+ T-cell transfusion. Tumour volume (m), tumour-infiltrating T cells (n) and T-cell cytokine profile (oq) are shown Mean ± s.e.m.; n = 5 per group; *P < 0.05; Mann–Whitney U-test. Total tumour-infiltrating CD8+ T cells were normalized to the tumour volume (absolute number of CD8+ T cells per mm3 of the tumour). T-cell cytokine profile was determined by FACS via gating on human CD45+CD8+ cells in tumour tissues. The percentages of TNFα+ and IFNγ+ cells are shown in CD8+ cells. Circles represent each mouse from the group. One of two experiments is shown. rt, Effects of anti-CXCR3 on T-cell survival. Tumour-specific human CD8+ T cells were transfused into NSG mice. The mice were treated with anti-CXCR3. Peripheral blood annexin V+CD8+ human T cells (mean ± s.e.m.; n = 5 per group) (r, s) and spleen CXCR3+CD8+ human T cells (t) were determined by FACS.

Extended Data Figure 2 EZH2 controls TH1-type chemokines.

a, Effect of DZNep on Cxcl10 transcript expression. Primary ovarian cancer cells were treated with DZNep in the presence of IFNγ for different time (hours). Cxcl10 gene expression was quantified by real-time PCR. One of three experiments is shown. b, c, Effects of DZNep on ovarian cancer TH1-type chemokine expression. Human primary ovarian cancer cells were treated for 24 (b) or 48 (c) hours with DZNep in the presence of IFNγ. CXCL9 and CXCL10 expression was quantified by real-time PCR (b) or detected by ELISA (c). (mean ± s.e.m.; n = 5, *P < 0.05, Wilcoxon test). d, Effects of DZNep on IFNGR2 transcript expression. Primary ovarian cancer cells were treated with DZNep in the presence of IFNγ for 24 h. IFNGR2 expression was quantified by real-time PCR. One of three experiments is shown. e, Effects of histone methyltransferase G9a/GLP inhibitors on TH1-type chemokine expression. Primary ovarian cancer cells were treated with BIX01294 or UNC0638 in the presence of IFNγ for 24 h. Cxcl10 gene expression was quantified by real-time PCR. One of three experiments is shown. f, Effects of DZNep on the expression of EZH2 and H3K27me3. Primary ovarian cancer cells were treated with or without DZNep for 24 h. The levels of EZH2 and H3K27me3 were detected by western blotting. One of three experiments is shown. g, h, Effects of EPZ6438 on histone marks (g) and Cxcl9 mRNA expression (h). Mouse ID8 ovarian cancer cells were treated with EPZ6438 in the presence or absence of IFNγ for 48 h. H3K27me3 and H3K9me2 were detected by western blotting. Cxcl9 transcripts were quantified by real-time PCR. (Mean ± s.e.m.; four repeats, *P < 0.05, Wilcoxon test). i, Ezh2 knockdown in primary ovarian cancer cells mediated by Ezh2 shRNA. Primary ovarian cancer cells were stably transduced with a lentiviral shRNA expressing vector (non-target shRNA (Ctl) or Ezh2 shRNA, shEZH2). The levels of EZH2 and H3K27me3 were detected by western blotting. j, k, Effects of EZH2 knockdown on IFNGR2 and HLA-B gene expression. Primary ovarian cancer cells were stably transduced with non-target shRNA (Ctl) or EZH2 shRNA (shEZH2). IFNGR2 (j) and HLA-B (k) gene expression was quantified by real-time PCR. (mean ± s.e.m.; n = 4). l, m, Effect of DZNep on H3K27me3 occupancy at TH1-type chemokine promoters. H3K27me3 ChIP assay was performed in primary ovarian cancer cells treated with DZNep with or without IFNγ. H3K27me3 levels at the gene promoter of Cxcl9 and Cxcl10 were normalized to the input (mean ± s.e.m.; n = 5, *P < 0.05, Wilcoxon test). n, Effects of EZH2 knockdown on H3K27me3 occupancy at the HOXB1 gene promoter. H3K27me3 ChIP assay was performed in shEZH2- or non-target shRNA-expressing primary ovarian cancer cells. H3K27me3 levels at the gene promoter of HOXB1 were normalized to the input (mean ± s.e.m.; n = 5, *P < 0.05, Wilcoxon test).

Extended Data Figure 3 H3K27-specific methyltransferase and demethylase regulates TH1-type chemokine expression.

a, Effects of GSK126 treatment on H3K27me3. Primary ovarian cancer cells were treated with GSK126 (0, 0.05, 0.2, 0.5, 2 or 10 μM) for 48 h. H3K27me3 was detected by western blotting. One of three experiments is shown. b, c, Effects of GSK126 on EZH2 and IFNGR2 transcript expression. Primary ovarian cancer cells were pre-treated with GSK126 for 48 h and stimulated with IFNγ for an additional 24 h. EZH2 (b) and IFNGR2 (c) transcripts were quantified by real-time PCR. Results are expressed as the mean ± s.e.m. Results from three experiments with duplicates are shown. d, Effects of GSK126 on cell apoptosis. Primary ovarian cancer cells were treated with GSK126 and stained with propidium iodide and annexin V. The percentage of apoptotic cells (annexin V-positive) was quantified. Mean ± s.e.m. from three experiments with duplicates. eh, Effects of histone methyltransferase inhibitors on ovarian cancer TH1-type chemokine expression. Human primary ovarian cancer cells (OC17) (e), or ovarian cancer cell lines (ES-2, CAOV3 and A2780) (fh) were treated with GSK126 with or without IFNγ. CXCL9 and CXCL10 expression was measured by ELISA (e) or real-time PCR (fh) (mean ± s.e.m., n = 5, *P < 0.05, Wilcoxon test). i, Effects of ectopic JMJD3 on histone marks. Primary ovarian cancer cells were transiently transfected with plasmid encoding HA–JMJD3. Histone markers H3K9me2, H3K9me3 and H3K27me3 were detected by western blotting. One of three experiments is shown. j, Effect of ectopic expression of JMJD3 on CXCL10 transcript expression. Primary ovarian cancer cells were transiently transfected with vector or different amounts of HA–JMJD3 plasmids and stimulated with IFNγ. CXCL10 transcripts were quantified by real-time PCR. Results are expressed as the mean values ± s.e.m. Data represent three independent experiments. (n = 5, *P < 0.05, Wilcoxon test). k, l, Effects of ectopic JMJD3 on IFNGR2 (k) and HLA-B (l) gene expression. Primary ovarian cancer cells were transiently transfected with plasmid encoding HA–JMJD3 and stimulated with IFNγ. IFNGR2 and HLA-B transcripts were quantified by real-time PCR. Results are expressed as the mean ± s.e.m. Data represent three independent experiments. m, Effect of JMJD3 knockdown on IFNGR2 gene expression. Primary ovarian cancer cells were stably transduced with a lentiviral shRNA specific for JMJD3 (shJMJD3) or non-target shRNA (Ctl), and stimulated with IFNγ. IFNGR2 transcripts were quantified by real-time PCR. Results are expressed as the mean ± s.e.m. Data represent three independent experiments. n, Effects of GSK-J4 on histone marks. Primary ovarian cancer cells were treated with GSK-J4 (10 μM) for 48 h. H3K27me3, H3K4me1, H3K4me2 and H3K4me3 were detected by western blotting. One of three experiments is shown. o, Effects of GSK-J4 on IFNGR2 gene expression. Primary ovarian cancer cells were pre-treated with GSK-J4 (10 μM) for 48 h and stimulated with IFNγ for an additional 24 h. IFNGR2 transcripts were quantified by real-time PCR. Results are expressed as the mean ± s.e.m. Data represent three independent experiments.

Extended Data Figure 4 DNA methylation controls TH1-type chemokine expression.

a, b, Effects of 5-AZA-dC on TH1-type chemokine expression. Human ovarian cancer cell line (A2780) or primary ovarian cancer cells (OC17) were treated with 5-AZA-dC and IFNγ. CXCL9 and CXCL10 expression were quantified by real-time PCR (a) or ELISA (b) (mean ± s.e.m., n = 6, *P < 0.05, Wilcoxon test). cf, Effects of 5-AZA-dC on IFNγ associated gene expression. Primary ovarian cancer cells (OC8) were treated with 5-AZA-dC and IFNγ for 24 h. CXCL9 (c), CXCL10 (d), IRF1 (e) and IFNGR2 (f) transcripts were quantified by real-time PCR. Results are expressed as the mean ± s.e.m. One of three independent experiments is shown. g, DNMT1 knockdown via DNMT1 shRNA. Primary ovarian cancer cells (OC8) were transduced with a lentiviral shRNA specific for DNMT1 (shDNMT1) or non-target shRNA (Ctl). DNMT1 was detected by western blotting. h, Effect of DNMT1 knockdown on IFNGR2 expression. Primary ovarian cancer cells (OC8) were transduced with a lentiviral shRNA specific for DNMT1 (shDNMT1) or non-target shRNA (Ctl) and stimulated with IFNγ for 24 h. IFNGR2 transcripts were quantified by real-time PCR. Results are expressed as the mean ± s.e.m. Data represent three independent experiments. i, STAT1-binding site at CXC10 gene promoter. STAT1 ChIP-seq data set from ENCODE/SYDH (top panel). K562 cells were treated with IFNγ for 30 min or 6 h. Non-treated GM12878 cells were used as control (no IFNγ). Gene Expression Omnibus accession numbers: GSM935487, GSM935488 and GSM935612. STAT1 occupancy at CXCL10 promoter (−5,143 to −4,699 base pairs) is shown as the peaks. Middle panel, schematic diagram of CXCL10 gene locus. STAT1-binding site (TTCCCGGAA) was predicted by TFSEARCH, score = 100. STAT1 ChIP-seq peaks overlap with the predicted STAT1-binding site (indicated as vertical lines). Bottom, homologous STAT1-binding site at CXCL10 gene promoter (Ensemble Genomic alignment).

Extended Data Figure 5 EZH2/H3K27 and DNMT1 interaction affects clinical outcome.

a, b, Representative images of immunohistochemistry staining of EZH2 (a) and DNMT1 (b) in human ovarian cancer tissues. The levels of DNMT1 and EZH2 expression in the tumour were assessed by the H-score method. c, d, The association between EZH2 (c), DNMT1 (d) and patient DFS in high-grade serous ovarian cancer. The high and low levels of EZH2 and DNMT1 were determined by the median values (see Extended Data Table 1). e, Relative impact of EZH2, DNMT1 and CD8 on patient DFS in high-grade serous ovarian cancer. The time-dependent receiver operating characteristic (ROC) curve analysis was applied to evaluate the predictive accuracy of each marker for DFS. AUC, the area under the ROC curve; t = 60 months. f, Impact of the two parameters (EZH2 and DNMT1) on patient DFS. The analysis was performed on patients with high-grade serous ovarian cancer. Multiple comparisons were performed with log-rank tests. EZH2lowDNMT1low group (n = 49) versus EZH2highDNMT1high (n = 55) P < 0.00001. g, Representative images of immunohistochemistry staining of CD8 in human ovarian cancer specimen. Intratumoural CD8+ T cells were shown with anti-CD8+ staining. The numbers of intratumoural CD8+ T cells were quantified in high-power fields (40×) (see Methods and Extended Data Table 1). h, The relationship between intratumoural CD8+ T cells and patient DFS in high-grade serous ovarian cancer (see Methods and Extended Data Table 1). i, Schematic diagram depicting the relationship among epigenetic TH1-type chemokine silencing, effector T-cell trafficking, and tumour immunity, immunotherapy and patient outcome. M, methylation.

Extended Data Table 1 Patient characteristics and risk factors for overall survival and DFS
Extended Data Table 2 Risk factors for overall survival and DFS
Extended Data Table 3 The nested multivariate models of overall survival and DFS
Extended Data Table 4 The AUC values of ROCs (t = 60) for DNMT1, EZH2 and CD8
Extended Data Table 5 Sequences for ChIP, PCR primers and lentiviral shRNAs

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Peng, D., Kryczek, I., Nagarsheth, N. et al. Epigenetic silencing of TH1-type chemokines shapes tumour immunity and immunotherapy. Nature 527, 249–253 (2015). https://doi.org/10.1038/nature15520

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