Abstract
A robust body of evidence, initiated by the seminal studies of Dr. Perou’s group at the dawn of the new millennium [1, 2] and repeatedly confirmed over the following decade, has convincingly demonstrated that breast cancer (BC) is a heterogeneous disease further classifiable in at least four molecular intrinsic subtypes (luminal A and B, HER2 enriched, basal-like, and normal breast), based on hierarchical clustering of the “intrinsic genes” (i.e., genes with minimal variation within a tumor sample, but maximal variation between different patients) expression profile. These studies were originally based on genome-wide gene expression profiling from microarray datasets and progressed to a PCR-based test with a list of 50 genes (the PAM50 gene signature) [3, 4] (Fig. 12.1).
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References
Perou CM, Sorlie T, Eisen MB et al (2000) Molecular portraits of human breast tumours. Nature 406(6797):747–752
Sorlie T, Perou CM, Tibshirani R et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 98(19):10869–10874
Parker JS, Mullins M, Cheang MC et al (2009) Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 27(8):1160–1167
Prat A, Pineda E, Adamo B et al (2015) Clinical implications of the intrinsic molecular subtypes of breast cancer. Breast 24(Suppl 2):S26–S35
Reis PP, Waldron L, Goswami RS et al (2011) mRNA transcript quantification in archival samples using multiplexed, color-coded probes. BMC Biotechnol 11:46
Burstein HJ, Temin S, Anderson H et al (2014) Adjuvant endocrine therapy for women with hormone receptor-positive breast cancer: American society of clinical oncology clinical practice guideline focused update. J Clin Oncol 32(21):2255–2269
Moja L, Tagliabue L, Balduzzi S et al (2012) Trastuzumab containing regimens for early breast cancer. Cochrane Database Syst Rev 4. CD006243
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. Ann Oncol 24(9):2206–2223
Regan MM, Pagani O, Walley B et al (2008) Premenopausal endocrine-responsive early breast cancer: who receives chemotherapy? Ann Oncol 19(7):1231–1241
Chereau E, Coutant C, Gligorov J et al (2011) Discordance with local guidelines for adjuvant chemotherapy in breast cancer: reasons and effect on survival. Clin Breast Cancer 11(1):46–51
Oyama T, Ishikawa Y, Hayashi M et al (2007) The effects of fixation, processing and evaluation criteria on immunohistochemical detection of hormone receptors in breast cancer. Breast Cancer 14(2):182–188
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
van’t Veer LJ, Dai H, van de Vijver MJ et al (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415(6871):530–536
Wittner BS, Sgroi DC, Ryan PD et al (2008) Analysis of the MammaPrint breast cancer assay in a predominantly postmenopausal cohort. Clin Cancer Res 14(10):2988–2993
Mook S, Schmidt MK, Weigelt B et al (2010) The 70-gene prognosis signature predicts early metastasis in breast cancer patients between 55 and 70 years of age. Ann Oncol 21(4):717–722
Straver ME, Glas AM, Hannemann J et al (2010) The 70-gene signature as a response predictor for neoadjuvant chemotherapy in breast cancer. Breast Cancer Res Treat 119(3):551–558
Eifel P, Axelson JA, Costa J et al (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
Goldhirsch A, Glick JH, Gelber RD et al (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
van de Vijver MJ, He YD, van’t Veer LJ et al (2002) A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347(25):1999–2009
Mook S, Schmidt MK, Viale G et al (2009) 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 116(2):295–302
Knauer M, Mook S, Rutgers EJ et al (2010) The predictive value of the 70-gene signature for adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat 120(3):655–661
Drukker CA, Bueno-de-Mesquita JM, Retel VP et al (2013) A prospective evaluation of a breast cancer prognosis signature in the observational RASTER study. Int J Cancer 133(4):929–936
Bueno-de-Mesquita JM, Linn SC, Keijzer R et al (2009) Validation of 70-gene prognosis signature in node-negative breast cancer. Breast Cancer Res Treat 117(3):483–495
CBO KvdG (2004) Adjuvante systemische therapie voor het operabel mammacarcinoom. Richtlijn Behandeling van het Mammacarcinoom:46–70
Adjuvant! for Breast Cancer (Version 8.0) Adjuvant! Inc. http://www.adjuvantonline.com
Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) (1998) Polychemotherapy for early breast cancer: an overview of the randomised trials. Lancet 352:930–952
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
Buyse M, Loi S, van’t Veer L 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
Joensuu H, Pylkkanen L, Toikkanen S (1998) Long-term survival in node-positive breast cancer treated by locoregional therapy alone. Br J Cancer 78(6):795–799
Cardoso F, Van’t Veer L, Rutgers E et al (2008) Clinical application of the 70-gene profile: the MINDACT trial. J Clin Oncol 26(5):729–735
Cardoso F, van’t Veer LI, Bogaerts J et al (2016) 70-gene signature as an aid to treatment decisions in early-stage breast cancer. N Engl J Med 375:717–729
Paik S, Shak S, Tang G et al (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351(27):2817–2826
Paik S, Tang G, Shak S et al (2006) Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol 24(23):3726–3734
Dowsett M, Cuzick J, Wale C et al (2010) 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 28(11):1829–1834
Forbes JF, Cuzick J, Buzdar A et al (2008) Effect of anastrozole and tamoxifen as adjuvant treatment for early-stage breast cancer: 100-month analysis of the ATAC trial. Lancet Oncol 9(1):45–53
Albain KS, Barlow WE, Shak S et al (2010) 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 11(1):55–65
Gianni L, Zambetti M, Clark K et al (2005) Gene expression profiles in paraffin-embedded core biopsy tissue predict response to chemotherapy in women with locally advanced breast cancer. J Clin Oncol 23(29):7265–7277
Carlson JJ, Roth JA (2013) The impact of the Oncotype dx breast cancer assay in clinical practice: a systematic review and meta-analysis. Breast Cancer Res Treat 141(1):13–22
Augustovski F, Soto N, Caporale J et al (2015) Decision-making impact on adjuvant chemotherapy allocation in early node-negative breast cancer with a 21-gene assay: systematic review and meta-analysis. Breast Cancer Res Treat 152(3):611–625
Eiermann W, Rezai M, Kummel S et al (2013) 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 24(3):618–624
Hornberger J, Chien R, Krebs K, Hochheiser L (2011) US insurance Program’s experience with a multigene assay for early-stage breast cancer. J Oncol Pract 7(3 Suppl):e38s–e45s
Anonymous (2014) Hormone therapy with or without combination chemotherapy in treating women who have undergone surgery for node-negative breast cancer (The TAILORx Trial). In: NCT00310180 ClinicalTrials gov. http://clinicaltrialsgov/show/NCT00310180
Sparano JA, Gray RJ, Makower DF, et al (2015) Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med 373(21):2005–2014
Milburn M, Rosman M, Mylander C, Tafra L (2013) Is Oncotype DX recurrence score (RS) of prognostic value once HER2-positive and. Low-ER expression patients are removed? Breast J 19(4):357–364
Allison KH, Kandalaft PL, Sitlani CM et al (2012) Routine pathologic parameters can predict Oncotype DX recurrence scores in subsets of ER positive patients: who does not always need testing? Breast Cancer Res Treat 131(2):413–424
Mattes MD, Mann JM, Ashamalla H, Tejwani A (2013) Routine histopathologic characteristics can predict Oncotype DX(TM) recurrence score in subsets of breast cancer patients. Cancer Invest 31(9):604–606
Ingoldsby H, Webber M, Wall D et al (2013) Prediction of Oncotype DX and TAILORx risk categories using histopathological and immunohistochemical markers by classification and regression tree (CART) analysis. Breast 22(5):879–886
Klein ME, Dabbs DJ, Shuai Y et al (2013) Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis. Mod Pathol 26(5):658–664
Auerbach J, Kim M, Fineberg S (2010) Can features evaluated in the routine pathologic assessment of lymph node-negative estrogen receptor-positive stage I or II invasive breast cancer be used to predict the Oncotype DX recurrence score? Arch Pathol Lab Med 134(11):1697–1701
Flanagan MB, Dabbs DJ, Brufsky AM et al (2008) Histopathologic variables predict Oncotype DX recurrence score. Mod Pathol 21(10):1255–1261
Geradts J, Bean SM, Bentley RC, Barry WT (2010) The Oncotype DX recurrence score is correlated with a composite index including routinely reported pathobiologic features. Cancer Invest 28(9):969–977
Tang P, Wang J, Hicks DG et al (2010) A lower Allred score for progesterone receptor is strongly associated with a higher recurrence score of 21-gene assay in breast cancer. Cancer Invest 28(9):978–982
Gage MM, Rosman M, Mylander WC et al (2015) A validated model for identifying patients unlikely to benefit from the 21-gene recurrence score assay. Clin Breast Cancer 15(6):467–472
Baxter E, Gondara L, Lohrisch C et al (2015) Using proliferative markers and Oncotype DX in therapeutic decision-making for breast cancer: the B.C. experience. Curr Oncol 22(3):192–198
Kronenwett R, Bohmann K, Prinzler J et al (2012) Decentral gene expression analysis: analytical validation of the Endopredict genomic multianalyte breast cancer prognosis test. BMC Cancer 12:456
Denkert C, Kronenwett R, Schlake W et al (2012) Decentral gene expression analysis for ER+/Her2− breast cancer: results of a proficiency testing program for the EndoPredict assay. Virchows Arch 460(3):251–259
Muller BM, Brase JC, Haufe F et al (2012) Comparison of the RNA-based EndoPredict multigene test between core biopsies and corresponding surgical breast cancer sections. J Clin Pathol 65(7):660–662
Dubsky P, Brase JC, Jakesz R et al (2013) The EndoPredict score provides prognostic information on late distant metastases in ER+/HER2− breast cancer patients. Br J Cancer 109(12):2959–2964
Filipits M, Rudas M, Jakesz R et al (2011) 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 17(18):6012–6020
Dubsky P, Filipits M, Jakesz R et al (2013) EndoPredict improves the prognostic classification derived from common clinical guidelines in ER-positive, HER2-negative early breast cancer. Ann Oncol 24(3):640–647
Muller BM, Keil E, Lehmann A et al (2013) The endoPredict gene-expression assay in clinical practice-performance and impact on clinical decisions. PLoS One 8(6):e68252
Bertucci F, Finetti P, Viens P, Birnbaum D (2014) EndoPredict predicts for the response to neoadjuvant chemotherapy in ER-positive, HER2-negative breast cancer. Cancer Lett 355(1):70–75
Martin M, Brase JC, Calvo L et al (2014) 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 16(2):R38
Perou CM, Parker JS, Prat A, Ellis MJ, Bernard PS (2010) Clinical implementation of the intrinsic subtypes of breast cancer. Lancet Oncol 11(8):718–719
Chia SK, Bramwell VH, Tu D et al (2012) A 50-gene intrinsic subtype classifier for prognosis and prediction of benefit from adjuvant tamoxifen. Clin Cancer Res 18(16):4465–4472
Kelly CM, Bernard PS, Krishnamurthy S et al (2012) 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 17(4):492–498
Nielsen TO, Parker JS, Leung S et al (2010) A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer. Clin Cancer Res 16(21):5222–5232
Dowsett M, Sestak I, Lopez-Knowles E et al (2013) Comparison of PAM50 risk of recurrence score with Oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol 31(22):2783–2790
Wang Y, Klijn JG, Zhang Y et al (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365(9460):671–679
Desmedt C, Piette F, Loi S et al (2007) Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series. Clin Cancer Res 13(11):3207–3214
Rakha EA, El-Sayed ME, Lee AH et al (2008) Prognostic significance of Nottingham histologic grade in invasive breast carcinoma. J Clin Oncol 26(19):3153–3158
Rakha EA, Reis-Filho JS, Baehner F et al (2010) Breast cancer prognostic classification in the molecular era: the role of histological grade. Breast Cancer Res 12(4):207
Paradiso A, Ellis IO, Zito FA et al (2009) Short- and long-term effects of a training session on pathologists’ performance: the INQAT experience for histological grading in breast cancer. J Clin Pathol 62(3):279–281
Longacre TA, Ennis M, Quenneville LA et al (2006) Interobserver agreement and reproducibility in classification of invasive breast carcinoma: an NCI breast cancer family registry study. Mod Pathol 19(2):195–207
Desmedt C, Giobbie-Hurder A, Neven P et al (2009) The gene expression grade index: a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1–98 trial. BMC Med Genet 2:40
Sotiriou C, Wirapati P, Loi S et al (2006) Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98(4):262–272
Loi S, Haibe-Kains B, Desmedt C et al (2007) Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade. J Clin Oncol 25(10):1239–1246
Liedtke C, Hatzis C, Symmans WF et al (2009) Genomic grade index is associated with response to chemotherapy in patients with breast cancer. J Clin Oncol 27(19):3185–3191
Ma XJ, Wang Z, Ryan PD et al (2004) A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell 5(6):607–616
Jerevall PL, Ma XJ, Li H et al (2011) Prognostic utility of HOXB13:IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial. Br J Cancer 104(11):1762–1769
Zhang Y, Schnabel CA, Schroeder BE et al (2013) Breast cancer index identifies early-stage estrogen receptor-positive breast cancer patients at risk for early- and late-distant recurrence. Clin Cancer Res 19(15):4196–4205
Cuzick J, Dowsett M, Pineda S et al (2011) 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 29(32):4273–4278
Buus R, Sestak I, Kronenwett R et al (2016) Comparison of EndoPredict and EPclin with Oncotype DX recurrence score for prediction of risk of distant recurrence after endocrine therapy. J Natl Cancer Inst 108(11) pii:djw149. doi:10.1093/jnci/djw149. Print 2016 Nov
Sgroi DC, Sestak I, Cuzick J et al (2013) 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 14(11):1067–1076
Wirapati P, Sotiriou C, Kunkel S et al (2008) Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res 10(4):R65
Reyal F, van Vliet MH, Armstrong NJ et al (2008) A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the proliferation, immune response and RNA splicing modules in breast cancer. Breast Cancer Res 10(6):R93
Desmedt C, Haibe-Kains B, Wirapati P et al (2008) Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res 14(16):5158–5165
Harris LN, Ismaila N, McShane LM et al (2016) 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 34(10):1134–1150
Gnant M, Sestak I, Filipits M et al (2015) Identifying clinically relevant prognostic subgroups of postmenopausal women with node-positive hormone receptor-positive early-stage breast cancer treated with endocrine therapy: a combined analysis of ABCSG-8 and ATAC using the PAM50 risk of recurrence score and intrinsic subtype. Ann Oncol 26(8):1685–1191
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Pruneri, G., Boggio, F. (2017). Prognostic and Predictive Role of Genetic Signatures. In: Veronesi, U., Goldhirsch, A., Veronesi, P., Gentilini, O., Leonardi, M. (eds) Breast Cancer. Springer, Cham. https://doi.org/10.1007/978-3-319-48848-6_12
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