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High-Risk Estrogen-Receptor-Positive Breast Cancer

Identification and Implications for Therapy

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Abstract

The estrogen receptor (ER) has long been recognized as a key discriminative feature of breast cancer, which carries profound implications for management. However, recent advances in the understanding of breast cancer heterogeneity have demonstrated the importance of biologic context to the interpretation of ER as a prognostic and predictive factor. The use of tumor subtyping methods and prognostic indicators based on molecular profiling of tumor tissue is now helping to delineate high-risk ER-positive cancer types that have distinct risk and treatment response profiles. These new approaches to breast cancer classification will have a major impact on the conduct of clinical trials and individual patient assessment in the future.

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References

  1. Althuis MD, Fergenbaum JH, Garcia-Closas M, et al. Etiology of hormone receptor-defined breast cancer: a systematic review of the literature. Cancer Epidemiol Biomarkers Prev 2004; 13 (10): 1558–68.

    PubMed  CAS  Google Scholar 

  2. Colditz GA, Rosner BA, Chen WY, et al. Risk factors for breast cancer according to estrogen and progesterone receptor status. J Natl Cancer Inst 2004; 96 (3): 218–28.

    Article  PubMed  CAS  Google Scholar 

  3. Chen WY, Hankinson SE, Schnitt SJ, et al. Association of hormone replacement therapy to estrogen and progesterone receptor status in invasive breast carcinoma. Cancer 2004; 101 (7): 1490–500.

    Article  PubMed  CAS  Google Scholar 

  4. Anderson WF, Chatterjee N, Ershler WB, et al. Estrogen receptor breast cancer phenotypes in the Surveillance, Epidemiology, and End Results database. Breast Cancer Res Treat 2002; 76 (1): 27–36.

    Article  PubMed  CAS  Google Scholar 

  5. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 2005; 365 (9472): 1687–717.

    Article  Google Scholar 

  6. Regan MM, Neven P, Giobbie-Hurder A, et al. Assessment of letrozole and tamoxifen alone and in sequence for postmenopausal women with steroid hormone receptor-positive breast cancer: the BIG 1–98 randomised clinical trial at 8.1 years median follow-up. Lancet Oncol 2011; 12 (12): 1101–8.

    Article  PubMed  CAS  Google Scholar 

  7. Goldhirsch A, Ingle JN, Gelber RD, et al. Thresholds for therapies: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2009. Ann Oncol 2009; 20 (8): 1319–29.

    Article  PubMed  CAS  Google Scholar 

  8. Goldhirsch A, Wood WC, Gelber RD, et al. Progress and promise: highlights of the International Expert Consensus on the Primary Therapy of Early Breast Cancer 2007. Ann Oncol 2007; 18 (7): 1133–44.

    Article  PubMed  CAS  Google Scholar 

  9. Goldhirsch A, Wood WC, Coates AS, et al. Strategies for subtypes — dealing with the diversity of breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol 2011; 22 (8): 1736–47.

    Article  PubMed  CAS  Google Scholar 

  10. Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001; 98 (19): 10869–74.

    Article  PubMed  CAS  Google Scholar 

  11. Sorlie T, Tibshirani R, Parker J, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A 2003; 100 (14): 8418–23.

    Article  PubMed  CAS  Google Scholar 

  12. Golub TR, Slonim DK, Tamayo P, et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 1999; 286 (5439): 531–7.

    Article  PubMed  CAS  Google Scholar 

  13. Vogt W, Nagel D. Cluster analysis in diagnosis. Clin Chem 1992; 38 (2): 182–98.

    PubMed  CAS  Google Scholar 

  14. Prat A, Perou CM. Deconstructing the molecular portraits of breast cancer. Mol Oncol 2011; 5 (1): 5–23.

    Article  PubMed  CAS  Google Scholar 

  15. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000; 406 (6797): 747–52.

    Article  PubMed  CAS  Google Scholar 

  16. Nielsen TO, Parker JS, Leung S, et al. A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer. Clin Cancer Res 2010; 16 (21): 5222–32.

    Article  PubMed  CAS  Google Scholar 

  17. Parker JS, Mullins M, Cheang MCU, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009; 27 (8): 1160–7.

    Article  PubMed  Google Scholar 

  18. Cheang MCU, Chia SK, Voduc D, et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst 2009; 101 (10): 736–50.

    Article  PubMed  CAS  Google Scholar 

  19. Haibe-Kains B, Desmedt C, Loi S, et al. A three-gene model to robustly identify breast cancer molecular subtypes. J Natl Cancer Inst 2012; 104 (4): 311–25.

    Article  PubMed  CAS  Google Scholar 

  20. Weigelt B, Mackay A, A’Hern R, et al. Breast cancer molecular profiling with single sample predictors: a retrospective analysis. Lancet Oncol 2010; 11 (4): 339–49.

    Article  PubMed  CAS  Google Scholar 

  21. Slamon D, Eiermann W, Robert N, et al. Adjuvant trastuzumab in HER2-positive breast cancer. N Engl J Med 2011; 365 (14): 1273–83.

    Article  PubMed  CAS  Google Scholar 

  22. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004; 351 (27): 2817–26.

    Article  PubMed  CAS  Google Scholar 

  23. Kelly CM, Bernard PS, Krishnamurthy S, et al. Agreement in risk prediction between the 21-gene recurrence score assay (Oncotype DX®) and the PAM50 Breast Cancer Intrinsic Classifier™ in early-stage estrogen receptor-positive breast cancer. Oncologist 2012; 17 (4): 492–8.

    Article  PubMed  Google Scholar 

  24. Loi S, Haibe-Kains B, Desmedt C, et al. Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade. J Clin Oncol 2007; 25 (10): 1239–46.

    Article  PubMed  CAS  Google Scholar 

  25. Cuzick J, Dowsett M, Pineda S, et al. Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and comparison with the Genomic Health recurrence score in early breast cancer. J Clin Oncol 2011; 29 (32): 4273–8.

    Article  PubMed  Google Scholar 

  26. Dowsett M, Cuzick J, Wale C, et al. Prediction of risk of distant recurrence using the 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study. J Clin Oncol 2010; 28 (11): 1829–34.

    Article  PubMed  Google Scholar 

  27. Tang G, Cuzick J, Costantino JP, et al. Risk of recurrence and chemotherapy benefit for patients with node-negative, estrogen receptor-positive breast cancer: recurrence score alone and integrated with pathologic and clinical factors. J Clin Oncol 2011; 29 (33): 4365–72.

    Article  PubMed  CAS  Google Scholar 

  28. Paik S, Tang G, Shak S, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol 2006; 24 (23): 3726–34.

    Article  PubMed  CAS  Google Scholar 

  29. Colleoni M, Viale G, Goldhirsch A. Lessons on responsiveness to adjuvant systemic therapies learned from the neoadjuvant setting. Breast 2009; 18 Suppl. 3: S137–40.

    Article  PubMed  Google Scholar 

  30. Hugh J, Hanson J, Cheang MCU, et al. Breast cancer subtypes and response to docetaxel in node-positive breast cancer: use of an immunohistochemical definition in the BCIRG 001 trial. J Clin Oncol 2009; 27 (8): 1168–76.

    Article  PubMed  CAS  Google Scholar 

  31. Penault-Llorca F, Andre F, Sagan C, et al. Ki67 expression and docetaxel efficacy in patients with estrogen receptor-positive breast cancer. J Clin Oncol 2009; 27 (17): 2809–15.

    Article  PubMed  CAS  Google Scholar 

  32. Dunbier AK, Anderson H, Ghazoui Z, et al. Association between breast cancer subtypes and response to neoadjuvant anastrozole. Steroids 2011; 76 (8): 736–40.

    Article  PubMed  CAS  Google Scholar 

  33. Viale G, Regan MM, Dell’Orto P, et al. Which patients benefit most from adjuvant aromatase inhibitors? Results using a composite measure of prognostic risk in the BIG 1–98 randomized trial. Ann Oncol 2011; 22 (10): 2201–7.

    Article  PubMed  CAS  Google Scholar 

  34. Coates AS, Colleoni M, Goldhirsch A. Is adjuvant chemotherapy useful for women with luminal A breast cancer? J Clin Oncol 2012; 30 (12): 1260–3.

    Article  PubMed  CAS  Google Scholar 

  35. Loi S, Sotiriou C, Haibe-Kains B, et al. Gene expression profiling identifies activated growth factor signaling in poor prognosis (Luminal-B) estrogen receptor positive breast cancer. BMC Med Genomics 2009; 2: 37.

    Article  PubMed  Google Scholar 

  36. Jonsson G, Staaf J, Vallon-Christersson J, et al. Genomic subtypes of breast cancer identified by array-comparative genomic hybridization display distinct molecular and clinical characteristics. Breast Cancer Res 2010; 12 (3): R42.

    Article  PubMed  Google Scholar 

  37. Ross-Innes CS, Stark R, Teschendorff AE, et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature 2011; 481 (7381): 389–93.

    Google Scholar 

  38. Curtis C, Shah SP, Chin SF, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 2012; 486 (7403): 346–52.

    PubMed  CAS  Google Scholar 

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Acknowledgments

Rosemary Balleine was a Cancer Institute New South Wales (CINSW) Fellow. The authors have no conflicts of interest that are directly relevant to the content of this review.

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Authors and Affiliations

  1. Translational Oncology, Sydney West Cancer Network, Western Sydney and Nepean Blue Mountains Local Health Districts, Sydney, New South Wales, Australia

    Rosemary L. Balleine

  2. Sydney Medical School — Westmead, University of Sydney, Sydney, New South Wales, Australia

    Rosemary L. Balleine & Nicholas R. Wilcken

  3. Westmead Institute for Cancer Research, Westmead Millennium Institute, Westmead, Sydney, New South Wales, Australia

    Rosemary L. Balleine

  4. Medical Oncology, Sydney West Cancer Network, Western Sydney and Nepean Blue Mountains Local Health Districts, Sydney, New South Wales, Australia

    Nicholas R. Wilcken

  5. Crown Princess Mary Cancer Centre Westmead, Westmead Hospital, PO Box 533, Wentworthville, New South Wales, 2145, Australia

    Rosemary L. Balleine

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  1. Rosemary L. Balleine
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  2. Nicholas R. Wilcken
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Correspondence to Rosemary L. Balleine.

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Balleine, R.L., Wilcken, N.R. High-Risk Estrogen-Receptor-Positive Breast Cancer. Mol Diagn Ther 16, 235–240 (2012). https://doi.org/10.1007/BF03262212

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