Natural killer (NK) cells are critical mediators of host immunity to pathogens. Here, we demonstrate that the endoplasmic reticulum stress sensor inositol-requiring enzyme 1 (IRE1α) and its substrate transcription factor X-box-binding protein 1 (XBP1) drive NK cell responses against viral infection and tumors in vivo. IRE1α-XBP1 were essential for expansion of activated mouse and human NK cells and are situated downstream of the mammalian target of rapamycin signaling pathway. Transcriptome and chromatin immunoprecipitation analysis revealed c-Myc as a new and direct downstream target of XBP1 for regulation of NK cell proliferation. Genetic ablation or pharmaceutical blockade of IRE1α downregulated c-Myc, and NK cells with c-Myc haploinsufficency phenocopied IRE1α-XBP1 deficiency. c-Myc overexpression largely rescued the proliferation defect in IRE1α−/− NK cells. Like c-Myc, IRE1α-XBP1 also promotes oxidative phosphorylation in NK cells. Overall, our study identifies a IRE1α-XBP1-cMyc axis in NK cell immunity, providing insight into host protection against infection and cancer.
Subscribe to Journal
Get full journal access for 1 year
only $4.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
The RNA-seq data were deposited in the Gene Expression Omnibus under the accession number GSE113214. The remaining data that support the findings of this study are available from the corresponding authors upon request. Materials will be provided with material transfer agreements in place as appropriate.
Caligiuri, M. A. Human natural killer cells. Blood 112, 461–469 (2008).
Madera, S. et al. Type I IFN promotes NK cell expansion during viral infection by protecting NK cells against fratricide. J. Exp. Med. 213, 225–233 (2016).
Zawislak, C. L. et al. Stage-specific regulation of natural killer cell homeostasis and response against viral infection by microRNA-155. Proc. Natl Acad. Sci. USA 110, 6967–6972 (2013).
Sun, J. C. et al. Proinflammatory cytokine signaling required for the generation of natural killer cell memory. J. Exp. Med. 209, 947–954 (2012).
Beaulieu, A. M., Zawislak, C. L., Nakayama, T. & Sun, J. C. The transcription factor Zbtb32 controls the proliferative burst of virus-specific natural killer cells responding to infection. Nat. Immunol. 15, 546–553 (2014).
Rapp, M. et al. Core-binding factor β and Runx transcription factors promote adaptive natural killer cell responses. Sci. Immunol. 2, eaan3796 (2017).
Morvan, M. G. & Lanier, L. L. NK cells and cancer: you can teach innate cells new tricks. Nat. Rev. Cancer 16, 7–19 (2016).
Yoshida, H., Matsui, T., Yamamoto, A., Okada, T. & Mori, K. XBP1 mRNA is induced by ATF6 and spliced by IRE1 in response to ER stress to produce a highly active transcription factor. Cell 107, 881–891 (2001).
Lee, A. H., Iwakoshi, N. N. & Glimcher, L. H. XBP-1 regulates a subset of endoplasmic reticulum resident chaperone genes in the unfolded protein response. Mol. Cell. Biol. 23, 7448–7459 (2003).
Lee, A. H., Heidtman, K., Hotamisligil, G. S. & Glimcher, L. H. Dual and opposing roles of the unfolded protein response regulated by IRE1alpha and XBP1 in proinsulin processing and insulin secretion. Proc. Natl Acad. Sci. USA 108, 8885–8890 (2011).
Lee, A. H., Scapa, E. F., Cohen, D. E. & Glimcher, L. H. Regulation of hepatic lipogenesis by the transcription factor XBP1. Science 320, 1492–1496 (2008).
Kaser, A. et al. XBP1 links ER stress to intestinal inflammation and confers genetic risk for human inflammatory bowel disease. Cell 134, 743–756 (2008).
Chen, X. et al. XBP1 promotes triple-negative breast cancer by controlling the HIF1α pathway. Nature 508, 103–107 (2014).
Condamine, T. et al. ER stress regulates myeloid-derived suppressor cell fate through TRAIL-R-mediated apoptosis. J. Clin. Invest. 124, 2626–2639 (2014).
Yan, D., Wang, H. W., Bowman, R. L. & Joyce, J. A. STAT3 and STAT6 signaling pathways synergize to promote cathepsin secretion from macrophages via IRE1α activation. Cell Rep. 16, 2914–2927 (2016).
Song, M. et al. IRE1alpha-XBP1 controls T cell function in ovarian cancer by regulating mitochondrial activity. Nature 562, 423–428 (2018).
Cubillos-Ruiz, J. R. et al. ER stress sensor XBP1 controls anti-tumor immunity by disrupting dendritic cell homeostasis. Cell 161, 1527–1538 (2015).
Beaulieu, A. M. & Sun, J. C. Tracking effector and memory NK cells during MCMV infection. Methods Mol. Biol. 1441, 1–12 (2016).
Iwawaki, T., Akai, R., Kohno, K. & Miura, M. A transgenic mouse model for monitoring endoplasmic reticulum stress. Nat. Med. 10, 98–102 (2004).
Madera, S. & Sun, J. C. Cutting edge: stage-specific requirement of IL-18 for antiviral NK cell expansion. J. Immunol. 194, 1408–1412 (2015).
Orr, M. T. et al. Ly49H signaling through DAP10 is essential for optimal natural killer cell responses to mouse cytomegalovirus infection. J. Exp. Med. 206, 807–817 (2009).
Brandt, C. et al. Food perception primes hepatic ER homeostasis via melanocortin-dependent control of mTOR activation. Cell 175, 1321–1335.e20 (2018).
Hsu, H. S. et al. Involvement of ER stress, PI3K/AKT activation, and lung fibroblast proliferation in bleomycin-induced pulmonary fibrosis. Sci. Rep. 7, 14272 (2017).
Zheng, H. et al. Leptin promotes allergic airway inflammation through targeting the unfolded protein response pathway. Sci. Rep. 8, 8905 (2018).
Cerwenka, A. & Lanier, L. L. Natural killer cell memory in infection, inflammation and cancer. Nat. Rev. Immunol. 16, 112–123 (2016).
Dokun, A. O. et al. Specific and nonspecific NK cell activation during virus infection. Nat. Immunol. 2, 951–956 (2001).
Sun, J. C., Beilke, J. N., Bezman, N. A. & Lanier, L. L. Homeostatic proliferation generates long-lived natural killer cells that respond against viral infection. J. Exp. Med. 208, 357–368 (2011).
Mao, Y. et al. IL-15 activates mTOR and primes stress-activated gene expression leading to prolonged antitumor capacity of NK cells. Blood 128, 1475–1489 (2016).
Wagner, J. A. et al. CD56bright NK cells exhibit potent antitumor responses following IL-15 priming. J. Clin. Invest. 127, 4042–4058 (2017).
Cross, B. C. et al. The molecular basis for selective inhibition of unconventional mRNA splicing by an IRE1-binding small molecule. Proc. Natl Acad. Sci. USA 109, E869–E878 (2012).
Sun, J. C., Beilke, J. N. & Lanier, L. L. Adaptive immune features of natural killer cells. Nature 457, 557–561 (2009).
Buck, M. D., Sowell, R. T., Kaech, S. M. & Pearce, E. L. Metabolic instruction of immunity. Cell 169, 570–586 (2017).
Loftus, R. M. et al. Amino acid-dependent cMyc expression is essential for NK cell metabolic and functional responses in mice. Nat. Commun. 9, 2341 (2018).
O’Sullivan, T. E. & Sun, J. C. Innate lymphoid cell immunometabolism. J. Mol. Biol. 429, 3577–3586 (2017).
Morrish, F. & Hockenbery, D. MYC and mitochondrial biogenesis. Cold Spring Harb. Perspect. Med. 4, a014225 (2014).
van Riggelen, J., Yetil, A. & Felsher, D. W. MYC as a regulator of ribosome biogenesis and protein synthesis. Nat. Rev. Cancer 10, 301–309 (2010).
Farrell, A. S. & Sears, R. C. MYC degradation. Cold Spring Harb. Perspect. Med. 4, a014365 (2014).
Lu, Y. et al. MYC targeted long noncoding RNA DANCR promotes cancer in part by reducing p21 levels. Cancer Res. 78, 64–74 (2018).
Clauss, I. M., Chu, M., Zhao, J. L. & Glimcher, L. H. The basic domain/leucine zipper protein hXBP-1 preferentially binds to and transactivates CRE-like sequences containing an ACGT core. Nucleic Acids Res. 24, 1855–1864 (1996).
Allan, D. S. et al. An in vitro model of innate lymphoid cell function and differentiation. Mucosal Immunol. 8, 340–351 (2015).
Robertson, M. J. et al. Characterization of a cell line, NKL, derived from an aggressive human natural killer cell leukemia. Exp. Hematol. 24, 406–415 (1996).
Frazier, W. R., Steiner, N., Hou, L., Dakshanamurthy, S. & Hurley, C. K. Allelic variation in KIR2DL3 generates a KIR2DL2-like receptor with increased binding to its HLA-C ligand. J. Immunol. 190, 6198–6208 (2013).
Foley, B. et al. The biology of NK cells and their receptors affects clinical outcomes after hematopoietic cell transplantation (HCT). Immunol. Rev. 258, 45–63 (2014).
Ruggeri, L. et al. Effectiveness of donor natural killer cell alloreactivity in mismatched hematopoietic transplants. Science 295, 2097–2100 (2002).
Molgora, M. et al. IL-1R8 is a checkpoint in NK cells regulating anti-tumour and anti-viral activity. Nature 551, 110–114 (2017).
Bottcher, J. P. et al. NK cells stimulate recruitment of cDC1 into the tumor microenvironment promoting cancer immune control. Cell 172, 1022–1037.e14 (2018).
Siddiquey, M. N. A., Zhang, H., Nguyen, C. C., Domma, A. J. & Kamil, J. P. The human cytomegalovirus endoplasmic reticulum-resident glycoprotein UL148 activates the unfolded protein response. J. Virol. 92, e00896-18 (2018).
Sun, J. C. & Lanier, L. L. Is there natural killer cell memory and can it be harnessed by vaccination? NK cell memory and immunization strategies against infectious diseases and cancer. Cold Spring Harb. Perspect. Biol. 10, a029538 (2018).
Orange, J. S. Natural killer cell deficiency. J. Allergy Clin. Immunol. 132, 515–525 (2013).
Vivier, E., Ugolini, S., Blaise, D., Chabannon, C. & Brossay, L. Targeting natural killer cells and natural killer T cells in cancer. Nat. Rev. Immunol. 12, 239–252 (2012).
Barrow, A. D. et al. Natural killer cells control tumor growth by sensing a growth factor. Cell 172, 534–548 e519 (2018).
Ferrari de Andrade, L. et al. Antibody-mediated inhibition of MICA and MICB shedding promotes NK cell-driven tumor immunity. Science 359, 1537–1542 (2018).
Adams, N. M. et al. Transcription factor IRF8 orchestrates the adaptive natural killer cell response. Immunity 48, 1172–1182 e1176 (2018).
Andre, P. et al. Anti-NKG2A mAb is a checkpoint inhibitor that promotes anti-tumor immunity by unleashing both T and NK cells. Cell 175, 1731–1743.e13 (2018).
van Montfoort, N. et al. NKG2A blockade potentiates CD8 T cell immunity induced by cancer vaccines. Cell 175, 1744–1755.e15 (2018).
Barry, K. C. et al. A natural killer-dendritic cell axis defines checkpoint therapy-responsive tumor microenvironments. Nat. Med. 24, 1178–1191 (2018).
Rabacal, W. et al. Transcription factor KLF2 regulates homeostatic NK cell proliferation and survival. Proc. Natl Acad. Sci. USA 113, 5370–5375 (2016).
Wang, Y. et al. The IL-15-AKT-XBP1s signaling pathway contributes to effector functions and survival in human NK cells. Nat. Immunol. 20, 10–17 (2019).
Marcais, A. et al. The metabolic checkpoint kinase mTOR is essential for IL-15 signaling during the development and activation of NK cells. Nat. Immun. 15, 749–757 (2014).
Yang, C. et al. mTORC1 and mTORC2 differentially promote natural killer cell development. eLife 7, e35619 (2018).
Zhao, N. et al. Pharmacological targeting of MYC-regulated IRE1/XBP1 pathway suppresses MYC-driven breast cancer. J. Clin. Invest. 128, 1283–1299 (2018).
Kortlever, R. M. et al. Myc cooperates with ras by programming inflammation and immune suppression. Cell 171, 1301–1315.e14 (2017).
Chou, C. et al. c-Myc-induced transcription factor AP4 is required for host protection mediated by CD8 + T cells. Nat. Immunol. 15, 884–893 (2014).
Cichocki, F. et al. The transcription factor c-Myc enhances KIR gene transcription through direct binding to an upstream distal promoter element. Blood 113, 3245–3253 (2009).
Zakiryanova, G. K. et al. Alterations of oncogenes expression in NK cells in patients with cancer. Immun. Inflamm. Dis. 5, 493–502 (2017).
Fodil-Cornu, N. et al. Ly49h-deficient C57BL/6 mice: a new mouse cytomegalovirus-susceptible model remains resistant to unrelated pathogens controlled by the NK gene complex. J. Immunol. 181, 6394–6405 (2008).
Iwawaki, T., Akai, R., Yamanaka, S. & Kohno, K. Function of IRE1 alpha in the placenta is essential for placental development and embryonic viability. Proc. Natl Acad. Sci. USA 106, 16657–16662 (2009).
Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 7, 562–578 (2012).
Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).
Anders, S. & Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11, R106 (2010).
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
Chen, X. et al. Integration of external signaling pathways with the core transcriptional network in embryonic stem cells. Cell 133, 1106–1117 (2008).
Peinado, H. et al. Melanoma exosomes educate bone marrow progenitor cells toward a pro-metastatic phenotype through MET. Nat. Med. 18, 883–891 (2012).
We thank E. Vivier (Aix Marseille University) for Ncr1iCre mice; R. Wang (Nationwide Children’s Hospital) for Mycfl/fl mice; R. Sears (Oregon Health & Science University) for Mycfsf/fsf mice; J. Ritz (Dana-Farber Cancer Institute) for the NKL cell line; C. Hurley (Georgetown University) for the KHYG-1 cell line; D. Lyden (Weill Cornell Medicine) for the B16F10 cell line; members of the Sun laboratory for sharing viral reagents, cytokines and flow cytometry antibodies and for providing experimental assistance; members of the Glimcher laboratory—M. Raundhal, C. Lentucci, R. Xu, S. Ghosh and A. Gonzalez for technical support; S. Adoro (Case Western Reserve University) and J. Cubillos-Ruiz (Weill Cornell Medicine) for critical reading of the manuscript and helpful discussion; M. Song (Weill Cornell Medicine) and the Wucherpfennig laboratory (Dana-Farber Cancer Institute) for insightful comments; J. Xiang (Weill Cornell Genomics and Epigenomics Core) for RNA-seq; J. McCormick (Weill Cornell Medicine) and DFCI Jimmy Fund Flow Cytometry Core for cell sorting; Specialized Histopathology Core at Brigham & Women’s Hospital for histology; L. Cohen-Gould and J. Jimenez (Microscopy and Image Analysis Core Facility at Weill Cornell Medicine) for electron microscopy; X. Liu (Metabolism and Mitochondrial Research Core, Beth Israel Deaconess Medical Center) for metabolic flux assays; D. Neuberg (Dana-Farber Cancer Institute) for advising on statistical analysis; and S. Schneider (Dana-Farber Cancer Institute) for manuscript editing. L.H.G. and H.D. were supported by Institutional Funding from The Dana-Farber Cancer Institute. H.D. was also supported by a Helen Gurley Brown Presidential Initiative Award (Dana-Farber Cancer Institute). J.C.S. was supported by the Ludwig Center for Cancer Immunotherapy, the American Cancer Society, the Burroughs Wellcome Fund and the NIH (grant nos. AI100874, AI130043 and P30CA008748). N.M.A. was supported by an MSTP Grant from the National Institute of General Medical Sciences of the NIH to the Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program (grant no. T32GM007739) and by an F30 Predoctoral Fellowship from National Institue of Allergy and Infectious Diseases of the NIH (no. F30 AI136239). X.C. was supported by a NIH grant (no. 1 R37 CA228304-01).
L.H.G. is a former Director of Bristol-Myers Squibb and is currently on the board of directors of and holds equity in GlaxoSmithKline Pharmaceuticals and the Waters Corporation. She chairs the scientific advisory board, is a co-founder of and holds equity in Quentis Therapeutics. She also serves on the scientific advisory boards of Repare Therapeutics, Abpro and Kaleido Therapeutics.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Integrated supplementary information
Supplementary Figure 1 qPCR validation of upregulation of the IRE1α/XBP1 pathway in activated NK cells, and requirement of STAT4 and mTOR signaling pathways in driving IRE1α /XBP1.
(a) Quantitative real time PCR analysis of indicated UPR genes in sorting, purified splenic NK cells from wild-type mice at day 1 post MCMV infection. β-ACTIN was used as reference, and data were normalized to the uninfected control expression levels. (b) Quantitative real time PCR analysis of indicated UPR genes in sorting-purified splenic NK cells from wild-type mice after 16 hr culture in the presence or absence of IL-12 and IL-18. (c) Heat map of RNA-seq analysis (GSE106138) showing the expression of canonical IRE1α/XBP1 target genes in WT and STAT4-deficient Ly49H+ NK cells sorted from the spleens of mixed BM chimeric mice at day 2 PI. (d) Flow cytometric analysis of IRE1α activation in cytokine-activated NK cells after pharmaceutical inhibition of mTOR. NK cells from ERAI reporter mice were stimulated with mouse recombinant IL-12 (20 ng/ml) and IL-18 (10 ng/ml) for 6 hrs in the presence of mTOR inhibitor rapamycin (Rapa, 5 nM and 10 nM for low and high dose, respectively), Ku-0063794 (Ku, 1.5 μM and 3 μM for low and high dose, respectively), PP242 (PP, 0.5 μM and 1 μM for low and high dose, respectively), or IRE1 inhibitor 4μ8C (2.5 μM and 5 μM for low and high dose, respectively), or DMSO control. Representative flow cytometric plot (upper) and quantifications of relative inhibition efficiency (bottom) are shown. ns, not significant; * p < 0.05, ** p < 0.01, *** p < 0.0001 and **** p < 0.0001. Two-way analysis of variance (ANOVA) with the Sidak post-test performed on a. Two tailed unpaired Student’s t-test performed on b. All error bars, mean with s.d. from biological replicates. n = 3 mice/group in a. n = 3 mice in b; with technical triplicates for ex vivo culture. Each column is a different mouse in c. n = 3 ERAI mice in d. Experiments were independently repeated three (a, b) and two (d) times.
(a) Validation of IRE1NK KO efficiency: XBP1 splicing assay (upper panel) and quantitative real time PCR analysis (bottom panel) of indicated UPR genes in sorting-purified splenic NK cells from IRE1NK and IRE1f/f littermate mice after 4 hr ex vivo incubation in the presence or absence of tunicamycin, a pharmacologic inducer of ER stress. The quantitative real time PCR data are presented as relative expression to β-Actin. (b) Flow cytometric analysis of NK cell percentages and absolute numbers in BM, spleen and lung of IRE1NK and XBP1NK naïve mice, in comparison to their Cre-littermate controls. BM NK cells are identified by Lin−CD122 and splenic NK cells are identified by Lin−NK1.1+. (c) Flow cytometric analysis of NK cell development in BM of IRE1NK and XBP1NK mice: percentages of NK cells that are NK progenitors (NKP, DX5− NK1.1−), immature NK cells (iNK, DX5− NK1.1+) or mature NK (mNK, DX5− NK1.1+) are shown. (d) Flow cytometric analysis of NK cell maturation in spleen of IRE1NK and XBP1NK mice: percentages of NK cells that are immature (CD27+ CD11b−), mature (CD27− CD11b+) or intermediate stage (CD27+ CD11b+) are shown. (e) Flow cytometric analysis of NK cell repopulation in mixed BM chimera mice: WT (CD45.1): IRE1NK (CD45.2), and WT (CD45.1): IRE1vav1 (CD45.2) BM chimeras were generated as in the schematic (left); NK cell repopulation in the irradiated recipient mice was assessed in the peripheral blood at week 8 after BM transfer (right). (f) As in d, representative histogram plots showing surface expression of cytokine receptors and activating receptors in splenic NK cells from naïve IRE1NK and XBP1NK in comparison to their Cre- littermate control mice. ns: not significant, * p < 0.05, ** p < 0.01, *** p < 0.001 and ****p < 0.0001. Two tailed unpaired Student’s t-test performed on a. All error bars, mean with s.d.. n = 3 mice/group in a, f. n = 5 mice/group in b-d. n = 10 mice/group in e. Experiments were independently repeated three (a-e) and two (a, f) times.
Supplementary Figure 3 Dispensable function of IRE1α/XBP1 in NK cell priming, cytokine production or cytotoxicity.
(a) Gating strategy applied in analysis of co-transfer and mixed BM chimera experiments. (b-c) Flow cytometric analysis of splenic WT or IRE1NK Ly49H+ NK cells from mixed BM chimeric mice as indicated in Supplementary Figure 2e at day 2 PI: (b)IFN-γ and (c)CD69 and intracellular Granzyme B. (d) Flow cytometric analysis of co-transferred WT or IRE1NK Ly49H+ NK cells from the spleen of Ly49H-deficient recipients at day 2 PI: pan-Akt, p-Akt, and p-S6 with quantification normalized to WT expression levels as 100%. Two tailed unpaired Student’s t-test performed on b and c. All error bars, mean with s.d. n = 6 mixed BM chimera mice in b. n = 4 mice in c. n = 3 mice in d. Data were independently repeated three times.
Supplementary Figure 4 Minimal impact of IRE1α depletion on RIDD in infection-activated NK cells, and specific pharmaceutical blockade of IRE1α by 4μ8C.
(a) The volcano plot of RNA-seq analysis showing all genes in IRE1NK versus WT Ly49H+ splenic NK cells harvested from IRE1NK (CD45.2): WT (CD45.1) mixed BM chimera mice day 1.5 PI. RIDD target genes1 and XBP1 target genes1 are highlighted in red and blue, respectively. (b) IRE1NK and IRE1f/f NK cells from littermate animals were pre-labeled with CTV and cultured ex vivo with IL-2 and IL-15 as in Fig. 4f, g, but in the presence of 4μ8C (5 uM) or DMSO control treatment. Representative flow cytometric plots of CTV dilution and Ki-67 levels at day 3 are shown. Proliferating cells are defined as Ki-67+ CTVlo. n = 2 mice/group in b with technical duplicates per mouse. Experiments in b were independently repeated two times.1. So, J.S. et al. Silencing of lipid metabolism genes through IRE1alpha-mediated mRNA decay lowers plasma lipids in mice. Cell Metab 16, 487-499 (2012).
Representative electron microscopy of IRE1NK versus WT Ly49H+ splenic NK cells harvested from IRE1NK(CD45.2): WT (CD45.1) mixed BM chimera mice day 7 PI. The high-resolution plots at bottom show mitochondrial morphology. n = 3 mixed BM chimera mice.
(a) IPA Upstream Analysis derived from RNA-seq (day 1.5 PI) as indicated in Fig. 6a: prediction of Myc regulation in IRE1NK cells. (b) IPA analysis of Functional overlap between IRE1- and c-Myc-regulated genes derived from RNA-seq analysis of Ly49H+ IRE1NK cells at day 1.5 PI. (c) Flow cytometric analysis of c-Myc induction at the level of transcription (upper row) and translation (middle row) in splenic NK cells from WT mice either naïve or at day 1 PI. (bottom row) Representative flow cytometric plots indicating the concomitant induction of c-Myc protein and Venus reporter expression in NK cells from indicated organs of ERAI transgenic mice at day 2 PI. (d) Quantitative real time PCR and flow cytometric analysis of the basal levels of c-Myc mRNA and protein in naïve NK cells from IRE1NK and IRE1f/f littermate control mice. (e) Quantitative real time PCR analysis of canonical c-Myc target genes in transferred Ly49H+ IRE1NK versus WT NK cells that were sorting-purified from the spleen of recipient Ly49H-deficient mice at day 1.5 PI. β-Actin was used as reference, and data are shown as the relative expression normalized to transferred WT NK cells. (f) Schematic of the putative XBP1 binding site in the c-Myc promoter region (based on SABiosciences’ proprietary database ENCODE). (g) Flow cytometric analysis of the kinetics of XBP1s, p-S6, p-Akt and pan-Akt expression in primary human NK cells after stimulation with IL-12 (20 ng/ml) and IL-18 (10 ng/ml) for the indicated time. (h) Purified splenic NK cells from IRE1NK and IRE1f/f littermate control mice were stimulated with mouse recombinant IL-12 (20 ng/ml) and IL-18 (10 ng/ml) for 1 hr and 16 hrs in the presence or absence of mTOR inhibitor rapamycin (10 nM). c-Myc levels were quantified by flow cytometry. (i) Flow cytometric analysis of c-Myc expression in transferred CD45.1 congenic WT and IRE1NK cells in the spleen of recipient Rag2−/−Il2rg−/− mice at specified time points after transfer. ns: not significant, * p < 0.05, ** p < 0.01, *** p < 0.001. One sample t-test performed on e. Two-way analysis of variance (ANOVA) with the Sidak post-test performed on h. Two tailed unpaired Student’s t-test performed on i. All error bars, mean with s.d. from biological replicates. n = 3~5 mice/group for all experiments and data were independently repeated two (c, g, h) or three times (d, e, i).
Supplementary Figure 7 Characterization of NK cell development and maturation in Myc+/− heterozygous mice (Het, referred to as ‘MycNK’ in Main Text) and Myc−/− (KO) mice.
(a) Quantitative real time PCR validation of c-Myc expression in Het and KO NK cells before and after IL-12 and IL-18 stimulation ex vivo. (b) Flow cytometric analysis of NK cell percentages and absolute numbers in BM and spleen of MycHet mice, in comparison to their Cre- littermate controls. BM NK cells are identified by Lin−CD122 and splenic NK cells are identified by Lin−NK1.1+. (c) as in b, except MycKO is shown. (d) Flow cytometric analysis of NK cell development in BM and NK cell maturation in spleen of MycHet mice. For BM (upper), percentages of NK cells that are NK progenitors (NKP, DX5− NK1.1−), immature NK cells (iNK, DX5− NK1.1+) or mature NK (mNK, DX5− NK1.1+) are shown; for spleen (bottom), percentages of NK cells that are immature (CD27+ CD11b−), mature (CD27− CD11b+) or intermediate stage (CD27+ CD11b+) are shown. (e) as in d, except MycKO is shown. (e) Representative histogram plots showing surface expression of cytokine receptors and activating receptors in splenic NK cells from MycHet mice in comparison to their Cre- littermate controls. (f) as in e, except MycKO is shown. p values as indicated. Two tailed unpaired Student’s t-test performed on a-e. All error bars, mean with s.e.m. Data are representative of three (a-e) and two (f, g) independent experiments. n = 3 mice/group for a, f, g. n = 4-5 mice/group for all experiments in b-e. Data were independently repeated three (b-e) or two (f, g) times.
Supplementary Figure 8 IRE1α-driven NK cell expansion is associated with the presence of immune cell types beneficial to tumor control.
(a) Representative flow cytometric plots and quantification of basal levels of NK cell numbers and relative percentage and Ki-67 and c-Myc expression in the lungs of naïve IRE1NK and IRE1f/f littermate control mice. (b) Gating strategy for c. (c) Percentage of conventional type 1 dendritic cells (cDC1) (left), CD8+ T cells (middle), and CD4+ T cells (right) in the lung and spleen of IRE1NK and IRE1f/f littermate control mice at day 20 following intravenous injection of B16F10 melanoma cells. * p < 0.05, ** p < 0.01. Two tailed unpaired Student’s t-test performed on c. All error bars, mean with s.e.m. n = 4 mice/group for a and 5 mice/group for c. Data were independently repeated three times.
About this article
Cite this article
Dong, H., Adams, N.M., Xu, Y. et al. The IRE1 endoplasmic reticulum stress sensor activates natural killer cell immunity in part by regulating c-Myc. Nat Immunol 20, 865–878 (2019). https://doi.org/10.1038/s41590-019-0388-z
Skin immunization for effective treatment of multifocal melanoma refractory to PD1 blockade and Braf inhibitors
Journal for ImmunoTherapy of Cancer (2021)
Journal of Clinical Pathology (2021)
Targeted regulation of lymphocytic ER stress response with an overall immunosuppression to alleviate allograft rejection
Journal of Experimental Medicine (2021)