Skip to main content

Advertisement

SpringerLink
Log in

Expression of cell cycle markers is predictive of the response to primary systemic therapy of locally advanced breast cancer

  • Original Article
  • Published:
Virchows Archiv Aims and scope Submit manuscript

Abstract

We aimed to analyze to what extent expression of four cell cycle regulation markers—minichromosome maintenance protein (MCM2), Ki-67, cyclin A, and phosphohistone-H3 (PHH3)—predict response to primary systemic therapy in terms of pathological complete remission (pCR). In search of an accurate and reproducible scoring method, we compared computer-assisted (CA) and routine visual assessment (VA) of immunoreactivity. We included 57 patients with breast cancer in the study. The cell cycle markers were detected using immunohistochemistry on pre-therapy core biopsy samples. Parallel CA (validated by manual labeling) and standard VA were performed and compared for diagnostic agreement and predictive value for pCR. CA and VA results were dichotomized based on receiver operating characteristic analysis defined optimal cut-off values. “High” was defined by staining scores above the optimal cut-off, while “low” had staining scores below the optimal cut-off. The CA method resulted in significantly lower values for Ki-67 and MCM2 compared to VA (mean difference, −3.939 and −4.323). Diagnostic agreement was highest for cyclin A and PHH3 (−0.586 and −0.666, respectively). Regardless of the method (CA/VA) used, all tested markers were predictive of pCR. Optimal cut-off-based dichotomization improved diagnostic agreement between the CA and VA methods for every marker, in particular for MCM2 (κ = 1, p < 0.000). Cyclin A displayed excellent agreement (κ = 0.925; p < 0.000), while Ki-67 and PHH3 showed good agreement (κ = 0.789, p < 0.000 and κ = 0.794, p < 0.000, respectively). We found all cell cycle markers (Ki-67, MCM2, cyclin A, and PHH3) predictive of pCR. Diagnostic agreement between CA and VA was better at lower staining scores but improved after optimal cut-off-based dichotomization.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Goldhirsch A, Wood WC, Gelber RD, Coates AS, Thurlimann B, Senn HJ (2007) 10th St. Gallen conference: progress and promise: highlights of the international expert consensus on the primary therapy of early breast cancer 2007. Ann Oncol 18(7):1133–1144. doi:10.1093/annonc/mdm271

    Article  CAS  PubMed  Google Scholar 

  2. Kaufmann M, von Minckwitz G, Bear HD, Buzdar A, McGale P, Bonnefoi H, Colleoni M, Denkert C, Eiermann W, Jackesz R, Makris A, Miller W, Pierga JY, Semiglazov V, Schneeweiss A, Souchon R, Stearns V, Untch M, Loibl S (2007) Recommendations from an international expert panel on the use of neoadjuvant (primary) systemic treatment of operable breast cancer: new perspectives 2006. Ann Oncol 18(12):1927–1934. doi:10.1093/annonc/mdm201

    Article  CAS  PubMed  Google Scholar 

  3. Wolmark N, Wang J, Mamounas E, Bryant J, Fisher B (2001) Preoperative chemotherapy in patients with operable breast cancer: nine-year results from National Surgical Adjuvant Breast and Bowel Project B-18. J Natl Cancer Inst Monogr 2001(30):96–102

    Article  Google Scholar 

  4. Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, Bonnefoi H, Cameron D, Gianni L, Valagussa P, Swain SM, Prowell T, Loibl S, Wickerham DL, Bogaerts J, Baselga J, Perou C, Blumenthal G, Blohmer J, Mamounas EP, Bergh J, Semiglazov V, Justice R, Eidtmann H, Paik S, Piccart M, Sridhara R, Fasching PA, Slaets L, Tang S, Gerber B, Geyer CE Jr., Pazdur R, Ditsch N, Rastogi P, Eiermann W, von Minckwitz G (2014) Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet 384(9938):164–172. doi:10.1016/S0140-6736(13)62422-8

    Article  PubMed  Google Scholar 

  5. Machiavelli MR, Romero AO, Perez JE, Lacava JA, Dominguez ME, Rodriguez R, Barbieri MR, Romero Acuna LA, Romero Acuna JM, Langhi MJ, Amato S, Ortiz EH, Vallejo CT, Leone BA (1998) Prognostic significance of pathological response of primary tumor and metastatic axillary lymph nodes after neoadjuvant chemotherapy for locally advanced breast carcinoma. Cancer J Sci Am 4(2):125–131

    CAS  PubMed  Google Scholar 

  6. Colozza M, Azambuja E, Cardoso F, Sotiriou C, Larsimont D, Piccart MJ (2005) Proliferative markers as prognostic and predictive tools in early breast cancer: where are we now? Ann Oncol 16(11):1723–1739. doi:10.1093/annonc/mdi352

    Article  CAS  PubMed  Google Scholar 

  7. Endl E, Gerdes J (2000) The Ki-67 protein: fascinating forms and an unknown function. Exp Cell Res 257(2):231–237. doi:10.1006/excr.2000.4888

    Article  CAS  PubMed  Google Scholar 

  8. Nishimura R, Osako T, Okumura Y, Hayashi M, Arima N (2010) Clinical significance of Ki-67 in neoadjuvant chemotherapy for primary breast cancer as a predictor for chemosensitivity and for prognosis. Breast Cancer 17(4):269–275. doi:10.1007/s12282-009-0161-5

    Article  PubMed  Google Scholar 

  9. Bottini A, Berruti A, Bersiga A, Brizzi MP, Bruzzi P, Aguggini S, Brunelli A, Bolsi G, Allevi G, Generali D, Betri E, Bertoli G, Alquati P, Dogliotti L (2001) Relationship between tumour shrinkage and reduction in Ki67 expression after primary chemotherapy in human breast cancer. Br J Cancer 85(8):1106–1112. doi:10.1054/bjoc.2001.2048

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. de Azambuja E, Cardoso F, de Castro G Jr., Colozza M, Mano MS, Durbecq V, Sotiriou C, Larsimont D, Piccart-Gebhart MJ, Paesmans M (2007) Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12,155 patients. Br J Cancer 96(10):1504–1513. doi:10.1038/sj.bjc.6603756

    Article  PubMed  PubMed Central  Google Scholar 

  11. Fasching PA, Heusinger K, Haeberle L, Niklos M, Hein A, Bayer CM, Rauh C, Schulz-Wendtland R, Bani MR, Schrauder M, Kahmann L, Lux MP, Strehl JD, Hartmann A, Dimmler A, Beckmann MW, Wachter DL (2011) Ki67, chemotherapy response, and prognosis in breast cancer patients receiving neoadjuvant treatment. BMC Cancer 11:486. doi:10.1186/1471-2407-11-486

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Inwald EC, Klinkhammer-Schalke M, Hofstadter F, Zeman F, Koller M, Gerstenhauer M, Ortmann O (2013) Ki-67 is a prognostic parameter in breast cancer patients: results of a large population-based cohort of a cancer registry. Breast Cancer Res Treat 139(2):539–552. doi:10.1007/s10549-013-2560-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Balmativola D, Marchio C, Maule M, Chiusa L, Annaratone L, Maletta F, Montemurro F, Kulka J, Figueiredo P, Varga Z, Liepniece-Karele I, Cserni G, Arkoumani E, Amendoeira I, Callagy G, Reiner-Concin A, Cordoba A, Bianchi S, Decker T, Glaser D, Focke C, van Diest P, Grabau D, Lips E, Wesseling J, Arisio R, Medico E, Wells C, Sapino A (2014) Pathological non-response to chemotherapy in a neoadjuvant setting of breast cancer: an inter-institutional study. Breast Cancer Res Treat 148(3):511–523. doi:10.1007/s10549-014-3192-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Polley MY, Leung SC, McShane LM, Gao D, Hugh JC, Mastropasqua MG, Viale G, Zabaglo LA, Penault-Llorca F, Bartlett JM, Gown AM, Symmans WF, Piper T, Mehl E, Enos RA, Hayes DF, Dowsett M, Nielsen TO, International Ki67 in Breast Cancer Working Group of the Breast International Group, North American Breast Cancer Group (2013) An international Ki67 reproducibility study. J Natl Cancer Inst 105(24):1897–1906. doi:10.1093/jnci/djt306

    Article  PubMed  PubMed Central  Google Scholar 

  15. Loddo M, Kingsbury SR, Rashid M, Proctor I, Holt C, Young J, El-Sheikh S, Falzon M, Eward KL, Prevost T, Sainsbury R, Stoeber K, Williams GH (2009) Cell-cycle-phase progression analysis identifies unique phenotypes of major prognostic and predictive significance in breast cancer. Br J Cancer 100(6):959–970. doi:10.1038/sj.bjc.6604924

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Shetty A, Loddo M, Fanshawe T, Prevost AT, Sainsbury R, Williams GH, Stoeber K (2005) DNA replication licensing and cell cycle kinetics of normal and neoplastic breast. Br J Cancer 93(11):1295–1300. doi:10.1038/sj.bjc.6602829

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Tokes AM, Szasz AM, Geszti F, Lukacs LV, Kenessey I, Turanyi E, Meggyeshazi N, Molnar IA, Fillinger J, Soltesz I, Balint K, Hanzely Z, Arato G, Szendroi M, Kulka J (2015) Expression of proliferation markers Ki67, cyclin A, geminin and aurora-kinase A in primary breast carcinomas and corresponding distant metastases. J Clin Pathol 68(4):274–282. doi:10.1136/jclinpath-2014-202607

    Article  PubMed  Google Scholar 

  18. Whitfield ML, George LK, Grant GD, Perou CM (2006) Common markers of proliferation. Nat Rev Cancer 6(2):99–106. doi:10.1038/nrc1802

    Article  CAS  PubMed  Google Scholar 

  19. Williams GH, Stoeber K (2012) The cell cycle and cancer. J Pathol 226(2):352–364. doi:10.1002/path.3022

    Article  CAS  PubMed  Google Scholar 

  20. Lei M (2005) The MCM complex: its role in DNA replication and implications for cancer therapy. Curr Cancer Drug Targets 5(5):365–380. doi:10.2174/1568009054629654

    Article  CAS  PubMed  Google Scholar 

  21. Tachibana KE, Gonzalez MA, Coleman N (2005) Cell-cycle-dependent regulation of DNA replication and its relevance to cancer pathology. J Pathol 205(2):123–129. doi:10.1002/path.1708

    Article  CAS  PubMed  Google Scholar 

  22. Gonzalez MA, Tachibana KE, Laskey RA, Coleman N (2005) Control of DNA replication and its potential clinical exploitation. Nat Rev Cancer 5(2):135–141. doi:10.1038/nrc1548

    Article  CAS  PubMed  Google Scholar 

  23. Vermeulen K, Van Bockstaele DR, Berneman ZN (2003) The cell cycle: a review of regulation, deregulation and therapeutic targets in cancer. Cell Prolif 36(3):131–149. doi:10.1046/j.1365-2184.2003.00266.x

    Article  CAS  PubMed  Google Scholar 

  24. Ahlin C, Aaltonen K, Amini RM, Nevanlinna H, Fjallskog ML, Blomqvist C (2007) Ki67 and cyclin A as prognostic factors in early breast cancer. What are the optimal cut-off values? Histopathology 51(4):491–498. doi:10.1111/j.1365-2559.2007.02798.x

    Article  CAS  PubMed  Google Scholar 

  25. Ahlin C, Zhou W, Holmqvist M, Holmberg L, Nilsson C, Jirstrom K, Blomqvist C, Amini RM, Fjallskog ML (2009) Cyclin A is a proliferative marker with good prognostic value in node-negative breast cancer. Cancer Epidemiol Biomark Prev 18(9):2501–2506. doi:10.1158/1055-9965.EPI-09-0169

    Article  CAS  Google Scholar 

  26. Strand C, Ahlin C, Bendahl PO, Fjallskog ML, Hedenfalk I, Malmstrom P, Ferno M (2012) Combination of the proliferation marker cyclin A, histological grade, and estrogen receptor status in a new variable with high prognostic impact in breast cancer. Breast Cancer Res Treat 131(1):33–40. doi:10.1007/s10549-011-1386-5

    Article  CAS  PubMed  Google Scholar 

  27. Poikonen P, Sjostrom J, Amini RM, Villman K, Ahlgren J, Blomqvist C (2005) Cyclin A as a marker for prognosis and chemotherapy response in advanced breast cancer. Br J Cancer 93(5):515–519. doi:10.1038/sj.bjc.6602735

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Bossard C, Jarry A, Colombeix C, Bach-Ngohou K, Moreau A, Loussouarn D, Mosnier JF, Laboisse CL (2006) Phosphohistone H3 labelling for histoprognostic grading of breast adenocarcinomas and computer-assisted determination of mitotic index. J Clin Pathol 59(7):706–710. doi:10.1136/jcp.2005.030452

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Skaland I, Janssen EA, Gudlaugsson E, Hui Ru Guo L, Baak JP (2009) The prognostic value of the proliferation marker phosphohistone H3 (PPH3) in luminal, basal-like and triple negative phenotype invasive lymph node-negative breast cancer. Cell Oncol 31(4):261–271. doi:10.3233/CLO-2009-0464

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Skaland I, Janssen EA, Gudlaugsson E, Klos J, Kjellevold KH, Soiland H, Baak JP (2009) Validating the prognostic value of proliferation measured by Phosphohistone H3 (PPH3) in invasive lymph node-negative breast cancer patients less than 71 years of age. Breast Cancer Res Treat 114(1):39–45. doi:10.1007/s10549-008-9980-x

    Article  CAS  PubMed  Google Scholar 

  31. Baak JP, Gudlaugsson E, Skaland I, Guo LH, Klos J, Lende TH, Soiland H, Janssen EA, Zur Hausen A (2009) Proliferation is the strongest prognosticator in node-negative breast cancer: significance, error sources, alternatives and comparison with molecular prognostic markers. Breast Cancer Res Treat 115(2):241–254. doi:10.1007/s10549-008-0126-y

    Article  CAS  PubMed  Google Scholar 

  32. Laurinavicius A, Laurinaviciene A, Dasevicius D, Elie N, Plancoulaine B, Bor C, Herlin P (2012) Digital image analysis in pathology: benefits and obligation. Anal Cell Pathol 35(2):75–78. doi:10.3233/ACP-2011-0033

    Article  Google Scholar 

  33. Krenacs T, Zsakovics I, Diczhazi C, Ficsor L, Varga VS, Molnar B (2009) The potential of digital microscopy in breast pathology. Pathol Oncol Res 15(1):55–58. doi:10.1007/s12253-008-9087-z

    Article  CAS  PubMed  Google Scholar 

  34. Laurinavicius A, Plancoulaine B, Laurinaviciene A, Herlin P, Meskauskas R, Baltrusaityte I, Besusparis J, Dasevicius D, Elie N, Iqbal Y, Bor C (2014) A methodology to ensure and improve accuracy of Ki67 labelling index estimation by automated digital image analysis in breast cancer tissue. Breast Cancer Res 16(2):R35. doi:10.1186/bcr3639

    Article  PubMed  PubMed Central  Google Scholar 

  35. Plancoulaine B, Laurinaviciene A, Meskauskas R, Baltrusaityte I, Besusparis J, Herlin P, Laurinavicius A (2014) Digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control. Diagn Pathol 9(Suppl 1):S8. doi:10.1186/1746-1596-9-S1-S8

    Article  PubMed  PubMed Central  Google Scholar 

  36. Lang I, Kahan Z, Pinter T, Dank M, Boer K, Pajkos G, Faluhelyi Z, Piko B, Eckhardt S, Horvath Z (2010) Pharmaceutical therapy of breast cancer. Magy Onkol 54(3):237–254. doi:10.1556/MOnkol.54.2010.3.5

    Article  PubMed  Google Scholar 

  37. Pinder SE, Provenzano E, Earl H, Ellis IO (2007) Laboratory handling and histology reporting of breast specimens from patients who have received neoadjuvant chemotherapy. Histopathology 50(4):409–417. doi:10.1111/j.1365-2559.2006.02419.x

    Article  CAS  PubMed  Google Scholar 

  38. Jones RL, Lakhani SR, Ring AE, Ashley S, Walsh G, Smith IE (2006) Pathological complete response and residual DCIS following neoadjuvant chemotherapy for breast carcinoma. Br J Cancer 94(3):358–362. doi:10.1038/sj.bjc.6602950

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Kiszner G, Wichmann B, Nemeth IB, Varga E, Meggyeshazi N, Teleki I, Balla P, Maros ME, Penksza K, Krenacs T (2014) Cell cycle analysis can differentiate thin melanomas from dysplastic nevi and reveals accelerated replication in thick melanomas. Virchows Arch 464(5):603–612. doi:10.1007/s00428-014-1570-1

    Article  CAS  PubMed  Google Scholar 

  40. Dowsett M, Nielsen TO, A'Hern R, Bartlett J, Coombes RC, Cuzick J, Ellis M, Henry NL, Hugh JC, Lively T, McShane L, Paik S, Penault-Llorca F, Prudkin L, Regan M, Salter J, Sotiriou C, Smith IE, Viale G, Zujewski JA, Hayes DF, International Ki-67 in Breast Cancer Working Group (2011) Assessment of Ki67 in breast cancer: recommendations from the International Ki67 in Breast Cancer Working Group. J Natl Cancer Inst 103(22):1656–1664. doi:10.1093/jnci/djr393

  41. Pathmanathan N, Balleine RL (2013) Ki67 and proliferation in breast cancer. J Clin Pathol 66(6):512–516. doi:10.1136/jclinpath-2012-201085

    Article  CAS  PubMed  Google Scholar 

  42. Ali HR, Dawson SJ, Blows FM, Provenzano E, Pharoah PD, Caldas C (2012) Aurora kinase A outperforms Ki67 as a prognostic marker in ER-positive breast cancer. Br J Cancer 106(11):1798–1806. doi:10.1038/bjc.2012.167

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Wienert S, Heim D, Saeger K, Stenzinger A, Beil M, Hufnagl P, Dietel M, Denkert C, Klauschen F (2012) Detection and segmentation of cell nuclei in virtual microscopy images: a minimum-model approach. Sci Rep 2:503. doi:10.1038/srep00503

    Article  PubMed  PubMed Central  Google Scholar 

  44. Powers, David MW (2011) Evaluation: from precision, recall and F-score to ROC, informedness, markedness & correlation. J Mach Learn Technol 2(1):37–63

    Google Scholar 

  45. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1(8476):307–310

    Article  CAS  PubMed  Google Scholar 

  46. Bland JM, Altman DG (2003) Applying the right statistics: analyses of measurement studies. Ultrasound Obstet Gynecol 22(1):85–93. doi:10.1002/uog.122

    Article  CAS  PubMed  Google Scholar 

  47. Bland JM, Altman DG (1995) Comparing methods of measurement: why plotting difference against standard method is misleading. Lancet 346(8982):1085–1087

    Article  CAS  PubMed  Google Scholar 

  48. Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 39(4):561–577

    CAS  PubMed  Google Scholar 

  49. Faraggi D (2000) The effect of random measurement error on receiver operating characteristic (ROC) curves. Stat Med 19(1):61–70. doi:10.1002/(SICI)1097-0258(20000115)19:1<61::AID-SIM297>3.0.CO

    Article  CAS  PubMed  Google Scholar 

  50. Schisterman EF, Perkins NJ, Liu A, Bondell H (2005) Optimal cut-point and its corresponding Youden Index to discriminate individuals using pooled blood samples. Epidemiology 16:73–78. doi:10.1097/01.ede.0000147512.81966.ba

    Article  PubMed  Google Scholar 

  51. Ludbrook J (2002) Statistical techniques for comparing measurers and methods of measurement: a critical review. Clin Exp Pharmacol Physiol 29(7):527–536. doi:10.1046/j.1440-1681.2002.03686.x

    Article  CAS  PubMed  Google Scholar 

  52. Fasanella S, Leonardi E, Cantaloni C, Eccher C, Bazzanella I, Aldovini D, Bragantini E, Morelli L, Cuorvo LV, Ferro A, Gasperetti F, Berlanda G, Dalla Palma P, Barbareschi M (2011) Proliferative activity in human breast cancer: Ki-67 automated evaluation and the influence of different Ki-67 equivalent antibodies. Diagn Pathol 6(Suppl 1):S7. doi:10.1186/1746-1596-6-S1-S7

    Article  PubMed  PubMed Central  Google Scholar 

  53. Konsti J, Lundin M, Joensuu H, Lehtimaki T, Sihto H, Holli K, Turpeenniemi-Hujanen T, Kataja V, Sailas L, Isola J, Lundin J (2011) Development and evaluation of a virtual microscopy application for automated assessment of Ki-67 expression in breast cancer. BMC Clin Pathol 11:3. doi:10.1186/1472-6890-11-3

    Article  PubMed  PubMed Central  Google Scholar 

  54. Mohammed ZM, McMillan DC, Elsberger B, Going JJ, Orange C, Mallon E, Doughty JC, Edwards J (2012) Comparison of visual and automated assessment of Ki-67 proliferative activity and their impact on outcome in primary operable invasive ductal breast cancer. Br J Cancer 106(2):383–388. doi:10.1038/bjc.2011.569

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Klauschen F, Wienert S, Schmitt W, Loibl S, Gerber B, Blohmer JU, Huober J, Ruediger T, Erbstoesser E, Mehta K, Lederer B, Dietel M, Denkert C, von Minckwitz G (2014) Standardized Ki67 diagnostics using automated scoring—clinical validation in the GeparTrio breast cancer study. Clin Cancer Res. doi:10.1158/1078-0432.CCR-14-1283. Published OnlineFirst Dec 11, 2014

    PubMed  Google Scholar 

  56. Gudlaugsson E, Skaland I, Janssen EA, Smaaland R, Shao Z, Malpica A, Voorhorst F, Baak JP (2012) Comparison of the effect of different techniques for measurement of Ki67 proliferation on reproducibility and prognosis prediction accuracy in breast cancer. Histopathology 61(6):1134–1144. doi:10.1111/j.1365-2559.2012.04329.x

    Article  PubMed  Google Scholar 

  57. Voros A, Csorgo E, Kovari B, Lazar P, Kelemen G, Rusz O, Nyari T, Cserni G (2015) Different methods of pretreatment Ki-67 labeling index evaluation in core biopsies of breast cancer patients treated with neoadjuvant chemotherapy and their relation to response to therapy. Pathol Oncol Res 21(1):147–155. doi:10.1007/s12253-014-9800-z

    Article  CAS  PubMed  Google Scholar 

  58. Zabaglo L, Salter J, Anderson H, Quinn E, Hills M, Detre S, A'Hern R, Dowsett M (2010) Comparative validation of the SP6 antibody to Ki67 in breast cancer. J Clin Pathol 63(9):800–804. doi:10.1136/jcp.2010.077578

    Article  PubMed  Google Scholar 

  59. Romero Q, Bendahl PO, Ferno M, Grabau D, Borgquist S (2014) A novel model for Ki67 assessment in breast cancer. Diagn Pathol 9:118. doi:10.1186/1746-1596-9-118

    Article  PubMed  PubMed Central  Google Scholar 

  60. Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thurlimann B, Senn HJ, Panel members (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 2013. Ann Oncol 24(9):2206–2223. doi:10.1093/annonc/mdt303

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. MacGrogan G, Mauriac L, Durand M, Bonichon F, Trojani M, de Mascarel I, Coindre JM (1996) Primary chemotherapy in breast invasive carcinoma: predictive value of the immunohistochemical detection of hormonal receptors, p53, c-erbB-2, MiB1, pS2 and GST pi. Br J Cancer 74(9):1458–1465

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

The whole research group expresses its gratitude for the language editorial support given by Elvira Rigóné Kálé (Semmelweis University, 2nd Department of Pathology). We thank the assistance of Enikő Grineusz in the collection of the selected paraffin-embedded tissue samples and we also thank Erzsébet Azumahné for her invaluable technical help in cutting the sections.

Author information

Authors and Affiliations

  1. 1st Department of Internal Medicine, Oncological Division, Semmelweis University, Tömő utca 25-29, 4th floor, Budapest, 1083, Hungary

    Tímea Tőkés, Gyöngyvér Szentmártoni & Magdolna Dank

  2. MTA-SE Tumor Progression Research Group, 2nd Department of Pahtology, Semmelweis University, Üllői út 93, Budapest, 1091, Hungary

    Anna-Mária Tőkés & Tibor Krenács

  3. 2nd Department of Pathology, Semmelweis University, Üllői út 93, Budapest, 1091, Hungary

    Anna-Mária Tőkés, Lilla Madaras & Janina Kulka

  4. 1st Department of Pathology and Experimental Cancer Research, Semmelweis University, Üllői út 26, Budapest, 1085, Hungary

    Gergő Kiszner & Tibor Krenács

Authors
  1. Tímea Tőkés
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anna-Mária Tőkés
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gyöngyvér Szentmártoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gergő Kiszner
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lilla Madaras
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Janina Kulka
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Tibor Krenács
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Magdolna Dank
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Magdolna Dank.

Ethics declarations

Ethical approval for the study was given by the Semmelweis University Institutional Review Board. Date and number of the ethical approval: 12 June 2013; TUKEB No. 120/2013. Written informed consent was waived.

Conflict of interest

The authors declare that they have no conflict of interest.

Funding

Funding was provided by the Doctoral School of the Semmelweis University, in the form of student scholarship and PhD budget, granted to Tímea Tőkés, MD. The study was co-financed from a 1-year student scholarship by the Hungarian Cancer Society awarded to Tímea Tőkés, MD, in 2014.

Electronic supplementary material

Online Resource 1

(PDF 197 kb)

Online Resource 2

(PDF 4.94 mb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tőkés, T., Tőkés, AM., Szentmártoni, G. et al. Expression of cell cycle markers is predictive of the response to primary systemic therapy of locally advanced breast cancer. Virchows Arch 468, 675–686 (2016). https://doi.org/10.1007/s00428-016-1925-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00428-016-1925-x

Keywords

Search

Navigation