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Normal and cancerous mammary stem cells evade interferon-induced constraint through the miR-199a–LCOR axis

Abstract

Tumour-initiating cells, or cancer stem cells (CSCs), possess stem-cell-like properties observed in normal adult tissue stem cells. Normal and cancerous stem cells may therefore share regulatory mechanisms for maintaining self-renewing capacity and resisting differentiation elicited by cell-intrinsic or microenvironmental cues. Here, we show that miR-199a promotes stem cell properties in mammary stem cells and breast CSCs by directly repressing nuclear receptor corepressor LCOR, which primes interferon (IFN) responses. Elevated miR-199a expression in stem-cell-enriched populations protects normal and malignant stem-like cells from differentiation and senescence induced by IFNs that are produced by epithelial and immune cells in the mammary gland. Importantly, the miR-199a–LCOR–IFN axis is activated in poorly differentiated ER breast tumours, functionally promotes tumour initiation and metastasis, and is associated with poor clinical outcome. Our study therefore reveals a common mechanism shared by normal and malignant stem cells to protect them from suppressive immune cytokine signalling.

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Figure 1: miR-199a is enriched in MaSCs and is functionally critical for MaSC activity.
Figure 2: miR-199a induces stem-cell-like gene signatures and is enriched in cancer stem cells.
Figure 3: Identification of LCOR as a direct target gene of miR-199a.
Figure 4: LCOR suppresses MaSC function and is downregulated in stem cell populations.
Figure 5: miR-199a and LCOR functionally influence the initiation of ER breast tumours in vivo.
Figure 6: LCOR primes the IFN-α response.
Figure 7: Stem cells and differentiated cells respond differently to the IFN-α signalling.
Figure 8: Immune and autocrine IFN-related effects on mammary gland and tumour cells.

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References

  1. 1

    Visvader, J. E. & Stingl, J. Mammary stem cells and the differentiation hierarchy: current status and perspectives. Genes Dev. 28, 1143–1158 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2

    Nguyen, L. V., Vanner, R., Dirks, P. & Eaves, C. J. Cancer stem cells: an evolving concept. Nat. Rev. Cancer 12, 133–143 (2012).

    CAS  PubMed  Google Scholar 

  3. 3

    Chakrabarti, R. et al. ΔNp63 promotes stem cell activity in mammary gland development and basal-like breast cancer by enhancing Fzd7 expression and Wnt signalling. Nat. Cell Biol. 16, 1004–1015 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4

    Guo, W. et al. Slug and Sox9 cooperatively determine the mammary stem cell state. Cell 148, 1015–1028 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5

    Shimono, Y. et al. Downregulation of miRNA-200c links breast cancer stem cells with normal stem cells. Cell 138, 592–603 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6

    Ben-Porath, I. et al. An embryonic stem cell-like gene expression signature in poorly differentiated aggressive human tumors. Nat. Genet. 40, 499–507 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7

    Prat, A. et al. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res. 12, R68 (2010).

    PubMed  PubMed Central  Google Scholar 

  8. 8

    Al-Hajj, M., Wicha, M. S., Benito-Hernandez, A., Morrison, S. J. & Clarke, M. F. Prospective identification of tumorigenic breast cancer cells. Proc. Natl Acad. Sci. USA 100, 3983–3988 (2003).

    CAS  PubMed  Google Scholar 

  9. 9

    Liu, S. et al. Breast cancer stem cells transition between epithelial and mesenchymal states reflective of their normal counterparts. Stem Cell Rep. 2, 78–91 (2014).

    CAS  Google Scholar 

  10. 10

    Mani, S. A. et al. The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell 133, 704–715 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11

    Gyorki, D. E., Asselin-Labat, M. L., van Rooijen, N., Lindeman, G. J. & Visvader, J. E. Resident macrophages influence stem cell activity in the mammary gland. Breast Cancer Res. 11, R62 (2009).

    PubMed  PubMed Central  Google Scholar 

  12. 12

    Drukker, M. & Benvenisty, N. The immunogenicity of human embryonic stem-derived cells. Trends Biotechnol. 22, 136–141 (2004).

    CAS  PubMed  Google Scholar 

  13. 13

    Cordon-Cardo, C. et al. Expression of HLA-A, B, C antigens on primary and metastatic tumor cell populations of human carcinomas. Cancer Res. 51, 6372–6380 (1991).

    CAS  PubMed  Google Scholar 

  14. 14

    Bruttel, V. S. & Wischhusen, J. Cancer stem cell immunology: key to understanding tumorigenesis and tumor immune escape? Front. Immunol. 5, 360 (2014).

    PubMed  PubMed Central  Google Scholar 

  15. 15

    Gangaraju, V. K. & Lin, H. MicroRNAs: key regulators of stem cells. Nat. Rev. Mol. Cell Biol. 10, 116–125 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16

    Lujambio, A. & Lowe, S. W. The microcosmos of cancer. Nature 482, 347–355 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17

    Pal, B. et al. Integration of microRNA signatures of distinct mammary epithelial cell types with their gene expression and epigenetic portraits. Breast Cancer Res. 17, 85 (2015).

    PubMed  PubMed Central  Google Scholar 

  18. 18

    Greene, S. B., Gunaratne, P. H., Hammond, S. M. & Rosen, J. M. A putative role for microRNA-205 in mammary epithelial cell progenitors. J. Cell Sci. 123, 606–618 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19

    Ibarra, I., Erlich, Y., Muthuswamy, S. K., Sachidanandam, R. & Hannon, G. J. A role for microRNAs in maintenance of mouse mammary epithelial progenitor cells. Genes Dev. 21, 3238–3243 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20

    Llobet-Navas, D. et al. The miR-424(322)/503 cluster orchestrates remodeling of the epithelium in the involuting mammary gland. Genes Dev. 28, 765–782 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21

    Ucar, A. et al. miR-212 and miR-132 are required for epithelial stromal interactions necessary for mouse mammary gland development. Nat. Genet. 42, 1101–1108 (2010).

    CAS  PubMed  Google Scholar 

  22. 22

    Bockmeyer, C. L. et al. MicroRNA profiles of healthy basal and luminal mammary epithelial cells are distinct and reflected in different breast cancer subtypes. Breast Cancer Res. Treat. 130, 735–745 (2011).

    CAS  PubMed  Google Scholar 

  23. 23

    Dvinge, H. et al. The shaping and functional consequences of the microRNA landscape in breast cancer. Nature 497, 378–382 (2013).

    CAS  PubMed  Google Scholar 

  24. 24

    Zhu, M. et al. Integrated miRNA and mRNA expression profiling of mouse mammary tumor models identifies miRNA signatures associated with mammary tumor lineage. Genome Biol. 12, R77 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25

    Liu, S., Clouthier, S. G. & Wicha, M. S. Role of microRNAs in the regulation of breast cancer stem cells. J. Mammary Gland Biol. Neoplasia 17, 15–21 (2012).

    PubMed  PubMed Central  Google Scholar 

  26. 26

    Plaks, V. et al. Lgr5-expressing cells are sufficient and necessary for postnatal mammary gland organogenesis. Cell Rep. 3, 70–78 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27

    Lim, E. et al. Transcriptome analyses of mouse and human mammary cell subpopulations reveal multiple conserved genes and pathways. Breast Cancer Res. 12, R21 (2010).

    PubMed  PubMed Central  Google Scholar 

  28. 28

    Gupta, P. B. et al. Identification of selective inhibitors of cancer stem cells by high-throughput screening. Cell 138, 645–659 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29

    Visvader, J. E. Keeping abreast of the mammary epithelial hierarchy and breast tumorigenesis. Genes Dev. 23, 2563–2577 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30

    Taube, J. H. et al. Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes. Proc. Natl Acad. Sci. USA 107, 15449–15454 (2010).

    CAS  PubMed  Google Scholar 

  31. 31

    Lee, Y. B. et al. Twist-1 regulates the miR-199a/214 cluster during development. Nucleic Acids Res. 37, 123–128 (2009).

    CAS  PubMed  Google Scholar 

  32. 32

    Beck, B. et al. Different levels of Twist1 regulate skin tumor initiation, stemness, and progression. Cell Stem Cell 16, 67–79 (2015).

    CAS  PubMed  Google Scholar 

  33. 33

    Celia-Terrassa, T. et al. Epithelial-mesenchymal transition can suppress major attributes of human epithelial tumor-initiating cells. J. Clin. Invest. 122, 1849–1868 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34

    Ocana, O. H. et al. Metastatic colonization requires the repression of the epithelial-mesenchymal transition inducer Prrx1. Cancer Cell 22, 709–724 (2012).

    CAS  PubMed  Google Scholar 

  35. 35

    Cho, R. W. et al. Isolation and molecular characterization of cancer stem cells in MMTV-Wnt-1 murine breast tumors. Stem Cells 26, 364–371 (2008).

    CAS  PubMed  Google Scholar 

  36. 36

    DeRose, Y. S. et al. Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nat. Med. 17, 1514–1520 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37

    Buffa, F. M. et al. microRNA-associated progression pathways and potential therapeutic targets identified by integrated mRNA and microRNA expression profiling in breast cancer. Cancer Res. 71, 5635–5645 (2011).

    CAS  PubMed  Google Scholar 

  38. 38

    Jiang, Y. Z. et al. Transcriptome analysis of triple-negative breast cancer reveals an integrated mRNA-lncRNA signature with predictive and prognostic value. Cancer Res. 76, 2105–2114 (2016).

    CAS  PubMed  Google Scholar 

  39. 39

    Calderon, M. R. et al. Ligand-dependent corepressor (LCoR) recruitment by Kruppel-like factor 6 (KLF6) regulates expression of the cyclin-dependent kinase inhibitor CDKN1A gene. J. Biol. Chem. 287, 8662–8674 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40

    Fernandes, I. et al. Ligand-dependent nuclear receptor corepressor LCoR functions by histone deacetylase-dependent and -independent mechanisms. Mol. Cell 11, 139–150 (2003).

    CAS  PubMed  Google Scholar 

  41. 41

    Lim, E. et al. Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers. Nat. Med. 15, 907–913 (2009).

    CAS  PubMed  Google Scholar 

  42. 42

    Gyorffy, B. et al. An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients. Breast Cancer Res. Treat. 123, 725–731 (2010).

    PubMed  PubMed Central  Google Scholar 

  43. 43

    Liu, R. et al. miR-199a-3p targets stemness-related and mitogenic signaling pathways to suppress the expansion and tumorigenic capabilities of prostate cancer stem cells. Oncotarget 7, 56628–56642 (2016).

    PubMed  PubMed Central  Google Scholar 

  44. 44

    Yin, G. et al. TWISTing stemness, inflammation and proliferation of epithelial ovarian cancer cells through MIR199A2/214. Oncogene 29, 3545–3553 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45

    Alemdehy, M. F. et al. ICL-induced miR139-3p and miR199a-3p have opposite roles in hematopoietic cell expansion and leukemic transformation. Blood 125, 3937–3948 (2015).

    CAS  PubMed  Google Scholar 

  46. 46

    Cuiffo, B. G. et al. MSC-regulated microRNAs converge on the transcription factor FOXP2 and promote breast cancer metastasis. Cell Stem Cell 15, 762–774 (2014).

    CAS  PubMed  Google Scholar 

  47. 47

    Chen, J. et al. miR-199a-5p confers tumor-suppressive role in triple-negative breast cancer. BMC Cancer 16, 887 (2016).

    PubMed  PubMed Central  Google Scholar 

  48. 48

    Asim, M. et al. Ligand-dependent corepressor acts as a novel androgen receptor corepressor, inhibits prostate cancer growth, and is functionally inactivated by the Src protein kinase. J. Biol. Chem. 286, 37108–37117 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49

    Bidwell, B. N. et al. Silencing of Irf7 pathways in breast cancer cells promotes bone metastasis through immune escape. Nat. Med. 18, 1224–1231 (2012).

    CAS  PubMed  Google Scholar 

  50. 50

    Zitvogel, L., Galluzzi, L., Kepp, O., Smyth, M. J. & Kroemer, G. Type I interferons in anticancer immunity. Nat. Rev. Immunol. 15, 405–414 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. 51

    McNab, F., Mayer-Barber, K., Sher, A., Wack, A. & O’Garra, A. Type I interferons in infectious disease. Nat. Rev. Immunol. 15, 87–103 (2015).

    CAS  PubMed  Google Scholar 

  52. 52

    Essers, M. A. et al. IFNα activates dormant haematopoietic stem cells in vivo. Nature 458, 904–908 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53

    Sato, T. et al. Interferon regulatory factor-2 protects quiescent hematopoietic stem cells from type I interferon-dependent exhaustion. Nat. Med. 15, 696–700 (2009).

    CAS  PubMed  Google Scholar 

  54. 54

    Schedin, P. Pregnancy-associated breast cancer and metastasis. Nat. Rev. Cancer 6, 281–291 (2006).

    CAS  PubMed  Google Scholar 

  55. 55

    Lehmann, B. D. et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J. Clin. Invest. 121, 2750–2767 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. 56

    Celia-Terrassa, T. & Kang, Y. Distinctive properties of metastasis-initiating cells. Genes Dev. 30, 892–908 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57

    Malladi, S. et al. Metastatic latency and immune evasion through autocrine inhibition of WNT. Cell 165, 45–60 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58

    Schatton, T., Frank, N. Y. & Frank, M. H. Identification and targeting of cancer stem cells. Bioessays 31, 1038–1049 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. 59

    Eriksson, M. et al. Oncolytic adenoviruses kill breast cancer initiating CD44+CD24−/low cells. Mol. Ther. 15, 2088–2093 (2007).

    CAS  PubMed  Google Scholar 

  60. 60

    James, C. D. et al. Chromosome 9 deletion mapping reveals interferon alpha and interferon beta-1 gene deletions in human glial tumors. Cancer Res. 51, 1684–1688 (1991).

    CAS  PubMed  Google Scholar 

  61. 61

    Lu, R., Au, W. C., Yeow, W. S., Hageman, N. & Pitha, P. M. Regulation of the promoter activity of interferon regulatory factor-7 gene. Activation by interferon snd silencing by hypermethylation. J. Biol. Chem. 275, 31805–31812 (2000).

    CAS  PubMed  Google Scholar 

  62. 62

    Shackleton, M. et al. Generation of a functional mammary gland from a single stem cell. Nature 439, 84–88 (2006).

    CAS  Google Scholar 

  63. 63

    Behan, J. W. et al. Activation of adipose tissue macrophages in obese mice does not require lymphocytes. Obesity 21, 1380–1388 (2013).

    CAS  PubMed  Google Scholar 

  64. 64

    Shultz, L. D. et al. Multiple defects in innate and adaptive immunologic function in NOD/LtSz-scid mice. J. Immunol. 154, 180–191 (1995).

    CAS  PubMed  Google Scholar 

  65. 65

    Chakrabarti, R. et al. Elf5 inhibits the epithelial-mesenchymal transition in mammary gland development and breast cancer metastasis by transcriptionally repressing Snail2. Nat. Cell Biol. 14, 1212–1222 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. 66

    Karantza-Wadsworth, V. & White, E. A mouse mammary epithelial cell model to identify molecular mechanisms regulating breast cancer progression. Methods Enzymol. 446, 61–76 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67

    Bonnefoy, F. et al. Plasmacytoid dendritic cells play a major role in apoptotic leukocyte-induced immune modulation. J. Immunol. 186, 5696–5705 (2011).

    CAS  PubMed  Google Scholar 

  68. 68

    Choi, Y. S., Chakrabarti, R., Escamilla-Hernandez, R. & Sinha, S. Elf5 conditional knockout mice reveal its role as a master regulator in mammary alveolar development: failure of Stat5 activation and functional differentiation in the absence of Elf5. Dev. Biol. 329, 227–241 (2009).

    CAS  PubMed  Google Scholar 

  69. 69

    Dontu, G. et al. In vitro propagation and transcriptional profiling of human mammary stem/progenitor cells. Genes Dev. 17, 1253–1270 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. 70

    Ritchie, M. E. et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

    PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank A. Welm for providing the PDX and A. Prat for technical advice for CL subtype classification. This work was supported by a Susan G. Komen Fellowship to T.C.-T. (PDF15332075), and grants from the Brewster Foundation, the Breast Cancer Research Foundation, Department of Defense (BC123187), and the National Institutes of Health (R01CA141062) to Y.K. This research was also supported by the Genomic Editing and Flow Cytometry Shared Resources of the Cancer Institute of New Jersey (P30CA072720).

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T.C.-T. and Y.K. designed experiments. T.C.-T., D.D.L., A.C., X.H., Y.W., R.A.-A., R.C., B.I.K. and H.A.S. performed the experiments. J.Z., Y.-Z.J., C.D., J.-J.L. and Z.-M.S. provided crucial samples and technical advice. T.C.-T. and Y.K. wrote the manuscript. All authors discussed the results and commented on the manuscript.

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Correspondence to Yibin Kang.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 miR-199a promotes MaSC activity and basal-like features.

(a) Mammary gland dissociation of different MEC (P3: Lin epithelial cells) populations and the lentiviral strategy to conduct gain- and loss-of function experiments. P4 denotes the MaSC-enriched LinCD24+CD29high basal population and P5 the LinCD24+CD29low luminal population. (b) qRT-PCR test of the miR-199a ectopic expression after lentiviral transduction of pLEX-miR-199a expression construct in different mammary epithelial cells (MECs) P3: total MECs; P4: basal/MaSC-enrich MECs; and P5: luminal MECs. The test was performed at least in 3 independent experiments for each cell population, and the figure shows one representative test. Source of data in Supplementary Table 4. (c) P3 cells were isolated and transduced with the control or miR-199a lentiviruses and subjected to limited dilution cleared fat pad reconstitution assay. (d) P4 cells were isolated and transduced with the indicated miRZIP constructs and subjected to limited dilution cleared fat pad reconstitution assay. In c and d Representative images show outgrowth. Each pie chart represents a mammary gland with the blackened area denoting the percentage of mammary gland outgrowth. Tables below represent serial dilution injections with the corresponding take rate. n = number of mammary fat pad injections as indicated in the table. Shown in red are the repopulation frequencies for each condition and P value by Pearson’s Chi-squared test, obtained with the ELDA software. (e) Keratin-14 (K14-green) and Keratin-8 (K8-red) staining with reconstituted mammary outgrowths from control and miR-199a-OE P5 cells. (f) Quantification of the K14+ basal cells of mammary outgrowth from control and miR-199a-OE P3, P4 and P5 cells. n = 10 ducts and terminal end buds (TEB) sections scored from 3 mammary outgrowths. (g) Table representing the mammary gland take-rate after cleared fat pad injection of unsorted MECs overexpressing miR-199a or control vector after 3 generations. Injected cell numbers are indicated. Scale bars: 2 mm in c and d; 25 μm in e. P < 0.05, P < 0.01 by two-tailed Student’s t-test in f.

Supplementary Figure 2 miR-199a enhances stem cell-like properties without inducing epithelial-mesenchymal transition (EMT).

(a) Venn diagram representation of the overlap of up-regulated miRNAs in P4-MaSCs with the up-regulated miRNAs in Claudin-low (CL) tumors based on the TCGA dataset (2015 release). The common core represents the top-5 common miRNAs in the CL subtype. (b) qRT-PCR quantification of miR-199a levels in control, TGF-β-treated and Twist1-ER-OE HMLE cells. (c) qRT-PCR analysis of EMT markers and transcription factors in miR-199a-OE and control HMLE cells. (d) GSEA of the reported transcriptional factors Nanog-Oct4-Sox2 (NOS-TFs) targets gene set1 in the ranked gene list of miR-199a-OE HMLE cells versus control cells. n = 3 biologically independent samples; data represents mean ± s.e.m. in b and c. P < 0.05, P < 0.01 by two-tailed Student’s t-test in b and c.

Supplementary Figure 3 Evaluation of LCOR as a miR-199a target.

(a) Western blot analysis of LCOR protein level in P4 (MaSCs) and P5 (Luminal) cells. (b) qRT-PCR analysis of Lcor in MaSC-enriched P4 cells, luminal progenitor cells (P5-CD61+) and luminal mature cells (P5-CD61); n = 3 biologically independent samples; data represents mean ± s.e.m. (c,d) qRT-PCR analysis of LCOR expression upon miR-199a ectopic expression in multiple mammary epithelial cell lines (c) and breast cancer cell lines (d). P < 0.05, P < 0.01 by two-tailed Student’s t-test in b and P value by two-tailed Student’s t-test in c,d.

Supplementary Figure 4 LCOR is a potent MaSC suppressor.

(a,b) qRT-PCR analysis of Lcor mRNA level in P4 transduced with pLEX vector or pLEX-Lcor (a) and P5 transduced with Lcor shRNA (b). (c) P4 cells were isolated and transduced with the indicated constructs, followed by cleared fat pad injections of 1,000 cells (n = 9 mouse mammary glands). Representative images and pie charts show the outgrowth and mammary gland filling percentage. Two-tailed Student’s t-test showed non-significance (n.s.). (d) qRT-PCR analysis of LCOR expression in control and LCOR-KD HMLE cells. (e) Quantification of mammospheres formed by 5,000 control and LCOR-KD HMLE cells. (f) Quantification of mammosphere formation of 10,000 control or LCOR-OE HMLE cells; counted at 8 days in e and f. Scale bars: 2 mm in c. n = 3 biologically independent samples; data represents mean ± s.e.m. and P < 0.05, P < 0.01, P < 0.005 by two-tailed Student’s t-test in a,b,d,e and f.

Supplementary Figure 5 miR-199a and LCOR clinical analysis and in vivo functional validation.

(a) Kaplan–Meier relapse free-survival (RFS) curve of triple-negative breast cancer (TNBC) patients stratified by higher or lower than the median miR-199a (n = 65 patients) and LCOR expression (n = 168 patients) in a previously described TNBC patient cohort2. (b) Multivariate analysis adjusted for age, tumor size, lymph nodes, tumor grade, miR-199a and LCOR expression in the TNBC samples2 (n = 168 patients). (c) Oncomine analysis of LCOR log2 median centered expression in triple-negative breast cancer (TN; n = 49 patients) compared to non-triple-negative breast cancer (n = 300 patients) (TCGA dataset). The box represents 75th, 50th and 25th percentile of values, and the whiskers represent maximum and minimum data points. (d) Inverse correlation of the expression of miR-199a and LCOR in TNBC, as analyzed by by ISH (miR-199a) and IHC (LCOR). Samples (n = 59 tumors) were scored as weak (low expression) or strong (high expression) according to staining intensities. (e) Kaplan-Meier distant metastasis-free survival (DMFS) curve of breast cancer patients stratified by higher or lower than the median LCOR expression using the NKI295 data-set3 (n = 147 patients). (f) Schematic diagram illustrating the procedure of patient-derived xenograft (PDX) maintenance in NSG mice, transduction and functional assays. (g) Tumor incidence of HCI-003 (ER+PR+) and HCI-009 (TNBC) upon mammary fat pad injection of indicated cells. n = number of mammary fat pad injections as indicated in the table. Tumor-initiating cell (TIC) frequency calculated by the ELDA software is indicated in red and P value by Pearson’s Chi-squared test. (h) Hematoxylin-eosin and LCOR IHC analysis of mammary tumors formed by mammary fat pad injection of the indicated PDX cells with or without the overexpression of miR-199a or LCOR. Scale bars: 50 μm in h. Log-rank test in a,e; Cox proportional hazard in b, Wilcoxon un-paired test in c, and Chi-square test in d.

Supplementary Figure 6 LCOR mutant functionality and response to interferons.

(a) Co-immunoprecipitation of co-transfected estrogen receptor (ER) and wild-type or LSKAA mutant LCOR in HMLE cells. LCOR and LSKAA are HA tagged and were immunoprecipitated with anti-HA antibody and inmmunoblotted for ER. Lanes correspond to: 10% Input and anti-HA pull-down. (b) Immunofluoresence analysis of WT and HTH mutant HA-LCOR using anti-HA antibody in HMLE cells. (c) Quantification of mammospheres formed by P4 (20,000 cells) and P5 (10,000 cells) mammospheres treated with 1000 U/ml IFN-α or IFN-γ (n = 5 biologically independent samples; data represented mean ± s.e.m.). Scale bars: 20 μm in b. P < 0.05 by two-tailed Student’s t-test in c.

Supplementary Figure 7 LCOR induces an interferon response and senescent-differentiation state.

(a) K14 (green) and K8 (red) immunofluorescence staining of mammospheres formed by control or Lcor-OE P4 cells with or without IFN-α (1,000 U ml−1) treatment. (b) Quantification of mammospheres formed by HMLE after transduction with the indicated expression constructs, and with or without treatment with 1,000 U ml−1 IFN-α (n = 3 biologically independent samples; data represents mean ± s.e.m.), 10,000 cells were seeded and mammospheres counted at 8 days. (c,d) Quantification of PDX cell tumorspheres formed by 10,000 HCI-010 cells, with the indicated conditions (n = 3 biologically independent samples; data represents mean ± s.e.m.). (e) Senescence-associated β-galactosidase (SA-β gal) assay of HMLE cells with or without wt and ΔHTH mutant LCOR expression, and with or without IFN-α treatment for 48 h (n = 3 biologically independent samples; data represents mean ± s.e.m.; source of data in Supplementary Table 4). (f) GSEA of the senescence up-regulated gene set (M9143; ref. 4) in the ranked gene list of LCOR, LCOR-ΔHTH or miR-199a overexpressing HMLE cells versus control. (f) K14 (green) and K8 (red) immunofluorescence staining of mammospheres formed by control or Lcor-OE P4 cells with or without IFN-α (1000 U/ml) treatment. Scale bars: 25 μm in a, and 100 μm in e. P < 0.05, P < 0.01, P < 0.005 by two-tailed Student’s t-test in b,c and d.

Supplementary Figure 8 IFN-α secretion and clinical significance of the Interferon-Stem Cell Down Signature (ISDS).

(a) Flow cytometry plots representative of Fig. 8a, b data showing Isotype control (FITC Rat IgG1), IFN-α positive cells and percentage of macrophages within the IFN-α positive population in the indicated conditions. Numbers in red are the percentage of positive cells. (b) qRT-PCR analysis of Ifn-α and Ifn-β genes in virgin mammary gland macrophages and peritoneal macrophages (n = 3 biologically independent samples; data represents mean ± s.e.m.). (c) Kaplan–Meier relapse free survival (RFS) curves of individual ISDS genes in ER breast cancer using the KM plotter5. P < 0.05, P < 0.01, P < 0.005 by two-tailed Student’s t-test in b. P-value by log-rank tests in c.

Supplementary Figure 9 Western blot scanned films.

Boxes highlight lanes used in figures.

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Celià-Terrassa, T., Liu, D., Choudhury, A. et al. Normal and cancerous mammary stem cells evade interferon-induced constraint through the miR-199a–LCOR axis. Nat Cell Biol 19, 711–723 (2017). https://doi.org/10.1038/ncb3533

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