Skip to main content

Advertisement

SpringerLink
Log in

Immunohistochemical versus molecular (BluePrint and MammaPrint) subtyping of breast carcinoma. Outcome results from the EORTC 10041/BIG 3-04 MINDACT trial

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

Abstract

Purpose

This study compares immunohistochemical (IHC) versus molecular subtyping (BluePrint and MammaPrint) in the population of patients enrolled in MINDACT and outcome based on molecular subtyping (MS) versus surrogate pathological subtyping (PS) as defined by the 2013 St. Gallen guidelines.

Methods

MS classified patients in the following subtypes: Luminal A, Luminal B, HER-2-, and Basal-type. IHC/FISH for pathological subtyping (ER, PgR, HER-2, and Ki67) was centrally assessed in the European Institute of Oncology (n = 5806). Hazard ratios for distant-metastasis-free survival (DMFS) by subtype were adjusted for chemotherapy and endocrine therapy administration and thus independent of adjuvant treatment allocation.

Results

PS Luminal cancers classified as HER-2+ or Basal-type by MS did not have a significantly lower DMFS than the Luminal-type cancers by MS (95.9%): HR = 1.40, 95% CI 0.75–2.60 (p = 0.294). More patients were identified with Luminal A disease by MS (63%) as compared with PS (47%) with comparable 5-year DMFS (≥96.0%). Among the 500 patients with PS TN cancers, MS identified 24 (5%) patients as Luminal-type with 5-year DMFS estimated at 100% versus 71.4% for MS HER-2+ or 90.1% for MS Basal-type.

Conclusions

MS was able to re-stratify 54% of patients with a Luminal-B PS subtype to a low-risk Luminal A-type group with comparable outcome. Among TN EBC, 5% were classified as Luminal by MS with Luminal-like outcome. Molecular classification can help to identify a larger group of patients with low risk of recurrence compared with the more contemporarily used classification methodology including high-quality assessed Ki67.

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

Similar content being viewed by others

References

  1. Perou CM, Sørlie T, Eisen MB et al (2000) Molecular portraits of human breast tumours. Nature 406(6797):747–752

    Article  CAS  PubMed  Google Scholar 

  2. Sørlie T, Tibshirani R, Parker J et al (2003) Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 100(14):8418–8423

    Article  PubMed  PubMed Central  Google Scholar 

  3. The Cancer Genome Atlas Network (2012) Comprehensive molecular portraits of human breast tumors. Nature 490(7418):61–70

    Article  PubMed Central  Google Scholar 

  4. Goldhirsch A, Winer EP, Coates AS et al (2013) Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol 24(9):2206–2223

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Krijgsman O, Roepman P, Zwart W et al (2012) A diagnostic gene profile for molecular subtyping of breast cancer associated with treatment response. Breast Cancer Res Treat 133(1):37–47

    Article  CAS  PubMed  Google Scholar 

  6. Groenendijk FH, Zwart W, Floore A et al (2013) Estrogen receptor splice variants as a potential source of false-positive estrogen receptor status in breast cancer diagnostics. Breast Cancer Res Treat 140(3):475–484

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Cardoso F, van ‘t Veer LJ, Bogaerts J et al (2016) 70-gene signature as an aid to treatment decisions in early-stage breast cancer. N Engl J Med 375(8):717–729

    Article  CAS  PubMed  Google Scholar 

  8. Viale G, Slaets L, de Snoo FA et al (2016) Discordant assessment of tumor biomarkers by histopathological and molecular assays in the EORTC randomized controlled 10041/BIG 03-04 MINDACT trial breast cancer: intratumoral heterogeneity and DCIS or normal tissue components are unlikely to be the cause of discordance. Breast Cancer Res Treat 155(3):463–469

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Rutgers E, Piccart-Gebhart MJ, Bogaerts J et al (2011) The EORTC 10041/BIG 03-04 MINDACT trial is feasible: results of the pilot phase. Eur J Cancer 00:2742–2749

    Article  Google Scholar 

  10. Rutgers E, Piccart-Gebhart MJ, Bogaerts J et al (2013) Baseline results of the EORTC 10041/MINDACT TRIAL (microarray in node 0-3 positive disease may avoid chemotherapy). ECCO

  11. Glas AM, Floore A, Delahaye LJ et al (2006) Converting a breast cancer microarray signature into a high-throughput diagnostic test. BMC Genom 7:278

    Article  Google Scholar 

  12. Hammond ME, Hayes DF, Dowsett M et al (2010) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J Clin Oncol 28:2784–2795

    Article  PubMed  PubMed Central  Google Scholar 

  13. Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20:37–46

    Article  Google Scholar 

  14. Maisonneuve P, Disalvatore D, Rotmensz N et al (2014) Proposed new clinicopathological surrogate definitions of luminal A and luminal B (HER2-negative) intrinsic breast cancer subtypes. Breast Cancer Res 16(3):R65

    Article  PubMed  PubMed Central  Google Scholar 

  15. Polley MY, Leung SC, McShane LM et al (2013) An international Ki67 reproducibility study. J Natl Cancer Inst 105(24):1897–1906

    Article  PubMed  PubMed Central  Google Scholar 

  16. Dowsett M, Nielsen TO, A’Hern R et al (2011) Assessment of Ki67 in breast cancer: recommendations from the International Ki67 in Breast Cancer Working Group. J Natl Cancer Inst 103:1656–1664

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Shui R, Yu B, Bi R et al (2015) An interobserver reproducibility analysis of Ki67 visual assessment in breast cancer. PLoS ONE 10(5):e0125131

    Article  PubMed  PubMed Central  Google Scholar 

  18. Coates AS, Winer EP, Goldhirsch A et al (2015) Tailoring therapies-improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015. Ann Oncol 26(8):1533–1546

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Cheang MC, Chia SK, Voduc D et al (2009) Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst 101(10):736–750

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Cheang MC, Martin M, Nielsen TO et al (2015) Defining breast cancer intrinsic subtypes by quantitative receptor expression. Oncologist 20:474–482

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Whitworth P, Stork-Sloots L, de Snoo FA et al (2014) Chemosensitivity predicted by BluePrint 80-gene functional subtype and MammaPrint in the Prospective Neoadjuvant Breast Registry Symphony Trial (NBRST). Ann Surg Oncol 21(10):3261–3267

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are grateful to all women participating in this study, all the investigators, surgeons, pathologists, and research nurses, EORTC, BIG, the National Coordinating Centers/BIG Groups (BOOG, CaCTUS, CEEOG, Unicancer, GOIRC, IBCSG, SAKK, SOLTI, WSG), and World Courier.

Funding

The MINDACT trial has funding Grants from the European Commission Framework Programme VI (FP6-LSHC-CT-2004-503426), the Breast Cancer Research Foundation, Novartis, F. Hoffman La Roche, Sanofi-Aventis, the National Cancer Institute (NCI), the EBCC-Breast Cancer Working Group (BCWG Grant for the MINDACT biobank), the Jacqueline Seroussi Memorial Foundation (2006 JSMF award), Prix Mois du Cancer du Sein (2004 award), Susan G. Komen for the Cure (SG05-0922-02), Fondation Belge Contre le Cancer (SCIE 2005-27), Dutch Cancer Society (KWF), Association Le Cancer du Sein, Parlons-en!, Deutsche Krebshilfe, and the Grant Simpson Trust and Cancer Research UK. This publication was supported by the EORTC Cancer Research Fund. Whole genome analysis was provided in kind by Agendia.

Author information

Authors and Affiliations

  1. Department of Pathology, European Institute of Oncology and University of Milan, Via Ripamonti 435, 20141, Milan, Italy

    G. Viale, L. Russo & P. Dell’Orto

  2. Medical Affairs, Agendia, Amsterdam, The Netherlands

    F. A. de Snoo, L. Stork-Sloots & A. Glas

  3. European Organization for Research and Treatment of Cancer Headquarters, Brussels, Belgium

    L. Slaets, J. Bogaerts, K. Tryfonidis & S. Litière

  4. Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA

    L. van ’t Veer

  5. Department of Surgery, Netherlands Cancer Institute, Amsterdam, The Netherlands

    E. J. Rutgers

  6. Department of Medical Oncology, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium

    M. J. Piccart-Gebhart

  7. Breast Unit, Champalimaud Clinical Center/Champalimaud Foundation, Lisbon, Portugal

    F. Cardoso

Authors
  1. G. Viale
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. F. A. de Snoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. L. Slaets
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. J. Bogaerts
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. L. van ’t Veer
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. E. J. Rutgers
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. M. J. Piccart-Gebhart
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. L. Stork-Sloots
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. A. Glas
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. L. Russo
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. P. Dell’Orto
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. K. Tryfonidis
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. S. Litière
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. F. Cardoso
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

for the MINDACT investigators

Corresponding author

Correspondence to G. Viale.

Ethics declarations

Conflict of interest

FdS and LS-S were employees of Agendia at the time of analysis and are consultants to Agendia for this work. LV reports being shareholder in and part-time employed by Agendia Inc. All other authors declare no competing interests.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 1674 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Viale, G., de Snoo, F.A., Slaets, L. et al. Immunohistochemical versus molecular (BluePrint and MammaPrint) subtyping of breast carcinoma. Outcome results from the EORTC 10041/BIG 3-04 MINDACT trial. Breast Cancer Res Treat 167, 123–131 (2018). https://doi.org/10.1007/s10549-017-4509-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-017-4509-9

Keywords

Search

Navigation