Advertisement

Breast Disease pp 173-189 | Cite as

Gene Arrays, Prognosis, and Therapeutic Interventions

  • Cagatay Arslan
  • Zeki G. Surmeli
  • Y. Yavuz Ozisik
Chapter

Abstract

Among women, breast cancer accounts for one-third of cancer cases and is the second most frequent cause of death. Improvements in treatment agents and screening procedures have increased the diagnosis of early breast cancer and survival rates. Adjuvant chemotherapy and endocrine treatment decrease the mortality of early breast cancer by approximately 50%. However, not all early breast cancer patients benefit equally from adjuvant endocrine treatment and/or chemotherapy. Patients at high risk are classically identified based on clinicopathological factors, such as age, tumor size, histopathological grade, nodal status, hormone and HER2 receptor positivity, and menopausal status. However, for patients with early breast cancer, using these standard clinicopathological factors might not thoroughly show the individual risk of disease recurrence and the benefits from adjuvant systemic chemotherapy. Many patients with early breast cancer do not derive benefit from adjuvant systemic chemotherapy. Quality-of-life issues, acute and long-term side effects of systemic chemotherapy, and the cost of unnecessary treatments are the main factors of concern for this group of patients. Quantitative approaches for defining prognoses and for individualizing treatments are required. In recent years, molecular signatures of gene expression have been correlated with breast cancer recurrence risk. Several tests for genomic expression have been developed and validated on specimens from previous phase III studies to improve the prognostication of early breast cancer patients and/or the prediction of adjuvant systemic treatment. The most commonly used genomic expression-based tests used for prognostic information and for the prediction of chemotherapy benefits in early breast cancer are summarized below.

Keywords

Early breast cancer Gene arrays Prognosis Prediction of treatment 

References

  1. 1.
    Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin. 2013;63:11–30.Google Scholar
  2. 2.
    Early Breast Cancer Trialists’ Collaborative G. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet. 2005;365:1687–717.Google Scholar
  3. 3.
    Polychemotherapy for early breast cancer: an overview of the randomised trials. Early Breast Cancer Trialists’ Collaborative Group. Lancet. 1998;352:930–42.Google Scholar
  4. 4.
    Tamoxifen for early breast cancer: an overview of the randomised trials. Early Breast Cancer Trialists’ Collaborative Group. Lancet. 1998;351:1451–67.Google Scholar
  5. 5.
    Bedard PL, Cardoso F. Can some patients avoid adjuvant chemotherapy for early-stage breast cancer? Nature reviews. Clin Oncol. 2011;8:272–9.Google Scholar
  6. 6.
    Bryant J, Fisher B, Gunduz N, Costantino JP, Emir B. S-phase fraction combined with other patient and tumor characteristics for the prognosis of node-negative, estrogen-receptor-positive breast cancer. Breast Cancer Res Treat. 1998;51:239–53.PubMedGoogle Scholar
  7. 7.
    Henderson IC, Patek AJ. The relationship between prognostic and predictive factors in the management of breast cancer. Breast Cancer Res Treat. 1998;52:261–88.PubMedGoogle Scholar
  8. 8.
    Fitzgibbons PL, Page DL, Weaver D, Thor AD, Allred DC, Clark GM, et al. Prognostic factors in breast cancer. College of American Pathologists Consensus Statement 1999. Arch Pathol Lab Med. 2000;124:966–78.PubMedPubMedCentralGoogle Scholar
  9. 9.
    Bast RC Jr, Ravdin P, Hayes DF, Bates S, Fritsche H Jr, Jessup JM, et al. 2000 update of recommendations for the use of tumor markers in breast and colorectal cancer: clinical practice guidelines of the American Society of Clinical Oncology. J Clin Oncol. 2001;19:1865–78.PubMedGoogle Scholar
  10. 10.
    Goldhirsch A, Glick JH, Gelber RD, Coates AS, Senn HJ. 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. 2001;19:3817–27.PubMedGoogle Scholar
  11. 11.
    Eifel P, Axelson JA, Costa J, Crowley J, Curran WJ Jr, Deshler A, et al. National Institutes of Health Consensus Development Conference Statement: adjuvant therapy for breast cancer, November 1–3, 2000. J Natl Cancer Inst. 2001;93:979–89.PubMedGoogle Scholar
  12. 12.
    Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406:747–52.PubMedPubMedCentralGoogle Scholar
  13. 13.
    Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science. 1999;286:531–7.PubMedGoogle Scholar
  14. 14.
    van’t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415:530–6.Google Scholar
  15. 15.
    van de Vijver MJ, He YD, van’t Veer LJ, Dai H, Hart AA, Voskuil DW, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med. 2002;347:1999–2009.Google Scholar
  16. 16.
    Harbeck N, Sotlar K, Wuerstlein R, Doisneau-Sixou S. Molecular and protein markers for clinical decision making in breast cancer: today and tomorrow. Cancer Treat Rev. 2014;40:434–44.PubMedGoogle Scholar
  17. 17.
    Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351:2817–26.PubMedPubMedCentralGoogle Scholar
  18. 18.
    Cronin M, Pho M, Dutta D, Stephans JC, Shak S, Kiefer MC, et al. Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay. Am J Pathol. 2004;164:35–42.PubMedPubMedCentralGoogle Scholar
  19. 19.
    Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98:10869–74.PubMedPubMedCentralGoogle Scholar
  20. 20.
    Esteva FJ, Sahin AA, Coombes K, Baker J, Cronin M, Walker M, et al. Multi-gene RT-PCR assay for predicting recurrence in node-negative breast cancer patients – M.D. Anderson Clinical Validation Study [abstract]. Breast Cancer Res Treat. 2003;82:A17.  https://doi.org/10.1023/B:BREA.0000003871.38587.8b. http://www.sabcs.orgPubMedGoogle Scholar
  21. 21.
    Cobleigh MA, Bitterman P, Baker J, Cronin M, Liu M-L, Borchik R, 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]. Proc Am Soc Clin Oncol. 2003;22:A3415.Google Scholar
  22. 22.
    Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, et al. Multi-gene RT-PCR assay for predicting recurrence in node-negative breast cancer patients – NSABP studies B-20 and B-14 [abstract]. Breast Cancer Res Treat. 2003;82:A16. http://www.sabcs.org
  23. 23.
    Habel LA, Shak S, Jacobs MK, Capra A, Alexander C, Pho M, et al. A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res. 2006;8(3):R25.  https://doi.org/10.1186/bcr1412.
  24. 24.
    Toi M, Iwata H, Yamanaka T, Masuda N, Ohno S, Nakamura S, et al. Clinical significance of the 21-gene signature (Oncotype DX) in hormone receptor-positive early stage primary breast cancer in the Japanese population. Cancer. 2010;116:3112–8.PubMedGoogle Scholar
  25. 25.
    Fisher B, Redmond C, Legault-Poisson S, Dimitrov NV, Brown AM, Wickerham DL, et al. Postoperative chemotherapy and tamoxifen compared with tamoxifen alone in the treatment of positive-node breast cancer patients aged 50 years and older with tumors responsive to tamoxifen: results from the National Surgical Adjuvant Breast and Bowel Project B-16. J Clin Oncol. 1990;8:1005–18.PubMedGoogle Scholar
  26. 26.
    Baum M, Budzar AU, Cuzick J, Forbes J, Houghton JH, Klijn JG, et al. Anastrozole alone or in combination with tamoxifen versus tamoxifen alone for adjuvant treatment of postmenopausal women with early breast cancer: first results of the ATAC randomised trial. Lancet. 2002;359:2131–9.PubMedGoogle Scholar
  27. 27.
    Arimidex, Tamoxifen, Alone or in Combination (ATAC) Trialists’ Group, Forbes JF, Cuzick J, Buzdar A, Howell A, Tobias JS, et al. Effect of anastrozole and tamoxifen as adjuvant treatment for early-stage breast cancer: 100-month analysis of the ATAC trial. Lancet Oncol. 2008;9:45–53.Google Scholar
  28. 28.
    Fisher B, Dignam J, Wolmark N, DeCillis A, Emir B, Wickerham DL, et al. Tamoxifen and chemotherapy for lymph node-negative, estrogen receptor-positive breast cancer. J Natl Cancer Inst. 1997;89:1673–82.PubMedGoogle Scholar
  29. 29.
    Berry DA, Cirrincione C, Henderson IC, Citron ML, Budman DR, Goldstein LJ, et al. Estrogen-receptor status and outcomes of modern chemotherapy for patients with node-positive breast cancer. JAMA. 2006;295:1658–67.PubMedPubMedCentralGoogle Scholar
  30. 30.
    Hayes DF, Thor AD, Dressler LG, Weaver D, Edgerton S, Cowan D, et al. HER2 and response to paclitaxel in node-positive breast cancer. N Engl J Med. 2007;357:1496–506.PubMedGoogle Scholar
  31. 31.
    Mamounas EP, Bryant J, Lembersky B, Fehrenbacher L, Sedlacek SM, Fisher B, et al. Paclitaxel after doxorubicin plus cyclophosphamide as adjuvant chemotherapy for node-positive breast cancer: results from NSABP B-28. J Clin Oncol. 2005;23:3686–96.PubMedGoogle Scholar
  32. 32.
    Mamounas EP, Tang G, Paik S, Baehner FL, Liu Q, Jeong JH, et al. 21-Gene Recurrence Score for prognosis and prediction of taxane benefit after adjuvant chemotherapy plus endocrine therapy: results from NSABP B-28/NRG Oncology. Breast Cancer Res Treat. 2018;168(1):69–77.Google Scholar
  33. 33.
    Albain KS, Barlow WE, Shak S, Hortobagyi GN, Livingston RB, Yeh IT, 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
  34. 34.
    Goldstein LJ, Gray R, Badve S, Childs BH, Yoshizawa C, Rowley S, et al. Prognostic utility of the 21-gene assay in hormone receptor-positive operable breast cancer compared with classical clinicopathologic features. J Clin Oncol. 2008;26:4063–71.PubMedPubMedCentralGoogle Scholar
  35. 35.
    Sparano JA, O’Neill A, Gray RJ, et al. 10-year update of E2197: phase III doxorubicin/docetaxel (AT) versus doxorubicin/cyclophosphamide (AC) adjuvant treatment of LN+ and high-risk LN- breast cancer and the comparison of the prognostic utility of the 21-gene Recurrence Score (RS) with clinicopathologic features. J Clin Oncol. 2012;30(Suppl 15). [abstract 1021].Google Scholar
  36. 36.
    Senkus E, Kyriakides S, Penault-Llorca F, Poortmans P, Thompson A, Zackrisson S, et al. Primary breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2013;24(Suppl 6):vi7–23.PubMedGoogle Scholar
  37. 37.
    Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thurlimann B, et al. 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. 2013;24:2206–23.PubMedPubMedCentralGoogle Scholar
  38. 38.
    Harris L, Fritsche H, Mennel R, Norton L, Ravdin P, Taube S, et al. American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol. 2007;25:5287–312.PubMedGoogle Scholar
  39. 39.
  40. 40.
    Oratz R, Kim B, Chao C, Skrzypczak S, Ory C, Bugarini R, et al. Physician survey of the effect of the 21-gene recurrence score assay results on treatment recommendations for patients with lymph node-positive, estrogen receptor-positive breast cancer. J Oncol Pract. 2011;7:94–9.PubMedPubMedCentralGoogle Scholar
  41. 41.
    Klang S, Liebermann N, Rizel S, et al. The recurrence score and chemotherapy treatment in node-positive, ER+ early-stage breast cancer patients in Israel. J Clin Oncol. 2010;28(15 Suppl). [Abstract] 6075.Google Scholar
  42. 42.
    de Boer RH, Baker C, Speakman D, Chao CY, Yoshizawa C, Mann GB. The impact of a genomic assay (Oncotype DX) on adjuvant treatment recommendations in early breast cancer. Med J Aust. 2013;199:205–8.PubMedGoogle Scholar
  43. 43.
    Estevez LG, Calvo I, Abad MF, et al. A retrospective study in the Spanish population with Oncotype dx recurrence score (RS) in breast cancer patients with positive and negative-lymph nodes. J Clin Oncol. 2013;31(Suppl; [abstract] e11531).Google Scholar
  44. 44.
    Carlson JJ, Roth JA. The impact of the Oncotype Dx breast cancer assay in clinical practice: a systematic review and meta-analysis. Breast Cancer Res Treat. 2013;141:13–22.PubMedPubMedCentralGoogle Scholar
  45. 45.
    Goncalves R, Bose R. Using multigene tests to select treatment for early-stage breast cancer. J Natl Compr Cancer Network. 2013;11:174–82; quiz 82.Google Scholar
  46. 46.
    Sparano JA. TAILORx: trial assigning individualized options for treatment (Rx). Clin Breast Cancer. 2006;7:347–50.PubMedGoogle Scholar
  47. 47.
    Sparano JA, Gray RJ, Makower DF, Pritchard KI, Albain KS, Hayes DF, et al. Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med. 2015;19:2005–14.Google Scholar
  48. 48.
    Sparano JA, Gray RJ, Makower DF, Pritchard KI, Albain KS, Hayes DF, et al. Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. N Engl J Med. 2018;379(2):111–21.Google Scholar
  49. 49.
    Gluz O, Kreipe H, Dehenhardt T, Christgen M, Kates R, Liedtke C, et al. Prospective comparison of risk assessment tools in early breast cancer (recurrence score, uPA/PAI-1, central grade, and luminal subtypes): final correlation analysis from the phase III WSG plan B trial. In: San Antonio Breast Cancer symposium; 2011. [Abstract] S4–3.Google Scholar
  50. 50.
    Gluz O, Nitz UA, Christgen M, Kates RE, Shak S, Clemens 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;10:2341–9.Google Scholar
  51. 51.
    Glas AM, Floore A, Delahaye LJ, Witteveen AT, Pover RC, Bakx N, et al. Converting a breast cancer microarray signature into a high-throughput diagnostic test. BMC Genomics. 2006;7:278.PubMedPubMedCentralGoogle Scholar
  52. 52.
    Martin M, Prat A, Rodriguez-Lescure A, Caballero R, Ebbert MT, Munarriz B, et al. PAM50 proliferation score as a predictor of weekly paclitaxel benefit in breast cancer. Breast Cancer Res Treat. 2013;138:457–66.PubMedPubMedCentralGoogle Scholar
  53. 53.
    Sapino A, Roepman P, Linn SC, Snel MH, Delahaye LJ, van den Akker J, et al. MammaPrint molecular diagnostics on formalin-fixed, paraffin-embedded tissue. J Mol Diagn. 2014;16:190–7.PubMedGoogle Scholar
  54. 54.
    Buyse M, Loi S, van’t Veer L, Viale G, Delorenzi M, Glas AM, et al. Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J Natl Cancer Inst. 2006;98:1183–92.PubMedGoogle Scholar
  55. 55.
    Mook S, Schmidt MK, Viale G, Pruneri G, Eekhout I, Floore A, 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.PubMedPubMedCentralGoogle Scholar
  56. 56.
    Saghatchian M, Mook S, Pruneri G, Viale G, Glas AM, Guerin S, et al. Additional prognostic value of the 70-gene signature (MammaPrint((R))) among breast cancer patients with 4–9 positive lymph nodes. Breast. 2013;22:682–90.PubMedGoogle Scholar
  57. 57.
    Drukker CA, Bueno-de-Mesquita JM, Retel VP, van Harten WH, van Tinteren H, Wesseling J, et al. A prospective evaluation of a breast cancer prognosis signature in the observational RASTER study. Int J Cancer. 2013;133:929–36.PubMedPubMedCentralGoogle Scholar
  58. 58.
    Knauer M, Mook S, Rutgers EJ, Bender RA, Hauptmann M, van de Vijver MJ, et al. The predictive value of the 70-gene signature for adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat. 2010;120:655–61.PubMedGoogle Scholar
  59. 59.
    Cusumano PG, Generali D, Ciruelos E, Manso L, Ghanem I, Lifrange E, et al. European inter-institutional impact study of MammaPrint. Breast. 2014;23:423–8.PubMedGoogle Scholar
  60. 60.
    Rutgers E, Piccart-Gebhart MJ, Bogaerts J, Delaloge S, Veer LV, Rubio IT, et al. The EORTC 10041/BIG 03–04 MINDACT trial is feasible: results of the pilot phase. Eur J Cancer. 2011;47:2742–9.PubMedGoogle Scholar
  61. 61.
    Cardoso F, van’t Veer LJ, Bogaerts J, Slaets L, Viale G, Delaloge S, et al. 70-gene signature as an aid to treatment decisions in early-stage breast cancer. N Engl J Med. 2016;25:717–29.Google Scholar
  62. 62.
    Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27:1160–7.PubMedPubMedCentralGoogle Scholar
  63. 63.
    Nielsen TO, Parker JS, Leung S, Voduc D, Ebbert M, Vickery T, 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;16:5222–32.PubMedPubMedCentralGoogle Scholar
  64. 64.
    Dowsett M, Sestak I, Lopez-Knowles E, Sidhu K, Dunbier AK, Cowens JW, 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;31:2783–90.PubMedPubMedCentralGoogle Scholar
  65. 65.
    Gnant M, Filipits M, Greil R, Stoeger H, Rudas M, Bago-Horvath Z, et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 Risk of Recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann Oncol. 2014;25:339–45.PubMedPubMedCentralGoogle Scholar
  66. 66.
    Sestak I, Cuzick J, Dowsett M, Lopez-Knowles E, Filipits M, Dubsky P, et al. Prediction of late distant recurrence after 5 years of endocrine treatment: a combined analysis of patients from the Austrian breast and colorectal cancer study group 8 and arimidex, tamoxifen alone or in combination randomized trials using the PAM50 risk of recurrence score. J Clin Oncol. 2015;33:916–22.Google Scholar
  67. 67.
    Chia SK, Bramwell VH, Tu D, Shepherd LE, Jiang S, Vickery T, et al. A 50-gene intrinsic subtype classifier for prognosis and prediction of benefit from adjuvant tamoxifen. Clin Cancer Res. 2012;18:4465–72.PubMedPubMedCentralGoogle Scholar
  68. 68.
    Bastien RR, Rodriguez-Lescure A, Ebbert MT, Prat A, Munarriz B, Rowe L, et al. PAM50 breast cancer subtyping by RT-qPCR and concordance with standard clinical molecular markers. BMC Med Genet. 2012;5:44.Google Scholar
  69. 69.
    Sweeney C, Bernard PS, Factor RE, Kwan ML, Habel LA, Quesenberry CP Jr, et al. Intrinsic subtypes from PAM50 gene expression assay in a population-based breast cancer cohort: differences by age, race, and tumor characteristics. Cancer Epidemiol Biomark Prev. 2014;23:714–24.Google Scholar
  70. 70.
    Caan BJ, Sweeney C, Habel LA, Kwan ML, Kroenke CH, Weltzien EK, et al. Intrinsic subtypes from the PAM50 gene expression assay in a population-based breast cancer survivor cohort: prognostication of short- and long-term outcomes. Cancer Epidemiol Biomark Prev. 2014;23:725–34.Google Scholar
  71. 71.
    Dunbier AK, Anderson H, Ghazoui Z, Salter J, Parker JS, Perou CM, et al. Association between breast cancer subtypes and response to neoadjuvant anastrozole. Steroids. 2011;76:736–40.PubMedGoogle Scholar
  72. 72.
    Cheang MC, Voduc KD, Tu D, Jiang S, Leung S, Chia SK, et al. Responsiveness of intrinsic subtypes to adjuvant anthracycline substitution in the NCIC.CTG MA.5 randomized trial. Clin Cancer Res. 2012;18:2402–12.PubMedPubMedCentralGoogle Scholar
  73. 73.
    Burnell M, Levine MN, Chapman JA, Bramwell V, Gelmon K, Walley B, et al. Cyclophosphamide, epirubicin, and Fluorouracil versus dose-dense epirubicin and cyclophosphamide followed by Paclitaxel versus Doxorubicin and cyclophosphamide followed by Paclitaxel in node-positive or high-risk node-negative breast cancer. J Clin Oncol. 2010;28:77–82.PubMedGoogle Scholar
  74. 74.
    Liu S, Chapman JA, Burnell MJ, Levine MN, Pritchard KI, Whelan TJ, et al. Prognostic and predictive investigation of PAM50 intrinsic subtypes in the NCIC CTG MA.21 phase III chemotherapy trial. Breast Cancer Res Treat. 2015;149:439–48.PubMedGoogle Scholar
  75. 75.
    Krijgsman O, Roepman P, Zwart W, Carroll JS, Tian S, de Snoo FA, et al. A diagnostic gene profile for molecular subtyping of breast cancer associated with treatment response. Breast Cancer Res Treat. 2012;133:37–47.PubMedGoogle Scholar
  76. 76.
    Whitworth P, Stork-Sloots L, de Snoo FA, Richards P, Rotkis M, Beatty J, et al. Chemosensitivity predicted by BluePrint 80-gene functional subtype and MammaPrint in the Prospective Neoadjuvant Breast Registry Symphony Trial (NBRST). Ann Surg Oncol. 2014;21:3261–7.PubMedPubMedCentralGoogle Scholar
  77. 77.
    Filipits M, Rudas M, Jakesz R, Dubsky P, Fitzal F, Singer CF, 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;17:6012–20.PubMedGoogle Scholar
  78. 78.
    Kronenwett R, Bohmann K, Prinzler J, Sinn BV, Haufe F, Roth C, et al. Decentral gene expression analysis: analytical validation of the Endopredict genomic multianalyte breast cancer prognosis test. BMC Cancer. 2012;5:12:456.PubMedGoogle Scholar
  79. 79.
    Dubsky P, Filipits M, Jakesz R, Rudas M, Singer CF, Greil R, et al. EndoPredict improves the prognostic classification derived from common clinical guidelines in ER-positive, HER2-negative early breast cancer. Ann Oncol. 2013;24:640–7.PubMedGoogle Scholar
  80. 80.
    Martin M, Brase JC, Calvo L, Krappmann K, Ruiz-Borrego M, Fisch K, 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;12:R38.Google Scholar
  81. 81.
    Jerevall PL, Ma XJ, Li H, Salunga R, Kesty NC, Erlander MG, Sgroi DC, et al. Prognostic utility of HOXB13:IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial. Br J Cancer. 2011;104:1762–9.PubMedPubMedCentralGoogle Scholar
  82. 82.
    Sgroi DC, Sestak I, Cuzick J, Zhang Y, Schnabel CA, Schroeder B, 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;14:1067–76.PubMedPubMedCentralGoogle Scholar
  83. 83.
    Sgroi DC, Chapman JA, Badovinac-Crnjevic T, Zarella E, Binns S, Zhang Y, et al. Assessment of the prognostic and predictive utility of the Breast Cancer Index (BCI): an NCIC CTG MA.14 study. Breast Cancer Res. 2016;18(1):1.  https://doi.org/10.1186/s13058-015-0660-6.PubMedPubMedCentralGoogle Scholar
  84. 84.
    Sgroi DC, Carney E, Zarrella E, Steffel L, Binns SN, Finkelstein DM, et al. Prediction of late disease recurrence and extended adjuvant letrozole benefit by the HOXB13/IL17BR biomarker. J Natl Cancer Inst. 2013;105:1036–42.PubMedPubMedCentralGoogle Scholar
  85. 85.
    Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J, et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst. 2006;98:262–72.PubMedGoogle Scholar
  86. 86.
    Liedtke C, Hatzis C, Symmans WF, Desmedt C, Haibe-Kains B, Valero V, et al. Genomic grade index is associated with response to chemotherapy in patients with breast cancer. J Clin Oncol. 2009;27:3185–91.PubMedPubMedCentralGoogle Scholar
  87. 87.
    Reyal F, Bollet MA, Caly M, Gentien D, Carpentier S, Peyro-Saint-Paul H, et al. Respective prognostic value of genomic grade and histological proliferation markers in early stage (pN0) breast carcinoma. PLoS One. 2012;7:e35184.PubMedPubMedCentralGoogle Scholar
  88. 88.
    Metzger-Filho O, Michiels S, Bertucci F, Catteau A, Salgado R, Galant C, et al. Genomic grade adds prognostic value in invasive lobular carcinoma. Ann Oncol. 2013;24:377–84.PubMedGoogle Scholar
  89. 89.
    Toussaint J, Sieuwerts AM, Haibe-Kains B, Desmedt C, Rouas G, Harris AL, 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.PubMedPubMedCentralGoogle Scholar
  90. 90.
    Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F, et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet. 2005;365:671–9.PubMedGoogle Scholar
  91. 91.
    Foekens JA, Atkins D, Zhang Y, Sweep FC, Harbeck N, Paradiso A, et al. Multicenter validation of a gene expression-based prognostic signature in lymph node-negative primary breast cancer. J Clin Oncol. 2006;24:1665–71.PubMedGoogle Scholar
  92. 92.
    Desmedt C, Piette F, Loi S, Wang Y, Lallemand F, Haibe-Kains B, et al. 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. 2007;13:3207–14.PubMedGoogle Scholar
  93. 93.
    Zhang Y, Sieuwerts AM, McGreevy M, Casey G, Cufer T, Paradiso A, et al. The 76-gene signature defines high-risk patients that benefit from adjuvant tamoxifen therapy. Breast Cancer Res Treat. 2009;116:303–9.PubMedGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Cagatay Arslan
    • 1
  • Zeki G. Surmeli
    • 2
  • Y. Yavuz Ozisik
    • 3
  1. 1.Department of Internal Medicine and Medical OncologyBahcesehir University Faculty of MedicineIstanbulTurkey
  2. 2.Department of Medical OncologyAnkara Medical Park HospitalAnkaraTurkey
  3. 3.Department of Medical OncologyHacettepe University Cancer InstituteAnkaraTurkey

Personalised recommendations