Abstract
Although chemotherapy can stimulate antitumor immunity by inducing interferon (IFN) response, the functional role of tumor-associated macrophages in this scenario remains unclear. Here, we found that IFN-activated proinflammatory macrophages after neoadjuvant chemotherapy enhanced antitumor immunity but promoted cancer chemoresistance. Mechanistically, IFN induced expression of cytoplasmic long noncoding RNA IFN-responsive nuclear factor-κB activator (IRENA) in macrophages, which triggered nuclear factor-κB signaling via dimerizing protein kinase R and subsequently increased production of protumor inflammatory cytokines. By constructing macrophage-conditional IRENA-knockout mice, we found that targeting IRENA in IFN-activated macrophages abrogated their protumor effects, while retaining their capacity to enhance antitumor immunity. Clinically, IRENA expression in post-chemotherapy macrophages was associated with poor patient survival. These findings indicate that lncRNA can determine the dichotomy of inflammatory cells on cancer progression and antitumor immunity and suggest that targeting IRENA is an effective therapeutic strategy to reversing tumor-promoting inflammation.
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 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
RNA microarray data generated for this study have been deposited in the NCBI GEO database and are accessible through GEO accession nos. GSE134599, GSE134600 and GSE134601. The sequence data generated have been deposited in NCBI’s Sequence Read Archive database and are accessible through accession nos. PRJNA555730 (RNA), PRJNA555733 (RNA) and PRJNA555732 (DNA). The PRIDE database accession nos. for proteomics data reported in this paper are PXD022673 and PXD022674. Source data for Figs. 1–5 and 7 and Extended Data Figs. 2–10 are provided in Source Data files. All other data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.
References
Sistigu, A. et al. Cancer cell-autonomous contribution of type I interferon signaling to the efficacy of chemotherapy. Nat. Med. 20, 1301–1309 (2014).
Parker, B. S., Rautela, J. & Hertzog, P. J. Antitumour actions of interferons: implications for cancer therapy. Nat. Rev. Cancer 16, 131–144 (2016).
Takeuchi, S. et al. Chemotherapy-derived inflammatory responses accelerate the formation of immunosuppressive myeloid cells in the tissue microenvironment of human pancreatic cancer. Cancer Res. 75, 2629–2640 (2015).
Valkenburg, K. C., de Groot, A. E. & Pienta, K. J. Targeting the tumour stroma to improve cancer therapy. Nat. Rev. Clin. Oncol. 15, 366–381 (2018).
Cassetta, L. & Pollard, J. W. Targeting macrophages: therapeutic approaches in cancer. Nat. Rev. Drug Discov. 17, 887–904 (2018).
Channappanavar, R. et al. Dysregulated type I interferon and inflammatory monocyte-macrophage responses cause lethal pneumonia in SARS-CoV-infected mice. J. Immunol. https://doi.org/10.1016/j.chom.2016.01.007 (2016).
Lawrence, T. & Natoli, G. Transcriptional regulation of macrophage polarization: enabling diversity with identity. Nat. Rev. Immunol. 11, 750–761 (2011).
Bronte, V. & Murray, P. J. Understanding local macrophage phenotypes in disease: modulating macrophage function to treat cancer. Nat. Med. 21, 117–119 (2015).
Muller, E. et al. Both type I and type II interferons can activate antitumor M1 macrophages when combined with TLR stimulation. Front. Immunol. 9, 2520 (2018).
Di Mitri, D. et al. Re-education of tumor-associated macrophages by CXCR2 blockade drives senescence and tumor inhibition in advanced prostate cancer. Cell Rep. 28, 2156–2168 (2019).
Pyonteck, S. M. et al. CSF-1R inhibition alters macrophage polarization and blocks glioma progression. Nat. Med. 19, 1264–1272 (2013).
Novikov, A. et al. Mycobacterium tuberculosis triggers host type I IFN signaling to regulate IL-1β production in human macrophages. J. Immunol. 187, 2540–2547 (2011).
Chittezhath, M. et al. Molecular profiling reveals a tumor-promoting phenotype of monocytes and macrophages in human cancer progression. Immunity 41, 815–829 (2014).
Xu, H. et al. Tumor-associated macrophage-derived IL-6 and IL-8 enhance invasive activity of LoVo cells induced by PRL-3 in a KCNN4 channel-dependent manner. BMC Cancer 14, 330 (2014).
Chen, Y. G., Satpathy, A. T. & Chang, H. Y. Gene regulation in the immune system by long noncoding RNAs. Nat. Immunol. 18, 962–972 (2017).
Satpathy, A. T. & Chang, H. Y. Long noncoding RNA in hematopoiesis and immunity. Immunity 42, 792–804 (2015).
Atianand, M. K. et al. A long noncoding RNA lincRNA-EPS acts as a transcriptional brake to restrain inflammation. Cell 165, 1672–1685 (2016).
Carpenter, S. et al. A long noncoding RNA mediates both activation and repression of immune response genes. Science 341, 789–792 (2013).
Liu, B. et al. A cytoplasmic NF-κB interacting long noncoding RNA blocks IκB phosphorylation and suppresses breast cancer metastasis. Cancer Cell 27, 370–381 (2015).
Liu, C. X. et al. Structure and degradation of circular RNAs regulate PKR activation in innate immunity. Cell 177, 865–880 (2019).
Jiang, M. et al. Self-recognition of an inducible host lncRNA by RIG-I feedback restricts innate immune response. Cell 173, 906–919 (2018).
Huang, D. et al. NKILA lncRNA promotes tumor immune evasion by sensitizing T cells to activation-induced cell death. Nat. Immunol. 19, 1112–1125 (2018).
Breschi, A., Gingeras, T. R. & Guigo, R. Comparative transcriptomics in human and mouse. Nat. Rev. Genet. 18, 425–440 (2017).
Ries, C. H. et al. Targeting tumor-associated macrophages with anti-CSF-1R antibody reveals a strategy for cancer therapy. Cancer Cell 25, 846–859 (2014).
Mehta, A. K. et al. Targeting immunosuppressive macrophages overcomes PARP inhibitor resistance in BRCA1-associated triple-negative breast cancer. Nat. Cancer https://doi.org/10.1038/s43018-020-00148-7 (2020).
Harbeck, N. & Gnant, M. Breast cancer. Lancet 389, 1134–1150 (2017).
Galluzzi, L., Buque, A., Kepp, O., Zitvogel, L. & Kroemer, G. Immunological effects of conventional chemotherapy and targeted anticancer agents. Cancer Cell 28, 690–714 (2015).
Su, S. C. et al. Blocking the recruitment of naive CD4(+) T cells reverses immunosuppression in breast cancer. Cell Res. 27, 461–482 (2017).
Su, S. C. et al. Immune checkpoint inhibition overcomes ADCP-induced immunosuppression by macrophages. Cell 175, 442–457 (2018).
Robbins, P. F. et al. Single and dual amino acid substitutions in TCR CDRs can enhance antigen-specific T cell functions. J. Immunol. 180, 6116–6131 (2008).
Patel, S. J. et al. Identification of essential genes for cancer immunotherapy. Nature 548, 537–542 (2017).
Du, B. & Waxman, D. J. Medium dose intermittent cyclophosphamide induces immunogenic cell death and cancer cell autonomous type I interferon production in glioma models. Cancer Lett. 470, 170–180 (2020).
Aldonza, M. B., Hong, J. Y. & Lee, S. K. Paclitaxel-resistant cancer cell-derived secretomes elicit ABCB1-associated docetaxel cross-resistance and escape from apoptosis through FOXO3a-driven glycolytic regulation. Exp. Mol. Med. 49, e286 (2017).
Williams, C. B., Yeh, E. S. & Soloff, A. C. Tumor-associated macrophages: unwitting accomplices in breast cancer malignancy. npj Breast Cancer https://doi.org/10.1038/npjbcancer.2015.25 (2016).
Takada, Y., Ichikawa, H., Pataer, A., Swisher, S. & Aggarwal, B. B. Genetic deletion of PKR abrogates TNF-induced activation of IκBα kinase, JNK, Akt and cell proliferation but potentiates p44/p42 MAPK and p38 MAPK activation. Oncogene 26, 1201–1212 (2007).
Gil, J., Alcami, J. & Esteban, M. Activation of NF-κB by the dsRNA-dependent protein kinase, PKR involves the I κB kinase complex. Oncogene 19, 1369–1378 (2000).
Kumar, A., Haque, J., Lacoste, J., Hiscott, J. & Williams, B. R. Double-stranded RNA-dependent protein kinase activates transcription factor NF-κB by phosphorylating I κB. Proc. Natl Acad. Sci. USA 91, 6288–6292 (1994).
Dabo, S. & Meurs, E. F. dsRNA-dependent protein kinase PKR and its role in stress, signaling and HCV infection. Viruses 4, 2598–2635 (2012).
Zuker, M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 31, 3406–3415 (2003).
Hofacker, I. L. Vienna RNA secondary structure server. Nucleic Acids Res. 31, 3429–3431 (2003).
Orillion, A. et al. Dietary protein restriction reprograms tumor-associated macrophages and enhances immunotherapy. Clin. Cancer Res. 24, 6383–6395 (2018).
Yeh, H. W. et al. PSPC1 mediates TGF-β1 autocrine signalling and Smad2/3 target switching to promote EMT, stemness and metastasis. Nat. Cell Biol. 20, 479–491 (2018).
Junt, T. & Barchet, W. Translating nucleic acid-sensing pathways into therapies. Nat. Rev. Immunol. 15, 529–544 (2015).
Chan, Y. K. & Gack, M. U. Viral evasion of intracellular DNA and RNA sensing. Nat. Rev. Microbiol. 14, 360–373 (2016).
Hou, Y. et al. Non-canonical NF-κB Antagonizes STING sensor-mediated DNA sensing in radiotherapy. Immunity 49, 490–503 (2018).
Gupta, S. C. & Tripathi, Y. N. Potential of long non-coding RNAs in cancer patients: from biomarkers to therapeutic targets. Int. J. Cancer 140, 1955–1967 (2017).
Shen, W. et al. Chemical modification of PS-ASO therapeutics reduces cellular protein-binding and improves the therapeutic index. Nat. Biotechnol. 37, 640–650 (2019).
Crooke, S. T. Molecular mechanisms of antisense oligonucleotides. Nucleic Acid Ther. 27, 70–77 (2017).
Arun, G. et al. Differentiation of mammary tumors and reduction in metastasis upon Malat1 LncRNA loss. Cancer Res. https://doi.org/10.1158/1538-7445.Nonrna15-Pr11 (2016).
Pandey, S. K. et al. Identification and characterization of modified antisense oligonucleotides targeting DMPK in mice and nonhuman primates for the treatment of myotonic dystrophy type 1. J. Pharmacol. Exp. Ther. 355, 329–340 (2015).
Adams, B. D., Parsons, C., Walker, L., Zhang, W. C. & Slack, F. J. Targeting noncoding RNAs in disease. J. Clin. Invest. 127, 761–771 (2017).
Cheng, C. J. et al. MicroRNA silencing for cancer therapy targeted to the tumour microenvironment. Nature 518, 107–110 (2015).
Shen, Y. et al. Loss-of-function mutations in QRICH2 cause male infertility with multiple morphological abnormalities of the sperm flagella. Nat. Commun. 10, 433 (2019).
Acknowledgements
We thank all the healthy donors and patients who volunteered their blood or tissue samples for this study. This work was supported by grants from the National Key Research and Development Program of China (2016YFC1302300 and 2017YFA0106300), the Natural Science Foundation of China (81621004, 81720108029, 81930081, 91940305, 91942309, 81672614, 81902699, 81802645 and 81860546), Guangdong Science and Technology Department (2017B030314026, 2019A1515011485, 2020B1212030004 and 2020B1212060018), Clinical Innovation Research Program of Bioland Laboratory (2018GZR0201004), Guangzhou Science Technology and Innovation Commission (201803040015), the Program for Guangdong Introducing Innovative and Entrepreneurial Teams (2019BT02Y198), Tip-top Scientific and Technical Innovative Youth Talents of Guangdong special support program (no. 2016TQ03R553) and China Postdoctoral Science Foundation (2018M640868, BX20190396 and 2019M663270). The research is partly supported by the Fountain-Valley Life Sciences Fund of the University of Chinese Academy of Sciences Education Foundation.
Author information
Authors and Affiliations
Contributions
E.S., S.S. and J.L. conceived the ideas and designed the research. J.L., L.L., J.C., J.L., W.Z., X.Z., J.L., X.C., L.Y., Y.X., F.C., D.H. and X.Z. performed the experiments. W.W., C.G., S.H., Z.Y., Z.L., L.Y., J.L., X.L., Q.Z. and X.M. provided external clinical samples. J.L., L.S., M.Z. and M.L. participated in study design. J.L., L.L., J.C., Q.L. and S.S. analyzed the data. J.L., L.L. and J.C. drafted the paper and figures. S.S. and E.S. revised the paper and figures. All authors reviewed the paper.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Peer review information Nature Cancer thanks George Calin, Luca Cassetta and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Infiltrated macrophages are associated with chemoresistance and poor prognosis.
a, Representative immunofluorescent images of CD68 and CD8 staining in human breast cancer before chemotherapy (upper) and after chemotherapy (lower). b, Representative immunofluorescent images of CD163 and CD8 staining in human breast cancer before chemotherapy (upper) and after chemotherapy (lower). a & b, Number of CD68+/CD163+ macrophages (green) or CD8+ T cells (red) per field was quantified by ImageJ and showed in Fig. 1b, Extended Data Fig. 1c. Complete remission (CR) or partial remission (PR) was classified as chemosensitive, while stable disease (SD) or progressive disease (PD) was chemoresistant. Scale bar, 50 μm. c, The counts of CD68+ macrophages in clinical breast tumor samples of internal cohort before and after neoadjuvant chemotherapy correlate with therapeutic efficacy. mean ± s.e.m., n = 409 patients, statistical significance was determined by two-sided one-way ANOVA with Tukey test. d & e, Kaplan-Meier survival curves for breast cancer patients with low (< 12 cells per field) and high CD163+ macrophage (≥ 12 cells per field) infiltration in the tumor samples before or after chemotherapy of internal cohort (d, n = 409 patients) and external cohort (e, n = 316 patients). f & g, Kaplan-Meier curves for disease-free survival of breast cancer patients with low (blue line) and high (red line) CD163+ macrophage infiltration in the biopsies of breast tumors of different subtypes before chemotherapy (f) and after chemotherapy (g) of two cohorts (ER positive, n = 325 patients; HER2 positive, n = 234 patients; Triple negative, n = 166 patients). d-g, P values were calculated with the two-sided log-rank test. h, Graphs depict the correlation between the counts of CD68+ macrophages and CD8+ T cells in breast cancer samples of internal cohort before (left) and after chemotherapy (right), P values were determined by two-tailed Pearson correlation coefficient test. i, Representative flow plots of the purified macrophages and CD8+ CTLs from breast tumor, > 90% purity of purified cells were confirmed.
Extended Data Fig. 2 Macrophages polarized by chemotherapy promote therapeutic resistance of breast cancer but enhance anti-tumor immunity.
a, left: flow cytometry measured transduction efficiency of CD8+ T cells transduced with a lentiviral vector encoding NY-ESO-1-TCR; right: western blot measured transduction efficiency of MCF-7 cells transduced with a lentiviral vector encoding NY-ESO-1. CD8+ T cells were obtained from the peripheral blood of breast cancer patients. The experiments were performed twice with similar results each. b, Representative flow plots of the purified macrophages and CD8+ T cells from PBMCs, > 90% purity of purified cells were confirmed. c, Schematic of tumor-conditioned macrophages (Tc-Mϕ) induced in vitro. Human peripheral blood derived macrophages (PBDMs) were cultured alone or co-cultured with tumor cells pretreated without chemotherapeutics (Tc-Mϕ) or with chemotherapeutics (chemo-macrophages, chemo-Mϕ). ADM, adriamycin; DTX, docetaxel. d, Representative flow plots showing ADM induced apoptosis of tumor cells cultured alone or co-cultured with PBDMs, Tc-Mϕ or chemo-Mϕ. mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with ADM treated tumor cells. e, Electron microscopy of MCF-7, SKBR3 and MDA-MB-231 cells treated with ADM co-cultured with PBDMs, Tc-Mϕ or chemo-Mϕ. The experiment was performed twice with similar results. Scale bar, 5 μm. f, ADM (2 μg/ml) affected cell cycle arrest. mean ± s.e.m., n = 3 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with untreated tumor cells; ns, not significant by two-sided one-way ANOVA with Tukey test compared with ADM treated tumor cells. g, The expression of perforin (upper) and granzyme B (lower) in CD8+ T cells cultured alone or co-cultured with PBDMs, Tc-Mϕ or chemo-Mϕ. mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test. h, Chemotaxis of CD8+ CTLs cultured alone or co-culture with PBDMs, Tc-Mϕ or chemo-Mϕ 16 hr after seeding in Boyden Chambers. mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test.
Extended Data Fig. 3 Macrophages exhibit proinflammatory phenotype after neoadjuvant chemotherapy.
a, Schematic of animal experiments showing treatment of chemotherapeutics. b, Representative images of CD8 staining in the tumors of PyMT;C3 or PyMT;Csf1op mice after ADM treatment. The experiment was performed three times with similar results. Scale bar, 400 μm. c, Representative heatmaps for the differentially expressed genes (fold change > 3) in the macrophages isolated from paired breast tumor samples of four patients before and after neoadjuvant chemotherapy. The expression levels were shown in log2-transformed values. d, GSEA analysis of mRNA profiles revealed enrichment of Jak1-STAT1 and NF-κB target genes in the macrophages isolated from breast cancer samples obtained after chemotherapy and enrichment of IL-4-STAT6 target genes before chemotherapy. e, Quantitative RT-PCR for cytokine mRNA expression in the macrophages obtained before or after chemotherapy. mean ± s.e.m., n = 5 patients, statistical significance was determined by two-tailed Student’s t test. f, Representative images of IFNα and IFNβ staining (green) in the CD163+ macrophages (red) and CK+ tumor cells (white) of the clinical samples from breast cancer patients before and after neo-adjuvant chemotherapy. The experiment was performed three times with similar results. Scale bar, 200 μm. g, ELISA for IFNα produced by primary tumor cells and macrophages isolated from PyMT mice with or without ADM treatment. mean ± s.e.m., n = 3 independent experiments, statistical significance was determined by two-tailed Student’s t test compared with PBS treated group. h, ELISA for the cytokines IL-6, CXCL15, TNFα, IL-15, CXCL9 and CXCL10 produced by macrophages isolated from breast tumors in MMTV-PyMT mice treated with or without chemotherapy in the presence of IgG or IFNAR1 neutralizing antibody. mean ± s.e.m., n = 8 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with ADM and IgG treated mice.
Extended Data Fig. 4 Macrophages polarized by chemotherapy promote anti-tumor immunity via Jak1-STAT1 signaling.
a, ELISA for cytokines released by macrophages obtained following chemotherapy treated with or without Jak-STAT1 inhibitors (Ruxolitinib or Fludarabine) or NF-κB inhibitors (SC3060 or JSH23). mean ± s.e.m., n = 4 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with PBS treated macrophages. b, IC50 for the ADM-treated MCF-7 (upper) and E0771 (lower) co-cultured with Tc-Mϕ or chemo-Mϕ in the presence or absence of IL-15, CXCL9, CXCL10 or IL-6 neutralizing antibody. mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with MCF-7 or E0771 cells co-cultured with untreated (-) chemo-Mϕ. c, Chemotactic assays for the CD8+ CTLs cultured alone or co-cultured with chemo-Mϕ in the presence or absence of CXCL9, CXCL10 or IL-6 neutralizing antibody. Scale bar, 200 μm. Quantitative data are shown as mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with CD8+ CTLs co-cultured with untreated (-) chemo-Mϕ. d, IC50 for the ADM treated (left) and DTX treated (right) MCF-7 cells co-cultured with PBDMs, Tc-Mϕ or chemo-Mϕ in the presence or absence of indicated inhibitors. SC3060 and JSH23, NF-κB inhibitors. mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with MCF-7 cells co-cultured with untreated (-) chemo-Mϕ.
Extended Data Fig. 5 IRENA is a conserved lncRNA between humans and mice.
a, qRT-PCR for IRENA expression in macrophages obtained from breast cancer patients before or after chemotherapy. mean ± s.e.m., n = 5 different patients, statistical significance was determined by two-tailed Student’s t test. b, qRT-PCR for IRENA expression in macrophages obtained from PyMT mice treated by ADM or DTX. mean ± s.e.m., n = 8 independent experiments, statistical significance was determined by two-tailed Student’s t test compared with PBS treated group respectively. c, Diagram for the genomic location of human IRENA (left) and mouse IRENA (right). d & e, Genome browser (UCSC, http://genome.ucsc.edu/) depiction of IRENA and its conserved analogs in human (d) and mouse (e), IRENA is annotated as ENST00000623256 in the human assembly and ENSMUST00000136998 in the mouse assembly. f, Assessment of the protein-coding potential of IRENA. The experiment was performed twice with similar results. g & h, The best match of predicted short peptides and mass spectrometer detected peptides of human (g) and mouse (h). i, qRT-PCR showing expression of IRENA in different tissues or cells in MMTV-PyMT mice with or without chemotherapy treatment. mean ± s.e.m., n = 3 independent experiments. j, Northern blot for IRENA expression in the cytoplasm and nucleus of macrophages treated with IFNα. The experiment was performed twice with similar results. k, qRT-PCR for mouse IRENA expression in the macrophages obtained from mouse treated with IFNα or IFNβ in the presence or absence of IFNAR1-neutralizing antibody. mean ± s.e.m., n = 3 independent experiments, statistical significance was determined by two-tailed Student’s t test compared with the IgG group respectively. l, qRT-PCR showing estimated copy numbers of IRENA per macrophage in human and mouse. Equivalent molecules per cell were calculated based on the assumption that total RNA per macrophage is 10 pg.
Extended Data Fig. 6 Type I interferon enhances IRENA expression in macrophages via Jak1-STAT1-ISGF3 signal.
a, qRT-PCR for IRENA expression in macrophages treated with or without Jak-STAT1 inhibitors (Ruxolitinib or Fludarabine) or NF-κB inhibitors (SC3060 or JSH23). mean ± s.e.m., n = 3 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with IFNα or IFNβ treated macrophages without DMSO/inhibitors respectively. b, Luciferase reporter assays for the transcription activities of IRENA promoter region (−1881 to +83 nt relative to TSS of human IRENA, −1787 to +126 nt relative to TSS of mouse IRENA) or its deleting variants cloned upstream of the firefly luciferase coding region. Data were normalized to renilla luciferase and presented with respect to control vector (Vec) set to a value of 1. mean ± s.e.m., n = 3 independent experiments; statistical significance was determined by two-tailed Student’s t test. c, Diagram for the ISRE motif at the human and mouse IRENA promoter region. d, shRNA mediated knockdown efficiency of STAT1, STAT2, IRF9 or STAT3 in THP-1. The experiment was performed twice with similar results. e, Expression of IRENA in IFNα activated THP-1 cells treated by STAT1, STAT2, IRF9 and STAT3 shRNA. mean ± s.e.m., n = 4 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with the IFNα treated THP-1 cells. f & g, ChIP analysis for the binding of STAT1, STAT2 and IRF9 to IRENA promoter in macrophages treated with IFNα. mean ± s.e.m., n = 3 independent experiments, statistical significance was determined by two-tailed Student’s t test compared with the PBS treated cells.
Extended Data Fig. 7 IRENA promotes NF-κB activation but not Jak1-STAT1 activation in macrophages.
a, Efficiency of IRENA knockdown. mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with untreated (-) chemo-Mϕ. b, Chemotactic assays for CD8+ T cells cultured alone or co-cultured with chemo-Mϕ with or without IRENA knockdown. Scale bar, 200 μm. Quantitative data are shown as mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with CD8+ CTLs co-cultured with untreated (-) chemo-Mϕ. c, Flow cytometry for perforin (upper) and granzyme B (lower) levels in the human CD8+ T cells co-cultured in presence of chemo-Mϕ with or without IRENA knockdown. mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with untreated (-) chemo-Mϕ group. d, Tumoricidal effects of ESO CTLs affected by macrophages. CMFDA+PI− cells were designated as surviving tumor cells. mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with ESO CTLs co-cultured with untreated (-) chemo-Mϕ. e, Upper, a representative western blot for total and phosphorylated Jak1, STAT1, IKK and IκBα in control or IFNα treated PBDMs with or without IRENA knockdown. Lower, relative phosphorylated IKK and IκBα protein levels quantified from n= 3 independent experiments using ImageJ. Protein levels were normalized using GAPDH as the loading control. mean ± s.e.m., statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with IFNα treated PBDMs. f, GSEA analysis revealed enrichment of NF-κB target genes in the PBDMs overexpressed IRENA compared with control group (vector).
Extended Data Fig. 8 PKR is bound by IRENA.
a & b, Mass spectrometry analysis for the peptides of IRENA-interacting PKR. c, Western blot for the total and phosphorylated PKR of PKR/IRENA two-overexpressed macrophages or control macrophages. The experiment was performed twice with similar results. d, RNA pulldown assay for the in vitro interaction of sequentially deleted mouse IRENA variants with mouse PKR, n = 3 independent experiments. Upper, sequentially deleted mouse IRENA variants; lower, western blot of mouse PKR pulled by mouse IRENA variants. e, Predicted secondary structure of mouse IRENA817–1032 truncation by Mfold. f, Upper, western blot for the total mouse PKR (mPKR) pulled down by indicated mutant mouse IRENA fragments. (mIRENA, full-length mouse IRENA; mIR817–1032: IRENA truncation mutant containing nt 817–1032; mIR817–1032mA: mutations of hairpin A of nt 817–1032; mIR817–1032mB: mutations of hairpin B of nt 817–1032; mIR817–1032mA+B: mutations of hairpin A and hairpin B of nt 817–1032. A representative blot from three independent experiments is shown. Lower, relative pulled PKR protein levels quantified using ImageJ. Protein levels were normalized using PKR of input. Results are shown as the mean ± s.e.m. g, Bio-layer interferometry assays for the in vitro interaction of indicated mutant mouse IRENA fragments with mouse PKR, n = 3 independent experiments. h, qRT-PCR for the IRENA undergone RNase protection assay. IRENA was incubated with PKR or IgG and subjected to RNase T1 digestion prior to qRT-PCR examination. The fold enrichment of IRENA-PKR/IgG is shown for every 10 nt region ranging from nt 465 to 895 of human IRENA. mean ± s.e.m., n = 3 independent experiments.
Extended Data Fig. 9 Enhanced anti-tumor immunity sustains in IRENA conditional knockout mice post-chemotherapy.
a, Orientation of IRENA and neighbor gene transcription (upper: human; lower: mouse). b & c, Schematic overviews for the strategy to generate an IRENAloxp/loxp allele (b) and macrophage-specific knockout by Csf1r-cre homologous recombination (c), PyMT;KO, PyMT;KO;Tg mice were generated by cross-fertilizing. d, Expression of Nkx2-2, IRENA and Pax1 in macrophages of IRENA knockout mice or wild type mice. e, IRENA expression in PyMT;Csf1r-cre;IRENAloxp/loxp (KO), PyMT;Csf1r-cre;IRENAloxp/loxp;IRENATg (Tg) mice or background PyMT (WT) mice treated with ADM or PBS. d & e, mean ± s.e.m., n = 5 independent experiments, nd, not detected, statistical significance was determined by two-tailed Student’s t test. f, Schematic overview for the strategy to generate mice with transgenic overexpression of IRENA from the ROSA26 locus. g, Representative images of TUNEL+ (green) apoptotic tumor cells in the tumor sections of mice with or without chemotherapy. The experiment was performed twice with similar results. Scale bar, 50 μm. h, Representative flow plots of the purified CD8+ CTLs > 90% purity of the populations from tumors of PyMT mice. i, Chemotactic assays for the mouse CD8+ T cells co-cultured with macrophages purified from the tumors of PyMT;KO, PyMT;KO;Tg and PyMT mice treated with or without chemotherapy. Scale bar, 200 μm. Quantitative data are shown as mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test. j-n, Representative flow plots for perforin (j), granzyme B (k), CD38 (l), CD69 (m) and IFNγ (n) levels of CD8+ T cells purified from the tumors of PyMT;KO, PyMT;KO;Tg and PyMT mice treated with or without chemotherapy. mean ± s.e.m., n = 5 independent experiments, statistical significance was determined by two-sided one-way ANOVA with Tukey test compared with ADM treated PyMT mice. o, Representative images of F4/80 staining (red) in the tumors of PyMT;C3 or PyMT;Csf1op mice with or without macrophage transfer. The experiment was performed twice with similar results. Scale bar, 400 μm.
Extended Data Fig. 10 High IRENA expression in macrophages is associated with poor clinical outcomes in breast cancer patients.
a, Correlation between RNA expression of IRENA and cytokines IL-6, IL-8, TNFα, IL-15, CXCL9 and CXCL10 in macrophages in the breast tumor samples obtained following chemotherapy, P values were determined by two-tailed Pearson correlation coefficient test, n = 26 patients. b, Representative images of FISH for IRENA and immunofluorescent staining for CD68 in the paraffin-embedded tumor sections of chemotherapy-sensitive or resistant breast cancer patients (IRENA, green; CD68, red). Scale bar, 50 μm. c, Number of IRENA+ macrophages per field correlated with therapeutic efficacy of internal cohort. mean ± s.e.m., statistical significance was determined by two-sided one-way ANOVA with Tukey test. d, Kaplan-Meier survival curves for breast cancer patients of two cohorts with low and high IRENA+ macrophage infiltration in three different subtypes. e, Kaplan-Meier survival curves for breast cancer patients with low and high IRENA+ macrophage infiltration in three grades (grade 1, grade 2 and grade 3). f, Kaplan-Meier survival curves for breast cancer patients with low and high IRENA+ macrophage infiltration in three stages (stage I, stage II and stage III). g, Kaplan-Meier survival curves for breast cancer patients with low and high IRENA+ macrophage infiltration stratified by Ki67 status (Ki67 < 15%, Ki67 ≥ 15%). d-g, P values were calculated with the two-sided log-rank test.
Supplementary information
Supplementary information
Supplementary Tables 1–10.
Source data
Source Data Fig. 1
Statistical Source Data
Source Data Fig. 2
Statistical Source Data
Source Data Fig. 3
Statistical Source Data
Source Data Fig. 4
Statistical Source Data
Source Data Fig. 4
Unprocessed western blots
Source Data Fig. 5
Statistical Source Data
Source Data Fig. 5
Unprocessed western blots and gel
Source Data Fig. 6
Unprocessed western blots
Source Data Fig. 7
Statistical Source Data
Source Data Fig. 7
Unprocessed western blots
Source Data Extended Data Fig. 2
Statistical Source Data
Source Data Extended Data Fig. 2
Unprocessed western blots
Source Data Extended Data Fig. 3
Statistical Source Data
Source Data Extended Data Fig. 4
Statistical Source Data
Source Data Extended Data Fig. 5
Statistical Source Data
Source Data Extended Data Fig. 5
Unprocessed western blots
Source Data Extended Data Fig. 6
Statistical Source Data
Source Data Extended Data Fig. 6
Unprocessed western blots
Source Data Extended Data Fig. 7
Statistical Source Data
Source Data Extended Data Fig. 7
Unprocessed western blots
Source Data Extended Data Fig. 8
Statistical Source Data
Source Data Extended Data Fig. 8
Unprocessed western blots
Source Data Extended Data Fig. 9
Statistical Source Data
Source Data Extended Data Fig. 10
Statistical Source Data
Rights and permissions
About this article
Cite this article
Liu, J., Lao, L., Chen, J. et al. The IRENA lncRNA converts chemotherapy-polarized tumor-suppressing macrophages to tumor-promoting phenotypes in breast cancer. Nat Cancer 2, 457–473 (2021). https://doi.org/10.1038/s43018-021-00196-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s43018-021-00196-7
This article is cited by
-
Cancer-associated fibroblast-specific lncRNA LINC01614 enhances glutamine uptake in lung adenocarcinoma
Journal of Hematology & Oncology (2022)
-
Cyclin G2 in macrophages triggers CTL-mediated antitumor immunity and antiangiogenesis via interferon-gamma
Journal of Experimental & Clinical Cancer Research (2022)
-
Reactive oxygen species-responsive and Raman-traceable hydrogel combining photodynamic and immune therapy for postsurgical cancer treatment
Nature Communications (2022)
-
The systemic effect of type 1 interferon responsiveness on tumor immunotherapy
Nature Immunology (2022)
-
Long noncoding RNA DIO3OS induces glycolytic-dominant metabolic reprogramming to promote aromatase inhibitor resistance in breast cancer
Nature Communications (2022)