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.

  • Letter
  • Published:

SMAD4-dependent barrier constrains prostate cancer growth and metastatic progression

Nature volume 470, pages 269–273 (2011)Cite this article

Abstract

Effective clinical management of prostate cancer (PCA) has been challenged by significant intratumoural heterogeneity on the genomic and pathological levels and limited understanding of the genetic elements governing disease progression1. Here, we exploited the experimental merits of the mouse to test the hypothesis that pathways constraining progression might be activated in indolent Pten-null mouse prostate tumours and that inactivation of such progression barriers in mice would engender a metastasis-prone condition. Comparative transcriptomic and canonical pathway analyses, followed by biochemical confirmation, of normal prostate epithelium versus poorly progressive Pten-null prostate cancers revealed robust activation of the TGFβ/BMP–SMAD4 signalling axis. The functional relevance of SMAD4 was further supported by emergence of invasive, metastatic and lethal prostate cancers with 100% penetrance upon genetic deletion of Smad4 in the Pten-null mouse prostate. Pathological and molecular analysis as well as transcriptomic knowledge-based pathway profiling of emerging tumours identified cell proliferation and invasion as two cardinal tumour biological features in the metastatic Smad4/Pten-null PCA model. Follow-on pathological and functional assessment confirmed cyclin D1 and SPP1 as key mediators of these biological processes, which together with PTEN and SMAD4, form a four-gene signature that is prognostic of prostate-specific antigen (PSA) biochemical recurrence and lethal metastasis in human PCA. This model-informed progression analysis, together with genetic, functional and translational studies, establishes SMAD4 as a key regulator of PCA progression in mice and humans.

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: SMAD4 is a putative suppressor of prostate tumour progression.
Figure 2: Smad4 deletion drives progression of Pten -deficient prostate tumour to highly aggressive prostate cancer metastatic to lymph node and lung.
Figure 3: Ccnd1 and Spp1 are mediators of prostate tumour cell proliferation and metastasis.
Figure 4: Prognostic potential of a four-gene signature in human PCA.

Similar content being viewed by others

Accession codes

Primary accessions

Gene Expression Omnibus

Data deposits

The microarray data have been deposited in the GOE database with accession number GSE25140.

References

  1. Andreoiu, M. & Cheng, L. Multifocal prostate cancer: biologic, prognostic, and therapeutic implications. Hum. Pathol. 41, 781–793 (2010)

    Article  Google Scholar 

  2. Jemal, A., Siegel, R., Xu, J. & Ward, E. Cancer statistics, 2010. CA Cancer J. Clin. (2010)

  3. Walsh, P. C., DeWeese, T. L. & Eisenberger, M. A. Localized prostate cancer. N. Engl. J. Med. 357, 2696–2705 (2007)

    Article  CAS  Google Scholar 

  4. Rubin, M. A. Targeted therapy of cancer: new roles for pathologists—prostate cancer. Mod. Pathol. 21 (Suppl 2). S44–S55 (2008)

    Article  CAS  Google Scholar 

  5. Taylor, B. S. et al. Integrative genomic profiling of human prostate cancer. Cancer Cell 18, 11–22 (2010)

    Article  CAS  Google Scholar 

  6. Jeet, V., Russell, P. J. & Khatri, A. Modeling prostate cancer: a perspective on transgenic mouse models. Cancer Metastasis Rev. 29, 123–142 (2010)

    Article  Google Scholar 

  7. Wang, S. et al. Prostate-specific deletion of the murine Pten tumor suppressor gene leads to metastatic prostate cancer. Cancer Cell 4, 209–221 (2003)

    Article  CAS  Google Scholar 

  8. Chen, Z. et al. Crucial role of p53-dependent cellular senescence in suppression of Pten-deficient tumorigenesis. Nature 436, 725–730 (2005)

    Article  ADS  CAS  Google Scholar 

  9. Trotman, L. C. et al. Pten dose dictates cancer progression in the prostate. PLoS Biol. 1, E59 (2003)

    Article  Google Scholar 

  10. Ma, X. et al. Targeted biallelic inactivation of Pten in the mouse prostate leads to prostate cancer accompanied by increased epithelial cell proliferation but not by reduced apoptosis. Cancer Res. 65, 5730–5739 (2005)

    Article  CAS  Google Scholar 

  11. Zeng, L., Rowland, R. G., Lele, S. M. & Kyprianou, N. Apoptosis incidence and protein expression of p53, TGF-beta receptor II, p27Kip1, and Smad4 in benign, premalignant, and malignant human prostate. Hum. Pathol. 35, 290–297 (2004)

    Article  CAS  Google Scholar 

  12. Aitchison, A. A. et al. Promoter methylation correlates with reduced Smad4 expression in advanced prostate cancer. Prostate 68, 661–674 (2008)

    Article  CAS  Google Scholar 

  13. Glinsky, G. V., Glinskii, A. B., Stephenson, A. J., Hoffman, R. M. & Gerald, W. L. Gene expression profiling predicts clinical outcome of prostate cancer. J. Clin. Invest. 113, 913–923 (2004)

    Article  CAS  Google Scholar 

  14. Hullinger, T. G., Pan, Q., Viswanathan, H. L. & Somerman, M. J. TGFβ and BMP-2 activation of the OPN promoter: roles of Smad- and Hox-binding elements. Exp. Cell Res. 262, 69–74 (2001)

    Article  CAS  Google Scholar 

  15. Packer, L. et al. Osteopontin is a downstream effector of the PI3-kinase pathway in melanomas that is inversely correlated with functional PTEN. Carcinogenesis 27, 1778–1786 (2006)

    Article  CAS  Google Scholar 

  16. Shi, X., Bai, S., Li, L. & Cao, X. Hoxa-9 represses transforming growth factor-β-induced osteopontin gene transcription. J. Biol. Chem. 276, 850–855 (2001)

    Article  CAS  Google Scholar 

  17. Paik, J. H. et al. FoxOs cooperatively regulate diverse pathways governing neural stem cell homeostasis. Cell Stem Cell 5, 540–553 (2009)

    Article  CAS  Google Scholar 

  18. Massague, J., Seoane, J. & Wotton, D. Smad transcription factors. Genes Dev. 19, 2783–2810 (2005)

    Article  CAS  Google Scholar 

  19. Yu, Y. P. et al. Gene expression alterations in prostate cancer predicting tumor aggression and preceding development of malignancy. J. Clin. Oncol. 22, 2790–2799 (2004)

    Article  CAS  Google Scholar 

  20. Dhanasekaran, S. M. et al. Delineation of prognostic biomarkers in prostate cancer. Nature 412, 822–826 (2001)

    Article  ADS  CAS  Google Scholar 

  21. Bardeesy, N. et al. Smad4 is dispensable for normal pancreas development yet critical in progression and tumor biology of pancreas cancer. Genes Dev. 20, 3130–3146 (2006)

    Article  CAS  Google Scholar 

  22. Zheng, H. et al. p53 and Pten control neural and glioma stem/progenitor cell renewal and differentiation. Nature 455, 1129–1133 (2008)

    Article  ADS  CAS  Google Scholar 

  23. Marino, S., Vooijs, M., van der Gulden, H., Jonkers, J. & Berns, A. Induction of medulloblastomas in p53-null mutant mice by somatic inactivation of Rb in the external granular layer cells of the cerebellum. Genes Dev. 14, 994–1004 (2000)

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Wu, X. et al. Generation of a prostate epithelial cell-specific Cre transgenic mouse model for tissue-specific gene ablation. Mech. Dev. 101, 61–69 (2001)

    Article  CAS  Google Scholar 

  25. Berger, R. et al. Androgen-induced differentiation and tumorigenicity of human prostate epithelial cells. Cancer Res. 64, 8867–8875 (2004)

    Article  CAS  Google Scholar 

  26. Wang, Y. et al. A human prostatic epithelial model of hormonal carcinogenesis. Cancer Res. 61, 6064–6072 (2001)

    CAS  PubMed  Google Scholar 

  27. Singh, D. et al. Gene expression correlates of clinical prostate cancer behavior. Cancer Cell 1, 203–209 (2002)

    Article  CAS  Google Scholar 

  28. Haibe-Kains, B., Desmedt, C., Sotiriou, C. & Bontempi, G. A comparative study of survival models for breast cancer prognostication based on microarray data: does a single gene beat them all? Bioinformatics 24, 2200–2208 (2008)

    Article  CAS  Google Scholar 

  29. Steering Committee of the Physicians’ Health Study Research Group. Final report on the aspirin component of the ongoing Physicians’ Health Study. N. Engl. J. Med. 321, 129–135 (1989)

  30. Christen, W. G., Gaziano, J. M. & Hennekens, C. H. Design of Physicians’ Health Study II—a randomized trial of beta-carotene, vitamins E and C, and multivitamins, in prevention of cancer, cardiovascular disease, and eye disease, and review of results of completed trials. Ann. Epidemiol. 10, 125–134 (2000)

    Article  CAS  Google Scholar 

  31. Sboner, A. et al. Molecular sampling of prostate cancer: a dilemma for predicting disease progression. BMC Med. Genomics 3, 8 (2010)

    Article  Google Scholar 

  32. Johansson, J. E. et al. Natural history of early, localized prostate cancer. J. Am. Med. Assoc. 291, 2713–2719 (2004)

    Article  CAS  Google Scholar 

  33. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005)

    Article  ADS  CAS  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the late W. Gerald for providing the primary gene expression data and clinical outcome files13. We thank S. Zhou for excellent mouse husbandry and care, B. Xiong and G. Tonon for bioinformatic assistance, and S. Jia, J. M. Stommel, J. Paik, M. Kim and A. C. Kimmelman for helpful discussion. We thank M. Vidal, the Ellison Foundation and DFCI ISR for support of ORF cloning efforts, R. Maser for MSCV-puro-v5 gateway vector, W. Hahn for shRNA constructs. We thank the DF/HCC Specialized Histopathology Core and the DF/HCC Tissue Microarray and Imaging core for the TMA IHC staining; the DFCI/BWH Center for Molecular Oncologic Pathology (CMOP) for the quantification of the IHC. Z.D was supported by the Damon Runyon Cancer Research Foundation. D.H. was supported by a graduate fellowship from the National Science Foundation. H.Z. was supported by the Helen Hay Whitney Foundation. Y.A.W. was supported by the Multiple Myeloma Research Foundation. This work is supported by the Belfer Institute for Applied Cancer Science, NCI U01-CA84313 (L.C. and R.A.D.), DF/HCC SPORE in Prostate Cancer P50 CA090381-08 (Z.D.), the National Cancer Institute (M.L. RO1CA131945 and P50 CA90381, L.M. RO1 5R01CA136578, M.S. R01CA141298), and the Linda and Arthur Gelb Center for Translational Research (M.L.). R.A.D. was supported by an American Cancer Society Research Professorship and L.M. was supported by the Prostate Cancer Foundation.

Author information

Author notes

  1. Chang-Jiun Wu and Gerald C. Chu: These authors contributed equally to this work.

Authors and Affiliations

  1. Belfer Institute for Applied Cancer Science, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Zhihu Ding, Chang-Jiun Wu, Gerald C. Chu, Yonghong Xiao, Dennis Ho, Samuel R. Perry, Emma S. Labrot, Baoli Hu, Shan Jiang, Hongwu Zheng, Alexander H. Stegh, Kenneth L. Scott, Y. Alan Wang, Lynda Chin & Ronald A. DePinho

  2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Zhihu Ding, Chang-Jiun Wu, Gerald C. Chu, Yonghong Xiao, Dennis Ho, Samuel R. Perry, Emma S. Labrot, Xiaoqiu Wu, Rosina Lis, Baoli Hu, Shan Jiang, Hongwu Zheng, Alexander H. Stegh, Kenneth L. Scott, Y. Alan Wang, Massimo Loda, Lynda Chin & Ronald A. DePinho

  3. Department of Genetics, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Zhihu Ding, Chang-Jiun Wu, Dennis Ho, Hongwu Zheng, Alexander H. Stegh, Kenneth L. Scott, David E. Hill, Lynda Chin & Ronald A. DePinho

  4. Department of Medicine, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Zhihu Ding, Chang-Jiun Wu, Dennis Ho, Hongwu Zheng, Alexander H. Stegh, Kenneth L. Scott, Lynda Chin & Ronald A. DePinho

  5. Department of Pathology, Brigham and Women’s Hospital, Boston, 02115, Massachusetts, USA

    Gerald C. Chu & Massimo Loda

  6. McArdle Lab for Cancer Research, University of Wisconsin, Madison, 53706-1526, Wisconsin, USA

    Jingfang Zhang

  7. Center for Molecular Oncologic Pathology, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Xiaoqiu Wu, Rosina Lis & Massimo Loda

  8. Pediatric Oncology, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Yujin Hoshida & Todd R. Golub

  9. The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, 02142, Massachusetts, USA

    Yujin Hoshida & Todd R. Golub

  10. Department of Statistics, Stanford University, Stanford, 94305, California, USA

    David Hiller & Wing H. Wong

  11. Renal Cancer Program, Dana-Farber/Harvard Cancer Center, Boston, 02115, Massachusetts, USA

    Sabina Signoretti

  12. Department of Medicine, Massachusetts General Hospital Cancer Center, Boston, 02114, Massachusetts, USA

    Nabeel Bardeesy

  13. Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    David E. Hill

  14. Department of Dermatology, Brigham and Women’s Hospital, Boston, 02115, Massachusetts, USA

    Lynda Chin

  15. Department of Epidemiology, Harvard School of Public Health, Boston, 02115, Massachusetts, USA

    Meir J. Stampfer & Lorelei Mucci

  16. Department of Nutrition, Harvard School of Public Health, Boston, 02115, Massachusetts, USA

    Meir J. Stampfer

  17. Channing Laboratory, Brigham and Women’s Hospital, Boston, 02115, Massachusetts, USA

    Meir J. Stampfer & Lorelei Mucci

Authors
  1. Zhihu Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chang-Jiun Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gerald C. Chu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yonghong Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dennis Ho
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jingfang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Samuel R. Perry
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Emma S. Labrot
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Xiaoqiu Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Rosina Lis
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Yujin Hoshida
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. David Hiller
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Baoli Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Shan Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Hongwu Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Alexander H. Stegh
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Kenneth L. Scott
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Sabina Signoretti
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Nabeel Bardeesy
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Y. Alan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. David E. Hill
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Todd R. Golub
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Meir J. Stampfer
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Wing H. Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Massimo Loda
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Lorelei Mucci
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Lynda Chin
    View author publications

    You can also search for this author in PubMed Google Scholar

  28. Ronald A. DePinho
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Z.D. designed and performed the experiments. L.C. and R.A.D. supervised experiments and computational analysis and contributed as senior authors. C.J.W., Y.X., Y.H., D.H., T.R.G., M.J.S., W.H.W. and L.M. performed the computational analysis. G.C.C. provided pathology analyses. X.W., R.L., S.S. and M.L. performed TMA staining and quantification. N.B. generated Smad4L mouse allele. D.E.H. provided the human ORFeome clones. D.H., J.Z., S.R.P., E.S.L., B.H., S.J., H.Z., A.H.S. and K.L.S. performed the experiments. Y.A.W. contributed to the writing of the manuscript.

Corresponding authors

Correspondence to Lynda Chin or Ronald A. DePinho.

Ethics declarations

Competing interests

The gene signature and technology developed in this paper have been licensed by Metamark GENETICS (http://www.metamarkgenetics.com/). L.C. and R.A.D. are the founders of Metamark GENETICS. Z.D., C.W. and M.L. are consultants for Metamark GENETICS.

Supplementary information

Supplementary Information

The file contains Supplementary Figures 1-21 with legends and Supplementary Tables 1-8. (PDF 1558 kb)

Supplementary Data 1

This table shows a complete differentially expressed gene list was generated by a class comparison between WT (n=3) and Ptenpc-/- (n=5) anterior prostates at 15 weeks of age. (XLS 705 kb)

Supplementary Data 2

This table shows a complete differentially expressed gene list was generated by a class comparison between Ptenpc-/- (n=5) and Ptenpc-/-Smad4pc-/- (n=5) anterior prostate tumors at 15 weeks of age. (XLS 103 kb)

Supplementary Data 3

This table shows a complete differentially expressed gene list was generated by a class comparison between Ptenpc-/- and Ptenpc-/-p53pc-/- mouse anterior prostates at 15 weeks of age. (XLS 89 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ding, Z., Wu, CJ., Chu, G. et al. SMAD4-dependent barrier constrains prostate cancer growth and metastatic progression. Nature 470, 269–273 (2011). https://doi.org/10.1038/nature09677

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature09677

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing