Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

TGF-β2 dictates disseminated tumour cell fate in target organs through TGF-β-RIII and p38α/β signalling

Nature Cell Biology volume 15, pages 1351–1361 (2013)Cite this article

Subjects

Abstract

In patients, non-proliferative disseminated tumour cells (DTCs) can persist in the bone marrow (BM) while other organs (such as lung) present growing metastasis. This suggested that the BM might be a metastasis ‘restrictive soil’ by encoding dormancy-inducing cues in DTCs. Here we show in a head and neck squamous cell carcinoma (HNSCC) model that strong and specific transforming growth factor-β2 (TGF-β2) signalling in the BM activates the MAPK p38α/β, inducing an (ERK/p38)low signalling ratio. This results in induction of DEC2/SHARP1 and p27, downregulation of cyclin-dependent kinase 4 (CDK4) and dormancy of malignant DTCs. TGF-β2-induced dormancy required TGF-β receptor-I (TGF-β-RI), TGF-β-RIII and SMAD1/5 activation to induce p27. In lungs, a metastasis ‘permissive soil’ with low TGF-β2 levels, DTC dormancy was short-lived and followed by metastatic growth. Importantly, systemic inhibition of TGF-β-RI or p38α/β activities awakened dormant DTCs, fuelling multi-organ metastasis. Our work reveals a ‘seed and soil’ mechanism where TGF-β2 and TGF-β-RIII signalling through p38α/β regulates DTC dormancy and defines restrictive (BM) and permissive (lung) microenvironments for HNSCC metastasis.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Growth behaviour of BM- and lung-derived DTCs.
Figure 2: Signalling pathways and genes regulating dormancy of BM-HEp3 cells.
Figure 3: Systemic p38α/β inhibition affects HNSCC DTC behaviour in growth-restrictive microenvironments.
Figure 4: Systemic p38α/β inhibition interrupts DTC dormancy in the lungs.
Figure 5: Role of TGF-β2 in dormant HEp3 DTCs.
Figure 6: Effect of TGF-β signalling on dormancy and self-renewal markers.
Figure 7: TGF-β2/TGF-β-RIII signalling regulates DTC dormancy.
Figure 8: Effect of TGF-β-RI inhibition on DTC burden.

Similar content being viewed by others

References

  1. Fidler, I. J. The pathogenesis of cancer metastasis: the ‘seed and soil’ hypothesis revisited. Nat. Rev. Cancer 3, 453–458 (2003).

    Article  CAS  PubMed  Google Scholar 

  2. Aguirre-Ghiso, J. A. Models, mechanisms and clinical evidence for cancer dormancy. Nat. Rev. Cancer 7, 834–846 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Klein, C. A. Framework models of tumor dormancy from patient-derived observations. Curr. Opin. Genet. Dev. 21, 42–49 (2011).

    Article  CAS  PubMed  Google Scholar 

  4. Ferlito, A., Shaha, A. R., Silver, C. E., Rinaldo, A. & Mondin, V. Incidence and sites of distant metastases from head and neck cancer. ORL J. Otorhinolaryngol. Relat. Spec. 63, 202–207 (2001).

    Article  CAS  PubMed  Google Scholar 

  5. Zhang, Y., Ma, B. & Fan, Q. Mechanisms of breast cancer bone metastasis. Cancer Lett. 292, 1–7 (2010).

    Article  CAS  PubMed  Google Scholar 

  6. Husemann, Y. & Klein, C. A. The analysis of metastasis in transgenic mouse models. Transgenic Res. 18, 1–5 (2009).

    Article  PubMed  Google Scholar 

  7. Husemann, Y. et al. Systemic spread is an early step in breast cancer. Cancer Cell 13, 58–68 (2008).

    Article  PubMed  Google Scholar 

  8. Adam, A. P. et al. Computational identification of a p38SAPK-regulated transcription factor network required for tumor cell quiescence. Cancer Res. 69, 5664–5672 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Onder, T. T. et al. Chromatin-modifying enzymes as modulators of reprogramming. Nature 483, 598–602 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Montagner, M. et al. SHARP1 suppresses breast cancer metastasis by promoting degradation of hypoxia-inducible factors. Nature 487, 380–384 (2012).

    Article  CAS  PubMed  Google Scholar 

  12. Bao, B. et al. Over-expression of FoxM1 leads to epithelial-mesenchymal transition and cancer stem cell phenotype in pancreatic cancer cells. J. Cell Biochem. 112, 2296–2306 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Sorrentino, A. et al. The type I TGF-beta receptor engages TRAF6 to activateTAK1 in a receptor kinase-independent manner. Nat. Cell Biol. 10, 1199–1207 (2008).

    Article  CAS  PubMed  Google Scholar 

  14. Ito, K. et al. Reactive oxygen species act through p38 MAPK to limit the lifespan of hematopoietic stem cells. Nat. Med. 12, 446–451 (2006).

    Article  CAS  PubMed  Google Scholar 

  15. Zijlstra, A. et al. A quantitative analysis of rate-limiting steps in the metastatic cascade using human-specific real-time polymerase chain reaction. Cancer Res. 62, 7083–7092 (2002).

    CAS  PubMed  Google Scholar 

  16. Riethdorf, S., Wikman, H. & Pantel, K. Review: biological relevance ofdisseminated tumor cells in cancer patients. Int. J. Cancer 123, 1991–2006 (2008).

    Article  CAS  PubMed  Google Scholar 

  17. Toolan, H. W. Transplantable human neoplasms maintained in cortisonetreated laboratory animals: H.S. #1; H.Ep. #1; H.Ep. #2; H.Ep. #3; and H.Emb.Rh. #1. Cancer Res. 14, 660–666 (1954).

    CAS  PubMed  Google Scholar 

  18. Ossowski, L. Plasminogen activator dependent pathways in the dissemination of human tumor cells in the chick embryo. Cell 52, 321–328 (1988).

    Article  CAS  PubMed  Google Scholar 

  19. Aguirre-Ghiso, J. A., Liu, D., Mignatti, A., Kovalski, K. & Ossowski, L. Urokinase receptor and fibronectin regulate the ERK(MAPK) to p38(MAPK) activity ratios that determine carcinoma cell proliferation or dormancy in vivo. Mol. Biol. Cell 12, 863–879 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Ossowski, L. & Reich, E. Experimental model for quantitative study of metastasis. Cancer Res. 40, 2300–2309 (1980).

    CAS  PubMed  Google Scholar 

  21. Aguirre-Ghiso, J. A., Ossowski, L. & Rosenbaum, S. K. Green fluorescent protein tagging of extracellular signal-regulated kinase and p38 pathways reveals novel dynamics of pathway activation during primary and metastatic growth. Cancer Res. 64, 7336–7345 (2004).

    Article  CAS  PubMed  Google Scholar 

  22. Alonso, D. F. et al. Characterization of F3II, a sarcomatoid mammary carcinoma cell line originated from a clonal subpopulation of a mouse adenocarcinoma. J. Surg. Oncol. 62, 288–297 (1996).

    Article  CAS  PubMed  Google Scholar 

  23. Aslakson, C. J. & Miller, F. R. Selective events in the metastatic process defined by analysis of the sequential dissemination of subpopulations of a mouse mammary tumor. Cancer Res. 52, 1399–1405 (1992).

    CAS  PubMed  Google Scholar 

  24. Aguirre-Ghiso, J. A., Estrada, Y., Liu, D. & Ossowski, L. ERK(MAPK) activity as a determinant of tumor growth and dormancy; regulation by p38(SAPK). Cancer Res. 63, 1684–1695 (2003).

    CAS  PubMed  Google Scholar 

  25. Kim, J., Yu, W., Kovalski, K. & Ossowski, L. Requirement for specific proteases in cancer cell intravasation as revealed by a novel semiquantitative PCR-based assay. Cell 94, 353–362 (1998).

    Article  CAS  PubMed  Google Scholar 

  26. Ossowski, L. & Reich, E. Antibodies to plasminogen activator inhibit human tumor metastasis. Cell 35, 611–619 (1983).

    Article  CAS  PubMed  Google Scholar 

  27. Henckaerts, E., Langer, J. C., Orenstein, J. & Snoeck, H-W. The positive regulatory effect of TGF-β2 on primitive murine hemopoietic stem and progenitor cells is dependent on age, genetic background, and serum factors. J. Immunol. 173, 2486–2493 (2004).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lopez-Casillas, F., Wrana, J. L. & Massague, J. Betaglycan presents ligand to the TGF beta signaling receptor. Cell 73, 1435–1444 (1993).

    Article  CAS  PubMed  Google Scholar 

  30. Criswell, T. L., Dumont, N., Barnett, J. V. & Arteaga, C. L. Knockdown of the transforming growth factor-beta type III receptor impairs motility and invasion of metastatic cancer cells. Cancer Res. 68, 7304–7312 (2008).

    Article  CAS  PubMed  Google Scholar 

  31. Siegel, P. M. & Massague, J. Cytostatic and apoptotic actions of TGF-beta in homeostasis and cancer. Nat. Rev. Cancer 3, 807–821 (2003).

    Article  CAS  PubMed  Google Scholar 

  32. Gath, H. J. & Brakenhoff, R. H. Minimal residual disease in head and neck cancer. Cancer Metastasis Rev. 18, 109–126 (1999).

    Article  CAS  PubMed  Google Scholar 

  33. Aguirre-Ghiso, J. A., Bragado, P. & Sosa, M. S. Metastasis awakening: targeting dormant cancer. Nat. Med. 19, 276–277 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Shiozawa, Y. et al. GAS6/AXL axis regulates prostate cancer invasion, proliferation, and survival in the bone marrow niche. Neoplasia 12, 116–127 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Padua, D. et al. TGFβ primes breast tumors for lung metastasis seeding through angiopoietin-like 4. Cell 133, 66–77 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Turley, R. S. et al. The type III transforming growth factor-beta receptor as a novel tumor suppressor gene in prostate cancer. Cancer Res. 67, 1090–1098 (2007).

    Article  CAS  PubMed  Google Scholar 

  38. Cheifetz, S. et al. The transforming growth factor-beta system, a complex pattern of cross-reactive ligands and receptors. Cell 48, 409–415 (1987).

    Article  CAS  PubMed  Google Scholar 

  39. Cheifetz, S. et al. Distinct transforming growth factor-beta (TGF-beta) receptor subsets as determinants of cellular responsiveness to three TGF-beta isoforms. J. Biol. Chem. 265, 20533–20538 (1990).

    CAS  PubMed  Google Scholar 

  40. Brown, C. B., Boyer, A. S., Runyan, R. B. & Barnett, J. V. Requirement of type III TGF-beta receptor for endocardial cell transformation in the heart. Science 283, 2080–2082 (1999).

    Article  CAS  PubMed  Google Scholar 

  41. You, H. J., Bruinsma, M. W., How, T., Ostrander, J. H. & Blobe, G. C. The type III TGF-beta receptor signals through both Smad3 and the p38 MAP kinase pathways to contribute to inhibition of cell proliferation. Carcinogenesis 28, 2491–2500 (2007).

    Article  CAS  PubMed  Google Scholar 

  42. Ajiboye, S., Sissung, T. M., Sharifi, N. & Figg, W. D. More than an accessory: implications of type III transforming growth factor-beta receptor loss in prostate cancer. BJU Int. 105, 913–916 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Dong, M. et al. The type III TGF-beta receptor suppresses breast cancer progression. J. Clin. Invest. 117, 206–217 (2007).

    Article  CAS  PubMed  Google Scholar 

  44. Sun, C. K., Chua, M. S., He, J. & So, S. K. Suppression of glypican 3 inhibits growth of hepatocellular carcinoma cells through up-regulation of TGF-beta2. Neoplasia 13, 735–747 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Yamazaki, S. et al. TGF-beta as a candidate bone marrow niche signal to induce hematopoietic stem cell hibernation. Blood 113, 1250–1256 (2009).

    Article  CAS  PubMed  Google Scholar 

  46. Sharifi, N., Hurt, E. M., Kawasaki, B. T. & Farrar, W. L. TGFBR3 loss and consequences in prostate cancer. Prostate 67, 301–311 (2007).

    Article  PubMed  Google Scholar 

  47. Morrissey, C. & Vessella, R. L. The role of tumor microenvironment in prostate cancer bone metastasis. J. Cell Biochem. 101, 873–886 (2007).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Ossowski, L., Russo, H., Gartner, M. & Wilson, E. L. Growth of a human carcinoma (HEp3) in nude mice: rapid and efficient metastasis. J. Cell Physiol. 133, 288–296 (1987).

    Article  CAS  PubMed  Google Scholar 

  50. Ranganathan, A. C., Zhang, L., Adam, A. P. & Aguirre-Ghiso, J. A. Functional coupling of p38-induced up-regulation of BiP and activation of RNA-dependent protein kinase-like endoplasmic reticulum kinase to drug resistance of dormant carcinoma cells. Cancer Res. 66, 1702–1711 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Deryugina, E. I. et al. Unexpected effect of matrix metalloproteinase down-regulation on vascular intravasation and metastasis of human fibrosarcoma cells selected in vivo for high rates of dissemination. Cancer Res. 65, 10959–10969 (2005).

    Article  CAS  PubMed  Google Scholar 

  52. Zijlstra, A., Lewis, J., Degryse, B., Stuhlmann, H. & Quigley, J. P. The inhibition of tumor cell intravasation and subsequent metastasis via regulation of in vivo tumor cell motility by the tetraspanin CD151. Cancer Cell 13, 221–234 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Grant support: Samuel Waxman Cancer Research Foundation Tumour Dormancy Program, NCI CA109182 and CA163131, NIEHS (ES017146) and NYSTEM grants to J.A.A-G; Mildred-Scheel postdoctoral grant by the Deutsche Krebshilfe and Max-Eder Junior Research Grant by the Deutsche Krebshilfe e. V. to D.M.S. C.C. is a research fellow and H.F. is an Investigator of CONICET—Argentina. This work was also supported by CONICET and UNQ grants to H.G.F.

Author information

Authors and Affiliations

  1. Division of Hematology and Oncology, Department of Medicine, Department of Otolaryngology, Tisch Cancer Institute, Mount Sinai School of Medicine, New York 10029, USA

    Paloma Bragado, Yeriel Estrada, Falguni Parikh, Denis M. Schewe & Julio A. Aguirre-Ghiso

  2. Department of General Pediatrics, University Hospital of Schleswig-Holstein, Kiel 24118, Germany

    Sarah Krause & Denis M. Schewe

  3. Department of Science and Technology, Laboratory of Molecular Oncology, Quilmes National University, B1876BXD Buenos Aires, Argentina

    Carla Capobianco & Hernan G. Farina

  4. Black Family Stem Cell Institute, Mount Sinai School of Medicine, New York 10029, USA

    Julio A. Aguirre-Ghiso

Authors
  1. Paloma Bragado
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yeriel Estrada
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Falguni Parikh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sarah Krause
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Carla Capobianco
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hernan G. Farina
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Denis M. Schewe
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Julio A. Aguirre-Ghiso
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceived and designed the experiments: P.B., Y.E., D.M.S., H.G.F., J.A.A-G. Performed the experiments: P.B., Y.E., F.P., S.K., C.C., J.A.A-G. Analysed the data: P.B., D.M.S., H.G.F., J.A.A-G. Contributed reagents/materials/analysis tools: D.M.S., H.G.F. Wrote the paper: P.B., J.A.A-G.

Corresponding author

Correspondence to Julio A. Aguirre-Ghiso.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Detection and characterization of HEp3 DTCs in lungs, BM and lymph nodes.

(a) Number of disseminated HEp3-GFP-tagged cells (DTCs - HEp3-GFP) found in live lungs suspensions and BM flushes, 4 weeks after surgery of the primary tumour (PT). n = 16 (BM), 35 (LU) mice per conditions. (b) Upper panel: representative live fluorescence microscopy image of a lymph node 4 weeks after surgery of the PT. Scale bar: 160 μm. Lower graph: number of disseminated HEp3-GFP cells in the lymph node of nude mice 4 weeks after PT surgery. n = 15 mice. (c) BM was collected from nude mice, and single cell suspensions were prepared as described in methods. Q-PCR for Alu sequences was performed on genomic DNA extracted from the indicated number of HEp3 cells serially diluted into individual mice BM cell suspensions. Q-PCR for Alu sequences was used to generate a standard curve from 10 to 103 HEp3 cells/BM by plotting the Alu Ct-mGAPDHCt against the number of cells per bone marrow (n = 3 BM samples per condition were assessed over 3 independent experiments) (d) Alu PCR was used to amplify Alu sequences in human (HEp3) DNA in BM cell suspensions from mice that carried HEp3 tumours and whose BM suspensions were apparently negative for HEp3-GFP cells when examined under the fluorescence microscope. The standard curve shown in c was used to calculate the number of HEp3 cells in these BM. (n = 3 (1, 4, 7, 9, 10), n = 2 (5, 6) Alu Ct values from independent qPCRs) see Supplementary Table S4 for the statistic source data. (e) Life fluorescence images from lungs at the time of surgery. (S = lung stroma). Scale bar: 160 μm. (f) Representative cleaved caspase-3 (C-C3) staining in PT-HEp3 (PT) (upper right panel), Lu-HEp3 (Lu, upper left panel) and BM-D1 (middle left panel) tumours. Scale bar: 40 μm. Representative P-H3 (right middle panel) and p27 (right bottom panel) staining in PT-HEp3 (PT) tumours. Scale bar: 40 μm. Arrows = positive cells. Lower left graph: Quantification of marker-positive cells. (n = 100 cells assessed/section. 15 sections assessed from 3 different tumour/condition). FOV = field of view. (g) Serial passage of BM-D1 cells on CAMs. Generation matched primary tumour (PT) HEp3 cells from the same animal were inoculated on CAM at (2×105 cells/animal) and transplanted weekly onto a new CAM (n = 5 (PT), 6 (BM) tumour nodules). (h) Dormant (BM-D1) and tumorigenic (BM-T1) BM-HEp3 cells were injected subcutaneous (s.c.) in nude mice (5×105 cells/animal). Graph: time, in days, it took for the tumours to reach 100mm3. n = 2 (BM-T1) 3 (BM-D1) mice, p = 0.0878 by unpaired t test. See Supplementary Table S4 for the statistic source data. (i) Scheme adapted from (Kim, et al., 1998)25: 2.5*105 T-HEp3 GFP cells were inoculated on the chorioallantoic membrane (CAM) of d10 chicken embryos. 5 days after inoculation the embryos were sacrificed. The BM, liver and lung were isolated and inspected under the fluorescence microscope for GFP cells. (j) Number of disseminated HEp3-GFP-tagged cells (DTCs - HEp3-GFP) found in the chicken embryo lungs, liver and BM 5 days after inoculation. n = 10 (liver), 10 (lung), 7 (BM) Chicken embryos assessed. (k) Serial passage of BM-D2,-D3 and -D4 cells on CAMs for two weeks. n = 8 (BM-D2, w1), 6 (BM-D3, w1), 8 (BM-D4, w1), 7 (PT, w1), 4 (BM-D2, w2), 3 (BM-D3, w2), 3, (BM-D4, w2) tumour nodules assessed in 2 independent experiments. See Supplementary Table S4 for the statistic source data. Data in c, d, f, g, h and k, represent mean±s.e.m. In a, f, g and k, *p<0.05, **p<0.01 and ***p<0.001 by Mann Whitney test. In j *p<0.05, **p<0.01 and ***p<0.001 by One-way ANOVA-Bonferroni’s multiple comparison test.

Supplementary Figure 2 DEC2 and p53 expression in HNSCC and breast cancer cell lines and in HNSCC patient samples.

(a) Lysates from 4T1, 4T07 and F3II cell lines were probed by immunoblot (IB) for the indicated antigens. Numbers on top of blots = [ERK/p38] ratio quantification(b-c) QPCR for DEC2 (b) and p53 (c) mRNAs in the indicated cell lines after 24 h in culture, n = 6 RNA samples per condition were assessed over 3 independent experiments, error bars denote s.e.m., *p<0.05, **p<0.01, ***p<0.001 by Mann Whitney test. (d) Left panel: p38α immunoblot in scrambled (scr) or p38α-siRNA transfected BM-D1 cells. Right and middle panels: qPCR for DEC2 and p53 mRNA in BM-D1 cells 24 h after transfection with the indicated siRNAs. n = 2 RNA samples (middle panel) 3 RNA samples (right panel) per condition were assessed over 2 independent experiments, *p<0.05 by Mann Whitney test. See Supplementary Table S4 for the statistic source data. (e) IB anti-HA (left panel) and anti-V5 (right panel) in Lu-HEp3 cells transfected with GFP, p38α constitutively active construct (p38α-CA-HA) or a DEC2-V5 construct. (f) P-H3 (left column) and Cleaved Caspase-3 (C-C3) (right column) immunohistochemistry in Lu-HEp3 cells transfected with vector (upper panels) or a p38α constitutively active construct (p38α-CA-HA) (lower panels). Scale bar: 40μm. Quantification of marker-positive cells is shown in the graphs on the right panels. Y axis shows the number of positive cells (for either Cleaved Caspase-3 (C-C3) or P-H3) per field of view (FOV). Graph: mean±s.e.m. (n = 100 cells assessed/section. 15 sections assessed from 3 different tumour/condition) **p<0.01 by Mann Whitney test. (g) Representative DEC2 staining in primary tumours (upper row) and lymph node metastasis (lower row) from 4 HNSCC patients. (S = stroma, T = primary tumour, M = Metastasis). Scale bar: 120μm.

Supplementary Figure 3 Effect of pharmacologic and genetic p38 inhibition on HEp3 DTC and metastasis burden.

(a) Representative images of Vimentin (Vim), p27, P-H3 and Cytokeratin8/18 (CK) staining in solitary liver (left column) and BM DTCs (right column). Arrows = marker positive cells. Scale bar: 40μm. (b) Tumour volume after 5 days inoculation on CAMs of T-HEp3 cells transfected with either scrambled (scr) or p38α siRNA. n = 4 tumour nodules per condition, p = 0.3830 by Mann Whitney test. (c) IB for p38α in T-HEp3 cells transfected with either scrambled (scr) or p38α siRNA. (d) Representative fluorescence intravital images of liver (upper panels) DTCs in chicken embryos 5 days after inoculation of T-HEp3-GFP cells transfected with scrambled (scr) (left panels) or p38α (right panels) siRNA. Scale bar: 160μm. Lower Graph: quantification of HEp3 DTCs in chicken embryo livers 5 days after inoculation of T-HEp3-GFP cells transfected with scrambled (scr) or p38α siRNAs. n = 7 chicken embryo livers analyzed per condition/2 independent experiments. p = 0.2610 by Mann Whitney test. (e) Left panel: Representative image of Vimentin staining on a T-HEp3 tumour. Scale bar: 40μm. Right panel: IB for Vimentin in T-HEp3 (T) and D-HEp3 (D) lysates.

Supplementary Figure 4 TGFβ1 & 2 expressions and signalling in HEp3-derived cell lines.

(a) Affymetrix array values for the expression of TGFβ2 mRNA in D-HEp3, T-HEp3 and R-HEp3 (D-HEp3 cells that resumed growth after a prolonged dormancy ∼ 2 months). (b) D-HEp3 cells were treated with a TGFβ receptor I inhibitor (LY-364947, 5μM) for 2, 4 and 6 h in serum free conditions and whole cell lysates were immunoblotted for P-p38 and p38α. (c) qPCR analysis of DEC2 mRNA expression in D-HEp3 cells treated with the TGFβRI inhibitor (LY-364947, 5μM) for 24 h in serum free conditions. n = 6 RNA samples per condition were assessed over 3 independent experiments, error bars denote s.e.m., *p<0.05 by Mann Whitney test. (d) D-HEp3 cells were treated with the TGFβRI inhibitor (LY-364947, 5 μM) for 24 h and then inoculated on CAM (2×105 cells/animal) and then treated with the LY-364947, 5 μM on the CAM every 24 h. 4 days later tumours were minced and the number D-HEp3 cells quantified in collagenase suspensions. Graph: number of cells/tumour, n = 6 tumour nodule assessed per condition, p = 0.0011 by Mann Whitney test. (e) qPCR for DEC2 in 4T1 cells treated with BM CM for 24 h. n = 6 RNA samples per condition were assessed over 3 independent experiments. Error bars denote s.e.m., *p<0.05 by Mann Whitney test (f) Representative cleaved caspase-3 (C-C3) staining in T-HEp3 tumours after treatment with either serum free, lung CM or BM CM for 4 days in vivo. Scale bar: 40 μm. Lower right graph: quantification of Cleaved Caspase-3 (C-C3) positive cells. Y axis: number of C-C3 positive cells per field of view (FOV), mean±s.e.m. (n = 100 cells assessed/section. 15 sections assessed from 3 different tumour/condition). (g) Top panel: IB against TGFβ1 after control IgG or anti-TGFβ1 IgG immunodepletion of the BM CM. Lower panel: Tumour growth of T-HEp3 cells treated with full (IP-IgG) or TGFβ1 immunodepleted (IP-TGFβ1) BM CM for 5 days in vivo, n = 6 (SF), 8 (IP-IgG), 9 (IP-TGFb1) tumour nodules assessed, *p<0.05 by One-way ANOVA-Bonferroni’s multiple comparison test. Right panel: IB showing p38α activation after treatment of T-HEp3 cells with full (IP-IgG) or TGFβ1 depleted (IP-TGFβ1) BM CM for 24 h.

Supplementary Figure 5 TGFβRIII knockdown effect on TGFβ2 signalling.

(a) DEC2 mRNA levels in 4T1 and F3II cell lines after treatment with 2 ng/ml TGFβ2 for 24 h in SF media. n = 6 RNA samples per condition were assessed over 3 independent experiments. Error bars denote s.e.m., *p<0.05 by Mann Whitney test. (b) Q-PCR for TGFβ2 mRNA expression in BM-D1 cells 24 h after transfection with TGFβ2 siRNAs. n = 6 RNA samples per condition were assessed over 3 independent experiments. Error bars denote s.e.m., *p<0.05 by Mann Whitney test. (c) Graph: number of 4T1 tumour spheres in control and TGFβ2 (2 ng/ml) treated cultures after 7 days (n = 6 wells per condition were assessed for tumour spheres/3 different experiments) Right column panels: representative images of control (upper panel) and TGFβ2 treated (lower panel) 4T1 tumour spheres. Scale bar: 100μm. (d-e) Effect of SB203580 (5μM) or LY-364947 (5μM) treatment in 4T07 tumour spheres cultures. The graph shows the number of tumour spheres as compared to control cells after 7 days (d) and the number of cells per sphere (e) (n = 6 wells per condition were assessed for tumour spheres/3 different experiments). Error bars denote s.e.m., **p<0.01 by Mann Whitney test. Representative images of 4T07 tumour spheres in control, 5μM SB203580 (SB) and 5μM LY-364947 (LY) treated cultures after 7 days. Scale bar: 100μm. (f) Affymetrix array values for the expression of Type I, II and III TGFβ receptors mRNA in T-HEp3 cells. (g) qPCR for TGFβ receptor III (TGFβR3) in T-HEp3 cells treated with 2 ng/ml TGFβ2 for 24 h in the presence or absence of TGFβ receptor III siRNA (si TGFβR3), n = 6 RNA samples per condition were assessed over 3 independent experiments. Error bars denote s.e.m., *p<0.05 by Mann Whitney test (h) IB for the indicated antigens on T-HEp3 cell lysates after treatment with 2 ng/ml TGFβ2 for 24 h in SF media and inhibition of TGFβ receptor III (TGFβR3).

Supplementary Table 1 HEp3 DTCs dissemination in nude mice.
Full size table
Supplementary Table 2 Expansion in vitro and cell lines establishment from HEp3 DTCs.
Full size table
Supplementary Table 3 BM DTCs incidence in control and SB203580 treated mice 4 weeks after surgery.
Full size table
Supplementary Table 4 Statistic Source Data.
Full size table
Supplementary Table 5 QPCR and Alu QPCR primer sequences.
Full size table
Supplementary Table 6 Antibodies information.
Full size table

Supplementary information

Supplementary Information

Supplementary Information (PDF 1878 kb)

Supplementary Table 1

Supplementary Information (XLSX 9 kb)

Supplementary Table 2

Supplementary Information (XLSX 9 kb)

Supplementary Table 3

Supplementary Information (XLSX 8 kb)

Supplementary Table 4

Supplementary Information (XLS 29 kb)

Supplementary Table 5

Supplementary Information (XLSX 10 kb)

Supplementary Table 6

Supplementary Information (XLSX 9 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bragado, P., Estrada, Y., Parikh, F. 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). https://doi.org/10.1038/ncb2861

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ncb2861

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer