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CC BY-NC-ND 4.0 · Senologie - Zeitschrift für Mammadiagnostik und -therapie 2017; 14(04): 209-213
DOI: 10.1055/s-0043-122833
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Eigentümer und Copyright ©Georg Thieme Verlag KG 2017

Gene Expression Analyses in Early Breast Carcinoma — Quo Vadis?

Article in several languages: English | deutsch
Katrin Almstedt
1   Section of Conservative and Molecular Gynecological Oncology, Department of Obstetrics and Gynecology, Mainz, University Medical Center, Mainz, Germany
,
Carsten Denkert
2   Institute of Pathology, Charité, Campus Charité Mitte, Charité – Universitätsmedizin Berlin, Berlin, Germany
,
Marcus Schmidt
1   Section of Conservative and Molecular Gynecological Oncology, Department of Obstetrics and Gynecology, Mainz, University Medical Center, Mainz, Germany
› Author Affiliations
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Publication History

Publication Date:
15 December 2017 (online)

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Abstract

In order to establish whether adjuvant therapy should be administered in patients with breast carcinoma, it is decisive to have as precise as possible an assessment of the risk of recurrence. In this context, gene expression — and thus gene expression signatures as well — have become a focus of attention as prognostic factors. For practical application, it is important to be able to analyze gene expression signatures in formalin-fixed, paraffin-embedded tumor tissue. Careful analytic and clinical validations and a high level of evidence (LoE) are required in order to avoid imprecise risk classification and thus potential overtreatment or undertreatment of the patients. Among the commercially available gene expression signatures, the Working Group on Gynecological Oncology (Arbeitsgemeinschaft Gynäkologische Onkologie, AGO) currently grades MammaPrint® and Oncotype DX® as having LoE IA, with prospective study results; and Endopredict® and Prosigna® as having LoE IB. The panel members at this year’s St. Gallen consensus conference also voted by a majority in favor of the possible usage of Oncotype DX®, MammaPrint®, Prosigna®, EndoPredict®, and Breast Cancer Index®. These multigene tests can be used in selected patients with hormone receptor–positive and HER2-negative findings if none of the other criteria allow a treatment decision to be made.

Key words

gene expression - breast carcinoma - intrinsic subtypes - prognosis - evidence

Schlüsselwörter

Genexpression - Mammakarzinom - intrinsische Subtypen - Prognose - Evidenz
 

  • References

  • 1 Peto R, Davies C. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). et al. Comparisons between different polychemotherapy regimens for early breast cancer: meta-analyses of long-term outcome among 100000 women in 123 randomised trials. Lancet 2012; 379: 432-444
    CrossrefPubMedGoogle Scholar
  • 2 Tao JJ, Visvanathan K, Wolff AC. Long term side effects of adjuvant chemotherapy in patients with early breast cancer. Breast 2015; 24 (Suppl. 02) S149-S153
    PubMedGoogle Scholar
  • 3 Simon RM, Paik S, Hayes DF. Use of archived specimens in evaluation of prognostic and predictive biomarkers. J Natl Cancer Inst 2009; 101: 1446-1452
    CrossrefPubMedGoogle Scholar
  • 4 Perou CM, Sørlie T, Eisen MB. et al. Molecular portraits of human breast tumours. Nature 2000; 406: 747-752
    CrossrefPubMedGoogle Scholar
  • 5 Parker JS, Mullins M, Cheang MCU. et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009; 27: 1160-1167
    CrossrefPubMedGoogle Scholar
  • 6 Martín M, Prat A, Rodríguez-Lescure A. et al. PAM50 proliferation score as a predictor of weekly paclitaxel benefit in breast cancer. Breast Cancer Res Treat 2013; 138: 457-466
    CrossrefPubMedGoogle Scholar
  • 7 Filipits M, Nielsen TO, Rudas M. et al. The PAM50 risk-of-recurrence score predicts risk for late distant recurrence after endocrine therapy in postmenopausal women with endocrine-responsive early breast cancer. Clin Cancer Res 2014; 20: 1298-1305
    CrossrefPubMedGoogle Scholar
  • 8 Buus R, Sestak I, Kronenwett R. et al. Comparison of EndoPredict and EPclin With Oncotype DX Recurrence Score for Prediction of Risk of Distant Recurrence After Endocrine Therapy. J Natl Cancer Inst 2016; 108: djw149
    CrossrefPubMedGoogle Scholar
  • 9 Varga Z, Lebeau A, Bu H. et al. An international reproducibility study validating quantitative determination of ERBB2, ESR1, PGR, and MKI67 mRNA in breast cancer using MammaTyper®. Breast Cancer Res 2017; 19: 55
    CrossrefPubMedGoogle Scholar
  • 10 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: 2817-2826
    CrossrefPubMedGoogle Scholar
  • 11 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: 3726-3734
    CrossrefPubMedGoogle Scholar
  • 12 Albain KS, Barlow WE, Shak S. et al. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial. Lancet Oncol 2010; 11: 55-65
    PubMedGoogle Scholar
  • 13 Sgroi DC, Sestak I, Cuzick J. et al. Prediction of late distant recurrence in patients with oestrogen-receptor-positive breast cancer: a prospective comparison of the breast-cancer index (BCI) assay, 21-gene recurrence score, and IHC4 in the TransATAC study population. Lancet Oncol 2013; 14: 1067-1076
    CrossrefPubMedGoogle Scholar
  • 14 Wolmark N, Mamounas EP, Baehner FL. et al. Prognostic Impact of the Combination of Recurrence Score and Quantitative Estrogen Receptor Expression (ESR1) on Predicting Late Distant Recurrence Risk in Estrogen Receptor-Positive Breast Cancer After 5 Years of Tamoxifen: Results From NRG Oncology/National Surgical Adjuvant Breast and Bowel Project B-28 and B-14. J Clin Oncol 2016; 34: 2350-2358
    CrossrefPubMedGoogle Scholar
  • 15 Denkert C, Kronenwett R, Schlake W. et al. Decentral gene expression analysis for ER+/Her2– breast cancer: results of a proficiency testing program for the EndoPredict assay. Virchows Arch 2012; 460: 251-259
    CrossrefPubMedGoogle Scholar
  • 16 Dubsky P, Filipits M, Jakesz R. et al. EndoPredict improves the prognostic classification derived from common clinical guidelines in ER-positive, HER2-negative early breast cancer. Ann Oncol 2013; 24: 640-647
    CrossrefPubMedGoogle Scholar
  • 17 Dubsky P, Brase JC, Jakesz R. et al. The EndoPredict score provides prognostic information on late distant metastases in ER+/HER2– breast cancer patients. Br J Cancer 2013; 109: 2959-2964
    CrossrefPubMedGoogle Scholar
  • 18 Martin M, Brase JC, Calvo L. et al. Clinical validation of the EndoPredict test in node-positive, chemotherapy-treated ER+/HER2– breast cancer patients: results from the GEICAM 9906 trial. Breast Cancer Res 2014; 16: R38
    CrossrefPubMedGoogle Scholar
  • 19 Bartlett JMS, Bayani J, Marshall A. et al. Comparing Breast Cancer Multiparameter Tests in the OPTIMA Prelim Trial: No Test Is More Equal Than the Others. J Natl Cancer Inst 2016; 108: djw050
    CrossrefPubMedGoogle Scholar
  • 20 Gluz O, Nitz UA, Christgen M. et al. West German Study Group Phase III PlanB Trial: First Prospective Outcome Data for the 21-Gene Recurrence Score Assay and Concordance of Prognostic Markers by Central and Local Pathology Assessment. J Clin Oncol 2016; 34: 2341-2349
    CrossrefPubMedGoogle Scholar
  • 21 Nitz U, Gluz O, Christgen M. et al. Reducing chemotherapy use in clinically high-risk, genomically low-risk pN0 and pN1 early breast cancer patients: five-year data from the prospective, randomised phase 3 West German Study Group (WSG) PlanB trial. Breast Cancer Res Treat 2017; 165: 573-583
    CrossrefPubMedGoogle Scholar
  • 22 Sparano JA, Gray RJ, Makower DF. et al. Prospective Validation of a 21-Gene Expression Assay in Breast Cancer. N Engl J Med 2015; 373: 2005-2014
    CrossrefPubMedGoogle Scholar
  • 23 Cardoso F, van't Veer LJ, Bogaerts J. et al. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N Engl J Med 2016; 375: 717-729
    CrossrefPubMedGoogle Scholar
  • 24 Harris LN, Ismaila N, McShane LM. et al. Use of Biomarkers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline. J Clin Oncol 2016; 34: 1134-1150
    CrossrefPubMedGoogle Scholar
  • 25 Krop I, Ismaila N, Andre F. et al. Use of Biomarkers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline Focused Update. J Clin Oncol 2017; 35: 2838-2847
    CrossrefPubMedGoogle Scholar
  • 26 Duffy MJ, Harbeck N, Nap M. et al. Clinical use of biomarkers in breast cancer: Updated guidelines from the European Group on Tumor Markers (EGTM). Eur J Cancer 1990 2017; 75: 284-298
    PubMedGoogle Scholar
  • 27 Institute for Quality and Efficiency in Health Care. Biomarker-based tests to support the decision for or against adjuvant systemic chemotherapy in primary breast cancer. Extract. Cologne: Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen (IQWiG), 2016. Available at: https://www.iqwig.de/en/projects-results/projects/non-drug-interventions/d14-01-biomarker-based-tests-for-the-decision-for-or-against-adjuvant-systemic-chemotherapy-in-primary-breast-cancer.6097.html Accessed November 15, 2017
    PubMedGoogle Scholar
  • 28 Curigliano G, Burstein HJ, Winer PE. et al. De-escalating and escalating treatments for early-stage breast cancer: the St. Gallen International Expert Consensus Conference on the Primary Therapy of Early Breast Cancer 2017. Ann Oncol 2017; 28: 1700-1712
    CrossrefPubMedGoogle Scholar