Advertisement

Breast Cancer Research and Treatment

, Volume 131, Issue 3, pp 827–836 | Cite as

Neoadjuvant chemotherapy in ER+ HER2− breast cancer: response prediction based on immunohistochemical and molecular characteristics

  • E. H. Lips
  • L. Mulder
  • J. J. de Ronde
  • I. A. M. Mandjes
  • A. Vincent
  • M. T. F. D. Vrancken Peeters
  • P. M. Nederlof
  • J. Wesseling
  • S. Rodenhuis
Preclinical study

Abstract

A pathological complete remission (pCR) is rarely achieved by neoadjuvant chemotherapy in estrogen receptor-positive (ER+) HER2-negative (HER2−) tumors. Therefore, its use might be questionable in specific groups of this tumor type. To select which patients benefit and which could be spared neoadjuvant chemotherapy, we tested standard pathology and molecular markers in ER+ HER2− breast tumors. Pretreatment biopsies were available from 211 ER+ HER2− tumors, who had been treated with neoadjuvant chemotherapy (adriamycin/cyclophosphamide). mRNA expression data were available for 132 tumors. We determined progesterone receptor expression (PR), endocrine sensitivity, HER2 expression, histology, proliferation, and molecular subtypes. We correlated these data to chemotherapy response using pCR rates and the previously published neoadjuvant response index (NRI). PR-negative tumors (n = 65, 30.8%) and luminal B type tumors (n = 43, 20.4%) responded significantly better to chemotherapy than other tumors. These associations remained significant in multivariate analysis. However, even in the subgroup of patients with the lowest response rate, comprising tumors that had both a positive-PR expression and the luminal A subtype (n = 58, 44%), the majority of the patients had downstaging because of chemotherapy. For histology (lobular vs. ductal), endocrine sensitivity, and proliferation, no associations with chemotherapy response were observed. Gene expression array analysis resulted in 28 significant genes (FDR < 0.1). PR expression and luminal B status are associated with a better response to neoadjuvant chemotherapy. However, both markers had only weak response predictive power, and it was not possible to identify a subgroup with no or only minimal chemotherapy benefit. Therefore, the decision to refrain from neoadjuvant chemotherapy to ER+ HER2− breast tumors should not be based on predictive markers, but exclusively on estimates of prognosis.

Keywords

Neoadjuvant chemotherapy Predictive factors Molecular subtypes Luminal subtype 

Notes

Acknowledgments

This study was carried out within the framework of CTMM, the Center for Translational Molecular Medicine (www.ctmm.nl), project Breast CARE (030-104).

Conflict of interest

None.

Supplementary material

10549_2011_1488_MOESM1_ESM.doc (184 kb)
Supplementary material 1 (DOC 184 kb)

References

  1. 1.
    Early Breast Cancer Trialists’ Collaborative Group (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(9472):1687–1717CrossRefGoogle Scholar
  2. 2.
    Bergh J, Holmquist M (2001) Who should not receive adjuvant chemotherapy? International databases. J Natl Cancer Inst Monogr 30:103–108PubMedGoogle Scholar
  3. 3.
    Ravdin PM, Siminoff LA, Davis GJ, Mercer MB, Hewlett J, Gerson N, Parker HL (2001) Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 19(4):980–991PubMedGoogle Scholar
  4. 4.
    Katz A, Saad ED, Porter P, Pusztai L (2007) Primary systemic chemotherapy of invasive lobular carcinoma of the breast. Lancet Oncol 8(1):55–62PubMedCrossRefGoogle Scholar
  5. 5.
    Cocquyt VF, Blondeel PN, Depypere HT, Praet MM, Schelfhout VR, Silva OE, Hurley J, Serreyn RF, Daems KK, Van Belle SJ (2003) Different responses to preoperative chemotherapy for invasive lobular and invasive ductal breast carcinoma. Eur J Surg Oncol 29(4):361–367PubMedCrossRefGoogle Scholar
  6. 6.
    Tubiana-Hulin M, Stevens D, Lasry S, Guinebretiere JM, Bouita L, Cohen-Solal C, Cherel P, Rouesse J (2006) Response to neoadjuvant chemotherapy in lobular and ductal breast carcinomas: a retrospective study on 860 patients from one institution. Ann Oncol 17(8):1228–1233PubMedCrossRefGoogle Scholar
  7. 7.
    Goldhirsch A, Wood WC, Gelber RD, Coates AS, Thurlimann B, Senn HJ (2007) Progress and promise: highlights of the international expert consensus on the primary therapy of early breast cancer 2007. Ann Oncol 18(7):1133–1144PubMedCrossRefGoogle Scholar
  8. 8.
    Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A, Deng S, Johnsen H, Pesich R, Geisler S, Demeter J, Perou CM, Lonning PE, Brown PO, Borresen-Dale AL, Botstein D (2003) Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 100(14):8418–8423PubMedCrossRefGoogle Scholar
  9. 9.
    Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, Lonning PE, Borresen-Dale AL, Brown PO, Botstein D (2000) Molecular portraits of human breast tumours. Nature 406(6797):747–752PubMedCrossRefGoogle Scholar
  10. 10.
    Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, Davies S, Fauron C, He X, Hu Z, Quackenbush JF, Stijleman IJ, Palazzo J, Marron JS, Nobel AB, Mardis E, Nielsen TO, Ellis MJ, Perou CM, Bernard PS (2009) Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 27(8):1160–1167PubMedCrossRefGoogle Scholar
  11. 11.
    Colleoni M, Bagnardi V, Rotmensz N, Viale G, Mastropasqua M, Veronesi P, Cardillo A, Torrisi R, Luini A, Goldhirsch A (2010) A nomogram based on the expression of Ki-67, steroid hormone receptors status and number of chemotherapy courses to predict pathological complete remission after preoperative chemotherapy for breast cancer. Eur J Cancer 46(12):2216–2224PubMedCrossRefGoogle Scholar
  12. 12.
    Straver ME, Glas AM, Hannemann J, Wesseling J, van de Vijver MJ, Rutgers EJ, Vrancken Peeters MJ, van Tinteren H, Van’t Veer LJ, Rodenhuis S (2010) The 70-gene signature as a response predictor for neoadjuvant chemotherapy in breast cancer. Breast Cancer Res Treat 119(3):551–558PubMedCrossRefGoogle Scholar
  13. 13.
    Paik S, Tang G, Shak S, Kim C, Baker J, Kim W, Cronin M, Baehner FL, Watson D, Bryant J, Costantino JP, Geyer CE Jr, Wickerham DL, Wolmark N (2006) Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol 24(23):3726–3734PubMedCrossRefGoogle Scholar
  14. 14.
    Thurlimann B, Price KN, Gelber RD, Holmberg SB, Crivellari D, Colleoni M, Collins J, Forbes JF, Castiglione-Gertsch M, Coates AS, Goldhirsch A (2009) Is chemotherapy necessary for premenopausal women with lower-risk node-positive, endocrine responsive breast cancer? 10-year update of International Breast Cancer Study Group Trial 11–93. Breast Cancer Res Treat 113(1):137–144PubMedCrossRefGoogle Scholar
  15. 15.
    Colleoni M, Viale G, Goldhirsch A (2009) Lessons on responsiveness to adjuvant systemic therapies learned from the neoadjuvant setting. Breast 18(3):S137–S140PubMedCrossRefGoogle Scholar
  16. 16.
    Blows FM, Driver KE, Schmidt MK, Broeks A, van Leeuwen FE, Wesseling J, Cheang MC, Gelmon K, Nielsen TO, Blomqvist C, Heikkila P, Heikkinen T, Nevanlinna H, Akslen LA, Begin LR, Foulkes WD, Couch FJ, Wang X, Cafourek V, Olson JE, Baglietto L, Giles GG, Severi G, McLean CA, Southey MC, Rakha E, Green AR, Ellis IO, Sherman ME, Lissowska J, Anderson WF, Cox A, Cross SS, Reed MW, Provenzano E, Dawson SJ, Dunning AM, Humphreys M, Easton DF, Garcia-Closas M, Caldas C, Pharoah PD, Huntsman D (2010) 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 7(5):e1000279PubMedCrossRefGoogle Scholar
  17. 17.
    Rodenhuis S, Mandjes IA, Wesseling J, van de Vijver MJ, Peeters MJ, Sonke GS, Linn SC (2010) A simple system for grading the response of breast cancer to neoadjuvant chemotherapy. Ann Oncol 21(3):481–487PubMedCrossRefGoogle Scholar
  18. 18.
    Loo CE, Teertstra HJ, Rodenhuis S, van de Vijver MJ, Hannemann J, Muller SH, Peeters MJ, Gilhuijs KG (2008) Dynamic contrast-enhanced MRI for prediction of breast cancer response to neoadjuvant chemotherapy: initial results. AJR Am J Roentgenol 191(5):1331–1338PubMedCrossRefGoogle Scholar
  19. 19.
    de Ronde JJ, Hannemann J, Halfwerk H, Mulder L, Straver ME, Vrancken Peeters MJ, Wesseling J, van de Vijver M, Wessels LF, Rodenhuis S (2010) Concordance of clinical and molecular breast cancer subtyping in the context of preoperative chemotherapy response. Breast Cancer Res Treat 119(1):119–126PubMedCrossRefGoogle Scholar
  20. 20.
    Colleoni M, Bagnardi V, Rotmensz N, Gelber RD, Viale G, Pruneri G, Veronesi P, Torrisi R, Cardillo A, Montagna E, Campagnoli E, Luini A, Intra M, Galimberti V, Scarano E, Peruzzotti G, Goldhirsch A (2009) Increasing steroid hormone receptors expression defines breast cancer subtypes non responsive to preoperative chemotherapy. Breast Cancer Res Treat 116(2):359–369PubMedCrossRefGoogle Scholar
  21. 21.
    Hannemann J, Oosterkamp HM, Bosch CA, Velds A, Wessels LF, Loo C, Rutgers EJ, Rodenhuis S, van de Vijver MJ (2005) Changes in gene expression associated with response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol 23(15):3331–3342PubMedCrossRefGoogle Scholar
  22. 22.
    Tusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 98(9):5116–5121PubMedCrossRefGoogle Scholar
  23. 23.
    Goldstein NS, Decker D, Severson D, Schell S, Vicini F, Margolis J, Dekhne NS (2007) Molecular classification system identifies invasive breast carcinoma patients who are most likely and those who are least likely to achieve a complete pathologic response after neoadjuvant chemotherapy. Cancer 110(8):1687–1696PubMedCrossRefGoogle Scholar
  24. 24.
    Rouzier R, Perou CM, Symmans WF, Ibrahim N, Cristofanilli M, Anderson K, Hess KR, Stec J, Ayers M, Wagner P, Morandi P, Fan C, Rabiul I, Ross JS, Hortobagyi GN, Pusztai L (2005) Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin Cancer Res 11(16):5678–5685PubMedCrossRefGoogle Scholar
  25. 25.
    Faneyte IF, Schrama JG, Peterse JL, Remijnse PL, Rodenhuis S, van de Vijver MJ (2003) Breast cancer response to neoadjuvant chemotherapy: predictive markers and relation with outcome. Br J Cancer 88(3):406–412PubMedCrossRefGoogle Scholar
  26. 26.
    Rastogi P, Anderson SJ, Bear HD, Geyer CE, Kahlenberg MS, Robidoux A, Margolese RG, Hoehn JL, Vogel VG, Dakhil SR, Tamkus D, King KM, Pajon ER, Wright MJ, Robert J, Paik S, Mamounas EP, Wolmark N (2008) Preoperative chemotherapy: updates of National Surgical Adjuvant Breast and Bowel Project Protocols B-18 and B-27. J Clin Oncol 26(5):778–785PubMedCrossRefGoogle Scholar
  27. 27.
    van der Hage JA, van de Velde CJ, Julien JP, Tubiana-Hulin M, Vandervelden C, Duchateau L (2001) Preoperative chemotherapy in primary operable breast cancer: results from the European Organization for Research and Treatment of Cancer trial 10902. J Clin Oncol 19(22):4224–4237PubMedGoogle Scholar
  28. 28.
    Symmans WF, Peintinger F, Hatzis C, Rajan R, Kuerer H, Valero V, Assad L, Poniecka A, Hennessy B, Green M, Buzdar AU, Singletary SE, Hortobagyi GN, Pusztai L (2007) Measurement of residual breast cancer burden to predict survival after neoadjuvant chemotherapy. J Clin Oncol 25(28):4414–4422PubMedCrossRefGoogle Scholar
  29. 29.
    Straver ME, Rutgers EJ, Rodenhuis S, Linn SC, Loo CE, Wesseling J, Russell NS, Oldenburg HS, Antonini N, Vrancken Peeters MT (2010) The relevance of breast cancer subtypes in the outcome of neoadjuvant chemotherapy. Ann Surg Oncol 17(9):2411–2418PubMedCrossRefGoogle Scholar
  30. 30.
    Cardoso F, Van’t Veer L, Rutgers E, Loi S, Mook S, Piccart-Gebhart MJ (2008) Clinical application of the 70-gene profile: the MINDACT trial. J Clin Oncol 26(5):729–735PubMedCrossRefGoogle Scholar
  31. 31.
    Sparano JA, Paik S (2008) Development of the 21-gene assay and its application in clinical practice and clinical trials. J Clin Oncol 26(5):721–728PubMedCrossRefGoogle Scholar
  32. 32.
    Bonnefoi H, Potti A, Delorenzi M, Mauriac L, Campone M, Tubiana-Hulin M, Petit T, Rouanet P, Jassem J, Blot E, Becette V, Farmer P, Andre S, Acharya CR, Mukherjee S, Cameron D, Bergh J, Nevins JR, Iggo RD (2011) Retraction–Validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00–01 clinical trial. Lancet Oncol 12(2):116PubMedCrossRefGoogle Scholar
  33. 33.
    Potti A, Dressman HK, Bild A, Riedel RF, Chan G, Sayer R, Cragun J, Cottrill H, Kelley MJ, Petersen R, Harpole D, Marks J, Berchuck A, Ginsburg GS, Febbo P, Lancaster J, Nevins JR (2011) Retraction: genomic signatures to guide the use of chemotherapeutics. Nat Med 17(1):135PubMedCrossRefGoogle Scholar
  34. 34.
    Borst P, Wessels L (2010) Do predictive signatures really predict response to cancer chemotherapy? Cell Cycle 9(24):4836–4840PubMedCrossRefGoogle Scholar
  35. 35.
    Popovici V, Chen W, Gallas BG, Hatzis C, Shi W, Samuelson FW, Nikolsky Y, Tsyganova M, Ishkin A, Nikolskaya T, Hess KR, Valero V, Booser D, Delorenzi M, Hortobagyi GN, Shi L, Symmans WF, Pusztai L (2010) Effect of training-sample size and classification difficulty on the accuracy of genomic predictors. Breast Cancer Res 12(1):R5PubMedCrossRefGoogle Scholar
  36. 36.
    Kim C, Paik S (2010) Gene-expression-based prognostic assays for breast cancer. Nat Rev Clin Oncol 7(6):340–347PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  • E. H. Lips
    • 1
    • 2
  • L. Mulder
    • 1
    • 2
  • J. J. de Ronde
    • 1
    • 3
  • I. A. M. Mandjes
    • 4
  • A. Vincent
    • 5
  • M. T. F. D. Vrancken Peeters
    • 6
  • P. M. Nederlof
    • 2
  • J. Wesseling
    • 2
  • S. Rodenhuis
    • 7
  1. 1.Departments of Experimental TherapyThe Netherlands Cancer InstituteAmsterdamThe Netherlands
  2. 2.Departments of PathologyThe Netherlands Cancer InstituteAmsterdamThe Netherlands
  3. 3.Departments of Bioinformatics and StatisticsThe Netherlands Cancer InstituteAmsterdamThe Netherlands
  4. 4.Data CenterThe Netherlands Cancer InstituteAmsterdamThe Netherlands
  5. 5.Departments of BiometricsThe Netherlands Cancer InstituteAmsterdamThe Netherlands
  6. 6.Departments of SurgeryThe Netherlands Cancer InstituteAmsterdamThe Netherlands
  7. 7.Department of Medical OncologyThe Netherlands Cancer InstituteAmsterdamThe Netherlands

Personalised recommendations