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ILC2-driven innate immune checkpoint mechanism antagonizes NK cell antimetastatic function in the lung

Nature Immunology volume 21, pages 998–1009 (2020)Cite this article

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Abstract

Metastasis constitutes the primary cause of cancer-related deaths, with the lung being a commonly affected organ. We found that activation of lung-resident group 2 innate lymphoid cells (ILC2s) orchestrated suppression of natural killer (NK) cell-mediated innate antitumor immunity, leading to increased lung metastases and mortality. Using multiple models of lung metastasis, we show that interleukin (IL)-33-dependent ILC2 activation in the lung is involved centrally in promoting tumor burden. ILC2-driven innate type 2 inflammation is accompanied by profound local suppression of interferon-γ production and cytotoxic function of lung NK cells. ILC2-dependent suppression of NK cells is elaborated via an innate regulatory mechanism, which is reliant on IL-5-induced lung eosinophilia, ultimately limiting the metabolic fitness of NK cells. Therapeutic targeting of IL-33 or IL-5 reversed NK cell suppression and alleviated cancer burden. Thus, we reveal an important function of IL-33 and ILC2s in promoting tumor metastasis via their capacity to suppress innate type 1 immunity.

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Fig. 1: IL-33-driven activation of ILC2s is critical for promoting lung metastases.
Fig. 2: IL-33 does not promote early seeding of the lung by CTCs.
Fig. 3: IL-33 suppresses lung NK cell function.
Fig. 4: ILC2s mediate an innate immune checkpoint on lung NK cell function.
Fig. 5: ILC2-derived IL-5 promotes eosinophil-mediated suppression of lung NK cells.
Fig. 6: IL-33-induced suppression of lung NK cells is not transcriptionally regulated.
Fig. 7: Activated ILC2s suppress NK cells via an eosinophil-mediated metabolic mechanism.
Fig. 8: Therapeutic targeting of the ILC2–eosinophil axis restores NK cell-mediated tumor control.

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Data availability

The transcriptomic data used in Fig. 6 and Extended Data Fig. 7 are available at the SRA under the BioProject no. PRJNA637311: lung NK cell transcriptomic. Bulk RNA-seq data are available under BioSample accession nos. SAMN15099850 (bulk PBS versus IL-33; the sample names are A1, D1, B2, C2, F2, E1 and H1 for the PBS-treated condition and D2, B1, F1, E2, A2 and G1 for the IL-33-treated condition) and SAMN15099866 (time course) with the following triplicate sample names: E4, A4, C3 (WT PBS day 2); H3, F4, D3 (WT IL-33 day 2); C4, G4, A3 (WT IL-33 day 7); B4, E3, G3 (WT IL-33 day 14); and D4, F3, B3 (ILC2 knockout IL-33 day 2).

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Acknowledgements

We thank the following funding sources: EMBO long-term post-doctoral fellowship (no. ALTF 423-2017 to M.J.S.); MRC Skills Development Fellowship (no. MR/P014178/1 to A.C.R.); European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement (Pan-ILC no. 840501 to J.S.); Wallonie-Bruxelles International Grant of Excellence WBI.WORLD (SUB/2019/441873 to J.S.); the Royal Society and Wellcome Trust (no. 204622/Z/16/Z to T.Y.H.); Cancer Research UK (CRUK) core award (no. A24995 to T.Y.H.); and the CRUK Grand Challenge Rosetta Consortium (no. C197/A25040 to K.M.B., R.J.A.G., A.T. and G.H.). DESI–MSI optimization was supported by N. Strittmatter. We thank the CRUK Cambridge Institute Research Instrumentation, flow cytometry, genomics, bioinformatics, histopathology, imaging and BRU cores for their expertise and help.

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Authors and Affiliations

  1. CRUK Cambridge Institute, University of Cambridge, Cambridge, UK

    Martijn J. Schuijs, Shaun Png, Arianne C. Richard, Anastasia Tsyben, Julie Stockis, Celine Garcia, Silvain Pinaud, Ashley Nicholls, Jing Su, Matthew D. Eldridge, Eva M. Serrao, Kevin M. Brindle, John C. Marioni & Timotheus Y. F. Halim

  2. Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK

    Arianne C. Richard

  3. Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK

    Anastasia Tsyben

  4. Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK

    Gregory Hamm & Richard J. A. Goodwin

  5. Bioscience Asthma, Research and Early Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK

    Xavier Romero Ros & E. Suzanne Cohen

  6. MRC Cancer Unit, University of Cambridge, Cambridge, UK

    Angela Riedel & Jacqueline D. Shields

  7. Division of Cellular Immunology, German Cancer Research Center, Heidelberg, Germany

    Hans-Reimer Rodewald

  8. Department of Internal Medicine, University Hospital Regensburg, Regensburg, Germany

    Matthias Mack

  9. MRC Laboratory of Molecular Biology, Cambridge, UK

    Andrew N. J. McKenzie

  10. Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK

    Richard J. A. Goodwin

  11. Department of Biochemistry, University of Cambridge, Cambridge, UK

    Kevin M. Brindle

  12. EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK

    John C. Marioni

  13. Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK

    John C. Marioni

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  1. Martijn J. Schuijs
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  2. Shaun Png
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  23. Timotheus Y. F. Halim
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Contributions

M.J.S. designed and conducted the experiments and wrote the manuscript. S. Png, A.C.R., A.T., G.J.H., S. Pinaud, C.G., A.N., J. Stockis, J. Su, A.R. and E.M.S. assisted with the experiments or analysis. J.D.S., M.D.E., A.N.J.M., H.-R.R., M.M., G.J.H., X.R.R., E.S.C., R.J.A.G., K.M.B. and J.C.M. provided reagents and/or advice. T.Y.F.H. supervised the study, designed and conducted experiments and wrote the manuscript.

Corresponding author

Correspondence to Timotheus Y. F. Halim.

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Competing interests

G.H., X.R.R., R.J.A.G. and E.S.C. are employees of AstraZeneca and have stock/stock options in AstraZeneca.

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Extended data

Extended Data Fig. 1 Pre-existing innate type-2 inflammation promotes lung metastasis formation.

a, WT mice were treated as in (Fig. 1a) and tumor burden was assessed by histological staining for Ki67+ tumor foci and quantification of tumor area over total lung area by automated image analysis (n = 10). b, Il33cit/+ reporter mice were treated intranasally with PBS or IL-33 on days 0 and 1, and citrine+ lung cells were assessed on day 3. c, WT mice were treated intranasally with IL-33 on days 0 and 1 (or PBS injection for day 0), followed by quantification of total lung eosinophils by flow cytometry (see Extended Data Fig. 4a for gating strategy) at the indicated time-points (n = 3). d, WT mice were treated as indicated, followed by visual quantification of lung metastases on day 28 (n = 9). e, WT mice were treated as indicated, followed by visual quantification of lung metastases on day 21 (n = 6). f, WT mice were treated intranasally with LPS, CpG or PBS on days 0 and 1, followed by intravenous transfer of B16.F10 cells on day 7, and sacrifice on day 21, followed by visual quantification of lung metastases (n = 10). g, 4T1 (n = 10) or 4T1-T (n = 13,14,10) breast cancer cells were implanted in the mammary fat pad (see Methods), primary tumors were dissected and weighed. h, B6.MMTV-PyMT mice were randomized, treated intranasally with PBS, IL-33, or Asp (from week 12 to 20, see Methods), followed by measurement of total primary breast tumor(s) weight at 20 weeks of age (n = 10,10,11). i, Representative flow cytometry gating strategy of lung lymphocytes and innate lymphocyte populations from WT mice treated with PBS or IL-33 on day 0 and 1, followed by sacrifice on day 3 description of gated cells is listed above the dot plot, cell exclusion performed by Boolean-gating. j, WT mice were treated as in (c), followed by quantification of total lung ILC2 (Live CD45+CD3–B220–NK1.1–Lineage–CD127+RORγt–GATA3+) at the indicated time points (n = 3). k, WT and Il33–/– mice were treated with PBS or Asp on day 0 and 1, followed by quantification of total lung eosinophils at day 3 (n = 10,10,5,10). Bar graphs indicate mean (±SEM) and show combined data of two (d-f, k, g) or three (a, h), or representative of three independent experiments (b, c, i, j c). Statistical analyses were calculated using one-way ANOVA with **** = p ≤ 0.0001.

Extended Data Fig. 2 IL-33 influences lung NK cells.

a, WT mice were treated as indicated, followed by visual quantification of lung metastases on day 21. b, WT mice were treated with anti-IFNγ or controlmAb similar to (a); Tumor burden was assessed on day 21 by visual quantification of lung metastases (n = 10). c, Mice were treated intranasally with PBS or IL-33 on days 0 and 1, followed by quantification of total lung NK cells by flow cytometry on day 3 (n = 3). d, WT mice were treated as in (c), followed by flow cytometric detection of Ki-67+ lung NK cells and ILC2 (n = 5). e, Representative flow cytometry gating strategy of lung NK cells and T lymphocytes from WT mice treated with PBS or IL-33 on day 0 and 1, followed by sacrifice on day 3. f,g, WT mice were treated as in (c), followed by quantification of IFNγ+ NK cells (Live CD45+NK1.1+/lowCD49b+) after 3 hr stimulation of total lung cells with plate bound anti-NK1.1 (f) (n = 3); or PI (g) (n = 3). h, Total WT mouse lung cells were stimulated for 3hrs ex vivo with a combination of IL-12 and IL-18, followed by quantification of IFNγ+ positive NK cells (n = 10). i, WT mice were treated as in (c) and cardiac WAT NK cell were ana lyzed for intracellular IFNγ (n = 9,6) and GzmB (n = 9,6) after 3 hr stimulation with PI. j, Lung CD4 and CD8 T cells from PBS or IL-33 treated WT mice were analyzed for intracellular IFNγ after 3 hr stimulation with PI or anti-NK1.1 (representative gating shown in (e)). k, WT mice were treated as in (c), followed by lung NK cells purification and co-cultured with CFSE labelled whole lung homogenates from PBS or IL-33 treated WT mice (12 h), followed by 3 hr PI stimulation and detection of GzmB positive NK cells; grey bars indicate CFSE-labelled NK cells present in whole lung homogenates (n = 6,11,10,11,2,8 biologically independent samples). l-m, WT mice housed at the MRC ARES facility were treated as in (c), followed by quantification of percent of IFNγ+ NK cells (after 3hrs of PI) (l) (n = 5), or treated as in Fig. 1a (50 K B16.F10) followed by visual quantification of lung metastases (m) (n = 5). Bar graphs indicate mean (±SEM) and show combined data of two (b, i) or three (h, k) independent experiments. (e, j) show representative flow cytometry plots of three independent experiments, whereas (c, d, f, g, I, and m) show a representative bar graph of two independent experiments. Statistical analyses were calculated using one-way ANOVA or unpaired two-tailed Student’s t-test (c, f-i, l, m) **** = p ≤ 0.0001.

Extended Data Fig. 3 ILC2 suppress NK cells via an indirect innate immune mechanism.

a, Il7raCre/+ or Il7raCre/+Rorafl/fl mice were treated with PBS or Asp on day 0 and 1, followed by quantification of IFNγ+ lung NKcells on day 3 (n = 12,13,11,12). b,c, WT mice were treated as in (a), followed by purification of lung ILC2 (flow cytometry) and lung NK cells (magnetic bead, see Methods) on day 3. Lung NK were cultured alone or with ILC2 and analyzed for intracellular IFNγ and GzmB (c) (n = 8). d, WT mice were treated as in (e) with PBS or IL-33 and A2AR antagonist or DMSO followed by quantification of IFNγ+ lung NK cells on day 3 (n = 6,7,6). e, WT mice were treated as indicated, followed by quantification of GzmB+ lung NK cells (n = 3, representative gating on right). f, WT and Foxp3DTR mice were treated with PBS or IL-33 and DTx, followed by quantification of percent IFNγ+ lung NK cells on day 3 (n = 3,3,4,5). g, WT and Rag2–/– mice were treated with PBS or IL-33 on days 0 and 1, and given adoptive transfer of LL/2 cells (i.v.) on day 7. Tumor burden was assessed on day 21 by visual quantification of lung metastases (n = 10,8,8,10). h, WT, Rag2–/– and Rag2–/–Il7raCre/+Rorafl/fl mice were treated with PBS or IL-33 on day 0 and 1, followed by flow cytometry analysis for the indicated lung lymphoid cells on day 3 (n = 5). Bar graphs indicate mean (±S EM) and show combined data of two (c, d, and g) or three (a) independent experiments. (e, f, and h) shows a representative bar graph of two independent experiments. Statistical analyses were calculated using one-way ANOVA with ns = not significant, and **** = p ≤ 0.0001.

Extended Data Fig. 4 Myeloid cell profiling after IL-33 administration and correlation with NK cell function.

a,b, WT mice were treated with PBS or IL-33 on day 0 and 1, followed by (a) flow cytometry analysis and (b) quantification for the indicated lung myeloid cellson day 3 (n = 6). c, Representative flow cytometry plot of eosinophils from mice injected and gated as in (a) assessed for expression of Ly-6G (left) Ly-6C (right). d, The correlation between percent IFNγ+ NK cells and total numbers of the indicated myeloid cells in the lung of PBS or IL-33 injected WT mice (day 0 and 1, sacrificed on day 3) was analyzed on pooled results (n = 125). Bar graphs indicate mean (±SEM) and show representative data from three independent experiments (a, b, and c) and (d) representing Pearson r.

Extended Data Fig. 5 IL-33-mediated suppression of NK cells is not dependent on neutrophils or alveolar macrophages.

a-e, WT mice were treated with PBS or IL-33 on day 0 and 1, and the indicated mAb (or clodronate liposomes, C.L.) on day -1 and 1 followed by quantification of percent IFNγ+ or GzmB+ lung NK cells (after PI stimulation) and quantification for the indicated lung myeloid cells on day 3 (a; GzmB n = 10,9,9,10, and depicted myeloid cells n = 15 ,14,14,15, b; n = 8,8,8,9, c; n = 7, d,e, n = 6). Bar graphs indicate mean (±S EM) and show combined data of two (b-e) or three (a) independent experiments. Statistical analyses were calculated using one-way ANOVA with ns = not significant, and **** = p ≤ 0.0001.

Extended Data Fig. 6 IL-5 and eosinophils mediate IL-33-driven suppression of NK cells.

a, WT mice were treated with PBS or IL-33 on day 0 and 1, followed by quantification of IL-5+ ILC2 (CD45+B220–Lineage–), or CD45+B220–lineage+ cells in the lungs on day 3 (n = 5); the identity of IL-5+ ILC2 was further confirmed by ICOS expression. b-d, WT mice were treated with PBS or IL-33 on day 0 and 1, and anti-IL-5 or control on day -6, -3 and -1 followed by quantification of the total numbers of the indicated myeloid cells in the lung (c) (n = 10), and the percent IFNγ+ and GzmB+ lung NK cells (after anti-NK1.1 stimulation) on day 3 (d) (n = 5). e, WT mice were treated intranasally with PBS or the indicated cytokines on day 0 and 1, followed by quantification of percent IFNγ+ NK cells (after PI stimulation), or lung eosinophil numbers on day 3 (n = 3). f, Mice of the indicated genotypes were treated intranasally Asp or PBS on days 0 and 1, followed by intravenous transfer of B16.F10 cells on day 7 and subsequent determination of lung metastases-related mortality by Kaplan-Meier survival curve (n = 15,14,15,9). g, Purified WT mouse lung NK cells were cultured alone or with ex vivo bone marrow derived eosinophils at the indicated ratios for 18 hours, followed by a 3 hr re-stimulation with PI and quantification of IFNγ+ and GzmB+ NK cells by flow cytometry (n = 6,6,9). Bar graphs indicate mean (±SEM) of combined data of two (c, g) or three (f) independent experiments. (d and e) show representative data of three independently performed experiments and (a) depicts representative flow cytometry plots. Statistical analyses were calculated using one-way ANOVA or Log-rank (Mantel-Cox) test (f) with **** = p ≤ 0.0001.

Extended Data Fig. 7 Single-cell and bulk-RNA-seq of naive and IL-33-inflammed lung NK cells.

a, Mice were treated with PBS or IL-33 on day 0 and 1, followed by FACS purification of lung NK cells at the indicated time-points for either scRNA-seq or bulk-RNA-seq analysis. b, Post FACS purity was assessed for all sorts. c, Clusters from (Fig. 6a) were annotated based on their gene expression patterns. Heatmap of genes significantly (FDR < 0.05) upregulated or downregulated in one cluster versusall others. Where more than 15 genes were significantly differentially expressed, only the 15 with the greatest average log-fold changes in each direction were included. Blue-to-yellow color gradient indicates log2 (normalized gene expression). d, scRNA-seq expression of Cd27 and Itgam (encoding CD11b) separated by cluster. Specific clusters were annotated as follows (where individual genes were significantly upregulated in one cluster compared to all others, the 5 with greate st average log-fold-change are listed as marker genes): Cluster 2: signaling/inflammatory-chemokine-expressing NK cells (Pim1, Nfkbia, Gadd45b, Ccl4, Icam1); Cluster 3: (Kcnj8, Ly6c2); Cluster 4: (Hsp90ab1, Hspe1, Nme1, Ptma, Rps2); Cluster 6: (Ccl5, Cma1, Klrg1, Itm2b); Cluster 7: immature NK cells (Ctla2a, Emb, Ccr2, Rps15a, Rpl10a). Cluster 2 was most similar to the previously identified splenic murine NK cell cluster 3, and Cluster 7 was most similar to the previously identified splenic and blood murine NK cell cluster 2 as identified by Crinier et al.32. e, Results of a differential abundance analysis comparing the abundance of cells in each cluster after IL-33 versus PBS treatment. P-values were calculated using empirical Bayes quasi-likelihood F-tests in a negative binomial GLM (as described in Methods). f,g, Expression of NK cell consensus32, effector, and both activating and inhibitory receptor transcripts from bulk-RNA-seq analysis of sorted lung NK cells. Data are represented as a heatmap of log2-transformed normalized read counts of individual genes, grouped by category (f), or z-scaled expression values for genes within the 4 gene lists. Each point represents the expression value obtained by one replicate for a given gene at a given time point (g). Box plots represent mean (black line), first and third quartiles (box) and range within 1.5 times the interquartile range from the box (whiskers). Violin plots represent median (black line), interquartile ranges (box) and a kernel density plot.

Extended Data Fig. 8 IL-33 increases glucose flux in the lung environment via ILC2 and IL-5.

a, BALB/c mice were treated intranasally with IL-33 or PBS on days 0 and 1, and anti-IL-5 or control antibody (i.p.) on day -6, -3, and 0 and sacrificed on day 3. Lung homogenates were cultured for 18 hours and glucose (Glu) and lactate (Lac) concentrations were measured in the supernatant by NMR analysis (n = 10,9,9). b, Spatial resolving glycolytic activity in lung by MSI. WT or Il7raCre/+Rorafl/fl (KO) mice were dosed with PBS or IL-33 on day 0 and 1, and sacrificed on day 3 and infused or not with [U-13C] glucose (as described in Methods). (Right to left) H&E stained lungs and post DESI-MSI molecular images of lactate, [U-13C] lactate, glucose, [U-13C] glucose, normal and [U-13C] lactate to glucose ratio (pixel per pixel). Intensity scale is fixed for each molecular species independently, and monochromatic lighter colors correspond to higher relative abundance. c, d, Bar graphs indicate mean relative abundances of [U-13C] glucose or [U-13C] lactate (c) (n = 4), or the ratio of [U-12C] lactate over glucose (d) (n = 4). e, BALB/c were treated intranasally with Asp or PBS on days 0 and 1, and anti-IL-5 or control antibody (i.p.) on day -6, -3, 0 and 3, followed by injected with 4T1-T breast cancer cells in the mammary fat pad on day 7, and sacrifice on day 21. f, Tumor burden of mice treated as in (e) with 4T1-T cells was quantified by visual examination and primary tumor weight was recorded (n = 9,10,9). g, Graphical abstract. Bar graphs indicate mean (±SEM) of combined data of two (a, c, d, and f) independent experiments. (b) depicts representative MSI images of two independent experiments. Statistical analyses were calculated using one-way ANOVA with **** = p ≤ 0.0001.

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Schuijs, M.J., Png, S., Richard, A.C. et al. ILC2-driven innate immune checkpoint mechanism antagonizes NK cell antimetastatic function in the lung. Nat Immunol 21, 998–1009 (2020). https://doi.org/10.1038/s41590-020-0745-y

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