Skip to main content

Advertisement

SpringerLink
Log in

Validation of 70-gene prognosis signature in node-negative breast cancer

  • Preclinical Study
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

Purpose The 70-gene prognosis signature (van’t Veer et al., Nature 415(6871):530–536, 2002) may improve the selection of lymph node-negative breast cancer patients for adjuvant systemic therapy. Optimal validation of prognostic classifiers is of great importance and we therefore wished to evaluate the prognostic value of the 70-gene prognosis signature in a series of relatively recently diagnosed lymph node negative breast cancer patients. Methods We evaluated the 70-gene prognosis signature in an independent representative series of patients with invasive breast cancer (N = 123; <55 years; pT1-2N0; diagnosed between 1996 and 1999; median follow-up 5.8 years) by classifying these patients as having a good or poor prognosis signature. In addition, we updated the follow-up of the node-negative patients of the previously published validation-series (Van de Vijver et al., N Engl J Med 347(25):1999–2009, 2002; N = 151; median follow-up 10.2 years). The prognostic value of the 70-gene prognosis signature was compared with that of four commonly used clinicopathological risk indexes. The endpoints were distant metastasis (as first event) free percentage (DMFP) and overall survival (OS). Results The 5-year OS was 82 ± 5% in poor (48%) and 97 ± 2% in good prognosis signature (52%) patients (HR 3.4; 95% CI 1.2–9.6; P = 0.021). The 5-years DMFP was 78 ± 6% in poor and 98 ± 2% in good prognosis signature patients (HR 5.7; 95% CI 1.6–20; P = 0.007). In the updated series (N = 151; 60% poor vs. 40% good), the 10-year OS was 51 ± 5% and 94 ± 3% (HR 10.7; 95% CI 3.9–30; P < 0.01), respectively. The DMFP was 50 ± 6% in poor and 86 ± 5% in good prognosis signature patients (HR 5.5; 95% CI 2.5–12; P < 0.01). In multivariate analysis, the prognosis signature was a strong independent prognostic factor in both series, outperforming the clinicopathological risk indexes. Conclusion The 70-gene prognosis signature is also an independent prognostic factor in node-negative breast cancer patients for women diagnosed in recent years.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) (2005) Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 365:1687–1717. doi:10.1016/S0140-6736(05)66544-0

    Article  CAS  Google Scholar 

  2. Eifel P (2001) National Institutes of Health Consensus Development Conference Statement: adjuvant therapy for breast cancer, November 1–3, 2000. J Natl Cancer Inst 93(13):979–989. doi:10.1093/jnci/93.13.979

    Article  PubMed  CAS  Google Scholar 

  3. Cleator S, Ashworth A (2004) Molecular profiling of breast cancer: clinical implications. Br J Cancer 90(6):1120–1124. doi:10.1038/sj.bjc.6601667

    Article  PubMed  CAS  Google Scholar 

  4. Harris JR (2004) Staging of breast cancer. In: Harris JR, Lippman ME, Morrow M, Osborne CK (eds) Disease of the breast, 3rd edn. Lippincott Williams & Wlkins, Philadelphia, pp 653–667

    Google Scholar 

  5. Early Breast Cancer Trialists’ Collaborative Group (1998) Tamoxifen for early breast cancer: an overview of the randomised trials. Lancet 351(9114):1451–1467. doi:10.1016/S0140-6736(97)11423-4

    Article  Google Scholar 

  6. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) (1998) Polychemotherapy for early breast cancer: an overview of the randomised trials. Lancet 352(9132):930–942. doi:10.1016/S0140-6736(98)03301-7

    Article  Google Scholar 

  7. 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(6797):747–752. doi:10.1038/35021093

    Article  PubMed  CAS  Google Scholar 

  8. West M, Blanchette C, Dressman H, Huang E, Ishida S, Spang R et al (2001) Predicting the clinical status of human breast cancer by using gene expression profiles. Proc Natl Acad Sci USA 98(20):11462–11467. doi:10.1073/pnas.201162998

    Article  PubMed  CAS  Google Scholar 

  9. 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(19):10869–10874. doi:10.1073/p006Eas.191367098

    Article  PubMed  CAS  Google Scholar 

  10. van’t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AAM, Mao M et al (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415(6871):530–536. doi:10.1038/415530a

    Article  Google Scholar 

  11. van de Vijver MJ, He YD, Van’t Veer LJ, Dai H, Hart AAM, Voskuil DW et al (2002) A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347(25):1999–2009. doi:10.1056/NEJMoa021967

    Article  PubMed  Google Scholar 

  12. Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A et al (2003) Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA 100(18):10393–10398. doi:10.1073/pnas.1732912100

    Article  PubMed  CAS  Google Scholar 

  13. Huang E, Cheng SH, Dressman H, Pittman J, Tsou MH, Horng CF et al (2003) Gene expression predictors of breast cancer outcomes. Lancet 361(9369):1590–1596. doi:10.1016/S0140-6736(03)13308-9

    Article  PubMed  CAS  Google Scholar 

  14. 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(27):2817–2826. doi:10.1056/NEJMoa041588

    Article  PubMed  CAS  Google Scholar 

  15. Habel LA, Shak S, Jacobs MK, Capra A, Alexander C, Pho M (2006) A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res 8(3):R25. doi:10.1186/bcr1412

    Article  PubMed  CAS  Google Scholar 

  16. Pawitan Y, Bjohle J, Amler L, Borg AL, Egyhazi S, Hall P et al (2005) Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts. Breast Cancer Res 7(6):R953–R964. doi:10.1186/bcr1325

    Article  PubMed  CAS  Google Scholar 

  17. 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(9460):671–679

    PubMed  CAS  Google Scholar 

  18. Foekens JA, Atkins D, Zhang Y, Sweep FCGJ, 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(11):1665–1671. doi:10.1200/JCO.2005.03.9115

    Article  PubMed  CAS  Google Scholar 

  19. Buyse M, Loi S, van’t Veer L, Viale G, Delorenzi M, Glas AM et al (2006) Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J Natl Cancer Inst 98(17):1183–1192

    Article  PubMed  CAS  Google Scholar 

  20. Wang Y, Klijn JGM, Zhang Y, Atkins D, Foekens JA (2005) A 76-gene signature to predict distant metastasis in lymph-node negative breast cancer. Am J Oncol Rev 4:448–454

    Google Scholar 

  21. Esteva FJ, Sahin AA, Cristofanilli M, Coombes K, Lee SJ, Baker J et al (2005) Prognostic role of a multigene reverse transcriptase-PCR assay in patients with node-negative breast cancer not receiving adjuvant systemic therapy. Clin Cancer Res 11(9):3315–3319. doi:10.1158/1078-0432.CCR-04-1707

    Article  PubMed  CAS  Google Scholar 

  22. Elston CW, Ellis IO (1991) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 19(5):403–410. doi:10.1111/j.1365-2559.1991.tb00229.x

    Article  PubMed  CAS  Google Scholar 

  23. Glas AM, Floore A, Delahaye LJ, Witteveen AT, Pover RC, Bakx N et al (2006) Converting a breast cancer microarray signature into a high-throughput diagnostic test. BMC Genomics 7:278. doi:10.1186/1471-2164-7-278

    Article  PubMed  CAS  Google Scholar 

  24. Goldhirsch A, Glick JH, Gelber RD, Senn HJ (1998) International Consensus Panel on the treatment of primary breast cancer. V: Update 1998. Recent Results Cancer Res 152:481–497

    PubMed  CAS  Google Scholar 

  25. Goldhirsch A, Glick JH, Gelber RD, Senn HJ (1998) Meeting highlights: International Consensus Panel on the treatment of primary breast cancer. J Natl Cancer Inst 90(21):1601–1608. doi:10.1093/jnci/90.21.1601

    Article  PubMed  CAS  Google Scholar 

  26. Goldhirsch A, Glick JH, Gelber RD, Coates AS, Senn HJ (2001) Meeting highlights: International Consensus Panel on the treatment of primary breast cancer. Seventh International Conference on adjuvant therapy of primary breast cancer. J Clin Oncol 19(18):3817–3827

    PubMed  CAS  Google Scholar 

  27. Colomer R, Vinas G, Beltran M, Izquierdo A, Lluch A, Llombart-Cussac A et al (2004) Validation of the 2001 St Gallen risk categories for node-negative breast cancer using a database from the Spanish Breast Cancer Research Group (GEICAM). J Clin Oncol 22(5):961–962. doi:10.1200/JCO.2004.99.143

    Article  PubMed  CAS  Google Scholar 

  28. Senn HJ, Thurlimann B, Goldhirsch A, Wood WC, Gelber RD, Coates AS (2003) Comments on the St. Gallen Consensus 2003 on the primary therapy of early breast cancer. Breast 12(6):569–582. doi:10.1016/j.breast.2003.09.007

    Article  PubMed  Google Scholar 

  29. Todd JH, Dowle C, Williams MR, Elston CW, Ellis IO, Hinton CP et al (1987) Confirmation of a prognostic index in primary breast cancer. Br J Cancer 56(4):489–492

    PubMed  CAS  Google Scholar 

  30. D’Eredita’ G, Giardina C, Martellotta M, Natale T, Ferrarese F (2001) Prognostic factors in breast cancer: the predictive value of the Nottingham Prognostic Index in patients with a long-term follow-up that were treated in a single institution. Eur J Cancer 37(5):591–596. doi:10.1016/S0959-8049(00)00435-4

    Article  PubMed  Google Scholar 

  31. Kattan MW, Giri D, Panageas KS, Hummer A, Cranor M, Van Zee KJ et al (2004) A tool for predicting breast carcinoma mortality in women who do not receive adjuvant therapy. Cancer 101(11):2509–2515. doi:10.1002/cncr.20635

    Article  PubMed  Google Scholar 

  32. Nationaal Borstkanker Overleg Nederland (2005) Richtlijn Behandeling van het Mammacarcinoom 2005 doi:www.oncoline.nl

  33. Kwaliteitsinstituut voor de Gezondheidszorg CBO Vereniging voor Integrale Kankercentra. Adjuvante Systemische Therapie voor het Operabel Mammacarcinoom. Richtlijn Behandeling van het Mammacarcinoom 2005. 2005, pp 46–70

  34. (2008) Adjuvant! Online Software (version 8.0) doi:www.adjuvantonline.com

  35. Olivotto IA, Bajdik CD, Ravdin PM, Speers CH, Coldman AJ, Norris BD et al (2005) Population-based validation of the prognostic model ADJUVANT! for early breast cancer. J Clin Oncol 23(12):2716–2725. doi:10.1200/JCO.2005.06.178

    Article  PubMed  Google Scholar 

  36. Ravdin PM, Siminoff LA, Davis GJ, Mercer MB, Hewlett J, Gerson N et al (2001) Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 19(4):980–991

    PubMed  CAS  Google Scholar 

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

    Article  Google Scholar 

  38. Cox DR (1972) Regression models and lifetables. J R Stat Soc B 34:187–220

    Google Scholar 

  39. Klein JP (1991) Small sample moments of the estimators of the variance of the Kaplan–Meier and Nelson-Aalen estimators. Scand J Stat 18:333–340

    Google Scholar 

  40. Fan C, Oh DS, Wessels L, Weigelt B, Nuyten DS, Nobel AB et al (2006) Concordance among gene-expression-based predictors for breast cancer. N Engl J Med 355(6):560–569. doi:10.1056/NEJMoa052933

    Article  PubMed  CAS  Google Scholar 

  41. Bueno-de-Mesquita JM, van Harten W, Retel V, van’t Veer L, van Dam F, Karsenberg K et al (2007) Use of 70-gene signature to predict prognosis of patients with node-negative breast cancer: a prospective community-based feasibility study (RASTER). Lancet Oncol 8(12):1079–1087. doi:10.1016/S1470-2045(07)70346-7

    Article  PubMed  CAS  Google Scholar 

  42. Bogaerts J, Cardoso F, Buyse M, Braga S, Loi S, Harrison JA et al (2006) Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial. Nat Clin Pract Oncol 3(10):540–551. doi:10.1038/ncponc0591

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

We are grateful to P.M. Ravdin (University of Texas, Health Science Centre, San Antonio (Texas), USA) for helpful advice with the use of Adjuvant! Online. In addition, we would like to thank G. Sonke for his help in the statistical analyses.

Competing interest statement

Dr. L.J. Van ‘t Veer, Dr. M.J. Van de Vijver and A.A.M. Hart are named inventors on a patent application for the 70-gene signature used in this study. Dr. Van’t Veer report being shareholder in and (part time) employed by Agendia, the commercial company that markets the 70-gene signature as MammaPrint®. A.N. Floore and A.M. Glas report being employed by Agendia.

Author information

Authors and Affiliations

  1. Department of Pathology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands

    J. M. Bueno-de-Mesquita, J. Wesseling, R. de Groot, L. J. van’t Veer & M. J. van de Vijver

  2. Department of Medical Oncology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands

    S. C. Linn

  3. Department of Surgery, Reinier de Graaf Hospital, Reinier de Graafweg 3-11, 2625 AD, Delft, The Netherlands

    R. Keijzer & P. W. de Graaf

  4. Department of Radiotherapy, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands

    D. S. A. Nuyten & A. A. M. Hart

  5. Department of Pathology, Kennemer Gasthuis, PO Box 417, 2000 AK, Haarlem, The Netherlands

    C. van Krimpen

  6. Department of Pathology, VU Medical Center, PO Box 7057, 1007 MB, Amsterdam, The Netherlands

    C. Meijers

  7. Department of Internal Medicine, Reinier de Graaf Hospital, Reinier de Graafweg 3-11, 2625 AD, Delft, The Netherlands

    M. M. E. M. Bos

  8. Department of Surgical Oncology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands

    E. J. T. Rutgers

  9. Department of Experimental Therapy, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands

    H. Halfwerk

  10. Department of Pathology, Reinier de Graaf Hospital, Reinier de Graafweg 3-11, 2625 AD, Delft, The Netherlands

    A. Pronk

  11. Agendia BV, Kruislaan 406, 1098 SM, Amsterdam, The Netherlands

    A. N. Floore, A. M. Glas & L. J. van’t Veer

  12. Department of Pathology, Academic Medical Centre, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands

    M. J. van de Vijver

Authors
  1. J. M. Bueno-de-Mesquita
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. C. Linn
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R. Keijzer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. J. Wesseling
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. D. S. A. Nuyten
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. C. van Krimpen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. C. Meijers
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. P. W. de Graaf
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. M. M. E. M. Bos
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. A. A. M. Hart
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. E. J. T. Rutgers
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. J. L. Peterse
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. H. Halfwerk
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. R. de Groot
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. A. Pronk
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. A. N. Floore
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. A. M. Glas
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. L. J. van’t Veer
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. M. J. van de Vijver
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. J. van de Vijver.

Additional information

J. L. Peterse—deceased.

Electronic supplementary material

Below is the link to the electronic supplementary material.

(DOC 115 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bueno-de-Mesquita, J.M., Linn, S.C., Keijzer, R. et al. Validation of 70-gene prognosis signature in node-negative breast cancer. Breast Cancer Res Treat 117, 483–495 (2009). https://doi.org/10.1007/s10549-008-0191-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-008-0191-2

Keywords

Search

Navigation