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Tumor immunoevasion by the conversion of effector NK cells into type 1 innate lymphoid cells

Nature Immunology volume 18, pages 1004–1015 (2017)Cite this article

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An Author Correction to this article was published on 21 March 2024

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Abstract

Avoiding destruction by immune cells is a hallmark of cancer, yet how tumors ultimately evade control by natural killer (NK) cells remains incompletely defined. Using global transcriptomic and flow-cytometry analyses and genetically engineered mouse models, we identified the cytokine-TGF-β-signaling-dependent conversion of NK cells (CD49a−CD49b+Eomes+) into intermediate type 1 innate lymphoid cell (intILC1) (CD49a+CD49b+Eomes+) populations and ILC1 (CD49a+CD49b−Eomesint) populations in the tumor microenvironment. Strikingly, intILC1s and ILC1s were unable to control local tumor growth and metastasis, whereas NK cells favored tumor immunosurveillance. Experiments with an antibody that neutralizes the cytokine TNF suggested that escape from the innate immune system was partially mediated by TNF-producing ILC1s. Our findings provide new insight into the plasticity of group 1 ILCs in the tumor microenvironment and suggest that the TGF-β-driven conversion of NK cells into ILC1s is a previously unknown mechanism by which tumors escape surveillance by the innate immune system.

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Figure 1: Three distinct populations of group 1 ILCs infiltrate MCA1956 tumors.
Figure 2: The conversion of NK cells into ILC1-like cells is dependent on TGF-β signaling.
Figure 3: intILC1s have the greatest proliferative capacity among group 1 ILC subsets in vivo.
Figure 4: TGF-β induces the conversion of NK cells into intILC1s in the tumor microenvironment.
Figure 5: TGF-β signaling limits tumor immunosurveillance by converting tumor NK cells into intILC1s and ILC1s.
Figure 6: TGF-β signaling abolishes control of metastasis by the innate immune system.
Figure 7: Functional differences among tumor group 1 ILC subsets.
Figure 8: IFN-γ and TNF control tumor growth and metastasis differentially.

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Acknowledgements

We thank R. Schreiber (Washington University School of Medicine) for MCA1956 fibrosarcoma cells and anti-IFN-γ and anti-TNF hybridomas; the animal house and flow cytometry facilities at QIMR Berghofer Medical Research Institute and Walter and Eliza Hall Institute of Medical Research; E. Loza, K. Elder, L. Town, L. Spencer, T. Camilleri and T. Kratina, for mouse breeding, maintenance and genotyping; and K. MacDonald, D. Smith, A. Kallies, L. Beattie, R. Allan, G. Hill and S. Nutt for discussion, comments and advice on this project. Supported by the National Health and Medical Research Council of Australia (Senior Principal Research Fellowship 1078671 to M.J.S.; Peter Doherty Early Career Fellowship 1088703 to F.S.-F.-G. and 1124690 to T.B.; project grant 1027472 to G.T.B.; Elizabeth Blackburn NHMRC Fellowship to G.T.B.; Independent Research Institute Infrastructure Support scheme grant to G.T.B.; project grants 1066770 & 1057852 N.D.H.; and RD Wright Career development Fellowship 1112113 to N.W.), the Cancer Research Institute Clinical and Laboratory Integration Programs (M.J.S. and N.D.H.), Queensland Institute of Medical Research Berghofer International PhD Scholarship (Y.G. and J.Y.), University of Queensland International Scholarship (Y.G. and J.Y.), the National Breast Cancer Foundation (PF-15-008 to F.S.-F.-G.), Cure Cancer Australia (Priority-Driven Young Investigator Project Grant 1082709 and 1120725 to F.S.-F.-G.), European Molecular Biology Organization (long-term fellowship ALTF 945-2015 to T.B.), the Naito Foundation (K.N.), Cancer Council Queensland (PhD fellowship to A.Y.), Griffith University (PhD scholarships to S.S.N.), Inserm-Avenir-Grant (L.B.), Ligue Nationale Contre le Cancer (L.B.), Fondation ARC Pour la Recherche sur le Cancer (L.B.), the Victorian State Government Operational Infrastructure Scheme (G.T.B.), the Harry J Lloyd Charitable Trust (Melanoma Research Grant to N.D.H.) and the DFG Excellence Cluster Immunosensation (EXC 1023 to M.H.).

Author information

Author notes

  1. Yulong Gao and Fernando Souza-Fonseca-Guimaraes: These authors contributed equally to this work.

Authors and Affiliations

  1. Immunology in Cancer and Infection, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia

    Yulong Gao, Fernando Souza-Fonseca-Guimaraes, Tobias Bald, Arabella Young, Shin Foong Ngiow, Kyohei Nakamura & Mark J Smyth

  2. School of Medicine, The University of Queensland, Herston, Queensland, Australia

    Yulong Gao, Arabella Young, Juming Yan, Michele W L Teng & Mark J Smyth

  3. Molecular Immunology Division, Department of Medical Biology and The University of Melbourne, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia

    Fernando Souza-Fonseca-Guimaraes, Jai Rautela, Gabrielle T Belz & Nicholas D Huntington

  4. Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia

    Fernando Souza-Fonseca-Guimaraes

  5. Immunology and Infection, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia

    Susanna S Ng & Christian R Engwerda

  6. School of Natural Sciences, Griffith University, Nathan, Queensland, Australia

    Susanna S Ng

  7. Medical Genomics, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia

    Jasmin Straube & Nic Waddell

  8. Cancer Immunoregulation and Immunotherapy, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia

    Stephen J Blake, Juming Yan & Michele W L Teng

  9. Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Centre Léon Bérard, Centre de recherche en cancérologie de Lyon, Lyon, France

    Laurent Bartholin

  10. Control of Gene Expression Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia

    Jason S Lee

  11. Centre d'Immunologie de Marseille-Luminy, Aix Marseille Université, INSERM, CNRS, Marseille, France

    Eric Vivier

  12. Division of Cell Biology, Biomedical Research Center and Department of Biofunctional Microbiota, Graduate School of Medicine, Juntendo University, Bunkyo-ku, Tokyo, Japan

    Kazuyoshi Takeda

  13. INSERM U1015, Gustave Roussy Cancer Campus, Villejuif, France

    Meriem Messaoudene

  14. Gustave Roussy Cancer Campus, Villejuif, France

    Meriem Messaoudene & Laurence Zitvogel

  15. University Paris-Saclay, Kremlin Bicêtre, Paris, France

    Laurence Zitvogel

  16. CIC1428, Gustave Roussy Cancer Campus, Villejuif, France

    Laurence Zitvogel

  17. Department of Clinical Chemistry and Clinical Pharmacology, Unit for RNA Biology, University of Bonn, Bonn, Germany

    Michael Hölzel

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  1. Yulong Gao
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Contributions

Y.G., F.S.-F.-G., T.B., N.D.H., K.N. and M.J.S. designed research, supervised work and wrote the paper; Y.G., F.S.-F.-G., T.B., A.Y., S.F.N., J.R., S.J.B., J.Y., J.S.L., M.M., L.Z., N.D.H., K.N. and M.J.S. performed research; Y.G., F.S.-F.-G., T.B., S.S.N., A.Y., S.F.N., J.R., J.S., N.W., S.J.B., J.Y., M.M., L.Z., M.W.L.T., G.T.B., C.R.E., N.D.H., K.N., M.H. and M.J.S. analyzed data; and L.B., E.V., K.T. and G.T.B. provided experimental materials.

Competing Interests StatementM.J.S. has research agreements with Bristol-Myers Squibb, Corvus Pharmaceuticals and Aduro Biotech; E.V. is a cofounder and shareholder in Innate Pharma; and N.D.H. and J.R. are cofounders and shareholders in oNKo-Innate.

Corresponding author

Correspondence to Mark J Smyth.

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Competing interests

M.J.S. has research agreements with Bristol-Myers Squibb, Corvus Pharmaceuticals and Aduro Biotech; E.V. is a cofounder and shareholder in Innate Pharma; and N.D.H. and J.R. are cofounders and shareholders in oNKo-Innate.

Integrated supplementary information

Supplementary Figure 1 Similarities among group 1 ILC subsets from tumor, liver and spleen.

(a) Representative flow cytometric plots illustrating the gating strategy for sorting of group 1 ILC subsets from MCA1956 tumors for transcriptomic analyses. (b) Representative flow cytometric plots illustrating post-sorting purity of tumor NK cells, intILC1s and ILC1s. (c) Heatmap visualizing gene expression profiles from NK cells and ILC1s isolated from liver/spleen (GSE52047) clustered by tumor NK cell and ILC1 gene signatures. (d) Quantification of gene signature expression by combined z-scores. Horizontal bars, median; boxes, 25th to 75th quartile; ‘whiskers’, 10th and 90th quartile. Statistical analysis by pairwise two-sided t-tests with Benjamini & Hochberg (FDR) correction for multiple testing. **P < 0.01, ****P < 0.0001; ns, non-significant. Sp: spleen; Liv: liver.

Supplementary Figure 2 TGF-b promotes NK cell conversion both in vitro and in vivo.

(a) Flow cytometric characterization of group 1 ILC composition based on CD49a and CD49b expression in livers and spleens of indicated transgenic mice. (b) Liver group 1 ILC composition as determined by flow cytometry based on CD49a and Eomes expression in indicated transgenic mice. (c) Corresponding quantification of liver group 1 ILC subsets amongst indicated transgenic mice. Data shown as mean ± s.e.m.; Mann-Whitney U-test; **P < 0.01. (a-c) Data represent n = 5 of one experiment. (d,e) Percentage and phenotype of NK-derived ILC1s (CD49a+Eomes−) in NK cell cultured for 5 days with 25 ng/mL rIL-15/IL-15Rα complex and TGF-β1 at indicated concentration. Statistical comparisons of in vitro NK cell-derived ILC1 percentage (d) and TRAILhiDNAM-1hi cell percentage in in vitro NK cell-derived ILC1s (e) at different rTGF-β1 concentrations. Data shown as mean ± s.e.m. of 5 replicates per group of one experiment. *P < 0.05, ***P < 0.001, ****P < 0.0001 determined by one-way ANOVA and Tukey’s multiple comparison test. (f) Purity of intILC1s and NK cells sorted from pooled spleens of indicated transgenic mice. (g) CD49a and CD49b expression profile of cells as sorted in (f) after cultured in serum-free medium in presence of 50 ng/mL rIL-15 for 4 days (n = 3 of one experiment). (h) Expression of CD49a and CD49b on splenic NK cells cultured in serum-free medium supplemented as indicated over time (n = 3 of one experiment). (i) Corresponding expression of CD49a and CD49b on liver ILC1s (n = 3 of one experiment).

Supplementary Figure 3 Analysis of proliferation-associated gene sets from liver and splenic NK cells and ILC1s.

Heatmap visualizing E2F gene set expression (a) and G2M checkpoint gene set expression (b) of liver/spleen NK cells and ILC1s (GSE52047) clustered by tumor NK cell and ILC1 gene signatures (left of each panel). Quantifications of gene set expression (right of each panel) by combined z-scores were compared by pairwise two-sided t-tests with Benjamini & Hochberg (FDR) correction for multiple testing. Horizontal lines in whisker boxplots represent quartiles. *P < 0.05; ns, non-significant. Sp: spleen; Liv: liver. Horizontal bars, median; boxes, 25th to 75th quartile; ‘whiskers’, 10th and 90th quartile.

Supplementary Figure 4 Mcl1FL mice are deficient in group 1 ILCs, while anti-asGM1 ‘preferentially’ depletes the tumor microenvironment of NK cells and intILC1s.

(a) Representative flow cytometric plots showing NK1.1+NKp46+ cells (left) and CD49a+CD49b− ILC1s and CD49a−CD49b+ NK cells (right) in the liver (top panel) and spleen (bottom panel) of Mcl1WT and Mcl1FL mice. (b) Corresponding quantifications of cell population in the liver (top panel) and spleen (bottom panel) as indicated. Rag2−/−γc−/− mice were used as negative control (mean ± s.e.m.; n = 5 for liver, n = 4 for spleen and n = 2 for Rag2−/−γc−/− mice from two independent experiments; unpaired two-sided t-tests; *P < 0.05, **P < 0.01). (c) Experimental setup for the treatment of MCA1956 tumor-bearing WT mice with two doses of 50 μg anti-asGM1 antibody or control IgG i.p. for two consecutive days. (d,e) Representative flow cytometric plots showing percentage of group 1 ILCs (in live CD45+Lin− population) (d) and group 1 ILC composition (e) in different tissues from mice treated as indicated (n = 5 for ctrl IgG treated group and n = 6 for anti-asGM1 antibody treated group of two independent experiments). (f-h) Corresponding quantifications of group 1 ILC subset number in the liver (f), spleen (g) and MCA1956 tumor (h) of mice treated as indicated (mean ± s.e.m.; n = 5 for ctrl IgG treated group and n = 6 for anti-asGM1 antibody treated group of two independent experiments; Mann-Whitney U-test; *P < 0.05, **P < 0.01).

Supplementary Figure 5 TGF-b signaling fosters tumor growth and NK cell conversion in SM1WT1 tumors.

(a) Representative flow cytometric plots showing group 1 ILC composition in SM1WT1 melanomas harvested from indicated transgenic mice at day 24 after tumor injection. ND, not determined. (b) Corresponding quantification of tumor group 1 ILC subsets (mean ± s.e.m.; n = 8 for Ncr1cre/wt mice, n = 7 for RIIFL mice and RICA-FL mice of two independent experiments; one-way ANOVA and Tukey’s multiple comparison test; ***P < 0.001, ****P < 0.0001). (c) Tumor growth of SM1WT1 melanomas in indicated transgenic mice (mean ± s.e.m.; n = 10 for Ncr1cre/wt, RICA-FL and RICA-WT mice, n = 5 for Mcl1WT and Mcl1FL mice of two independent experiments; one-way ANOVA and Tukey’s multiple comparison test; **P < 0.01). (d) Tumor growth of SM1WT1 melanomas in RIIFL and RIIWT mice treated with 50 μg control IgG or anti-asGM1 antibody i.p. on day -1, 0, 7, 14 and 21 before or after tumor cell injection at day 0 (mean ± s.e.m.; n = 10 for RIIFL and RIIWT mice of two independent experiments; one-way ANOVA and Tukey’s multiple comparison test; ***P < 0.001, ****P < 0.0001).

Supplementary Figure 6 TGF-β signaling in NKp46+ cells controls lung metastasis.

Lung metastasis in WT or indicated transgenic mice following i.v. injection of 2 × 105 RM-1 prostate carcinoma cells (a) and 3.5 × 105 EO771-LMB mCherry+ breast cancer cells (b-d). Total fluorescence radiant efficiency (b), relative mCherry mRNA expression (c) and representative fluorescence imaging (d) of lung metastases were shown. Results shown as mean ± s.e.m. and represent 3 mice per group (RICA-WT), 6 mice per group (RIIWT, RIIFL and RICA-FL), and 15 mice per group (WT and Ncr1cre/wt) for (a) and 6 mice per group (Ncr1cre/wt and RICA-FL), 5 mice per group (RIIFL and Mcl1FL) for (b-d) of one experiment. *P < 0.05, **P < 0.01, ****P < 0.0001 determined by one-way ANOVA and Tukey’s multiple comparison test.

Supplementary Figure 7 Expression of inhibitory immune cell receptors on tumor group 1 ILC subsets.

(a) Comparisons of inhibitory immune cell receptor expression among tumor group 1 ILC subsets isolated from s.c. transplanted MCA1956 tumors (mean ± s.e.m.; n = 5 of two experiments; one-way ANOVA and Tukey’s multiple comparison test; *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; N.D., not detected). (b) Representative flow cytometric plots showing the expression of indicated receptors in tumor group 1 ILC subsets isolated from primary MCA-induced fibrosarcomas (n = 5 of one experiment). (c) Representative histogram showing NKG2A expression in tumor group 1 ILC subsets isolated from s.c. MCA1956 tumors (n = 5 of two independent experiments).

Supplementary Figure 8 Antibody-mediated neutralization of TNF impairs the growth of SM1WT1 melanomas.

(a) IFN-γ (left) and TNF (middle) production by tumor group 1 ILC subsets from SM1WT1 melanomas after 4 h stimulation by PMA/ionomycin. Percentages of cytokine producing cells were determined by flow cytometry and ratios of IFN-γ/TNF-producing cells (right) were calculated (mean ± s.e.m.; n = 7 tumors from one experiment; one-way ANOVA and Tukey’s multiple comparison; *P < 0.05, **P < 0.01). (b) Experimental setup for antibody-mediated cytokine neutralization in SM1WT1 melanoma-bearing mice. (c) Tumor growth in RIIWT (left) and RIIFL (right) mice treated as indicated (mean ± s.e.m.; n = 5 mice per group of two independent experiments; one-way ANOVA and Tukey’s multiple comparison test; ***P < 0.001, ****P < 0.0001). (d) Representative flow cytometric plots showing the gating strategy for the analyses of CXCR6 expression on CD3−CD56dim and CD3−CD56bright human NK cells from PBMC of healthy volunteers (HV) and GIST patients as well as tumor infiltrating lymphocytes (TILs) from GIST patients. (e) Representative flow cytometric plots showing the gating strategy for the analyses of CXCR6 expression on NK1.1+NKp46+ tumor group 1 ILCs in MCA1956 tumors (n = 5 per group of two independent experiments).

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Gao, Y., Souza-Fonseca-Guimaraes, F., Bald, T. et al. Tumor immunoevasion by the conversion of effector NK cells into type 1 innate lymphoid cells. Nat Immunol 18, 1004–1015 (2017). https://doi.org/10.1038/ni.3800

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