Breast Cancer Research and Treatment

, Volume 127, Issue 3, pp 591–599 | Cite as

MIB1/Ki-67 labelling index can classify grade 2 breast cancer into two clinically distinct subgroups

  • Mohammed A. Aleskandarany
  • Emad A. Rakha
  • R. Douglas Macmillan
  • Desmond G. Powe
  • Ian O. Ellis
  • Andrew R. Green
Preclinical study

Abstract

Histological grade is recognized as one of the strongest prognostic factors in operable breast cancer (BC). Although grade 1 and grade 3 tumours are biologically and clinically distinct, grade 2 tumours bear considerable difficulty in outcome prediction and planning therapies. Several attempts such as genomic grade index have been performed to subclassify grade 2 into two subgroups with clinical relevance. Here, we present evidence that the routinely evaluable immunohistochemical MIB1/Ki67 labelling index (MIB-LI) can classify grade 2 tumours into two clinically distinct subgroups. In this study, growth fractions of 1,550 primary operable invasive breast carcinomas were immunohistochemically assayed on full-face tissue sections using the MIB1 clone of Ki-67. Growth fractions were assessed as number of MIB1 positive nuclei in 1,000 tumour nuclei at high-power magnification and expressed as MIB1-LI. Using a 10% cut-point of MIB1-LI, grade 2 BCs were classified into low (49.8%) and high (50.2%) proliferative subgroups. Univariate and multivariate survival analysis revealed statistically significant differences between these subgroups regarding patients’ BC specific survival (P < 0.001), and metastasis free survival (P < 0.001) which was independent of the well-established prognostic factors (HR = 2.944, 95% CI = 1.634–5.303, P < 0.001). In conclusion, our results further demonstrate that grade 2 BCs may represent at least two biological or behaviourally different entities. Assay of growth fraction in BC using MIB1/Ki67 immunohistochemistry is a robust cost-effective diagnostic tool that subdivides grade 2 tumours into low and high risk populations providing additional prognostic information in planning therapies and outcome prediction.

Keywords

Breast carcinoma Growth fraction Grade Immunohistochemistry Ki67 

Notes

Acknowledgements

MAA is funded by the Ministry of High Education (Egypt). Part of this work has been partially funded by the Breast Cancer Campaign.

Conflict of interest statement

None of the authors has any competing interests.

References

  1. 1.
    Soerjomataram I, Louwman MW, Ribot JG, Roukema JA, Coebergh JW (2008) An overview of prognostic factors for long-term survivors of breast cancer. Breast Cancer Res Treat 107:309–330PubMedCrossRefGoogle Scholar
  2. 2.
    Pereira H, Pinder SE, Sibbering DM, Galea MH, Elston CW, Blamey RW, Robertson JF, Ellis IO (1995) Pathological prognostic factors in breast cancer. IV: should you be a typer or a grader? A comparative study of two histological prognostic features in operable breast carcinoma. Histopathology 27:219–226PubMedCrossRefGoogle Scholar
  3. 3.
    Dalton LW, Page DL, Dupont WD (1994) Histologic grading of breast carcinoma. A reproducibility study. Cancer 73:2765–2770PubMedCrossRefGoogle Scholar
  4. 4.
    Frierson HF Jr, Wolber RA, Berean KW, Franquemont DW, Gaffey MJ, Boyd JC, Wilbur DC (1995) Interobserver reproducibility of the Nottingham modification of the Bloom and Richardson histologic grading scheme for infiltrating ductal carcinoma. Am J Clin Pathol 103:195–198PubMedGoogle Scholar
  5. 5.
    Ignatiadis M, Sotiriou C (2008) Understanding the molecular basis of histologic grade. Pathobiology 75:104–111PubMedCrossRefGoogle Scholar
  6. 6.
    Whitfield ML, George LK, Grant GD, Perou CM (2006) Common markers of proliferation. Nat Rev Cancer 6:99–106PubMedCrossRefGoogle Scholar
  7. 7.
    Elston CW, Ellis IO (1991) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 19:403–410PubMedCrossRefGoogle Scholar
  8. 8.
    Hall PA, Levison DA (1990) Review: assessment of cell proliferation in histological material. J Clin Pathol 43:184–192PubMedCrossRefGoogle Scholar
  9. 9.
    Meyer JS, Alvarez C, Milikowski C, Olson N, Russo I, Russo J, Glass A, Zehnbauer BA, Lister K, Parwaresch R (2005) Breast carcinoma malignancy grading by Bloom–Richardson system vs proliferation index: reproducibility of grade and advantages of proliferation index. Mod Pathol 18:1067–1078PubMedCrossRefGoogle Scholar
  10. 10.
    Lynch J, Pattekar R, Barnes DM, Hanby AM, Camplejohn RS, Ryder K, Gillett CE (2002) Mitotic counts provide additional prognostic information in grade II mammary carcinoma. J Pathol 196:275–279PubMedCrossRefGoogle Scholar
  11. 11.
    Haibe-Kains B, Desmedt C, Piette F, Buyse M, Cardoso F, Van’t Veer L, Piccart M, Bontempi G, Sotiriou C (2008) Comparison of prognostic gene expression signatures for breast cancer. BMC Genomics 9:394PubMedCrossRefGoogle Scholar
  12. 12.
    Dai H, vant Veer L, Lamb J, He YD, Mao M, Fine BM, Bernards R, van de Vijver M, Deutsch P, Sachs A, Stoughton R, Friend S (2005) A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients 65:4059–4066Google Scholar
  13. 13.
    Bonnefoi H, Underhill C, Iggo R, Cameron D (2009) Predictive signatures for chemotherapy sensitivity in breast cancer: are they ready for use in the clinic? Eur J Cancer 45:1733–1743PubMedCrossRefGoogle Scholar
  14. 14.
    Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, Haibe-Kains B, Desmedt C, Ignatiadis M, Sengstag T, Schutz F, Goldstein DR, Piccart M, Delorenzi M (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:R65PubMedCrossRefGoogle Scholar
  15. 15.
    Cheang MC, Chia SK, Voduc D, Gao D, Leung S, Snider J, Watson M, Davies S, Bernard PS, Parker JS, Perou CM, Ellis MJ, Nielsen TO (2009) Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst 101:736–750PubMedCrossRefGoogle Scholar
  16. 16.
    Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J, Nordgren H, Farmer P, Praz V, Haibe-Kains B, Desmedt C, Larsimont D, Cardoso F, Peterse H, Nuyten D, Buyse M, Van de Vijver MJ, Bergh J, Piccart M, Delorenzi M (2006) Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98:262–272PubMedCrossRefGoogle Scholar
  17. 17.
    Ma XJ, Salunga R, Dahiya S, Wang W, Carney E, Durbecq V, Harris A, Goss P, Sotiriou C, Erlander M, Sgroi D (2008) A five-gene molecular grade index and HOXB13:IL17BR are complementary prognostic factors in early stage breast cancer. Clin Cancer Res 14:2601–2608PubMedCrossRefGoogle Scholar
  18. 18.
    Rakha EA, El-Sayed ME, Reis-Filho JS, Ellis IO (2008) Expression profiling technology: its contribution to our understanding of breast cancer. Histopathology 52:67–81PubMedCrossRefGoogle Scholar
  19. 19.
    Srinivasan M, Sedmak D, Jewell S (2002) Effect of fixatives and tissue processing on the content and integrity of nucleic acids. Am J Pathol 161:1961–1971PubMedCrossRefGoogle Scholar
  20. 20.
    McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM (2005) REporting recommendations for tumor MARKer prognostic studies (REMARK). Nat Clin Pract Oncol 2:416–422PubMedCrossRefGoogle Scholar
  21. 21.
    Ellis IO et al (2005) Pathology reporting of breast disease: a joint document incorporating the third edition of the NHS Breast Screening Programme’s Guidelines for pathology reporting in breast cancer screening and the second edition of the Royal College of Pathologists’ Minimum dataset for breast cancer histopathology. NHS Cancer Screening Programmes; Royal College of PathologistsGoogle Scholar
  22. 22.
    Abd El-Rehim DM, Ball G, Pinder SE, Rakha E, Paish C, Robertson JFR, Macmillan D, Blamey RW, Ellis IO (2005) High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses. Int J Cancer 116:340–350PubMedCrossRefGoogle Scholar
  23. 23.
    Aleskandarany MA, Green AR, Rakha EA, Mohammed RA, Elsheikh SE, Powe DG, Paish EC, Macmillan RD, Chan S, Ahmed SI, Ellis IO (2010) Growth fraction as a predictor of response to chemotherapy in node negative breast cancer. Int J Cancer 126(7):1761–1769PubMedGoogle Scholar
  24. 24.
    Rakha EA, Elsheikh SE, Aleskandarany MA, Habashi HO, Green AR, Powe DG, El-Sayed ME, Benhasouna A, Brunet JS, Akslen LA, Evans AJ, Blamey R, Reis-Filho JS, Foulkes WD, Ellis IO (2009) Triple-negative breast cancer: distinguishing between basal and nonbasal subtypes. Clin Cancer Res 15:2302–2310PubMedCrossRefGoogle Scholar
  25. 25.
    Camp RL, Dolled-Filhart M, Rimm DL (2004) X-Tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization 10:7252–7259Google Scholar
  26. 26.
    Simpson PT, Reis-Filho JS, Gale T, Lakhani SR (2005) Molecular evolution of breast cancer. J Pathol 205:248–254PubMedCrossRefGoogle Scholar
  27. 27.
    Elston CW, Ellis IO, Pinder SE (1999) Pathological prognostic factors in breast cancer. Crit Rev Oncol Hematol 31:209–223PubMedCrossRefGoogle Scholar
  28. 28.
    Pusztai L, Hortobagyi GN (1998) High-dose chemotherapy: how resistant is breast cancer? Drug Resist Updat 1:62–72PubMedCrossRefGoogle Scholar
  29. 29.
    Elston CW, Ellis IO (2002) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 41:154–161PubMedCrossRefGoogle Scholar
  30. 30.
    Le Doussal V, Tubiana-Hulin M, Friedman S, Hacene K, Spyratos F, Brunet M (1989) Prognostic value of histologic grade nuclear components of Scarff-Bloom-Richardson (SBR). An improved score modification based on a multivariate analysis of 1262 invasive ductal breast carcinomas. Cancer 64:1914–1921PubMedCrossRefGoogle Scholar
  31. 31.
    Baak JP, van Diest PJ, Voorhorst FJ, van der Wall E, Beex LV, Vermorken JB, Janssen EA (2005) Prospective multicenter validation of the independent prognostic value of the mitotic activity index in lymph node-negative breast cancer patients younger than 55 years. J Clin Oncol 23:5993–6001PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2010

Authors and Affiliations

  • Mohammed A. Aleskandarany
    • 1
    • 2
  • Emad A. Rakha
    • 3
  • R. Douglas Macmillan
    • 4
  • Desmond G. Powe
    • 3
  • Ian O. Ellis
    • 1
    • 3
  • Andrew R. Green
    • 1
  1. 1.Division of Pathology, School of Molecular Medical Sciences, Queen’s Medical CentreUniversity of NottinghamNottinghamUK
  2. 2.Pathology Department, Faculty of MedicineMenoufyia UniversityShibin el KomEgypt
  3. 3.Department of PathologyNottingham University Hospitals NHS TrustNottinghamUK
  4. 4.Breast InstituteNottingham University Hospitals NHS TrustNottinghamUK

Personalised recommendations