European Surgery

, Volume 41, Issue 5, pp 221–227 | Cite as

Gene expression profiling in breast cancer – design of a pooled database to address open questions

  • M. Knauer
  • E. Wenzl
  • E. J. T. Rutgers
  • S. C. Linn
  • L. J. van't Veer
Original Scientific Paper


BACKGROUND: The Netherlands Cancer Institute used DNA microarray analyses to identify a 70-gene expression profile strongly predictive of a short interval to distant metastases in breast cancer. For patients with small tumors, the signature is not yet adequately validated. Furthermore, 95% of estrogen-receptor or triple-negative tumors are assigned to poor prognosis by the profile. METHODS: A pooled database was constructed containing clinical, pathological and microarray data of 1696 patients. The database will be used to study the performance of the 70-gene profile in patients with small-sized T1 tumors. In addition, patients with triple-negative tumors will be identified and whole genome microarray analysis will be performed of these tumors to develop a new prognostic gene expression profile for this subgroup. RESULTS AND CONCLUSIONS: If the 70-gene profile is accurate for small tumors, patients at risk may be assigned to adjuvant treatment. A new prognostic classifier for triple-negative tumors may help to identify women, in whom adjuvant treatment may safely be omitted.


Gene expression profiling Breast cancer Prognostic marker Database Tumor size Triple-negative 

Mammakarzinom: Genexpressionsprofil


GRUNDLAGEN: Das Netherlands Cancer Institute hat DNA-microarrays zur Identifizierung eines 70-Gen-Expressionsprofils verwendet, welches ein signifikant kürzeres Intervall bis zur Fernmetastasierung beim Mammakarzinom voraussagen kann. Für Patientinnen mit kleinen Tumoren ist das 70-Genprofil noch nicht ausreichend validiert. Außerdem werden 95 % aller Patienten mit triple-negativen Tumoren in die Hochrisikogruppe eingeteilt, obwohl 50 % keine Metastasen entwickeln werden. METHODIK: Eine Datenbank mit klinischen, pathologischen und microarray-Daten von 1696 Patientinnen wurde konstruiert, um die folgenden wissenschaftlichen Fragestellungen zu beantworten: 1. Validierung des 70-Genprofils bei kleinen T1-Tumoren und 2. Identifizierung von triple-negativen Tumoren und Durchführung von DNA-mircoarrays, um ein neues Genexpressionsprofil für diese Subgruppe zu finden. ERGEBNISSE UND SCHLUSSFOLGERUNGEN: Falls das 70-Genprofil für kleine Tumoren prädiktiv ist, könnten diese Patientinnen einer adjuvanten Therapie zugeführt werden. Das neue Profil für triple-negative Tumoren könnte Patientinnen identifizieren, bei denen sicher auf adjuvante Therapie verzichtet werden kann.


Genexpressionsanalyse Mammakarzinom Prognostische Faktoren Datenbank Tumorgröße Triple-negativ 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Hayes DF, Bast RC, Desch CE, et al. Tumor marker utility grading system: a framework to evaluate clinical utility of tumor markers. J Natl Cancer Inst 1996;88:1456–66CrossRefPubMedGoogle Scholar
  2. van 't Veer LJ, Bernards R. Enabling personalized cancer medicine through analysis of gene-expression patterns. Nature 2008;452:564–70CrossRefGoogle Scholar
  3. Polychemotherapy for early breast cancer: an overview of the randomised trials. Early Breast Cancer Trialists' Collaborative Group. Lancet 1998;352:930–42Google Scholar
  4. Tamoxifen for early breast cancer: an overview of the randomised trials. Early Breast Cancer Trialists' Collaborative Group. Lancet 1998;351:1451–67Google Scholar
  5. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 2005;365:1687–717Google Scholar
  6. Goldhirsch A, Glick JH, Gelber RD, et al. 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;19:3817–27PubMedGoogle Scholar
  7. Olivotto IA, Bajdik CD, Ravdin PM, et al. Population-based validation of the prognostic model ADJUVANT! for early breast cancer. J Clin Oncol 2005;23:2716–25CrossRefPubMedGoogle Scholar
  8. D'Eredita G, Giardina C, Martellotta M, et al. Prognostic factors in breast cancer: the predictive value of the Nottingham Prognostic Index in patients with a long-term follow-up that were treated in a single institution. Eur J Cancer 2001;37:591–96CrossRefPubMedGoogle Scholar
  9. Todd JH, Dowle C, Williams MR, et al. Confirmation of a prognostic index in primary breast cancer. Br J Cancer 1987;56:489–92PubMedGoogle Scholar
  10. van't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415:530–6CrossRefGoogle Scholar
  11. van de Vijver MJ, He YD, van't Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002;347:1999–2009CrossRefPubMedGoogle Scholar
  12. Buyse M, Loi S, van't Veer L, et al. Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J Natl Cancer Inst 2006;98:1183–92PubMedCrossRefGoogle Scholar
  13. Cleator S, Ashworth A. Molecular profiling of breast cancer: clinical implications. Br J Cancer 2004;90:1120–4CrossRefPubMedGoogle Scholar
  14. Bogaerts J, Cardoso F, Buyse M, et al. Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial. Nat Clin Pract Oncol 2006;3:540–51CrossRefPubMedGoogle Scholar
  15. Mook S, Schmidt MK, Viale G, 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;116:295–302CrossRefPubMedGoogle Scholar
  16. Bueno-de-Mesquita JM, van Harten WH, Retel VP, et al. Use of 70-gene signature to predict prognosis of patients with node-negative breast cancer: a prospective community-based feasibility study (RASTER). Lancet Oncol 2007;8:1079–87CrossRefPubMedGoogle Scholar
  17. Frey M, Schrögendorfer K, Kropf N, et al. Immediate breast reconstruction – a review of indications, techniques and results. Eur Surg 2007;39:238–48CrossRefGoogle Scholar
  18. Goldhirsch A, Wood WC, Gelber RD, et al. Progress and promise: highlights of the international expert consensus on the primary therapy of early breast cancer 2007. Ann Oncol 2007;18:1133–44CrossRefPubMedGoogle Scholar
  19. Ravdin PM, Siminoff LA, Davis GJ, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 2001;19:980–91PubMedGoogle Scholar
  20. Bueno-de-Mesquita JM, Linn SC, Keijzer R, et al. Validation of 70-gene prognosis signature in node-negative breast cancer. Breast Cancer Res Treat 2009;117:483–95CrossRefPubMedGoogle Scholar
  21. Mook S, Schmidt MK, Weigelt B, et al. The 70-gene prognosis-signature predicts early metastasis in breast cancer patients between 55 and 70 years of age. Ann Oncol (in press)Google Scholar
  22. Kreike B, van Kouwenhove M, Horlings H, et al. Gene expression profiling and histopathological characterization of triple-negative/basal-like breast carcinomas. Breast Cancer Res 2007;9:R65CrossRefPubMedGoogle Scholar
  23. Hu Z, Fan C, Oh DS, et al. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics 2006;7:96CrossRefPubMedGoogle Scholar
  24. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000;406:747–52CrossRefPubMedGoogle Scholar
  25. Hosack DA, Dennis G Jr, Sherman BT, et al. Identifying biological themes within lists of genes with EASE. Genome Biol 2003;4:R70CrossRefPubMedGoogle Scholar
  26. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 2001;98:5116–21CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • M. Knauer
    • 1
    • 2
    • 3
  • E. Wenzl
    • 1
  • E. J. T. Rutgers
    • 2
  • S. C. Linn
    • 4
  • L. J. van't Veer
    • 1
  1. 1.Department of General and Thoracic SurgeryAcademic Teaching Hospital FeldkirchFeldkirchAustria
  2. 2.Division of Surgical OncologyNetherlands Cancer InstituteAmsterdamNetherlands
  3. 3.Private University UFL, Principality of LiechtensteinTriesen
  4. 4.Division of Medical OncologyNetherlands Cancer InstituteAmsterdamNetherlands
  5. 5.Division of Diagnostic OncologyNetherlands Cancer InstituteAmsterdamNetherlands
  6. 6.Agendia B.V.AmsterdamNetherlands

Personalised recommendations