Abstract
High-grade serous ovarian cancers have low survival rates because of their late presentation with extensive peritoneal metastases and frequent chemoresistance1, and require new treatments guided by novel insights into pathogenesis. Here we describe the intrinsic tumour-suppressive activities of interferon-ε (IFNε). IFNε is constitutively expressed in epithelial cells of the fallopian tube, the cell of origin of high-grade serous ovarian cancers, and is then lost during development of these tumours. We characterize its anti-tumour activity in several preclinical models: ovarian cancer patient-derived xenografts, orthotopic and disseminated syngeneic models, and tumour cell lines with or without mutations in Trp53 and Brca genes. We use manipulation of the IFNε receptor IFNAR1 in different cell compartments, differential exposure status to IFNε and global measures of IFN signalling to show that the mechanism of the anti-tumour activity of IFNε involves direct action on tumour cells and, crucially, activation of anti-tumour immunity. IFNε activated anti-tumour T and natural killer cells and prevented the accumulation and activation of myeloid-derived suppressor cells and regulatory T cells. Thus, we demonstrate that IFNε is an intrinsic tumour suppressor in the female reproductive tract whose activities in models of established and advanced ovarian cancer, distinct from other type I IFNs, are compelling indications of potential new therapeutic approaches for ovarian cancer.
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Data availability
Gene expression data were uploaded to GEO with SuperSeries accession number GSE201525. For the ID8 microarrays, raw and processed expression data were deposited with SubSeries accession number GSE201345. For the RNA-seq, the original multiplexed R1 and R2 FASTQ files were de-multiplexed using cutadapt57 (v3.0 with error rate 1 and action none) and uploaded to GEO, along with UMI counts generated by scPipe, with SubSeries accession numbers GSE201337 (PDX RNA-seq) and GSE215261 (Ifnar1−/− ID8 RNA-seq). Source data are provided with this paper.
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Acknowledgements
This work was supported by project grants from the National Health and Medical Research Council of Australia (NHMRC) to P.J.H., M.D.T., D.D.L.B. and the Stafford Fox Medical Research Foundation to C.L.S. This work was supported from the Operational Infrastructure Fund of the State Government of Victoria. Z.R.C.M. was supported by an Australian Postgraduate Award; M.B. and A.N.S. are supported by the Ovarian Cancer Foundation of Australia; N.E.M. was supported by a Fielding Foundation Fellowship; P.J.H. was supported by NHMRC Senior Principal Research fellowship and B.S.P. and C.L.S. were supported by Victorian Cancer Agency fellowship. The authors acknowledge E. M. Swisher, for BROCA sequencing of PDX; S. Stoev, R. Hancock and K. Barber for technical assistance with the PDX studies; use of the services and facilities at the Monash Histology Platform, MHTP FlowCore, medical genomics and animal services and Micromon Genomics at Monash University; and R. Smith for assistance with preparation of the manuscript. This work was also supported by the US Office of the Assistant Secretary of Defense for Health Affairs through the Ovarian Cancer Research Program under award no. W81XWH-15-1-0106. Opinions, interpretations, conclusions and recommendations are those of the author and are not necessarily endorsed by the US Department of Defense. In conducting research using animals, the investigators adhered to the laws of Australia, the USA and regulations of the US Department of Agriculture, and received ethical approval for this research from the Animal Ethics Committees of Monash University and the Walter and Eliza Hall Institute of Medical Research. In conducting research using human tissues, the investigators adhered to the laws of Australia and received ethical approval for this research from the Walter and Eliza Hall Institute of Medical Research Human Research Ethics Committee.
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Z.R.C.M. and N.K.C. were involved in performing mouse model experiments, analysis of endpoints, immunophenotyping, in vitro tumour growth assays, conceptualization, interpretation and write up of the work and editing the manuscript. N.E.M. was involved in assays of immune effects of IFNε, conceptualization and interpretation of data. C.J.V. and G.-Y.H. performed xenograft models, planned and interpreted data. L.J.G. performed bioinformatics analysis of RNA-seq and microarrays and contributed to editing the manuscript. A.Y.M., S.S.L. and N.A.d.W. produced, purified and assayed recombinant IFNs. J.A.G. performed microarray and RNA-seq experiments and analysis. M.D.T., G.W.-M., L.Y., S.R. and E.d.G. provided technical assistance and contributed to planning and analysis of animal models. N.B. and B.S.P. analysed tumour responses by IHC and analysed results. E.L.C. and M.J.W. performed genetic and bioinformatic analysis and tumour genomic data curation. M.B. and A.N.S. provided cell lines and advised and planned tumour growth experiments. O.M. and Australian Ovarian Cancer Study provided patient and tumour data, curated the databases and contributed to interpretation of data. I.A.M. provided ID8 tumour models and advised on planning and interpretation of results. D.D.L.B. advised on strategy and planning of tumour experiments and genomic data analysis. C.L.S. provided human tumour samples and associated data, performed xenografts, planned experiments and interpreted results. N.M.B. and P.J.H. performed conceptualization, methodology, formal analysis, investigation, contribution to original manuscript draft, review and editing the manuscript, supervision and acquisition of funding. All authors had input into review or editing the manuscript.
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The authors P.J.H., Z.R.C.M., N.B., S.S.L., N.A.d.W., N.E.M. and A.Y.M. are listed as inventors on the patent PCT/AU2018/050054 regarding use of IFNε as a method of treatment for cancer.
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Extended data figures and tables
Extended Data Fig. 1 Suppression of epithelial IFNε in high-grade serous ovarian cancer and IFNε effects on “primary” orthotopic tumour tissue in the ID8 model of ovarian cancer.
(a) mRNA expression (mean ± interquartile range) of IFNε in the CSIOVDB cohort13. Significance was determined by Mann-Whitney U tests compared to healthy Fallopian tube epithelium (FTE). Doubling times of (b) CaOV3 and (c) OVCAR4 cell cultures treated with 1–1,000 IU/ml of IFNε for 48 h. Cell proliferation was measured using xCELLigence. Data is presented as mean ± SD of n = 3 independent experiments performed in technical quadruplicates. Significance was determined by one-way ANOVA with Dunnett’s multiple comparisons test. (d–i) ID8 cells were implanted into C57BL/6J mice via intrabursal injection of the left ovary to form orthotopic ovarian tumours and peritoneal metastases. (d) Images show excised ovaries and uterine horn of mice treated with PBS or IFNε (500 IU per dose); (e) weights of orthotopic tumour-bearing ovaries from mice treated with PBS or IFNε (50 or 500 IU per dose) (“developing” model) and mice that commenced treatment with IFNε or IFNβ (500 IU per dose) 4 weeks post-implantation (“established” model). Data is presented as mean ± SD of individual mice, n = 6 mice per group. (f–i) Multiplex IHC staining of IRF9 (f,g) and CD3 (h,i) expression in “primary” ID8 ovarian tumors derived from vehicle- or IFNε-treated mice (500 IU per dose) as shown for 2 mice per group as representative of n = 5. Data shown are means ± SD of individual data points. Significance was determined by unpaired two-tailed t-test. Scale bars = 200 μm. ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05.
Extended Data Fig. 2 Disease scores and immunophenotyping of peritoneal cells in orthotopic and disseminated models of ovarian cancer.
Ascites volume and peritoneal haemorrhaging (RBC count within peritoneal fluid) were measured in the “developing”, “established” (a,c), and “advanced” (b,d) models of ovarian cancer, as described in Fig. 2 and the Methods. Data are presented as means ± SD of individual mice: in both “developing” and “established” models n = 6 mice per treatment, in the “advanced” model n = 5 mice per IFN treatment and n = 3 mice treated with PBS. Significance was determined by Kruskal-Wallis test with Dunn’s multiple comparisons test (a,c), or one-way ANOVA with Dunnett’s multiple comparisons test (b,d). The numbers of immune cells in peritoneal lavage fluid from mice with (e) “developing” or “established” orthotopic tumours, and (f) “advanced” disseminated tumours were determined by flow cytometry. Data shown are means of immune cell counts measured for each treatment group and presented in stacked bar graphs. Significance was determined by two-way ANOVA with Tukey’s multiple comparisons test. IFN-driven immune cell activation in orthotopic ovarian tumour models demonstrated by (g) PD1 levels on CD4+ T cells and CD69 expression on (h) CD4+ T cells, (i) CD8+ T cells and (j) NK cells, as detected by flow cytometry. Data are presented as means ± SD of individual data points, in both “developing” and “established” models n = 6 mice per group. Significance was determined by one-way ANOVA with Dunnett’s multiple comparisons test. ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05. NT: non-tumour bearing; RBC: red blood cells.
Extended Data Fig. 3 Mechanisms of intrinsic anti-tumour activities of IFNε in vitro.
(a) CD107a expression was measured as a marker of degranulation on NK cells from in vivo primed PECs co-cultured with ID8 cells. Data is presented as mean ± SD of individual mice (n = 3 per group). Significance was determined by unpaired two-tailed t-test. (b) Plots show induction of apoptosis (Annexin V-FITC/PI staining) in ID8 cells treated with IFNε or PBS, as measured by flow cytometry. Data presented as representative plots from n = 6 independent experiments. (c) Plots show inhibition of proliferation of ID8 cells treated with 100 or 1,000 IU/ml of IFNε (top panel) or IFNβ (bottom panel) for 48 h. Cell proliferation was measured by xCELLigence and is representative of n = 3 independent experiments. (d) Heat maps of log2 fold changes comparing IFN-treated ID8 cells to untreated controls, showing differentially expressed genes associated with cell cycle and apoptosis or cell death gene sets from the Molecular Signatures Database (scale truncated to ± 5). Expression data is derived from n = 3 independent experiments, performed in technical triplicate. (e) Images show examples of characteristic nodule formation throughout the mesentery (dotted lines) and adhered to the peritoneal wall (black arrows) of WT and Ifnar1−/− mice with disseminated tumour treated with PBS or IFNε. (f) Stacked bar graph summarising the number of immune cells present in peritoneal lavage fluid from WT and Ifnar1−/− mice as described in Fig. 3. Data shown are means of immune cell counts measured for each treatment group and genotype. Significance was determined by two-way ANOVA with Tukey’s multiple comparisons test, n = 6 mice per IFNε treatment group, n = 5 WT mice treated with PBS, n = 8 Ifnar1−/− mice treated with PBS. ***p < 0.001, *p < 0.05. NT: non-tumour bearing.
Extended Data Fig. 4 Effect of huIFNε, huIFNβ and muIFNε in PDX models of HGSOC.
Two PDX models of HGSOC were performed using tumours obtained from two different patients, as described in the Methods. PDX #111 demonstrated induction of ISGs with huIFNε treatment and was designated a “responder” to IFNε. (a) Total number of metastatic deposits found in the peritoneal cavity in mice bearing “responder” PDX #111 tumours, treated with either PBS or equivalent IU of huIFNβ, huIFNε or muIFNε. Data is presented as mean ± SD of individual mice. Significance was determined by Mann-Whitney U test. (b,c) Plots of log2 fold changes of significantly differentially expressed genes in tumour cells from (b) huIFNε vs huIFNβ and (c) huIFNε vs muIFNε treated mice, highlighting significantly differentially up- and down-regulated genes with huIFNε treatment (red and blue respectively). (d) Heat map of RNA-seq analysis of mice bearing tumours from “responder” PDX #111 and “non-responder” PDX #183, showing all genes identified from the Reactome IFN alpha/beta signalling gene set. Genes in bold were significantly induced by huIFNε in the “responder” PDX and also had significantly higher basal levels in the “non-responder” PDX (scale truncated to ± 6). For PDX #111, n = 6 mice per treatment group. For PDX #183, n = 7 mice treated with PBS or huIFNβ, n = 6 mice treated with huIFNε or muIFNε.
Extended Data Fig. 5 Effect of IFNε in the human oncogene mutated ID8TB model of advanced ovarian cancer.
(a–d) ID8TB cells were implanted via intraperitoneal injection and administered muIFNε therapy (100–1,000 IU/dose), as described previously. Quantitation of (a) the total number of peritoneal metastases, (b) mesentery tumour burden, (c) volume of ascites fluid, and (d) peritoneal haemorrhage score. Data are expressed as means ± SD of individual mice. Significance was determined by Kruskal-Wallis test with Dunn’s multiple comparisons test. (e–o) ID8TB cells were implanted via intraperitoneal injection and administered muIFNε therapy (500 IU/dose), as described previously. Quantitation of (e) the total number of peritoneal metastases, (f) mesentery tumour burden, (g) volume of ascites fluid, and (h) degree of peritoneal haemorrhaging (RBC count within peritoneal lavage fluid). The numbers of peritoneal lavage (i) lymphocytes (CD4+ T cells, CD8+ T cells, Tregs and NK cells) and (j) myeloid cells (MDSC, neutrophils, monocytes and dendritic cells) were detected by flow cytometry. Data shown are means of immune cell counts measured for each treatment group, presented in stacked bar graphs. Significance was determined by two-way ANOVA with Tukey’s multiple comparisons test. IFNε-driven immune cell activation in peritoneal lymphocytes demonstrated by CD69 expression on (k) NK cells, (l) CD4+ T cells, and (m) CD8+ T cells, or PD1 expression on (n) CD4+ and (o) CD8+ T cells, as detected by flow cytometry. Data are expressed as means ± SD of individual mice. Significance was determined by unpaired two-tailed t-test. For a–d, n = 5 mice in the NT group, n = 10 mice in all other groups. For e–o, n = 9 mice treated with PBS, n = 8 mice treated with IFNε. ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05. RBC: red blood cell; Treg: T regulatory cell; DC: dendritic cell; NT: non-tumour bearing.
Extended Data Fig. 6 Validation of Ifnar1−/− ID8TB cells.
(a) Tracking of Indels by Decomposition (TIDE) analysis of the 1CF10 Ifnar1−/− cell clone (green lines) versus empty vector (EV) transfected control ID8TB cells (black lines), demonstrating increased sequence discordance around and following the expected cut site. (b) Inference of CRISPR Edits (ICE) analysis depicting a single ‘G’ base insertion at base 56 in the edited sample (1CF10) compared to the control (EV) sample. This insertion is anticipated to produce a frame-shift error and consequent introduction of an early stop codon. (c) Histograms depict surface IFNAR1 staining in WT and 1CF10 cells stained with anti-IFNAR1, and WT cells stained with an isotype control antibody. The MFI values for IFNAR1/IgG in each sample are listed to the right of the histogram. (d-e) EV and 1CF10 cells were treated in technical triplicate in vitro with 10,000 IU/ml muIFNβ or left untreated (UT). Gene expression was measured by RNA-seq: (d) heat map depicts significant differences in Hallmark gene sets between UT EV and 1CF10 cells (basal gene expression) and between UT and IFNβ stimulated EV and 1CF10 cells (IFN response). Heat map colour shows the average log2 fold change of genes in each gene set (scale truncated to ± 2); individual p values are presented on the figure. (e) Heat map depicting log2 expression of all genes identified from the Hallmark IFN alpha response gene set, relative to EV UT controls (scale truncated to ± 6). Genes in bold were significantly induced by IFNβ in the EV cellls and also had significantly lower basal levels in the UT 1CF10 cells (f) Proliferation of EV and 1CF10 cells treated with muIFNε or muIFNβ, expressed as percentage CFSE MFI of vehicle control-treated cells, with increased % CFSE MFI indicative of inhibition of cell proliferation. Data depicts mean ± SD of n = 4 independent experiments. Significance was determined by two-way ANOVA with Dunnett’s multiple comparisons test; p values for relevant comparisons depicted.
Extended Data Fig. 7 Immunophenotyping of Ifnar1−/− ID8TB model of advanced ovarian cancer.
WT or Ifnar1−/− ID8TB cells were implanted i.p. prior to commencing muIFNε treatment. (a) The numbers of peritoneal lavage myeloid cells (MDSC, neutrophils, monocytes, dendritic cells, large peritoneal macrophages (LPM), small peritoneal macrophages (SPM), F480loMHCII− cells and SiglecF+ cells) were detected by flow cytometry. (b) The numbers of peritoneal lavage lymphocytes (CD4+ T cells, CD8+ T cells, Tregs, B cells and NK cells) were detected by flow cytometry. Data shown for a & b are means of immune cell counts measured for each treatment group, presented in stacked bar graphs. (c) Pearson correlation matrix of all disease scores and measurements of peritoneal immune cell numbers, proliferation and activation by flow cytometry.
Extended Data Fig. 8 Summary of the mechanism of anti-tumour actions of IFNε.
Wild type (WT) tumours grow in WT mice treated with PBS (i); but tumours shrink when treated with IFNε (ii); with unresponsive Ifnar1−/− mouse immune cells (iii), tumours shrink partially due to the direct actions of IFNε on the responsive tumour cells (1), but inhibition is less than in model (ii); with unresponsive Ifnar1−/− tumour cells (iv), IFNε activates immune cells (2) to kill tumour cells to a greater degree than model (iii) and similar to the inhibition in model (ii). IFNε-treated tumour cells can produce non-IFN signals to immune cells (3) which influence tumour growth in scenarios (ii) and (iii). Created with Biorender.com.
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Marks, Z.R.C., Campbell, N.K., Mangan, N.E. et al. Interferon-ε is a tumour suppressor and restricts ovarian cancer. Nature 620, 1063–1070 (2023). https://doi.org/10.1038/s41586-023-06421-w
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DOI: https://doi.org/10.1038/s41586-023-06421-w
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