Abstract
Intratumoral stimulatory dendritic cells (SDCs) play an important role in stimulating cytotoxic T cells and driving immune responses against cancer. Understanding the mechanisms that regulate their abundance in the tumor microenvironment (TME) could unveil new therapeutic opportunities. We find that in human melanoma, SDC abundance is associated with intratumoral expression of the gene encoding the cytokine FLT3LG. FLT3LG is predominantly produced by lymphocytes, notably natural killer (NK) cells in mouse and human tumors. NK cells stably form conjugates with SDCs in the mouse TME, and genetic and cellular ablation of NK cells in mice demonstrates their importance in positively regulating SDC abundance in tumor through production of FLT3L. Although anti-PD-1 ‘checkpoint’ immunotherapy for cancer largely targets T cells, we find that NK cell frequency correlates with protective SDCs in human cancers, with patient responsiveness to anti-PD-1 immunotherapy, and with increased overall survival. Our studies reveal that innate immune SDCs and NK cells cluster together as an excellent prognostic tool for T cell–directed immunotherapy and that these innate cells are necessary for enhanced T cell tumor responses, suggesting this axis as a target for new therapies.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Topalian, S. L., Drake, C. G. & Pardoll, D. M. Immune checkpoint blockade: a common denominator approach to cancer therapy. Cancer Cell. 27, 450–461 (2015).
Rizvi, N. A. et al. Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer. Science 348, 124–128 (2015).
Broz, M. L. et al. Dissecting the tumor myeloid compartment reveals rare activating antigen-presenting cells critical for T cell immunity. Cancer Cell. 26, 638–652 (2014).
Salmon, H. et al. Expansion and activation of CD103+ dendritic cell progenitors at the tumor site enhances tumor responses to therapeutic PD-L1 and BRAF inhibition. Immunity 44, 924–938 (2016).
Sánchez-Paulete, A. R. et al. Cancer immunotherapy with immunomodulatory anti-CD137 and ant-PD-1 monoclonal antibodies requires BATF3-dependent dendritic cells. Cancer Discov. 6, 71–79 (2016).
Hildner, K. et al. Batf3 deficiency reveals a critical role for CD8α+ dendritic cells in cytotoxic T cell immunity. Science 322, 1097–1100 (2008).
Spranger, S., Dai, D., Horton, B. & Gajewski, T. F. Tumor-residing Batf3 dendritic cells are required for effector t cell trafficking and adoptive T cell therapy. Cancer Cell. 31, 711–723.e4 (2017).
Lavin, Y. et al. Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses. Cell 169, 750–765.e17 (2017).
Spranger, S., Bao, R. & Gajewski, T. F. Melanoma-intrinsic β-catenin signalling prevents anti-tumor immunity. Nature 523, 231–235 (2015).
Bogunovic, D. et al. Immune profile and mitotic index of metastatic melanoma lesions enhance clinical staging in predicting patient survival. Proc. Natl. Acad. Sci. USA 106, 20429–20434 (2009).
Cancer Genome Atlas Network. Genomic classification of cutaneous melanoma. Cell 161, 1681–1696 (2015).
Wei, S. C. et al. Distinct cellular mechanisms underlie anti-CTLA-4 and anti-PD-1 checkpoint blockade. Cell 170, 1120–1133.e17 (2017).
Liu, K. & Nussenzweig, M. C. Origin and development of dendritic cells. Immunol. Rev. 234, 45–54 (2010).
Engelhardt, J. J. et al. Marginating dendritic cells of the tumor microenvironment cross-present tumor antigens and stably engage tumor-specific T cells. Cancer Cell. 21, 402–417 (2012).
Böttcher, J. P. et al. NK cells stimulate recruitment of cDC1 into the tumor microenvironment promoting cancer immune control. Cell 172, 1022–1037.e14 (2018).
Du, X. et al. Genomic profiles for human peripheral blood T cells, B cells, natural killer cells, monocytes, and polymorphonuclear cells: comparisons to ischemic stroke, migraine, and Tourette syndrome. Genomics 87, 693–703 (2006).
Bezman, N. A. et al. Molecular definition of the identity and activation of natural killer cells. Nat. Immunol. 13, 1000–1009 (2012).
Loo, K. et al. Partially exhausted tumor-infiltrating lymphocytes predict response to combination immunotherapy. JCI Insight 2, 93433 (2017).
Philip, M. et al. Chromatin states define tumour-specific T cell dysfunction and reprogramming. Nature 545, 452–456 (2017).
Krieg, C. et al. High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy. Nat. Med. 24, 144–153 (2018).
Zitvogel, L. Dendritic and natural killer cells cooperate in the control/switch of innate immunity. J. Exp. Med. 195, F9–F14 (2002).
Fernandez, N. C. et al. Dendritic cells directly trigger NK cell functions: cross-talk relevant in innate anti-tumor immune responses in vivo. Nat. Med. 5, 405–411 (1999).
Solanilla, A. et al. Expression of Flt3-ligand by the endothelial cell. Leukemia 14, 153–162 (2000).
Miloud, T., Fiegler, N., Suffner, J., Hämmerling, G. J. & Garbi, N. Organ-specific cellular requirements for in vivo dendritic cell generation. J. Immunol. 188, 1125–1135 (2012).
Goding, S. R., Yu, S., Bailey, L. M., Lotze, M. T. & Basse, P. H. Adoptive transfer of natural killer cells promotes the anti-tumor efficacy of T cells. Clin. Immunol. 177, 76–86 (2017).
Blake, S. J. et al. Suppression of metastases using a new lymphocyte checkpoint target for cancer immunotherapy. Cancer Discov. 6, 446–459 (2016).
Dougall, W. C., Kurtulus, S., Smyth, M. J. & Anderson, A. C. TIGIT and CD96: new checkpoint receptor targets for cancer immunotherapy. Immunol. Rev. 276, 112–120 (2017).
Cheng, P. F., Dummer, R. & Levesque, M. P. Data mining The Cancer Genome Atlas in the era of precision cancer medicine. Swiss Med. Wkly. 145, w14183 (2015).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Stat. Methodol. 57, 289–300 (1995).
Wu, C., Jin, X., Tsueng, G., Afrasiabi, C. & Su, A. I. BioGPS: building your own mash-up of gene annotations and expression profiles. Nucleic Acids Res. 44 D1, D313–D316 (2016).
Ruffell, B. et al. Leukocyte composition of human breast cancer. Proc. Natl. Acad. Sci. USA 109, 2796–2801 (2012).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinforma. 12, 323 (2011).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
McKenna, H. J. et al. Mice lacking flt3 ligand have deficient hematopoiesis affecting hematopoietic progenitor cells, dendritic cells, and natural killer cells. Blood 95, 3489–3497 (2000).
Cao, X. et al. Defective lymphoid development in mice lacking expression of the common cytokine receptor γ chain. Immunity 2, 223–238 (1995).
Gazit, R. et al. Lethal influenza infection in the absence of the natural killer cell receptor gene Ncr1. Nat. Immunol. 7, 517–523 (2006).
Hadjantonakis, A.-K., Macmaster, S. & Nagy, A. Embryonic stem cells and mice expressing different GFP variants for multiple non-invasive reporter usage within a single animal. BMC Biotechnol. 2, 11 (2002).
Hogquist, K. A. et al. T cell receptor antagonist peptides induce positive selection. Cell 76, 17–27 (1994).
Yamazaki, C. et al. Critical roles of a dendritic cell subset expressing a chemokine receptor, XCR1. J. Immunol. 190, 6071–6082 (2013).
Khanna, K. M. et al. T cell and APC dynamics in situ control the outcome of vaccination. J. Immunol. 185, 239–252 (2010).
Fidler, I. J. Biological behavior of malignant melanoma cells correlated to their survival in vivo. Cancer Res. 35, 218–224 (1975).
Graf, L. H. Jr., Kaplan, P. & Silagi, S. Efficient DNA-mediated transfer of selectable genes and unselected sequences into differentiated and undifferentiated mouse melanoma clones. Somat. Cell. Mol. Genet. 10, 139–151 (1984).
Corbett, T. H., Griswold, D. P. Jr., Roberts, B. J., Peckham, J. C. & Schabel, F. M. Jr. Tumor induction relationships in development of transplantable cancers of the colon in mice for chemotherapy assays, with a note on carcinogen structure. Cancer Res. 35, 2434–2439 (1975).
Pinkard, H., Stuurman, N., Corbin, K., Vale, R. & Krummel, M. F. Micro-Magellan: open-source, sample-adaptive, acquisition software for optical microscopy. Nat. Methods 13, 807–809 (2016).
Acknowledgements
We thank L. Lanier, J. Roose and L. Fong for advice, and we thank M. Spasic and N. Khurana for support with response data. This work was supported by National Institutes of Health (NIH) grant R01CA197363, awarded to M.F.K. Acquisition and processing of human melanoma samples in cohort A described in this study was funded in part by contributions from AbbVie, Amgen, and Bristol-Myers Squibb as members of the Immunoprofiler Consortium. Further support came from NIH grant 5P30CA082103, awarded to the University of California, San Francisco (UCSF) Hellen Diller Family Comprehensive Cancer Center. M.B. was supported by the Genentech Predoctoral Research Fellowship, the Margaret A. Cunningham Immune Mechanisms in Cancer Research Fellowship Award, and the Achievement Reward for College Scientists Scholarship. K.C.B. was supported by a postdoctoral fellowship from the Cancer Research Institute and Fibrolamellar Cancer Foundation.
Author information
Authors and Affiliations
Contributions
K.C.B. designed and performed the experiments and wrote and edited the manuscript. J.H. assisted in analysis of tumor-infiltrating myeloid populations and data analysis. M.L.B. designed and performed experiments with melanoma cohort B. F.J.C. assisted in imaging data analysis. M.B. assisted in analysis of tumor-infiltrating myeloid populations and T cell–depletion experiments. A.J.C. assisted in analysis of HNSCC tumor samples. R.K. and A.E.N. assisted in analysis of tumor-infiltrating myeloid populations. K.L. and A.I.D. provided human melanoma biopsies, clinical data, and edited the manuscript. M.D.R. read the manuscript and provided useful discussion. M.D.A. provided human melanoma biopsies and clinical data. D.B. and N.B. provided metastatic melanoma data, and D.B. edited the manuscript. D.M.W. performed statistical analyses. P.K.H and W.R.R provided human HNSCC samples. J.L.P., B.S., and S.A. provided bioinformatics analyses. V.C. managed sample collection, assisted in analysis of tumor-infiltrating myeloid populations, read the manuscript, and provided useful discussion. M.F.K. conceived the project and wrote and edited the manuscript.
Corresponding author
Ethics declarations
Competing interests
J.L.P. was an employee at Pionyr Immunotherapeutics at the time of manuscript writing. The other authors declare no competing interests.
Additional information
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–7 and Supplementary Tables 1–3
Supplementary Video 1
Stable interaction of NK cells and XCR1+ DCs
Supplementary Video 2
NK cells distant from XCR1+ DCs have increased motility
Rights and permissions
About this article
Cite this article
Barry, K.C., Hsu, J., Broz, M.L. et al. A natural killer–dendritic cell axis defines checkpoint therapy–responsive tumor microenvironments. Nat Med 24, 1178–1191 (2018). https://doi.org/10.1038/s41591-018-0085-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41591-018-0085-8
