Multigene Assays for Classification, Prognosis, and Prediction in Breast Cancer: a Critical Review on the Background and Clinical Utility

Abstract

Gene signatures which are based on multigene profiling assays have been developed for the purpose to better define the prognosis and prediction of therapy results in early-stage breast cancer. These assays were designed to be more specific than conventional clinico-pathologic parameters in the selection of patients for (neo-)adjuvant treatment and in effect help to avoid unnecessary cytotoxic treatment. In this review we describe molecular risk scores, for which tests are commercially available (PAM50®, MammaTyper®, MammaPrint®, Oncotype DX®, Endopredict®, Genomic Grade Index®) and IHC risk scores (Mammostrat® and IHC4), and discuss the current evidence of their clinical use.

Zusammenfassung

In den letzten Jahren wurden eine Reihe verschiedener Gensignaturen, die auf Multigenassays basieren, für die Abschätzung der Prognose und Prädiktion beim frühen Mammakarzinom entwickelt. Die Zielsetzung dieser Assays ist die Verbesserung der Spezifität gegenüber konventionellen klinisch-pathologischen Parametern für die Therapieplanung, speziell für die Optimierung der Selektion von Patienten für die (neo-)adjuvante Therapie und zur Vermeidung überflüssiger zytotoxischer Therapien. In diesem Review beschreiben wir wichtige molekulare Risikoscores, für die Tests kommerziell angeboten werden (PAM50®, MammaTyper®, MammaPrint®, Oncotype DX®, Endopredict®, Genomic Grade Index®), sowie vergleichbare immunhistochemische (IHC) Risikoscores (Mammostrat®, IHC4), und diskutieren die wissenschaftliche Evidenz dieser Tests und deren klinischen Anwendungsbereich.

Key words

breast cancer - multigene assays - prognosis

Schlüsselwörter

Mammakarzinom - Multigenassays - Prognose

• References

• 1 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: 1736-1747
• 2 Peto R, Davies C, Godwin J et al. Comparisons between different polychemotherapy regimens for early breast cancer: meta-analyses of long-term outcome among 100,000 women in 123 randomised trials. Lancet 2012; 379: 432-444
• 3 Kreipe HH, Ahrens P, Christgen M et al. Jenseits von Staging, Typing und Grading. Herausforderungen und Perspektiven fur die Tumorpathologie der Mamma. Pathologe 2010; 31: 54-59
• 4 Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 2012; 490: 61-70
• 5 Weigelt B, Baehner FL, Reis-Filho JS. The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade. J Pathol 2010; 220: 263-280
• 6 Lehmann BD, Bauer JA, Chen X et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 2011; 121: 2750-2767
• 7 Perou CM, Sorlie T, Eisen MB et al. Molecular portraits of human breast tumours. Nature 2000; 406: 747-752
• 8 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: 10869-10874
• 9 Sotiriou C, Pusztai L. Gene-expression signatures in breast cancer. N Engl J Med 2009; 360: 790-800
• 10 Blows FM, Driver KE, Schmidt MK et al. Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies. PLoS Med 2010; 7: e1000279
• 11 Bastien RR, Rodriguez-Lescure A, Ebbert MT et al. PAM50 breast cancer subtyping by RT-qPCR and concordance with standard clinical molecular markers. BMC Med Genomics 2012; 5: 44
• 12 Weigelt B, Horlings HM, Kreike B et al. Refinement of breast cancer classification by molecular characterization of histological special types. J Pathol 2008; 216: 141-150
• 13 Cheang MC, Voduc KD, Tu D et al. Responsiveness of intrinsic subtypes to adjuvant anthracycline substitution in the NCIC.CTG MA.5 randomized trial. Clin Cancer Res 2012; 18: 2402-2412
• 14 Parker JS, Mullins M, Cheang MC et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009; 27: 1160-1167
• 15 Reis PP, Waldron L, Goswami RS et al. mRNA transcript quantification in archival samples using multiplexed, color-coded probes. BMC Biotechnol 2011; 11: 46
• 16 Perou CM, Parker JS, Prat A et al. Clinical implementation of the intrinsic subtypes of breast cancer. Lancet Oncol 2010; 11: 718-719 author reply 720-711
• 17 Chia SK, Bramwell VH, Tu D et al. A 50-gene intrinsic subtype classifier for prognosis and prediction of benefit from adjuvant tamoxifen. Clin Cancer Res 2012; 18: 4465-4472
• 18 Kelly CM, Bernard PS, Krishnamurthy S et al. Agreement in risk prediction between the 21-gene recurrence score assay (Oncotype DX(R)) and the PAM50 breast cancer intrinsic Classifier in early-stage estrogen receptor-positive breast cancer. Oncologist 2012; 17: 492-498
• 19 Nguyen B, Cusumano PG, Deck K et al. Comparison of molecular subtyping with BluePrint, MammaPrint, and TargetPrint to local clinical subtyping in breast cancer patients. Ann Surg Oncol 2012; 19: 3257-3263
• 20 Varga Z, Diebold J, Dommann-Scherrer C et al. How reliable is Ki-67 immunohistochemistry in grade 2 breast carcinomas? A QA study of the Swiss Working Group of Breast- and Gynecopathologists. PLoS ONE 2012; 7: e37379
• 21 Fountzilas G, Valavanis C, Kotoula V et al. HER2 and TOP2A in high-risk early breast cancer patients treated with adjuvant epirubicin-based dose-dense sequential chemotherapy. J Transl Med 2012; 10: 10
• 22 Noske A, Loibl S, Darb-Esfahani S et al. Comparison of different approaches for assessment of HER2 expression on protein and mRNA level: prediction of chemotherapy response in the neoadjuvant GeparTrio trial (NCT00544765). Breast Cancer Res Treat 2011; 126: 109-117
• 23 Kim C, Tang G, Pogue-Geile KL et al. Estrogen receptor (ESR1) mRNA expression and benefit from tamoxifen in the treatment and prevention of estrogen receptor-positive breast cancer. J Clin Oncol 2011; 29: 4160-4167
• 24 Goldhirsch A, Ingle J, Gelber R 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: 1319-1329
• 25 Desmedt C, Haibe-Kains B, Wirapati P et al. Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res 2008; 14: 5158-5165
• 26 Wirapati P, Sotiriou C, Kunkel S et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res 2008; 10: R65
• 27 vanʼt Veer L, Dai H, van de Vijver M et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002; 415: 530-536
• 28 Tian S, Roepman P, vanʼt Veer LJ et al. Biological functions of the genes in the mammaprint breast cancer profile reflect the hallmarks of cancer. Biomark Insights 2010; 5: 129-138
• 29 van de Vijver M, He Y, vanʼt Veer L et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002; 347: 1999-2009
• 30 Buyse M, Loi S, vanʼt Veer L et al. Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J Natl Cancer Inst 2006; 98: 1183-1192
• 31 Bueno-de-Mesquita JM, Linn SC, Keijzer R et al. Validation of 70-gene prognosis signature in node-negative breast cancer. Breast Cancer Res Treat 2009; 117: 483-495
• 32 Wittner BS, Sgroi DC, Ryan PD et al. Analysis of the MammaPrint breast cancer assay in a predominantly postmenopausal cohort. Clin Cancer Res 2008; 14: 2988-2993
• 33 Mook S, Schmidt MK, Viale G et al. The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1–3 positive lymph nodes in an independent validation study. Breast Cancer Res Treat 2009; 116: 295-302
• 34 Mook S, Schmidt MK, Weigelt B et al. The 70-gene prognosis signature predicts early metastasis in breast cancer patients between 55 and 70 years of age. Ann Oncol 2010; 21: 717-722
• 35 Knauer M, Mook S, Rutgers EJ et al. The predictive value of the 70-gene signature for adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat 2010; 120: 655-661
• 36 Esteban J, Baker J, Cronin M et al. Tumor Gene Expression and Prognosis in Breast Cancer: Multi-Gene RT-PCR Assay of Paraffin-embedded Tissue. Abstract #3416. Chicago, IL: ASCO Annual Meeting; 2003
• 37 Cobleigh MA, Bitterman P, Baker J et al. Tumor Gene Expression predicts distant disease-free Survival (DDFS) in Breast Cancer Patients with 10 or more positive Nodes: high throughput RT-PCR Assay of Paraffin-embedded Tumor Tissues. Abstract #3466. Chicago, IL: ASCO Annual Meeting; 2003
• 38 Paik S, Shak S, Tang G et al. Multi-gene RT-PCR assay for predicting recurrence in node negative breast cancer patients – NSABP studies B-20 and B-14. Breast Cancer Res Treat 2003; 82 (Suppl.) S10-S11
• 39 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
• 40 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
• 41 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
• 42 Sparano JA, Paik S. Development of the 21-gene assay and its application in clinical practice and clinical trials. J Clin Oncol 2008; 26: 721-728
• 43 Markopoulos C. Overview of the use of Oncotype DX((R)) as an additional treatment decision tool in early breast cancer. Expert Rev Anticancer Ther 2013; 13: 179-194
• 44 Eiermann W, Rezai M, Kummel S et al. The 21-gene recurrence score assay impacts adjuvant therapy recommendations for ER-positive, node-negative and node-positive early breast cancer resulting in a risk-adapted change in chemotherapy use. Ann Oncol 2013; 24: 618-624
• 45 Hornberger J, Chien R, Krebs K et al. US insurance programʼs experience with a multigene assay for early-stage breast cancer. J Oncol Pract 2011; 7: e38s-e45s
• 46 Filipits M, Rudas M, Jakesz R et al. A new molecular predictor of distant recurrence in ER-positive, HER2-negative breast cancer adds independent information to conventional clinical risk factors. Clin Cancer Res 2011; 17: 6012-6020
• 47 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
• 48 Dubsky PC, Jakesz R, Mlineritsch B et al. Tamoxifen and anastrozole as a sequencing strategy: a randomized controlled trial in postmenopausal patients with endocrine-responsive early breast cancer from the Austrian Breast and Colorectal Cancer Study Group. J Clin Oncol 2012; 30: 722-728
• 49 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
• 50 Muller BM, Keil E, Lehmann A et al. The EndoPredict gene-expression assay in clinical practice – performance and impact on clinical decisions. PLoS ONE 2013; 8: e68252
• 51 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: 5222-5232
• 52 Dowsett M, Sestak I, Lopez-Knowles E et al. Comparison of PAM50 risk of recurrence score with Oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol 2013; 31: 2783-2790
• 53 Martin M, Prat A, Rodriguez-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
• 54 Rakha EA, El-Sayed ME, Lee AH et al. Prognostic significance of Nottingham histologic grade in invasive breast carcinoma. J Clin Oncol 2008; 26: 3153-3158
• 55 Rakha EA, Reis-Filho JS, Baehner F et al. Breast cancer prognostic classification in the molecular era: the role of histological grade. Breast Cancer Res 2010; 12: 207
• 56 Paradiso A, Ellis IO, Zito FA et al. Short- and long-term effects of a training session on pathologistsʼ performance: the INQAT experience for histological grading in breast cancer. J Clin Pathol 2009; 62: 279-281
• 57 Sotiriou C, Wirapati P, Loi S et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 2006; 98: 262-272
• 58 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: 1239-1246
• 59 Desmedt C, Giobbie-Hurder A, Neven P et al. The Gene expression Grade Index: a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1-98 trial. BMC Med Genomics 2009; 2: 40
• 60 Naoi Y, Kishi K, Tanei T et al. High genomic grade index associated with poor prognosis for lymph node-negative and estrogen receptor-positive breast cancers and with good response to chemotherapy. Cancer 2011; 117: 472-479
• 61 Liedtke C, Hatzis C, Symmans WF et al. Genomic grade index is associated with response to chemotherapy in patients with breast cancer. J Clin Oncol 2009; 27: 3185-3191
• 62 Toussaint J, Sieuwerts AM, Haibe-Kains B et al. Improvement of the clinical applicability of the Genomic Grade Index through a qRT-PCR test performed on frozen and formalin-fixed paraffin-embedded tissues. BMC Genomics 2009; 10: 424
• 63 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: 4273-4278
• 64 Barton S, Zabaglo L, AʼHern R et al. Assessment of the contribution of the IHC4+C score to decision making in clinical practice in early breast cancer. Br J Cancer 2012; 106: 1760-1765
• 65 Ring BZ, Seitz RS, Beck R et al. Novel prognostic immunohistochemical biomarker panel for estrogen receptor-positive breast cancer. J Clin Oncol 2006; 24: 3039-3047
• 66 Ross DT, Kim CY, Tang G et al. Chemosensitivity and stratification by a five monoclonal antibody immunohistochemistry test in the NSABP B14 and B20 trials. Clin Cancer Res 2008; 14: 6602-6609
• 67 Bartlett JM, Bloom KJ, Piper T et al. Mammostrat as an immunohistochemical multigene assay for prediction of early relapse risk in the tamoxifen versus exemestane adjuvant multicenter trial pathology study. J Clin Oncol 2012; 30: 4477-4484
• 68 Weigelt B, Pusztai L, Ashworth A et al. Challenges translating breast cancer gene signatures into the clinic. Nat Rev Clin Oncol 2012; 9: 58-64
• 69 Weigelt B, Reis-Filho JS. Molecular profiling currently offers no more than tumour morphology and basic immunohistochemistry. Breast Cancer Res 2010; 12 (Suppl. 04) S5
• 70 Braun L, Mietzsch F, Seibold P et al. Intrinsic breast cancer subtypes defined by estrogen receptor signalling-prognostic relevance of progesterone receptor loss. Mod Pathol 2013;
• 71 Elsawaf Z, Sinn HP, Rom J et al. Biological subtypes of triple-negative breast cancer are associated with distinct morphological changes and clinical behaviour. Breast 2013;
• 72 Weigelt B, Reis-Filho JS. Histological and molecular types of breast cancer: is there a unifying taxonomy?. Nat Rev Clin Oncol 2009; 6: 718-730
• 73 Rakha EA, Reis-Filho JS, Ellis IO. Combinatorial biomarker expression in breast cancer. Breast Cancer Res Treat 2010; 120: 293-308
• 74 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
• 75 Fan C, Oh DS, Wessels L et al. Concordance among gene-expression-based predictors for breast cancer. N Engl J Med 2006; 355: 560-569
• 76 Varga Z, Sinn P, Fritzsche F et al. Comparison of EndoPredict and Oncotype DX test results in hormone receptor positive invasive breast cancer. PLoS ONE 2013; 8: e58483
• 77 Prat A, Parker JS, Fan C et al. Concordance among gene expression-based predictors for ER-positive breast cancer treated with adjuvant tamoxifen. Ann Oncol 2012; 23: 2866-2873
• 78 Robbins P, Pinder S, de Klerk N et al. Histological grading of breast carcinomas: a study of interobserver agreement. Hum Pathol 1995; 26: 873-879
• 79 Gudlaugsson E, Skaland I, Janssen EA et al. Comparison of the effect of different techniques for measurement of Ki67 proliferation on reproducibility and prognosis prediction accuracy in breast cancer. Histopathology 2012; 61: 1134-1144
• 80 Weigelt B, Mackay A, AʼHern R et al. Breast cancer molecular profiling with single sample predictors: a retrospective analysis. Lancet Oncol 2010; 11: 339-349
• 81 Geyer FC, Marchio C, Reis-Filho JS. The role of molecular analysis in breast cancer. Pathology 2009; 41: 77-88
• 82 Chang JC, Makris A, Gutierrez MC et al. Gene expression patterns in formalin-fixed, paraffin-embedded core biopsies predict docetaxel chemosensitivity in breast cancer patients. Breast Cancer Res Treat 2008; 108: 233-240
• 83 Esteva F, Sahin A, Cristofanilli M et al. Prognostic role of a multigene reverse transcriptase-PCR assay in patients with node-negative breast cancer not receiving adjuvant systemic therapy. Clin Cancer Res 2005; 11: 3315-3319
• 84 Denkert C, Loibl S, Kronenwett R et al. RNA-based determination of ESR1 and HER2 expression and response to neoadjuvant chemotherapy. Ann Oncol 2013; 24: 632-639
• 85 Symmans WF, Hatzis C, Sotiriou C et al. Genomic index of sensitivity to endocrine therapy for breast cancer. J Clin Oncol 2010; 28: 4111-4119
• 86 Bhargava R, Dabbs DJ. Oncotype DX test on unequivocally HER2-positive cases: potential for harm. J Clin Oncol 2012; 30: 570-571
• 87 Azim Jr. HA, Michiels S, Zagouri F et al. Utility of prognostic genomic tests in breast cancer practice: the IMPAKT 2012 Working Group consensus statement. Ann Oncol 2013; 24: 647-654
• 88 Scharl A. Mammakarzinom-Therapie: Der routinemäßige Einsatz von Gentests ist derzeit nicht sinnvoll. Dtsch Arztebl International 2012; 109: 2085-2086
• 89 Cardoso F, vanʼt Veer L, Rutgers E et al. Clinical application of the 70-gene profile: the MINDACT trial. J Clin Oncol 2008; 26: 729-735