Breast Cancer Research and Treatment

, Volume 116, Issue 2, pp 303–309 | Cite as

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

  • Yi Zhang
  • Anieta M. Sieuwerts
  • Michelle McGreevy
  • Graham Casey
  • Tanja Cufer
  • Angelo Paradiso
  • Nadia Harbeck
  • Paul N. Span
  • David G. Hicks
  • Joseph Crowe
  • Raymond R. Tubbs
  • G. Thomas Budd
  • Joanne Lyons
  • Fred C. G. J. Sweep
  • Manfred Schmitt
  • Francesco Schittulli
  • Rastko Golouh
  • Dmitri Talantov
  • Yixin Wang
  • John A. Foekens
Clinical Trial

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.

Keywords

Breast cancer Gene signature Prognosis Tamoxifen benefit 

Notes

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).

References

  1. 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-UPubMedCrossRefGoogle Scholar
  2. 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 PubMedCrossRefGoogle Scholar
  3. 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 PubMedCrossRefGoogle Scholar
  4. 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 PubMedCrossRefGoogle Scholar
  5. 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 PubMedCrossRefGoogle Scholar
  6. 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 61:5979–5984PubMedGoogle Scholar
  7. 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 PubMedCrossRefGoogle Scholar
  8. 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 PubMedCrossRefGoogle Scholar
  9. 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 365:671–679PubMedGoogle Scholar
  10. 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 PubMedCrossRefGoogle Scholar
  11. 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 98:262–272PubMedCrossRefGoogle Scholar
  12. 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 PubMedCrossRefGoogle Scholar
  13. 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 PubMedCrossRefGoogle Scholar
  14. 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 PubMedCrossRefGoogle Scholar
  15. 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 PubMedCrossRefGoogle Scholar
  16. 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 PubMedCrossRefGoogle Scholar
  17. 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 PubMedCrossRefGoogle Scholar
  18. 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 PubMedCrossRefGoogle Scholar
  19. 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 PubMedCrossRefGoogle Scholar
  20. 20.
    Lipshutz RJ, Fodor SP, Gingeras TR, Lockhart DJ (1999) High density synthetic oligonucleotide arrays. Nat Genet 21:20–24. doi: 10.1038/4447 PubMedCrossRefGoogle Scholar
  21. 21.
    Kaplan EL, Meier P (1958) Non-parametric estimation from incomplete observations. J Am Stat Assoc 53:457–481. doi: 10.2307/2281868 CrossRefGoogle Scholar
  22. 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. 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 9:239PubMedCrossRefGoogle Scholar
  24. 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 PubMedCrossRefGoogle Scholar
  25. 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 62:4617–4622PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2008

Authors and Affiliations

  • Yi Zhang
    • 1
  • Anieta M. Sieuwerts
    • 2
  • Michelle McGreevy
    • 3
  • Graham Casey
    • 4
  • Tanja Cufer
    • 5
  • Angelo Paradiso
    • 6
  • Nadia Harbeck
    • 7
  • Paul N. Span
    • 8
  • David G. Hicks
    • 9
  • Joseph Crowe
    • 10
  • Raymond R. Tubbs
    • 11
  • G. Thomas Budd
    • 12
  • Joanne Lyons
    • 10
  • Fred C. G. J. Sweep
    • 8
  • Manfred Schmitt
    • 7
  • Francesco Schittulli
    • 6
  • Rastko Golouh
    • 5
  • Dmitri Talantov
    • 1
  • Yixin Wang
    • 1
  • John A. Foekens
    • 2
  1. 1.Veridex LLCJohnson & Johnson CompanySan DiegoUSA
  2. 2.Department of Medical OncologyErasmus Medical Center—Josephine Nefkens Institute and Cancer Genomics CentreRotterdamThe Netherlands
  3. 3.Department of Cancer BiologyCancer Clinic FoundationClevelandUSA
  4. 4.Department of Preventive MedicineUniversity of Southern CaliforniaLos AngelesUSA
  5. 5.Institute of OncologyLjubljanaSlovenia
  6. 6.National Cancer InstituteBariItaly
  7. 7.Department of Obstetrics and Gynecology, Klinikum rechts der IsarTechnische Universitaet MuenchenMunichGermany
  8. 8.Department of Chemical EndocrinologyRadboud University Nijmegen Medical CentreNijmegenThe Netherlands
  9. 9.Department of PathologyUniversity of Rochester Medical CenterRochesterUSA
  10. 10.Department of Breast ServicesCleveland Clinic FoundationClevelandUSA
  11. 11.Department of Molecular PathologyCleveland Clinic FoundationClevelandUSA
  12. 12.Department of Solid Tumor OncologyCleveland Clinic FoundationClevelandUSA

Personalised recommendations