Breast Cancer Research and Treatment

, Volume 137, Issue 1, pp 57–67 | Cite as

Validity of the proliferation markers Ki67, TOP2A, and RacGAP1 in molecular subgroups of breast cancer

  • Karin Milde-Langosch
  • Thomas Karn
  • Volkmar Müller
  • Isabell Witzel
  • Achim Rody
  • Markus Schmidt
  • Ralph M. Wirtz
Preclinical Study

Abstract

High proliferation rates are characteristic of cancer, and proliferation markers make up the majority of genes included in RNA-based prognostic gene signatures applied for breast cancer patients. Based on prior data on differences in molecular subgroups of breast cancer, we hypothesized that the significance of single proliferation markers might differ in luminal, Her2-positive and triple-negative subtypes. Therefore, we compared mRNA expression data of Ki67, TOP2A, and RacGAP1 using a pool of 562 Affymetrix U133A microarrays from breast cancer samples. “Luminal,” “triple-negative,” and “Her2-positive” subcohorts were defined by ESR1 and ERBB2 mRNA expression using pre-defined cut-offs. The analysis of the three potential proliferation markers revealed subtype-specific differences: in luminal carcinomas, expression of all three markers was a significant indictor of early recurrence in univariate and multivariate analysis, but RacGAP1 was superior to Ki67 and TOP2A in significance. In triple-negative tumors, only Ki67 was a significant and independent marker, whereas none of the markers showed a significant prognostic impact in Her2-positive cases. Within the group of luminal carcinomas, the proliferation markers had different impact depending on the treatment of patients: in untreated patients, Ki67, TOP2A, and RacGAP1 were significant and independent prognostic markers. In chemotherapy-treated patients, overexpression of all three markers was predictive for early recurrence, but only RacGAP1 retained significance in multivariate analysis. In contrast, RacGAP1 was the only predictive proliferation marker in the endocrine treatment group. These data point to subtype-specific differences in the relevance of proliferation-associated genes, and RacGAP1 might be a strong prognostic and predictive marker in the luminal subgroup.

Keywords

Proliferation Breast cancer Molecular subgroups Ki67 TOP2A RacGAP1 

Supplementary material

10549_2012_2296_MOESM1_ESM.docx (19 kb)
Supplementary material 1 (DOCX 18 kb)

References

  1. 1.
    Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100:57–70PubMedCrossRefGoogle Scholar
  2. 2.
    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 16:1723–1739PubMedCrossRefGoogle Scholar
  3. 3.
    Beresford MJ, Wilson GD, Makris A (2006) Measuring proliferation in breast cancer: practicalities and applications. Breast Cancer Res 8:216PubMedCrossRefGoogle Scholar
  4. 4.
    Stuart-Harris R, Caldas C, Pinder SE, Pharoah P (2008) Proliferation markers and survival in early breast cancer: a systematic review and meta-analysis of 85 studies in 32,825 patients. Breast 17:323–334PubMedCrossRefGoogle Scholar
  5. 5.
    Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, Baehner FL, Walker MG, Watson D, Park T et al (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351:2817–2826PubMedCrossRefGoogle Scholar
  6. 6.
    Chang HY, Sneddon JB, Alizadeh AA, Sood R, West RB, Montgomery K, Chi JT, van de Rijn M, Botstein D, Brown PO (2004) Gene expression signature of fibroblast serum response predicts human cancer progression: similarities between tumors and wounds. PLoS Biol 2:E7PubMedCrossRefGoogle Scholar
  7. 7.
    Foekens JA, Atkins D, Zhang Y, Sweep FC, Harbeck N, Paradiso A, Cufer T, Sieuwerts AM, Talantov D, Span PN et al (2006) Multicenter validation of a gene expression-based prognostic signature in lymph node-negative primary breast cancer. J Clin Oncol 24:1665–1671PubMedCrossRefGoogle Scholar
  8. 8.
    van’t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AAM, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT et al (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415:530–536CrossRefGoogle Scholar
  9. 9.
    Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F, Talantov D, Timmermans M, Meijer-van Gelder ME, Yu J et al (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365:671–679PubMedGoogle Scholar
  10. 10.
    Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, Haibe-Kains B, Desmedt C, Ignatiadis M, Sengstag T, Schutz F 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:R65PubMedCrossRefGoogle Scholar
  11. 11.
    Desmedt C, Haibe-Kains B, Wirapati P, Buyse M, Larsimont D, Bontempi G, Delorenzi M, Piccart M, Sotiriou C (2008) Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res 14:5158–5165PubMedCrossRefGoogle Scholar
  12. 12.
    Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA et al (2000) Molecular portraits of human breast tumours. Nature 406:747–752PubMedCrossRefGoogle Scholar
  13. 13.
    Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnson H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98:10869–10874PubMedCrossRefGoogle Scholar
  14. 14.
    Iwamoto T, Bianchini G, Booser D, Qi Y, Coutant C, Ya-Hui Shiang C, Santarpia L, Matsuoka J, Hortobagyi GN, Symmans WF et al (2010) Gene pathways associated with prognosis and chemotherapy sensitivity in molecular subtypes of breast cancer. J Natl Cancer Inst 103:264–272PubMedCrossRefGoogle Scholar
  15. 15.
    Dowsett M, Nielsen TO, A’Hern R, Bartlett J, Coombes RC, Cuzick J, Ellis M, Henry NL, Hugh JC, Lively T et al (2011) Assessment of Ki67 in breast cancer: recommendations from the International Ki67 in Breast Cancer Working Group. J Natl Cancer Inst 103:1656–1664PubMedCrossRefGoogle Scholar
  16. 16.
    Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thurlimann B, Senn HJ (2011) Strategies for subtypes—dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol 22:1736–1747PubMedCrossRefGoogle Scholar
  17. 17.
    Varga Z, Diebold J, Dommann-Scherrer C, Frick H, Kaup D, Noske A, Obermann E, Ohlschlegel C, Padberg B, Rakozy C et al (2012) How reliable is Ki-67 immunohistochemistry in grade 2 breast carcinomas? A QA study of the Swiss Working Group of Breast- and Gynecopathologists. PLoS One 7:e37379PubMedCrossRefGoogle Scholar
  18. 18.
    van den Akker EB, Verbruggen B, Heijmans BT, Beekman M, Kok JN, Slagboom PE, Reinders MJ (2011) Integrating protein–protein interaction networks with gene–gene co-expression networks improves gene signatures for classifying breast cancer metastasis. J Integr Bioinform 8:188PubMedGoogle Scholar
  19. 19.
    Gerdes J, Li L, Schlueter C, Duchrow M, Wohlenberg C, Gerlach C, Stahmer I, Kloth S, Brandt E, Flad HD (1991) Immunobiochemical and molecular biologic characterization of the cell proliferation-associated nuclear antigen that is defined by monoclonal antibody Ki-67. Am J Pathol 138:867–873PubMedGoogle Scholar
  20. 20.
    Urruticoechea A, Smith IE, Dowsett M (2005) Proliferation marker Ki-67 in early breast cancer. J Clin Oncol 23:7212–7220PubMedCrossRefGoogle Scholar
  21. 21.
    Yerushalmi R, Woods R, Ravdin PM, Hayes MM, Gelmon KA (2010) Ki67 in breast cancer: prognostic and predictive potential. Lancet Oncol 11:174–183PubMedCrossRefGoogle Scholar
  22. 22.
    Rody A, Karn T, Ruckhaberle E, Muller V, Gehrmann M, Solbach C, Ahr A, Gatje R, Holtrich U, Kaufmann M (2009) Gene expression of topoisomerase II alpha (TOP2A) by microarray analysis is highly prognostic in estrogen receptor (ER) positive breast cancer. Breast Cancer Res Treat 113:457–466PubMedCrossRefGoogle Scholar
  23. 23.
    Nielsen KV, Ejlertsen B, Moller S, Jorgensen JT, Knoop A, Knudsen H, Mouridsen HT (2008) The value of TOP2A gene copy number variation as a biomarker in breast cancer: update of DBCG trial 89D. Acta Oncol 47:725–734PubMedCrossRefGoogle Scholar
  24. 24.
    O’Malley FP, Chia S, Tu D, Shepherd LE, Levine MN, Bramwell VH, Andrulis IL, Pritchard KI (2009) Topoisomerase II alpha and responsiveness of breast cancer to adjuvant chemotherapy. J Natl Cancer Inst 101:644–650PubMedCrossRefGoogle Scholar
  25. 25.
    Brase JC, Schmidt M, Fischbach T, Sultmann H, Bojar H, Koelbl H, Hellwig B, Rahnenfuhrer J, Hengstler JG, Gehrmann MC (2010) ERBB2 and TOP2A in breast cancer: a comprehensive analysis of gene amplification, RNA levels, and protein expression and their influence on prognosis and prediction. Clin Cancer Res 16:2391–2401PubMedCrossRefGoogle Scholar
  26. 26.
    Hirose K, Kawashima T, Iwamoto I, Nosaka T, Kitamura T (2001) MgcRacGAP is involved in cytokinesis through associating with mitotic spindle and midbody. J Biol Chem 276:5821–5828PubMedCrossRefGoogle Scholar
  27. 27.
    Minoshima Y, Kawashima T, Hirose K, Tonozuka Y, Kawajiri A, Bao YC, Deng X, Tatsuka M, Narumiya S, May WS Jr et al (2003) Phosphorylation by aurora B converts MgcRacGAP to a RhoGAP during cytokinesis. Dev Cell 4:549–560PubMedCrossRefGoogle Scholar
  28. 28.
    Kawashima T, Bao YC, Minoshima Y, Nomura Y, Hatori T, Hori T, Fukagawa T, Fukada T, Takahashi N, Nosaka T et al (2009) A Rac GTPase-activating protein, MgcRacGAP, is a nuclear localizing signal-containing nuclear chaperone in the activation of STAT transcription factors. Mol Cell Biol 29:1796–1813PubMedCrossRefGoogle Scholar
  29. 29.
    Lu KH, Patterson AP, Wang L, Marquez RT, Atkinson EN, Baggerly KA, Ramoth LR, Rosen DG, Liu J, Hellstrom I et al (2004) Selection of potential markers for epithelial ovarian cancer with gene expression arrays and recursive descent partition analysis. Clin Cancer Res 10:3291–3300PubMedCrossRefGoogle Scholar
  30. 30.
    Stone R 2nd, Sabichi AL, Gill J, Lee IL, Adegboyega P, Dai MS, Loganantharaj R, Trutschl M, Cvek U, Clifford JL (2010) Identification of genes correlated with early-stage bladder cancer progression. Cancer Prev Res (Phila) 3:776–786CrossRefGoogle Scholar
  31. 31.
    Wang SM, Ooi LL, Hui KM (2011) Upregulation of Rac GTPase-activating protein 1 is significantly associated with the early recurrence of human hepatocellular carcinoma. Clin Cancer Res 17:6040–6051PubMedCrossRefGoogle Scholar
  32. 32.
    McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM (2006) Reporting recommendations for tumor MARKer prognostic studies (REMARK). Breast Cancer Res Treat 100:229–235PubMedCrossRefGoogle Scholar
  33. 33.
    Schmidt M, Bohm D, von Torne C, Steiner E, Puhl A, Pilch H, Lehr HA, Hengstler JG, Kolbl H, Gehrmann M (2008) The humoral immune system has a key prognostic impact in node-negative breast cancer. Cancer Res 68:5405–5413PubMedCrossRefGoogle Scholar
  34. 34.
    Ruckhäberle E, Rody A, Engels K, Gaetje R, von Minckwitz G, Schiffmann S, Grosch S, Geisslinger G, Holtrich U, Karn T et al (2008) Microarray analysis of altered sphingolipid metabolism reveals prognostic significance of sphingosine kinase 1 in breast cancer. Breast Cancer Res Treat 112:41–52PubMedCrossRefGoogle Scholar
  35. 35.
    Ihnen M, Muller V, Wirtz RM, Schroder C, Krenkel S, Witzel I, Lisboa BW, Janicke F, Milde-Langosch K (2008) Predictive impact of activated leukocyte cell adhesion molecule (ALCAM/CD166) in breast cancer. Breast Cancer Res Treat 112(3):419–427PubMedCrossRefGoogle Scholar
  36. 36.
    Karn T, Metzler D, Ruckhaberle E, Hanker L, Gatje R, Solbach C, Ahr A, Schmidt M, Holtrich U, Kaufmann M et al (2010) Data-driven derivation of cutoffs from a pool of 3,030 Affymetrix arrays to stratify distinct clinical types of breast cancer. Breast Cancer Res Treat 120:567–579PubMedCrossRefGoogle Scholar
  37. 37.
    Fountzilas G, Valavanis C, Kotoula V, Eleftheraki AG, Kalogeras KT, Tzaida O, Batistatou A, Kronenwett R, Wirtz RM, Bobos M et al (2012) HER2 and TOP2A in high-risk early breast cancer patients treated with adjuvant epirubicin-based dose-dense sequential chemotherapy. J Transl Med 10:10PubMedCrossRefGoogle Scholar
  38. 38.
    Dai H, van’t Veer L, Lamb J, He YD, Mao M, Fine BM, Bernards R, van de Vijver M, Deutsch P, Sachs A et al (2005) A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients. Cancer Res 65:4059–4066PubMedCrossRefGoogle Scholar
  39. 39.
    Aleskandarany MA, Rakha EA, Macmillan RD, Powe DG, Ellis IO, Green AR (2011) MIB1/Ki-67 labelling index can classify grade 2 breast cancer into two clinically distinct subgroups. Breast Cancer Res Treat 127:591–599PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Karin Milde-Langosch
    • 1
  • Thomas Karn
    • 2
  • Volkmar Müller
    • 1
  • Isabell Witzel
    • 1
  • Achim Rody
    • 3
  • Markus Schmidt
    • 4
  • Ralph M. Wirtz
    • 5
  1. 1.Department of GynecologyUniversity Hospital Hamburg-EppendorfHamburgGermany
  2. 2.Department of Obstetrics and GynecologyGoethe-University FrankfurtFrankfurtGermany
  3. 3.Department of Obstetrics and GynecologyUniversity Clinics Schleswig-HolsteinLübeckGermany
  4. 4.Department of Obstetrics and GynecologyJohannes Gutenberg University MainzMainzGermany
  5. 5.STRATIFYER Molecular Pathology GmbHCologneGermany

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