Movatterモバイル変換

[0]ホーム
URL:

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.

Advertisement

Nature
  • Letter
  • Published:

Gene expression profiling predicts clinical outcome of breast cancer

Naturevolume 415, pages530–536 (2002)Cite this article

Abstract

Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour1,2,3. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70–80% of patients receiving this treatment would have survived without it4,5. None of the signatures of breast cancer gene expression reported to date6,7,8,9,10,11,12 allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases (‘poor prognosis’ signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours ofBRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.

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

Access options

Access through your institution

Subscription info for Japanese customers

We have a dedicated website for our Japanese customers. Please go tonatureasia.com to subscribe to this journal.

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

￥ 4,980

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

Figure 1: Unsupervised two-dimensional cluster analysis of 98 breast tumours.
Figure 2: Supervised classification on prognosis signatures.
Figure 3: Supervised classification on ER andBRCA1 signatures.

Similar content being viewed by others

References

  1. McGuire, W. L. Breast cancer prognostic factors: evaluation guidelines.J. Natl Cancer Inst.83, 154–155 (1991).

    Article CAS  Google Scholar 

  2. Goldhirsch, A., Glick, J. H., Gelber, R. D. & Senn, H. J. Meeting highlights: international consensus panel on the treatment of primary breast cancer.J. Natl Cancer Inst.90, 1601–1608 (1998).

    Article CAS  Google Scholar 

  3. Eifel, P. et al. National institutes of health consensus development conference statement: adjuvant therapy for breast cancer, November 1–3, 2000.J. Natl Cancer Inst.93, 979–989 (2001).

    Article CAS  Google Scholar 

  4. Early Breast Cancer Trialists' Collaborative Group. Polychemotherapy for early breast cancer: an overview of the randomised trials.Lancet352, 930–942 (1998).

    Article  Google Scholar 

  5. Early Breast Cancer Trialists' Collaborative Group. Tamoxifen for early breast cancer: an overview of the randomised trials.Lancet351, 1451–1467 (1998).

    Article  Google Scholar 

  6. Perou, C. M. et al. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers.Proc. Natl Acad. Sci. USA96, 9212–9217 (1999).

    Article ADS CAS  Google Scholar 

  7. Perou, C. M. et al. Molecular portraits of human breast tumours.Nature406, 747–752 (2000).

    Article ADS CAS  Google Scholar 

  8. Gruvberger, S. et al. Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns.Cancer Res.61, 5979–5984 (2001).

    CAS PubMed  Google Scholar 

  9. Martin, K. J. et al. Linking gene expression patterns to therapeutic groups in breast cancer.Cancer Res.60, 2232–2238 (2000).

    CAS PubMed  Google Scholar 

  10. Zajchowski, D. A. et al. Identification of gene expression profiles that predict the aggressive behavior of breast cancer cells.Cancer Res.61, 5168–5178 (2001).

    CAS PubMed  Google Scholar 

  11. Sorlie, T. et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.Proc. Natl Acad. Sci. USA98, 10869–10874 (2001).

    Article ADS CAS  Google Scholar 

  12. West, M. et al. Predicting the clinical status of human breast cancer by using gene expression profiles.Proc. Natl Acad. Sci. USA98, 11462–11467 (2001).

    Article ADS CAS  Google Scholar 

  13. Hughes, T. R. et al. Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer.Nature Biotechnol.19, 342–347 (2001).

    Article CAS  Google Scholar 

  14. Roberts, C. J. et al. Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles.Science287, 873–880 (2000).

    Article ADS CAS  Google Scholar 

  15. Lakhani, S. R. et al. Multifactorial analysis of differences between sporadic breast cancers and cancers involving BRCA1 and BRCA2 mutations.J. Natl Cancer Inst.90, 1138–1145 (1998).

    Article CAS  Google Scholar 

  16. Brenton, J. D., Aparicio, S. A. & Caldas, C. Molecular profiling of breast cancer: portraits but not physiognomy.Breast Cancer Res.3, 77–80 (2001).

    Article CAS  Google Scholar 

  17. Khan, J. et al. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks.Naure Med.7, 673–679 (2001).

    CAS  Google Scholar 

  18. He, Y. D. & Friend, S. H. Microarrays—the 21st century divining rod?Nature Med.7, 658–659 (2001).

    Article CAS  Google Scholar 

  19. Bieche, I. et al. Genetic alterations in breast cancer.Genes Chromosomes Cancer14, 227–251 (1995).

    Article CAS  Google Scholar 

  20. Steeg, P. S. & Zhou, Q. Cyclins and breast cancer.Breast Cancer Res. Treat.52, 17–28 (1998).

    Article CAS  Google Scholar 

  21. Janicke, F. et al. Randomized adjuvant chemotherapy trial in high-risk, lymph node-negative breast cancer patients identified by urokinase-type plasminogen activator and plasminogen activator inhibitor type 1.J. Natl Cancer Inst.93, 913–920 (2001).

    Article CAS  Google Scholar 

  22. van Diest, P. J. et al. Cyclin D1 expression in invasive breast cancer. Correlations and prognostic value.Am. J. Pathol.150, 705–711 (1997).

    CAS PubMed PubMed Central  Google Scholar 

  23. Zheng, L., Annab, L. A., Afshari, C. A., Lee, W. H. & Boyer, T. G. BRCA1 mediates ligand-independent transcriptional repression of the estrogen receptor.Proc. Natl Acad. Sci. USA98, 9587–9592 (2001).

    Article ADS CAS  Google Scholar 

  24. Esteller, M. et al. Promoter hypermethylation and BRCA1 inactivation in sporadic breast and ovarian tumors.J. Natl Cancer Inst.92, 564–569 (2000).

    Article CAS  Google Scholar 

  25. Chapman, M. S. & Verma, I. M. Transcriptional activation by BRCA1.Nature382, 678–679 (1996).

    Article ADS CAS  Google Scholar 

  26. Hedenfalk, I. et al. Gene-expression profiles in hereditary breast cancer.N. Engl. J. Med.344, 539–548 (2001).

    Article CAS  Google Scholar 

Download references

Acknowledgements

We thank D. Atsma and D. Majoor for assistance with the histological analyses and the preparation of tumour RNA; T. van der Velde, W. van Waardenburg and O. Dalesio for medical record data extraction; D. Slade, J. McDonald, J. Koch, T. Erkkila, M. Parrish and others at Rosetta's High Throughput Gene Expression Profiling Facility for microarray experiments; R. Stoughton, F. van Leeuwen, M. Rookus, P. Nederlof, F. Hogervorst and D. Voskuil for suggestions; and A. Berns, L. Hartwell, J. Radich and S. Rodenhuis for support and reading of the manuscript. This work was supported by a grant from the Center for Biomedical Genetics.

Author information

Author notes

  1. Laura J. van 't Veer, Hongyue Dai, Marc J. van de Vijver, Yudong D. He, Mao Mao, Matthew J. Marton, George J. Schreiber, Chris Roberts, Peter S. Linsley and Stephen H. Friend: These authors contributed equally to this work

Authors and Affiliations

  1. Divisions of Diagnostic Oncology, Radiotherapy and Molecular Carcinogenesis and Center for Biomedical Genetics, The Netherlands Cancer Institute, 121 Plesmanlaan, Amsterdam, 1066 CX, The Netherlands

    Laura J. van 't Veer, Marc J. van de Vijver, Augustinus A. M. Hart, Hans L. Peterse, Karin van der Kooy, Anke T. Witteveen, Ron M. Kerkhoven & René Bernards

  2. Rosetta Inpharmatics, 12040 115th Avenue NE, Kirkland, 98034, Washington, USA

    Hongyue Dai, Yudong D. He, Mao Mao, Matthew J. Marton, George J. Schreiber, Chris Roberts, Peter S. Linsley & Stephen H. Friend

Authors
  1. Laura J. van 't Veer
  2. Hongyue Dai
  3. Marc J. van de Vijver
  4. Yudong D. He
  5. Augustinus A. M. Hart
  6. Mao Mao
  7. Hans L. Peterse
  8. Karin van der Kooy
  9. Matthew J. Marton
  10. Anke T. Witteveen
  11. George J. Schreiber
  12. Ron M. Kerkhoven
  13. Chris Roberts
  14. Peter S. Linsley
  15. René Bernards
  16. Stephen H. Friend

Corresponding author

Correspondence toStephen H. Friend.

Ethics declarations

Competing interests

S.H.F. is the Vice President of the MRC Merck Research Laboratories.

Rights and permissions

About this article

Cite this article

van 't Veer, L., Dai, H., van de Vijver, M.et al. Gene expression profiling predicts clinical outcome of breast cancer.Nature415, 530–536 (2002). https://doi.org/10.1038/415530a

Download citation

This article is cited by

Access through your institution
Buy or subscribe

Associated content

The molecular outlook

  • Carlos Caldas
  • Samuel A. J. Aparicio
NatureNews & Views

Advertisement

Search

Advanced search

Quick links

Nature Briefing

Sign up for theNature 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
[8]ページ先頭
©2009-2026 Movatter.jp