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Crosstalk with lung epithelial cells regulates Sfrp2-mediated latency in breast cancer dissemination

Abstract

The process of metastasis is complex1. In breast cancer, there are frequently long time intervals between cells leaving the primary tumour and growth of overt metastases2,3. Reasons for disease indolence and subsequent transition back to aggressive growth include interactions with myeloid and fibroblastic cells in the tumour microenvironment and ongoing immune surveillance4,5,6. However, the signals that cause actively growing cells to enter an indolent state, thereby enabling them to survive for extended periods of time, are not well understood. Here we reveal how the behaviour of indolent breast cancer cells in the lung is determined by their interactions with alveolar epithelial cells, in particular alveolar type 1 cells. This promotes the formation of fibronectin fibrils by indolent cells that drive integrin-dependent pro-survival signals. Combined in vivo RNA sequencing and drop-out screening identified secreted frizzled-related protein 2 (SFRP2) as a key mediator of this interaction. Sfrp2 is induced in breast cancer cells by signals from lung epithelial cells and promotes fibronectin fibril formation and survival, whereas blockade of Sfrp2 expression reduces the burden of indolent disease.

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Fig. 1: AT1 cells regulate behaviour of disseminated indolent breast cancer cells.
Fig. 2: Mass cytometry analysis reveals signalling pathways involved in the crosstalk between AT1 and indolent breast cancer cells.
Fig. 3: Gene-expression analysis of lung disseminated indolent breast cancer cells in vivo.
Fig. 4: A loss-of-function screen in vivo identifies SFRP2 as a survival regulator in lung disseminated indolent breast cancer cells.
Fig. 5: SFRP2 regulates Src-mediated fibrillogenesis, protrusions and survival.

Data availability

RNAseq data have been deposited at the Gene Expression Omnibus with accession number GSE120628. Other data that support the findings of this study are available upon reasonable request from the corresponding authors.

References

  1. 1.

    Lambert, A. W., Pattabiraman, D. R. & Weinberg, R. A. Emerging biological principles of metastasis. Cell 168, 670–691 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Hedley, B. D. & Chambers, A. F. Tumor dormancy and metastasis. Adv. Cancer Res. 102, 67–101 (2009).

    CAS  PubMed  Google Scholar 

  3. 3.

    Sosa, M. S., Bragado, P. & Aguirre-Ghiso, J. A. Mechanisms of disseminated cancer cell dormancy: an awakening field. Nat. Rev. Cancer 14, 611–622 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Obenauf, A. C. & Massagué, J. Surviving at a distance: organ-specific metastasis.Trends Cancer 1, 76–91 (2015).

    PubMed  PubMed Central  Google Scholar 

  5. 5.

    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 

  6. 6.

    Avgustinova, A. et al. Tumour cell-derived Wnt7a recruits and activates fibroblasts to promote tumour aggressiveness. Nat. Commun. 7, 10305 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Naumov, G. N. et al. Persistence of solitary mammary carcinoma cells in a secondary site: a possible contributor to dormancy. Cancer Res. 62, 2162–2168 (2002).

    CAS  PubMed  Google Scholar 

  8. 8.

    Barkan, D. et al. Inhibition of metastatic outgrowth from single dormant tumor cells by targeting the cytoskeleton. Cancer Res. 68, 6241–6250 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Sowder, M. E. & Johnson, R. W. Enrichment and detection of bone disseminated tumor cells in models of low tumor burden. Sci. Rep. 8, 14299 (2018).

    PubMed  PubMed Central  Google Scholar 

  10. 10.

    Shibue, T., Brooks, M. W. & Weinberg, R. A. An integrin-linked machinery of cytoskeletal regulation that enables experimental tumor initiation and metastatic colonization. Cancer Cell 24, 481–498 (2013).

    CAS  PubMed  Google Scholar 

  11. 11.

    Shibue, T., Brooks, M. W., Inan, M. F., Reinhardt, F. & Weinberg, R. A. The outgrowth of micrometastases is enabled by the formation of filopodium-like protrusions. Cancer Discov. 2, 706–721 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Ghajar, C. M. et al. The perivascular niche regulates breast tumour dormancy. Nat. Cell Biol. 15, 807–817 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    van den Bogaard, E. H., Dailey, L. A., Thorley, A. J., Tetley, T. D. & Forbes, B. Inflammatory response and barrier properties of a new alveolar type 1-like cell line (TT1). Pharm. Res. 26, 1172–1180 (2009).

    PubMed  Google Scholar 

  14. 14.

    Bohinski, R. J., Huffman, J. A., Whitsett, J. A. & Lattier, D. L. Cis-active elements controlling lung cell-specific expression of human pulmonary surfactant protein B gene. J. Biol. Chem. 268, 11160–11166 (1993).

    CAS  PubMed  Google Scholar 

  15. 15.

    Kemp, S. J. et al. Immortalization of human alveolar epithelial cells to investigate nanoparticle uptake. Am. J. Respir. Cell Mol. Biol. 39, 591–597 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Seguin, L., Desgrosellier, J. S., Weis, S. M. & Cheresh, D. A. Integrins and cancer: regulators of cancer stemness, metastasis, and drug resistance. Trends Cell Biol. 25, 234–240 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Qin, X. et al. Single-cell signalling analysis of heterocellular organoids. Preprint at bioRxiv https://doi.org/10.1101/659896 (2019).

  18. 18.

    El Touny, L. H. et al. Combined SFK/MEK inhibition prevents metastatic outgrowth of dormant tumor cells. J. Clin. Invest. 124, 156–168 (2014).

    CAS  PubMed  Google Scholar 

  19. 19.

    Bragado, P. et al. TGF-β2 dictates disseminated tumour cell fate in target organs through TGF-β-RIII and p38α/β signalling. Nat. Cell Biol. 15, 1351–1361 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Gawrzak, S. et al. MSK1 regulates luminal cell differentiation and metastatic dormancy in ER+ breast cancer. Nat, Cell Biol. 20, 211–221 (2018).

    CAS  Google Scholar 

  21. 21.

    Gao, H. et al. The BMP inhibitor Coco reactivates breast cancer cells at lung metastatic sites. Cell 150, 764–779 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Kobayashi, A. et al. Bone morphogenetic protein 7 in dormancy and metastasis of prostate cancer stem-like cells in bone. J. Exp. Med. 208, 2641–2655 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Cackowski, F. C. et al. Mer tyrosine kinase regulates disseminated prostate cancer cellular dormancy. J. Cell Biochem. 118, 891–902 (2017).

    CAS  PubMed  Google Scholar 

  24. 24.

    Fluegen, G. et al. Phenotypic heterogeneity of disseminated tumour cells is preset by primary tumour hypoxic microenvironments. Nat. Cell Biol. 19, 120–132 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Sosa, M. S. et al. NR2F1 controls tumour cell dormancy via SOX9- and RARβ-driven quiescence programmes. Nat. Commun. 6, 6170 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Malanchi, I. et al. Interactions between cancer stem cells and their niche govern metastatic colonization. Nature 481, 85–89 (2011).

    PubMed  Google Scholar 

  27. 27.

    Oskarsson, T. et al. Breast cancer cells produce tenascin C as a metastatic niche component to colonize the lungs. Nat. Med. 17, 867–874 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Zhang, X. H., Giuliano, M., Trivedi, M. V., Schiff, R. & Osborne, C. K. Metastasis dormancy in estrogen receptor-positive breast cancer. Clin. Cancer Res. 19, 6389–6397 (2013).

    CAS  PubMed  Google Scholar 

  29. 29.

    Kim, R. S. et al. Dormancy signatures and metastasis in estrogen receptor positive and negative breast cancer. PLoS One 7, e35569 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Cheng, Q. et al. A signature of epithelial-mesenchymal plasticity and stromal activation in primary tumor modulates late recurrence in breast cancer independent of disease subtype. Breast Cancer Res. 16, 407 (2014).

    PubMed  PubMed Central  Google Scholar 

  31. 31.

    Lee, J. L., Lin, C. T., Chueh, L. L. & Chang, C. J. Autocrine/paracrine secreted Frizzled-related protein 2 induces cellular resistance to apoptosis: a possible mechanism of mammary tumorigenesis. J. Biol. Chem. 279, 14602–14609 (2004).

    CAS  PubMed  Google Scholar 

  32. 32.

    Bovolenta, P., Esteve, P., Ruiz, J. M., Cisneros, E. & Lopez-Rios, J. Beyond Wnt inhibition: new functions of secreted Frizzled-related proteins in development and disease. J. Cell. Sci. 121, 737–746 (2008).

    CAS  PubMed  Google Scholar 

  33. 33.

    Kaur, A. et al. sFRP2 in the aged microenvironment drives melanoma metastasis and therapy resistance. Nature 532, 250–254 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Ombrato, L. et al. Metastatic-niche labelling reveals parenchymal cells with stem features. Nature 572, 603–608 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Liberzon, A. et al. Molecular signatures database (MSigDB) 3.0. Bioinformatics 27, 1739–1740 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Merico, D., Isserlin, R., Stueker, O., Emili, A. & Bader, G. D. Enrichment map: a network-based method for gene-set enrichment visualization and interpretation. PLoS One 5, e13984 (2010).

    PubMed  PubMed Central  Google Scholar 

  37. 37.

    Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics 26, 589–595 (2010).

    PubMed  PubMed Central  Google Scholar 

  38. 38.

    Behbehani, G. K., Bendall, S. C., Clutter, M. R., Fantl, W. J. & Nolan, G. P. Single-cell mass cytometry adapted to measurements of the cell cycle. Cytometry A 81, 552–566 (2012).

    PubMed  PubMed Central  Google Scholar 

  39. 39.

    Zunder, E. R. et al. Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm. Nat. Protoc. 10, 316–333 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Finck, R. et al. Normalization of mass cytometry data with bead standards. Cytometry A 83, 483–494 (2013).

    PubMed  PubMed Central  Google Scholar 

  41. 41.

    van Dijk, D. et al. Recovering gene interactions from single-cell data using data diffusion. Cell 174, 716–729 (2018). e727.

    PubMed  PubMed Central  Google Scholar 

  42. 42.

    Pocaterra, A. et al. F-actin dynamics regulates mammalian organ growth and cell fate maintenance. J. Hepatol. 71, 130–142 (2019).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank J. Downward, D. Barkan and R. Gomis for gifts of cell lines; I. Malanchi, S. Piccolo, S. Dupont and G. Martello for thoughtful discussion and reagents; Flow Cytometry, Experimental Histopathology, Bioinformatics and Biostatistics (in particular S. Horswell), Biological Research, Cell Services and Advanced Sequencing facilities at the Crick Institute for exceptional scientific and technical support throughout the project; and C. Mein for support and advice with RNA sequencing. E.S. and M.M. were funded by the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001144), the UK Medical Research Council (FC001144) and the Wellcome Trust (FC001144). M.M. also received funding from Marie Curie Actions—Intra-European Fellowships no. 625496 and BIRD Seed grant from Department of Molecular Medicine (University of Padua). C.J.T. and J.S. are supported by a Cancer Research UK Career Development Fellowship awarded to C.J.T.

Author information

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Authors

Contributions

M.M. and E.S. conceived, designed, and wrote the study. M.M. performed all the experiments with the exception of: the CyTOF analysis, which was performed by R.B. with assistance from X.Q. and J.S., and supervision from C.J.T.; some of the in vitro co-cultures, which were performed by S.H. and E.S.; and the in vivo analysis of proliferation in the lungs and sFRP2 overexpression, which were performed by S.H. with assistance from A.B., Y.N. and E.S. C.D.H.R. and A.P. assisted with cell culture and analysis of gene expression. P.C. performed the bioinformatics analysis.

Corresponding authors

Correspondence to Marco Montagner or Erik Sahai.

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Extended data

Extended Data Fig. 1 Response of lung stromal cells to dissemination of indolent breast cancer cells.

a, Heatmap of Estrogen Receptor (ESR1) and HER2 (ERBB2) expression in D2 cells in vivo based on RNAseq presented in Fig. 3. Heatmap has been generated with ClustVis tool (https://biit.cs.ut.ee/clustvis/#pathways). b, Immunohistochemistry for GFP of lungs from nude mice injected with D2.0R- or D2A1-EGFP labelled cells. n = 2. Scale bar is 100 μm. c, Representative images of lungs from wild-type BALB/c mice injected either with D2.0R-EGFP or with D2A1-EGFP. Lungs were collected and imaged on the GFP channel at the lung surface. Dashed box, lung area magnified in the middle image. n = 4. Scale bars, 1 mm (low magnification) or 100μm (high magnification). d, Circularity of D2.0R and D2A1 cells within the lung parenchyma at 4 days after injection (n = 23 cells). Unpaired t-test. e, Fluorescent IHC of D2.0R-EGFP cells in the lungs two weeks after intravenous injection Left: Magenta, AT2 cells (TTF1 + ). Middle and Right: Magenta, AT2 cells (SP-C + ); Yellow: myeloid cells (CD68 + ); Blue, AT1 cells (PDPN + ). Right panel shows a control lung without D2.0R-EGFP cells. n = 3. Scale bar, 20μm. f, Percentage of D2.0R-EGFP cells in contact with each lung stromal cell type at 3- or 14-days post-injection. n = 3 mice. Black: in contact; white: not in contact. AT1: Alveolar Type 1 cells (PDPN + ); F: Fibroblasts (VIM + ); EC: Endothelial cells (MUC + ); AT2: Alvelolar Type 2 cells (SFPC + ); Act-F: Activated Fibroblasts (aSMA + ); M: Macrophages (CD68 + ). g, Colony area (left) and proliferating number (right) of disseminated D2A1-EGFP or D2.0R-EGFP cells upon tail vein injection at different time points. n = 3 mice/group. h, Number of proliferating PDPN + ve (left) and PDPN-ve (right) cells surrounding metastatic lesions and disseminated cells in g. i, Number of proliferating PDPN + ve cells surrounding MCF7-GFP cells after tail vein injection. n = 3 mice/group. d,g,h,i plots show data as whisker plots: midline, median; box, 25–75th percentile; whisker, minimum to maximum.

Source data

Extended Data Fig. 2 Lung stromal cells regulate proliferation of breast cancer cells in vitro.

a, Relative mRNA levels of stromal cell-type specific markers of the different cellular populations included in the lung coculture system. AT1, alveolar type1 cells; AT2, alveolar type2 cells. Dots are means from independent experiments (n = 3). Unpaired t-test. b, Percentage of Ki67 + -D2.0R-EGFP or -D2A1-EGFP cells cultivated together with lung stromal cell lines in Mitogen Low-Nutrients Low medium (MLNL) for 4 days. Mean normalized pooled samples (n = 7) from independent experiments (n = 2). Data presented as whisker plot: midline, median; box, 25–75th percentile; whisker, minimum to maximum. Unpaired t-test. c, Growth curves of D2.0R-EGFP and D2A1-EGFP cells in vitro with permissive (MHNH) or restrictive (MLNL) medium. d, D2.0R-EGFP cells were cocultured with lung stromal cells for 5 days (or on air-permeable surface only as control), isolated by fluorescence-activated cell sorting (FACS), and their growth kinetic in vitro in MLNL on standard plastic plates measured over time (lines are overlapped). n = 2 independent experiments. For c and d, Confluency values at indicated time points were log10-transformed and linear regression was calculated. Line was forced to go through the origin. n = 6 biological replicates/group, n = 2 independent experiments. Solid line, mean of best-fit line; dashed lines, 95% confidence bands.

Source data

Extended Data Fig. 3 Alveolar type I cells promote formation of protrusions and survival of indolent breast cancer cells in vitro.

a, Relative number of 4T07-EGFP or MCF7-EGFP cells cultivated alone or together with AT1-like cells in MLNL medium for 5 days. Mean normalized pooled samples, n = 12 from 3 independent experiments for 4T07 (Mann-Whitney test), n = 24 from 4 independent experiments for MCF7 (unpaired t-test). b, Plots show the relative frequency (number of events/starting number of D2.0R cells) of mitotic (left) and apoptotic (right) events in D2.0R cells cultured in MLNL media in the absence or presence of AT1-like cells. n = 7 independent experiments. Wilcoxon test. c, Relative number of D2.0R-EGFP cells cocultured with different combinations of lung stromal cells (as indicated) in MLNL medium for 5 days. Mean normalized pooled samples (n = 9) from independent experiments (n = 3). Mann-Whitney test. d, Quantification of D2.0R cells co-cultured with individual lung stromal cells in MHNH medium for 7 days. Pooled samples (n = 8) from independent experiments (n = 3). Dunn’s multiple comparisons test. e, Circularity of D2.0R cells alone or cocultured with AT1-like cells (n = 26–29 cells). Unpaired t-test. f, Percentage of indicated human breast cancer cells with protrusions alone or in coculture with AT1-like cells. n = 3 independent experiments. Paired t-test. g, Representative images of protrusions induced by coculturing of MCF7 cells with AT1-like cells. n = 3. Scale bar, 20μm. h, Immunofluorescence for fibronectin (FN) of 4T07 cells cultured alone (left) or co-cultured with AT1-like cells (right). n = 3. Scale bar, 20μm. i, Percentage of D2A1 cells with protrusions alone or in coculture with AT1-like cells. n = 3 independent experiments. Paired t-test. j, Percentage of MCF7 cells with protrusions, in coculture with AT1-like cells, upon treatment with cilengitide. n = 3 independent experiments. Paired t-test. ae plots show data as whisker plots: midline, median; box, 25–75th percentile; whisker, minimum to maximum.

Source data

Extended Data Fig. 4 Mass cytometry analysis reveals signaling pathways involved in the crosstalk between AT1 and indolent breast cancer cells.

a, Schematics representation of the experimental outline of mass cytometry assay. b, Heatmaps of EMD values showing the activation of relevant markers in AT1-like cells cocultured with D2.0R or MCF7. n = 1 experiment. c, Plot showing increase phospho-HistoneH3 (S28) signal in AT1-like cells co-cultured with D2.0R cells. Representative of two independent experiments. d, DREVI plots showing the relationship between the indicated phospho-antibody signals in D2.0R monocultures or cocultures with AT1-like cells (DREMI score in upper left corner). Representative of two independent experiments. e, Number of cells after the indicated treatment (for two days) relative to untreated cells. Mean values from n = 3 (for Control, EGFRi, SFKi) and 4 (for MEKi) independent experiments. One-way ANOVA test. f, Histogram of EMD values showing the inhibition of P-ERK abundance in D2.0R cells cocultured with AT1-like cells. Bars show the average of two technical replicates. g, Plot shows the area of D2.0R colonies ten days after intravenous delivery into either control Balb/C nude mice (n = 1147 across 5 mice) or Trametinib treated mice (n = 179 across 4 mice, MEKi). Mann-Whitney test. e, g plots show data as whisker plots: midline, median; box, 25–75th percentile; whisker, minimum to maximum.

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Extended Data Fig. 5 EGFR and SFK, but not MEK, regulate protrusions and fibrillogenesis induced by coculture of indolent breast cancer cells with AT1-like cells.

a, Percentage of D2.0R cells with protrusions after treatment with indicated inhibitors for two days. Mean values of n = 3 independent experiments. One-way ANOVA test. b, D2.0R-EGFP cells have been treated for two days with indicated drugs. Fibronectin fibrils were quantified after immunostaining. Mean values from n = 3 (for EGFRi and MEKi) and 5 (for Control and SFKi) experiments. One-way ANOVA test between “extensive fibrils” category. c, Percentage of MCF7 cells with protrusions after treatment with SFKi in monoculture or coculture with AT1-like cells. n = 2 (for Control alone) and 3 (for Control coculture and SFKi treated) independent experiments. One-way ANOVA test. d, Relative expression of Fn mRNA in D2.0R-EGFP cells cultivated with AT1-like cells in MLNL medium -/ + SFKi for 4 days. Mean normalized pooled samples (n = 12) from independent experiments (n = 3). Mann-Whitney test. e, Images showing F-actin and activated phospho-Src (Y418) in D2.0R cells cocultured with AT1-like cells. n = 2. Scale bar is 20μm.

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Extended Data Fig. 6 Gene expression analysis of lung-disseminated indolent breast cancer cells in vivo.

a, Representative GSEA analysis from the top up- and down-regulated gene sets in D2.0R cells in vivo compared to the other groups (relative to Fig. 3a). NES, normalized enrichment score. FDR, false discovery rate. b, Heatmap shows normalized expression values for two dormancy markers (Bhlhe41 is also known as Dec2 and Sharp1).

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Extended Data Fig. 7 Survival analysis of patients according to dormancy signature.

a, Kaplain-Meier curves of ER + breast cancer patients from publicly available datasets used in Kim et al., 2012, stratified according to the dormancy signature. b, Overlap between our dormancy signature and genes included in the dormancy score or 51-gene signature (Supplementary Table 1). c, Kaplain-Meier curves showing DMFS (Distant Metastasis Free Survival) of ER + breast with high and low expression of dormancy signature. Data have been plotted starting from month 0 (left) or month 24 (right). Indicated statistical tests are two-sided. d, Kaplan-Meier curves showing DMSF of patients derived from http://co.bmc.lu.se/gobo/gsa.pl stratified according additional signatures generated from the other groups analysed with RNAseq in Fig. 3 (Supplementary Table 1). f, BMP and Wnt target genes expression as in Fig. 3f. Mean normalized pooled samples, n = 8 samples from 3 independent experiments. Mann-Whitney test.

Source data

Extended Data Fig. 8 A loss-of-function screen in vivo identifies SFRP2 as survival regulator in lung disseminated indolent breast cancer cells.

a, Volcano plot of RNAseq expression data of D2.0R cells in vivo compared to the other groups (as in Fig. 3a). In blue, candidate genes selected for step 2 validation. b, Step 2 validation of candidate genes. Subpopulations of D2.0R-EGFP cells bearing a single shRNA for the indicated gene were individually generated (3 shRNA sequences/gene). Cells with shRNA for the same gene were mixed together in equal amount, injected in tail vein of BALB/c nude mice (n = 6 mice for Control and n = 3 for the other groups) and processed as in Fig. 4c. Unpaired t-test with Welch’s correction. c, Subpopulations of D2.0R-EGFP-shSfrp2 cells were mixed and injected in the tail vein with an equal amount of D2.0R-mCherry-shControl. After 3 days to allow seeding and extravasation in the lung parenchyma, lungs were collected and GFP + and mCherry + simultaneously quantified to rule out pre-dissemination role of SFRP2 (n = 4 mice). Scale bar, 1 mm. Unpaired t-test with Welch’s correction. d, In vitro growth curves of D2.0R-EGFP cells bearing the indicated shRNAs for Sfrp2. Confluency values at indicated time points were log10-transformed and linear regression was calculated (n = 2 independent experiments). Line was forced to go through the origin. Solid line, mean of best-fit line; dashed lines, 95% confidence bands. e, Relative expression levels of Sfrp2 in D2.0R.EGFP cells on plastic, isolated from mammary fat pad or lung-disseminated (n = 5 wells for Control group, n = 3 mice for the other groups). Unpaired t-test. f, Histogram showing the induction of SFRP family members by AT1-like conditioned media in both D2.0R and 4TO7 cells. Mean normalized pooled samples (n = 9) from independent experiments (n = 3–4). Mann-Whitney test.

Source data

Extended Data Fig. 9 SFRP2 regulates protrusions independently of Wnt signaling.

a, Left, qPCR for canonical Wnt target genes of D2.0R-EGFP carrying interfering sequences for Sfrp2 cultivated with AT1-like cells in MLNL medium for 4 days. Right, qPCR for the Wnt target Axin2 in control and SFRP2-overexpressing cells. Mean normalized pooled samples from independent experiments (n = 3 for CCND2 and n = 4 for Axin2). Mann-Whitney test. b, Conditioned media from confluent D2.0R-EGFP-Control or SFRP2 OE cells plated in MLNL were concentrated and analyzed by Western Blotting. Cells have been treated or not with 50ug/mL of Heparin to allow SFRP2 solubilization in the medium. Representative of two independent experiments. Unprocessed blots are available as Source Data file. c, Plot shows the effect of heparin, which binds and inhibits SFRP family proteins, on D2.0R cell number when co-cultured with AT1-like cells. Mean normalized pooled samples (n = 18) from independent experiments (n = 3). Plots shows data as whisker plots: midline, median; box, 25–75th percentile; whisker, minimum to maximum. Unpaired t-test. d, Control or SFRP2 overexpressing MCF7 cells were plated alone or in presence of AT1-like cells. Plot shows the percentage of cells with protrusions in each experiment. n = 3 independent experiments. Paired t-test. e, Quantification of cell D2.0R cell proliferation (as judged by mitoses) in the indicated conditions: + /- AT1-like cells, + /- SFRP2 over-expression, and + /- SFKi treatment. Mean and S.E.M. are shown (n = 5 independent experiments). Unpaired t-test.

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Extended Data Fig. 10 SFRP2 regulates survival of disseminated indolent breast cancer cells.

a, Quantification of metastatic burden two weeks after intravenous injection of human indolent breast cancer cell. n = 6 slices across 3 mice for T47D-DBM cells and n = 10 slices across 3 mice for MCF7 cells. Plots show data as whisker plots: midline, median; box, 25–75th percentile; whisker, minimum to maximum. Unpaired t-test. b, In vitro growth curves of Control and SFRP2 over-expressing D2.0R and 4T07 cells. Confluency values at indicated time points were log10-transformed and linear regression was calculated. Line was forced to go through the origin. Solid line, mean of best-fit line; dashed lines, 95% confidence bands. n = 2 independent experiments. c, Proximity of disseminated SFRP2-overexpressing D2.0R cells to indicated lung stromal cells at 3 or 14-days post-injection. Lung slices from 3 mice injected with D2.0R-EGFP cells have been stained with multiple markers for different stromal subpopulations. Graphs indicate the percentage of EGFP + cells in contact with each stromal cells subtype (black: in contact; white: not in contact). Staining as in Extended Data Fig. 1f. d, Schematic illustration of the signaling between AT1 cells and breast cancer cells that supports metastatic persistence.

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Supplementary Table

Supplementary Tables 1–5: Gene signatures, shRNA library sequences, oligos and antibodies used in the manuscript.

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Montagner, M., Bhome, R., Hooper, S. et al. Crosstalk with lung epithelial cells regulates Sfrp2-mediated latency in breast cancer dissemination. Nat Cell Biol 22, 289–296 (2020). https://doi.org/10.1038/s41556-020-0474-3

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