Skip to main content

Advertisement

Log in

The 76-gene signature defines high-risk patients that benefit from adjuvant tamoxifen therapy

  • Clinical Trial
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

Purpose To assess the benefit from adjuvant systemic tamoxifen therapy in breast cancer risk groups identified by the previously established prognostic 76-gene signature. Methods In 300 lymph node-negative (LNN), estrogen receptor-positive (ER+) breast cancer patients (136 treated with adjuvant tamoxifen, 164 having received no systemic adjuvant therapy), distant metastasis-free survival (DMFS) as a function of the 76-gene signature was determined in a multicenter fashion. Results In 136 tamoxifen-treated patients, the 76-gene signature identified a group of patients with a poor prognosis [hazard ratio (HR), 4.62; P = 0.0248]. These patients showed a 12.3% absolute benefit of tamoxifen in 10-year DMFS (HR, 0.52; P = 0.0318) compared with untreated high-risk patients. This represented a 71% increase in relative benefit compared with the 7.2% absolute benefit observed for all 300 patients without using the gene signature. In the low-risk group there was no significant 10-year DMFS benefit of tamoxifen. Conclusions The 76-gene signature defines high-risk patients who benefit from adjuvant tamoxifen therapy. Although we did not study the value of chemotherapy in this study, low-risk patients identified by the 76-gene signature have a prognosis good enough that chemotherapy would be difficult to justify. The prognosis of these patients is sufficiently good, in fact, that a disease-free benefit for tamoxifen therapy is difficult to prove, though benefits in terms of loco-regional relapse and a reduction in risk for contralateral breast cancer might justify hormonal therapy in these patients.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Osborne CK, Yochmowitz MG, Knight WAIII, McGuire WL (1980) The value of estrogen and progesterone receptors in the treatment of breast cancer. Cancer 46:2884–2888. doi:10.1002/1097-0142(19801215)46:12+<2884::AID-CNCR2820461429>3.0.CO;2-U

    Article  PubMed  CAS  Google Scholar 

  2. Fisher B, Dignam J, Bryant J, DeCillis A, Wickerham DL, Wolmark N et al (1996) Five versus more than five years of tamoxifen therapy for breast cancer patients with negative lymph nodes and estrogen receptor-positive tumors. J Natl Cancer Inst 88:1529–1542. doi:10.1093/jnci/88.21.1529

    Article  PubMed  CAS  Google Scholar 

  3. Fisher B, Jeong JH, Bryant J, Anderson S, Dignam J, Fisher ER et al (2004) Treatment of lymph-node-negative, oestrogen-receptor-positive breast cancer: long-term findings from National Surgical Adjuvant Breast and Bowel Project randomised clinical trials. Lancet 364:858–868. doi:10.1016/S0140-6736(04)16981-X

    Article  PubMed  CAS  Google Scholar 

  4. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA et al (2000) Molecular portraits of human breast tumours. Nature 406:747–752. doi:10.1038/35021093

    Article  PubMed  CAS  Google Scholar 

  5. Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98:10869–10874. doi:10.1073/pnas.191367098

    Article  PubMed  CAS  Google Scholar 

  6. Gruvberger S, Ringner M, Chen Y, Panavally S, Saal LH, Borg A et al (2001) Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns. Cancer Res 61:5979–5984

    PubMed  CAS  Google Scholar 

  7. Hedenfalk I, Duggan D, Chen Y, Radmacher M, Bittner M, Simon R et al (2001) Gene-expression profiles in hereditary breast cancer. N Engl J Med 344:539–548. doi:10.1056/NEJM200102223440801

    Article  PubMed  CAS  Google Scholar 

  8. Van ‘t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M et al (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415:530–536. doi:10.1038/415530a

    Article  PubMed  Google Scholar 

  9. Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F et al (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365:671–679

    PubMed  CAS  Google Scholar 

  10. Ma XJ, Wang Z, Ryan PD, Isakoff SJ, Barmettler A, Fuller A et al (2004) A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell 5:607–616. doi:10.1016/j.ccr.2004.05.015

    Article  PubMed  CAS  Google Scholar 

  11. Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J et al (2006) Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98:262–272

    Article  PubMed  CAS  Google Scholar 

  12. Jansen MP, Foekens JA, van Staveren IL, Dirkzwager-Kiel MM, Ritstier K, Look MP et al (2005) Molecular classification of tamoxifen-resistant breast carcinomas by gene expression profiling. J Clin Oncol 23:732–740. doi:10.1200/JCO.2005.05.145

    Article  PubMed  CAS  Google Scholar 

  13. Hess KR, Anderson K, Symmans WF, Valero V, Ibrahim N, Mejia JA et al (2006) Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer. J Clin Oncol 24:4236–4244. doi:10.1200/JCO.2006.05.6861

    Article  PubMed  CAS  Google Scholar 

  14. Potti A, Dressman HK, Bild A, Riedel RF, Chan G, Sayer R et al (2006) Genomic signatures to guide the use of chemotherapeutics. Nat Med 12:1294–1300. doi:10.1038/nm1491

    Article  PubMed  CAS  Google Scholar 

  15. Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M et al (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351:2817–2826. doi:10.1056/NEJMoa041588

    Article  PubMed  CAS  Google Scholar 

  16. Paik S, Tang G, Shak S, Kim C, Baker J, Kim W et al (2006) Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol 24:3726–3734. doi:10.1200/JCO.2005.04.7985

    Article  PubMed  CAS  Google Scholar 

  17. Foekens JA, Atkins D, Zhang Y, Sweep FC, Harbeck N, Paradiso A et al (2006) Multicenter validation of a gene expression-based prognostic signature in lymph node-negative primary breast cancer. J Clin Oncol 24:1665–1671. doi:10.1200/JCO.2005.03.9115

    Article  PubMed  CAS  Google Scholar 

  18. Desmedt C, Piette F, Loi S, Wang Y, Lallemand F, Haibe-Kains B et al (2007) 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. doi:10.1158/1078-0432.CCR-06-2765

    Article  PubMed  CAS  Google Scholar 

  19. McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM (2006) REporting recommendations for tumor MARKer prognostic studies (REMARK). Breast Cancer Res Treat 100:229–235. doi:10.1007/s10549-006-9242-8

    Article  PubMed  Google Scholar 

  20. Lipshutz RJ, Fodor SP, Gingeras TR, Lockhart DJ (1999) High density synthetic oligonucleotide arrays. Nat Genet 21:20–24. doi:10.1038/4447

    Article  PubMed  CAS  Google Scholar 

  21. Kaplan EL, Meier P (1958) Non-parametric estimation from incomplete observations. J Am Stat Assoc 53:457–481. doi:10.2307/2281868

    Article  Google Scholar 

  22. Harvell D, Spoelstra N, Singh M, McManaman J, Finlayson C, Phang T, et al (2008) Molecular signatures of neoadjuvant endocrine therapy for breast cancer: characteristics of response or intrinsic resistance. Breast Cancer Res Treat. doi: 10.1007/s10549-008-9897-4 press)

  23. Loi S, Haibe-Kains B, Desmedt C, Wirapati P, Lallemand F, Tutt AM et al (2008) Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen. BMC Genomics 9:239

    Article  PubMed  CAS  Google Scholar 

  24. Gasparini G, Pozza F, Harris AL (1993) Evaluating the potential usefulness of new prognostic and predictive indicators in node-negative breast cancer patients. J Natl Cancer Inst 85:1206–1219. doi:10.1093/jnci/85.15.1206

    Article  PubMed  CAS  Google Scholar 

  25. Harbeck N, Kates RE, Look MP, Meijer-Van Gelder ME, Klijn JG, Kruger A et al (2002) Enhanced benefit from adjuvant chemotherapy in breast cancer patients classified high-risk according to urokinase-type plasminogen activator (uPA) and plasminogen activator inhibitor type 1 (n = 3424). Cancer Res 62:4617–4622

    PubMed  CAS  Google Scholar 

Download references

Acknowledgments

We thank Mieke Timmermans, Anita Trapman-Jansen, Vanja de Weerd and Wendy van der Smissen for technical assistance, and Marion Meijer-van Gelder for handling of the clinical data. This study was supported in part by The Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to John A. Foekens.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhang, Y., Sieuwerts, A.M., McGreevy, M. et al. The 76-gene signature defines high-risk patients that benefit from adjuvant tamoxifen therapy. Breast Cancer Res Treat 116, 303–309 (2009). https://doi.org/10.1007/s10549-008-0183-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-008-0183-2

Keywords

Navigation