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:

Identification of molecular determinants of primary and metastatic tumour re-initiation in breast cancer

Nature Cell Biology volume 17, pages 651–664 (2015)Cite this article

Subjects

Abstract

Through in vivo selection of multiple ER-negative human breast cancer populations for enhanced tumour-forming capacity, we have derived subpopulations that generate tumours more efficiently than their parental populations at low cell numbers. Tumorigenic-enriched subpopulations exhibited increased expression of LAMA4, FOXQ1 and NAP1L3—genes that are also expressed at greater levels by independently derived metastatic subpopulations. These genes promote metastatic efficiency. FOXQ1 promotes LAMA4 expression, and LAMA4 enhances clonal expansion following substratum detachment in vitro, tumour re-initiation in multiple organs, and disseminated metastatic cell proliferation and colonization. The promotion of cancer cell proliferation and tumour re-initiation by LAMA4 requires β1-integrin. Increased LAMA4 expression marks the transition of human pre-malignant breast lesions to malignant carcinomas, and tumoral LAMA4 overexpression predicts reduced relapse-free survival in ER-negative patients. Our findings reveal common features that govern primary and metastatic tumour re-initiation and identify a key molecular determinant of these processes.

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: In vivo selection for tumour re-initiation.
Figure 2: TE cells robustly colonize multiple organs as compared with their parental populations.
Figure 3: TE cells express increased levels of LAMA4, FOXQ1 and NAP1L3—genes also expressed at greater levels by highly metastatic cells that promote metastatic efficiency.
Figure 4: LAMA4 promotes the re-initiation of tumours in multiple organ microenvironments.
Figure 5: LAMA4 promotes cancer cell proliferation in the absence of substratum attachment in vitro in a β1-integrin-dependent manner.
Figure 6: LAMA4 promotes the proliferation of disseminated metastatic cells and micro-metastasis formation in vivo.
Figure 7: FOXQ1 promotes the expression of LAMA4
Figure 8: Increased expression of LAMA4 marks early breast cancer progression and is correlated with clinical relapse.

Similar content being viewed by others

References

  1. Klein, C. A. Parallel progression of primary tumours and metastases. Nat. Rev. Cancer 9, 302–312 (2009).

    CAS  PubMed  Google Scholar 

  2. Maheswaran, S. & Haber, D. A. Circulating tumor cells: a window into cancer biology and metastasis. Curr. Opin. Genet. Dev. 20, 96–99 (2010).

    CAS  PubMed Central  PubMed  Google Scholar 

  3. Chiang, A. C. & Massague, J. Molecular basis of metastasis. N. Engl. J. Med. 359, 2814–2823 (2008).

    CAS  PubMed Central  PubMed  Google Scholar 

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

    CAS  Google Scholar 

  5. Pavlova, N. N. et al. A role for PVRL4-driven cell–cell interactions in tumorigenesis. eLife 2, e00358 (2013).

    PubMed Central  PubMed  Google Scholar 

  6. Williams, S. A., Anderson, W. C., Santaguida, M. T. & Dylla, S. J. Patient-derived xenografts, the cancer stem cell paradigm, and cancer pathobiology in the 21st century. Lab. Invest. 93, 970–982 (2013).

    PubMed  Google Scholar 

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

    CAS  PubMed Central  PubMed  Google Scholar 

  8. Visvader, J. E. & Lindeman, G. J. Cancer stem cells: current status and evolving complexities. Cell Stem Cell 10, 717–728 (2012).

    CAS  PubMed  Google Scholar 

  9. Chaffer, C. L. et al. Poised chromatin at the ZEB1 promoter enables breast cancer cell plasticity and enhances tumorigenicity. Cell 154, 61–74 (2013).

    CAS  PubMed Central  PubMed  Google Scholar 

  10. Magee, J. A., Piskounova, E. & Morrison, S. J. Cancer stem cells: impact, heterogeneity, and uncertainty. Cancer Cell 21, 283–296 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  11. Vanharanta, S. & Massague, J. Origins of metastatic traits. Cancer Cell 24, 410–421 (2013).

    CAS  PubMed Central  PubMed  Google Scholar 

  12. Clark, E. A., Golub, T. R., Lander, E. S. & Hynes, R. O. Genomic analysis of metastasis reveals an essential role for RhoC. Nature 406, 532–535 (2000).

    CAS  PubMed  Google Scholar 

  13. Kang, Y. et al. A multigenic program mediating breast cancer metastasis to bone. Cancer Cell 3, 537–549 (2003).

    CAS  PubMed  Google Scholar 

  14. Minn, A. J. et al. Genes that mediate breast cancer metastasis to lung. Nature 436, 518–524 (2005).

    CAS  PubMed Central  PubMed  Google Scholar 

  15. Pencheva, N. et al. Convergent multi-miRNA targeting of ApoE drives LRP1/LRP8-dependent melanoma metastasis and angiogenesis. Cell 151, 1068–1082 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  16. Tavazoie, S. F. et al. Endogenous human microRNAs that suppress breast cancer metastasis. Nature 451, 147–152 (2008).

    CAS  PubMed Central  PubMed  Google Scholar 

  17. Png, K. J., Halberg, N., Yoshida, M. & Tavazoie, S. F. A microRNA regulon that mediates endothelial recruitment and metastasis by cancer cells. Nature 481, 190–194 (2012).

    CAS  Google Scholar 

  18. Putti, T. C. et al. Estrogen receptor-negative breast carcinomas: a review of morphology and immunophenotypical analysis. Mod. Pathol. 18, 26–35 (2005).

    CAS  PubMed  Google Scholar 

  19. Cailleau, R., Olive, M. & Cruciger, Q. V. Long-term human breast carcinoma cell lines of metastatic origin: preliminary characterization. In vitro 14, 911–915 (1978).

    CAS  PubMed  Google Scholar 

  20. Bos, P. D. et al. Genes that mediate breast cancer metastasis to the brain. Nature 459, 1005–1009 (2009).

    CAS  PubMed Central  PubMed  Google Scholar 

  21. Rhim, A. D. et al. EMT and dissemination precede pancreatic tumor formation. Cell 148, 349–361 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  22. Diehn, M. & Majeti, R. Metastatic cancer stem cells: an opportunity for improving cancer treatment? Cell Stem Cell 6, 502–503 (2010).

    CAS  PubMed  Google Scholar 

  23. Brabletz, T., Jung, A., Spaderna, S., Hlubek, F. & Kirchner, T. Opinion: migrating cancer stem cells—an integrated concept of malignant tumour progression. Nat. Rev. Cancer 5, 744–749 (2005).

    CAS  PubMed  Google Scholar 

  24. Brabletz, T. EMT and MET in metastasis: where are the cancer stem cells? Cancer Cell 22, 699–701 (2012).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed Central  PubMed  Google Scholar 

  26. Reymond, N., d’Agua, B. B. & Ridley, A. J. Crossing the endothelial barrier during metastasis. Nat. Rev. Cancer 13, 858–870 (2013).

    CAS  PubMed  Google Scholar 

  27. Nguyen, D. X., Bos, P. D. & Massague, J. Metastasis: from dissemination to organ-specific colonization. Nat. Rev. Cancer 9, 274–284 (2009).

    CAS  PubMed  Google Scholar 

  28. Stenzel, D. et al. Endothelial basement membrane limits tip cell formation by inducing Dll4/Notch signalling in vivo. EMBO Rep. 12, 1135–1143 (2011).

    CAS  PubMed Central  PubMed  Google Scholar 

  29. Goering, W. et al. Impairment of gastric acid secretion and increase of embryonic lethality in Foxq1-deficient mice. Cytogenet. Genome Res. 121, 88–95 (2008).

    CAS  PubMed  Google Scholar 

  30. Zhang, H. et al. Forkhead transcription factor foxq1 promotes epithelial-mesenchymal transition and breast cancer metastasis. Cancer Res. 71, 1292–1301 (2011).

    CAS  PubMed Central  PubMed  Google Scholar 

  31. Attia, M. et al. Interaction between nucleosome assembly protein 1-like family members. J. Mol. Biol. 407, 647–660 (2011).

    CAS  PubMed  Google Scholar 

  32. Buchstaller, J., McKeever, P. E. & Morrison, S. J. Tumorigenic cells are common in mouse MPNSTs but their frequency depends upon tumor genotype and assay conditions. Cancer Cell 21, 240–252 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  33. Grassian, A. R., Coloff, J. L. & Brugge, J. S. Extracellular matrix regulation of metabolism and implications for tumorigenesis. Cold Spring Harb. Symp. Quant. Biol. 76, 313–324 (2011).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed Central  PubMed  Google Scholar 

  35. Polyak, K. et al. p27Kip1, a cyclin-Cdk inhibitor, links transforming growth factor-β and contact inhibition to cell cycle arrest. Genes Dev. 8, 9–22 (1994).

    CAS  PubMed  Google Scholar 

  36. Zhu, X., Ohtsubo, M., Bohmer, R. M., Roberts, J. M. & Assoian, R. K. Adhesion-dependent cell cycle progression linked to the expression of cyclin D1, activation of cyclin E-cdk2, and phosphorylation of the retinoblastoma protein. J. Cell Biol. 133, 391–403 (1996).

    CAS  PubMed  Google Scholar 

  37. Harper, J. W., Adami, G. R., Wei, N., Keyomarsi, K. & Elledge, S. J. The p21 Cdk-interacting protein Cip1 is a potent inhibitor of G1 cyclin-dependent kinases. Cell 75, 805–816 (1993).

    CAS  PubMed  Google Scholar 

  38. Geberhiwot, T. et al. Laminin-8 (α4β1γ1) is synthesized by lymphoid cells, promotes lymphocyte migration and costimulates T cell proliferation. J. Cell Sci. 114, 423–433 (2001).

    CAS  PubMed  Google Scholar 

  39. Fujiwara, H., Kikkawa, Y., Sanzen, N. & Sekiguchi, K. Purification and characterization of human laminin-8. Laminin-8 stimulates cell adhesion and migration through α3β1 and α6β1 integrins. J. Biol. Chem. 276, 17550–17558 (2001).

    CAS  PubMed  Google Scholar 

  40. Kortesmaa, J., Yurchenco, P. & Tryggvason, K. Recombinant laminin-8 (α(4)β(1)γ(1)). Production, purification, and interactions with integrins. J. Biol. Chem. 275, 14853–14859 (2000).

    CAS  PubMed  Google Scholar 

  41. Hohenester, E. & Yurchenco, P. D. Laminins in basement membrane assembly. Cell Adhes. Migration 7, 56–63 (2013).

    Google Scholar 

  42. Moreno-Layseca, P. & Streuli, C. H. Signalling pathways linking integrins with cell cycle progression. Matrix Biol. 34, 144–153 (2014).

    CAS  PubMed  Google Scholar 

  43. Miranti, C. K. & Brugge, J. S. Sensing the environment: a historical perspective on integrin signal transduction. Nat. Cell Biol. 4, E83–90 (2002).

    CAS  PubMed  Google Scholar 

  44. Giancotti, F. G. Mechanisms governing metastatic dormancy and reactivation. Cell 155, 750–764 (2013).

    CAS  PubMed Central  PubMed  Google Scholar 

  45. Shibue, T. & Weinberg, R. A. Integrin β1-focal adhesion kinase signaling directs the proliferation of metastatic cancer cells disseminated in the lungs. Proc. Natl Acad. Sci. USA 106, 10290–10295 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Espina, V. & Liotta, L. A. What is the malignant nature of human ductal carcinoma in situ? Nat. Rev. Cancer 11, 68–75 (2011).

    CAS  PubMed  Google Scholar 

  47. Lee, S. et al. Differentially expressed genes regulating the progression of ductal carcinoma in situ to invasive breast cancer. Cancer Res. 72, 4574–4586 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  48. Ma, X. J. et al. Gene expression profiles of human breast cancer progression. Proc. Natl Acad. Sci. USA 100, 5974–5979 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Ma, X. J., Dahiya, S., Richardson, E., Erlander, M. & Sgroi, D. C. Gene expression profiling of the tumor microenvironment during breast cancer progression. Breast Cancer Res. 11, R7 (2009).

    PubMed Central  PubMed  Google Scholar 

  50. Schuetz, C. S. et al. Progression-specific genes identified by expression profiling of matched ductal carcinomas in situ and invasive breast tumors, combining laser capture microdissection and oligonucleotide microarray analysis. Cancer Res. 66, 5278–5286 (2006).

    CAS  PubMed  Google Scholar 

  51. Desmedt, C. et al. Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series. Clin. Cancer Res. 13, 3207–3214 (2007).

    CAS  PubMed  Google Scholar 

  52. Hatzis, C. et al. A genomic predictor of response and survival following taxane-anthracycline chemotherapy for invasive breast cancer. JAMA 305, 1873–1881 (2011).

    CAS  PubMed Central  PubMed  Google Scholar 

  53. van de Vijver, M. J. et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347, 1999–2009 (2002).

    CAS  PubMed  Google Scholar 

  54. Wang, Y. et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365, 671–679 (2005).

    CAS  PubMed  Google Scholar 

  55. Peduto, L. et al. ADAM12 is highly expressed in carcinoma-associated stroma and is required for mouse prostate tumor progression. Oncogene 25, 5462–5466 (2006).

    CAS  PubMed  Google Scholar 

  56. Kessenbrock, K., Plaks, V. & Werb, Z. Matrix metalloproteinases: regulators of the tumor microenvironment. Cell 141, 52–67 (2010).

    CAS  PubMed Central  PubMed  Google Scholar 

  57. Goss, P. E. & Chambers, A. F. Does tumour dormancy offer a therapeutic target? Nat. Rev. Cancer 10, 871–877 (2010).

    CAS  PubMed  Google Scholar 

  58. Nelson, C. M. & Bissell, M. J. Of extracellular matrix, scaffolds, and signaling: tissue architecture regulates development, homeostasis, and cancer. Annu. Rev. Cell Dev. Biol. 22, 287–309 (2006).

    CAS  PubMed Central  PubMed  Google Scholar 

  59. Kusuma, N. et al. Integrin-dependent response to laminin-511 regulates breast tumor cell invasion and metastasis. Int. J. Cancer 130, 555–566 (2012).

    CAS  PubMed  Google Scholar 

  60. Yurchenco, P. D. Basement membranes: cell scaffoldings and signaling platforms. Cold Spring Harb. Perspect. Biol. 3, a004911 (2011).

    PubMed Central  PubMed  Google Scholar 

  61. Fujita, M. et al. Overexpression of β1-chain-containing laminins in capillary basement membranes of human breast cancer and its metastases. Breast Cancer Res. 7, R411–421 (2005).

    CAS  PubMed Central  PubMed  Google Scholar 

  62. Hamill, K. J., Kligys, K., Hopkinson, S. B. & Jones, J. C. Laminin deposition in the extracellular matrix: a complex picture emerges. J. Cell Sci. 122, 4409–4417 (2009).

    CAS  PubMed Central  PubMed  Google Scholar 

  63. Ilani, T. et al. A secreted disulfide catalyst controls extracellular matrix composition and function. Science 341, 74–76 (2013).

    CAS  PubMed  Google Scholar 

  64. Vainionpaa, N., Lehto, V. P., Tryggvason, K. & Virtanen, I. α4 chain laminins are widely expressed in renal cell carcinomas and have a de-adhesive function. Lab. Invest. 87, 780–791 (2007).

    CAS  PubMed  Google Scholar 

  65. Jemal, A. et al. Global cancer statistics. CA Cancer J. Clin. 61, 69–90 (2011).

    PubMed  Google Scholar 

  66. Ali, S. & Coombes, R. C. Endocrine-responsive breast cancer and strategies for combating resistance. Nat. Rev. Cancer 2, 101–112 (2002).

    PubMed  Google Scholar 

  67. Ponomarev, V. et al. A novel triple-modality reporter gene for whole-body fluorescent, bioluminescent, and nuclear noninvasive imaging. Eur. J. Nucl. Med. Mol. Imaging 31, 740–751 (2004).

    CAS  PubMed  Google Scholar 

  68. Hickson, J. et al. Noninvasive molecular imaging of apoptosis in vivo using a modified firefly luciferase substrate, Z-DEVD-aminoluciferin. Cell Death Differ. 17, 1003–1010 (2010).

    CAS  PubMed  Google Scholar 

  69. Gazdar, A. F. et al. Characterization of paired tumor and non-tumor cell lines established from patients with breast cancer. Int. J. Cancer. 78, 766–774 (1998).

    CAS  PubMed  Google Scholar 

  70. Li, Q., Birkbak, N. J., Gyorffy, B., Szallasi, Z. & Eklund, A. C. Jetset: selecting the optimal microarray probe set to represent a gene. BMC Bioinformatics 12, 474 (2011).

    PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgements

We are grateful to members of our laboratory for insightful discussion and C. Alarcon, N. Halberg, N. Pencheva and A. Nguyen for providing comments on previous versions of this manuscript. We thank C. Blobel, S. Simon and J. Friedman for intellectual input and helpful suggestions. We thank A. Nguyen and J. M. Loo for assistance with splenic injections. We thank N. Halberg for assistance with tail-vein injections. We thank H. Goodarzi for assistance with statistical analysis. We thank P. Furlow for cloning assistance. We thank C. Zhao of the Rockefeller Genomics Resource Center for assistance with transcriptomic profiling. We thank S. Mazel and members of the Rockefeller Flow Cytometry Resource Center for FACS sorting. J.B.R., D.H. and L.B.N. are members of the Weill Cornell/Rockefeller/Sloan-Kettering Tri-Institutional MD-PhD Program supported by NIH MSTP grant GM07739. S.F.T. is a DOD Era of Hope Scholar and Collaborative Scholars and Innovators Award recipient and Head of the Elizabeth and Vincent Meyer Laboratory of Systems Cancer Biology.

Author information

Authors and Affiliations

  1. Laboratory of Systems Cancer Biology, Rockefeller University, Box 16, 1230 York Avenue New York, New York 10065, USA,

    Jason B. Ross, Doowon Huh, Lisa B. Noble & Sohail F. Tavazoie

Authors
  1. Jason B. Ross
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Doowon Huh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lisa B. Noble
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sohail F. Tavazoie
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.F.T. conceived the project and supervised all research. J.B.R. and S.F.T. wrote the manuscript. J.B.R. conducted in vivo selection for tumour re-initiation. J.B.R., D.H. and L.B.N. designed, performed and analysed the experiments.

Corresponding author

Correspondence to Sohail F. Tavazoie.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 5 Characterization of tumorigenic-enriched derivatives.

(a) 2.5 × 104 MDA-parental or MDA-TE3 cells were seeded into 6-well adherent tissue-culture plates. The number of cells per well on day 5 was counted and normalized to cell counts on day 1. n = 3 independent wells. (b) 2.5 × 104 CN34-parental or CN34-TE2 cells were seeded into 6-well adherent tissue-culture plates. The number of cells per well on day 5 was counted and normalized to cell counts on day 1. n = 3 independent wells. (c) 1 × 102 MDA-parental or MDA-TE3 cells were seeded into 10cm adherent tissue-culture plates. The number of colonies per well on day 14 was counted upon staining with crystal-violet. n = 3 independent plates. (d) 1 × 102 CN34-parental or CN34-TE2 cells were seeded into 10cm adherent tissue-culture plates. The number of colonies per well on day 14 was counted upon staining with crystal-violet. n = 3 independent plates. (e) Assessment of cell attachment to adherent tissue culture plates of MDA-parental cells compared to MDA-TE3 cells. n = 3 independent wells. (f) Assessment of cell attachment to adherent tissue culture plates of CN34-parental cells compared to CN34-TE3 cells. n = 6 independent wells. (g) Endothelial recruitment assay comparing the relative capacity of MDA-parental cells and MDA-TE3 cells recruit Human Vein Endothelial Cells (HUVECs). n = 6 independent trans-well inserts. (h) Endothelial recruitment assay comparing the relative capacity of CN34-parental cells and CN34-TE3 cells recruit Human Vein Endothelial Cells (HUVECs). n = 8 independent trans-well inserts. (i) MDA-parental and MDA-TE3 populations were stained with antibodies specific to the cell surface markers CD44 and CD24 and analyzed using flow cytometry. For the MDA-parental population, 86.1% of the cells were CD44 + CD24-. For the MDA-TE3 population, 84.4% of the cells were CD44 + CD24-. (j) CN34-parental and CN34-TE2 populations were stained with antibodies specific to the cell surface markers CD44 and CD24 and analyzed using flow cytometry. For the CN34-parental population, 89.1% of the cells were CD44 + CD24-. For the CN34-TE2 population, 86.1% of the cells were CD44 + CD24-. NS is not significant. ∗∗P < 0.01,∗∗∗P < 0.001 were obtained using a two-sided student’s t-test (a–h). All data are represented as mean ± S.E.M.

Supplementary Figure 6 Independent shRNA knockdown of LAMA4, FOXQ1, and NAP1L3 leads to suppression of metastasis in vivo.

(a) 1.5 × 105 CN34-LM1a cells transduced with either a control shRNA hairpin or an independent shRNA hairpin targeting LAMA4 were inoculated intravenously into immunodeficient mice. shRNA depletion of LAMA4 led to a significant reduction in metastasis as measured by bioluminescence imaging on day 25 normalized to post-injection signal on day 0. n = 4 (shControl), n = 3 (shLAMA4_2) independent mice. (b) 5 × 104 CN34-LM1a cells transduced with either a control shRNA hairpin or an independent shRNA hairpin targeting FOXQ1 were inoculated intravenously into immunodeficient mice. shRNA depletion of FOXQ1 led to a significant reduction in metastasis as measured by bioluminescence imaging on day 84 normalized to post-injection signal on day 0. n = 4 (shControl), n = 5 (shFOXQ1_2) independent mice. (c) 5 × 104 CN34-LM1a cells transduced with either a control shRNA hairpin or an independent shRNA hairpin targeting NAP1L3 were inoculated intravenously into immunodeficient mice. shRNA depletion of NAP1L3 led to a significant reduction in metastasis as measured by bioluminescence imaging on day 42 normalized to post-injection signal on day 0. n = 4 independent mice. ∗P < 0.05,∗∗P < 0.01, were obtained using one-sided Mann–Whitney test (a–c). All data are represented as mean + S.E.M.

Supplementary Figure 7 Assessment of laminin-α4 protein levels in vitro and in vivo.

(a) Anti-laminin-α4 antibody was used to detect endogenous LAMA4 protein in supernatant collected from in vitro culture of MDA-parental, MDA-TE3, and MDA-LM2 cells. (b) Anti-laminin-α4 antibody was used to detect endogenous LAMA4 protein in supernatant collected from in vitro culture of CN34-parental and CN34-TE2 cells. (c) Anti-laminin-α4 antibody was used to detect endogenous protein in supernatant collected from in vitro culture of MDA-parental empty vector control (C), MDA-parental LAMA4-overexpression (oe), MDA-TE3 shControl (shC), MDA-TE3 shLAMA4_1 (sh1), and MDA-TE3 shLAMA4_2 (sh2) cells. All Western blots (a–c) are representative and based on multiple experiments (see Supplementary Fig. 8 for un-cropped images). (d) Anti-human laminin-α4 antibody was used to detect endogenous LAMA4 protein in xenograft tumors derived from MDA-parental, MDA-TE3, or MDA-LM2 populations. Upper panels: Red is anti-laminin-α4 antibody (LAMA4), Blue is DAPI. Core is representative of tumor core, Edge is representative of tumor edge. Lower panels: Red is non-specific isotype-matched control antibody (IgG), Blue is DAPI. Core is representative of tumor core. Scale bars: 25 μm (d) Immunofluorescence of xenograft tumors at higher magnification. Co-staining of xenograft tumors with anti-laminin-α4 antibody and anti-Collagen-IV antibody revealed areas of overlap. Red is anti-laminin-α4 antibody (LAMA4), Green is anti-Collagen-IV antibody (Col-IV), Blue is DAPI. Scale bars: 25 μm. Immunofluorescence (d–e) is representative of multiple samples/experiments.

Supplementary Figure 8 LAMA4 is sufficient to promote metastatic colonization and promotes tumor re-initiation from low cell numbers.

(a–b) 2 × 105 HCC1806 cells transfected with either a control siRNA or two independent siRNAs targeting LAMA4 were inoculated intravenously into immunodeficient mice. siRNA depletion of LAMA4 led to a significant reduction in metastasis as measured by bioluminescence imaging on day 42 normalized to post-injection signal on day 0 (a). n = 6 independent mice. Lungs were harvested on day 42, H&E-stained, and the number of macroscopic nodules per lung section was counted. Representative lungs on day 42 (b). n = 6 (siControl), n = 5 (siLAMA4_5), n = 6 (siLAMA4_6) lungs from independent mice. Scale bars: 1mm. Insets are magnified 5×. (c–d) 5 × 105 CN34-parental cells transduced with either an empty vector control or LAMA4 over-expression vector were inoculated intravenously into immunodeficient mice. Lung bioluminescence was measured on day 133 and normalized to post-injection signal at day 0 (c). n = 7 independent mice. Lungs were harvested on day 133, vimentin-stained, and the number of macroscopic nodules per lung section was counted. Representative vimentin-stained lungs on day 133 (d). n = 7 lungs from 7 independent mice. Scale bars: 1mm. Insets are magnified 5×. (e) 1 × 101 MDA-TE3 cells transduced with either a control shRNA or an independent shRNA targeting LAMA4 were injected into the mammary fat pads of immunodeficient mice. MDA-TE3 shControl cells yielded tumors in 14/24 sites as compared to 6/24 sites for MDA-TE3 shLAMA4_2 after 10 weeks (left). n = 24 independent mammary fat pad injections (pooled from 6 mice with 4 injections each per condition and represented as open squares, right). (f) The number of tumors formed upon injection of 5 × 105 MDA-TE3 cells transduced with either a control shRNA or two independent shRNAs targeting LAMA4 into the mammary fat pads of immunodeficient mice was quantified (see Fig. 4f). Tumors were formed in all cases. n = 8 independent mammary fat pad injections (pooled from 2 mice with 4 injections each per condition). (g,h) 1 × 102 MDA-TE3 cells transduced with either a control shRNA or an independent shRNA targeting LAMA4 were injected directly into the lung parenchyma to assess ectopic tumor re-initiation capacity. Lung bioluminescence was measured on day 63 (g). n = 5 independent mice. On day 63 lungs were sectioned, vimentin stained, and the number of macroscopic nodules per lung was counted (h). n = 5 lungs from 5 independent mice. Scale bars: 1mm. Insets are magnified 5×.∗P < 0.05,∗∗P < 0.01 were obtained using one-sided Mann–Whitney test (a–d,g–h) or one-sided Fisher’s exact test (e). All data are represented as mean + S.E.M.

Supplementary Figure 9 LAMA4’s promotion of proliferation in vitro and tumor re-initiation in vivo requires β1-integrin.

(a) Cells were sorted at clonal density (one cell per well) into low-attachment 96-well plates to assess proliferation in the absence of substratum-attachment. (b) MDA-parental, MDA-TE3, or MDA-LM2 cells were sorted at clonal density into low-attachment plates. The number of wells containing one cell versus the number of wells containing multiple cells was assessed on D3. n = 145 (parental), n = 156 (TE3), n = 133 (LM2) wells. Data from Fig. 5b. (c) MDA-TE3-control cells or MDA-TE3-LAMA4-knockdown cells were sorted at clonal density into low-attachment plates. The number of wells containing one cell compa versus the number of wells containing multiple cells was assessed on D3. n = 189 (shControl), n = 196 (shLAMA4_1), n = 197 (shLAMA4_2) wells. Data from Fig. 5a. (d) Cells were seeded at low densitiy into low-attachment 6-well plates in high-viscosity media and isolated for cell-cycle analysis. (e) Cell-cycle analysis of MDA-TE3-control cells or MDA-TE3-LAMA4-knockdown cells. n = 5 samples. (f) Ki67-positive fraction was assessed in MDA-TE3-control cells or MDA-TE3-LAMA4-knockdown cells. n = 6 samples. (g) β1-integrin blocking antibody suppressed the proliferation of CN34-TE2 cells upon sorting at clonal density into low-attachment plates. Counts on D3. n = 383 (IgG), n = 438 (β1) wells. (h) The reduced proliferation of MDA-TE3-LAMA4-knockdown cells was rescued by recombinant LAMA4-containing protein upon sorting at clonal density into low-attachment plates. Counts on D3. n = 4 independent experiments. (i) Incubation of MDA-Parental-control cells with β1-integrin blocking antibody did not lead to significant changes in proliferation upon sorting at clonal density into low-attachment plates (in contrast to MDA-Parental-LAMA4-overexpressing cells, Fig. 5g). Counts on D3. n = 233 (IgG), n = 221 (β1), n = 214 (αvβ3) wells. (j) Incubation of MDA-TE3-shControl cells with laminin-411 did not lead to significant changes in proliferation upon sorting at clonal density into low-attachment plates (in contrast to MDA-TE3-LAMA4-knockdown cells, Supplementary Fig. 5h). Counts on D3. n = 237 (neg), n = 242 (BSA), n = 269 (411) wells. (k) Pre-incubation of MDA-TE3-shControl cells with β1-integrin blocking antibody led to decreased proliferation independent of the addition of laminin-411 upon sorting at clonal density into low-attachment plates. Counts on D3. n = 169 (IgG + BSA), n = 337 (IgG + 411), n = 299 (β1 + BSA), n = 313 (β1 + 411) wells. (l) Western of lysates from MDA-TE3-control cells or MDA-TE3-LAMA4-knockdown cells cultured in the absence of substratum attachment. Western representative and based on multiple experiments (Supplementary Fig. 8, un-cropped images). ∗P < 0.05,∗∗P < 0.01,∗∗∗P < 0.001 were obtained using one-sided Fisher’s exact test (b,c), one-sided student’s t-test (e,f,h) or one-sided Mann–Whitney test (g,i–k). All data are represented as mean + S.E.M.

Supplementary Figure 10 LAMA4 does not significantly regulate apoptosis at early time points during metastatic colonization.

(a) 3 × 105 CN34-LM1a cells transduced with either control shRNA or an shRNA targeting LAMA4 were injected intravenously into immunodeficient mice (see Fig. 6a, b). In vivo quantification of apoptotic cells was monitored by measurement of a luciferase-based caspase-3/7 reporter normalized to cancer cell luciferase signal over several days (left). Representative luciferase-based caspase-3/7 (non-normalized) bioluminescence signal (right). n = 5 independent mice. NS is not significant based on a two-sided Student’s t-test. (b) Cumulative fraction plot depicting the distribution of metastatic foci size in the lungs of animals injected with CN34-LM1a cells that were transduced with either a control shRNA hairpin or an shRNA hairpin targeting LAMA4 (see Fig. 6a, b). n = 5 lungs from 5 independent mice. (c) Cumulative fraction plot depicting the distribution of metastatic foci size in the lungs of animals injected with CN34-LM1a cells that were transduced with either a control shRNA hairpin or two independent shRNA hairpins targeting LAMA4 (see Fig. 6e, f). n = 4 lungs from 4 independent mice. P values were obtained using a Kolmogorov-Smirnov test. All data are represented as mean ± S.E.M.

Supplementary Figure 11 Assessment of LAMA4 expression upon depletion of NAP1L3.

(a–b) Relative expression of LAMA4 and NAP1L3 following siRNA knockdown of NAP1L3 in LM1as (a; n = 12) or LM2s (b; n = 10) compared to control siRNA. n is the number of samples collected over 4 (a) or 3 (b) independent experiments. NS is not significant. ∗P < 0.05,∗∗∗P < 0.001 were obtained using a two-sided one-sample t-test (a–b). All data are represented as mean ± S.E.M.

Supplementary Figure 12 Un-cropped Western blots.

Rectangle includes cropped images present in Supplementary Fig. 3 (a–c) and Supplementary Fig. 5 (l).

Supplementary Table 1 Genes with increased expression in tumorigenic-enriched (TE) derivatives relative to parental populations.
Full size table
Supplementary Table 2 Genes with increased expression in lung-metastatic (LM) derivatives relative to parental populations.
Full size table
Supplementary Table 3 Genes with increased expression in tumorigenic-enriched (TE) and lung-metastatic (LM) cells relative to parental populations.
Full size table
Supplementary Table 4 siRNA, shRNA, and Primer Sequences.
Full size table

Supplementary information

Supplementary Information

Supplementary Information (PDF 2278 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ross, J., Huh, D., Noble, L. et al. Identification of molecular determinants of primary and metastatic tumour re-initiation in breast cancer. Nat Cell Biol 17, 651–664 (2015). https://doi.org/10.1038/ncb3148

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ncb3148

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