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Comparison of gene expression profiles predicting progression in breast cancer patients treated with tamoxifen

  • Preclinical Study
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Abstract

Background Molecular signatures that predict outcome in tamoxifen treated breast cancer patients have been identified. For the first time, we compared these response profiles in an independent cohort of (neo)adjuvant systemic treatment naïve breast cancer patients treated with first-line tamoxifen for metastatic disease. Methods From a consecutive series of 246 estrogen receptor (ER) positive primary tumors, gene expression profiling was performed on available frozen tumors using 44K oligoarrays (n = 69). A 78-gene tamoxifen response profile (formerly consisting of 81 cDNA-clones), a 21-gene set (microarray-based Recurrence Score), as well as the HOXB13-IL17BR ratio (Two-Gene-Index, RT-PCR) were analyzed. Performance of signatures in relation to time to progression (TTP) was compared with standard immunohistochemical (IHC) markers: ER, progesterone receptor (PgR) and HER2. Results In univariate analyses, the 78-gene tamoxifen response profile, 21-gene set and HOXB13-IL17BR ratio were all significantly associated with TTP with hazard ratios of 2.2 (95% CI 1.3–3.7, P = 0.005), 2.3 (95% CI 1.3–4.0, P = 0.003) and 4.2 (95% CI 1.4–12.3, P = 0.009), respectively. The concordance among the three classifiers was relatively low, they classified only 45–61% of patients in the same category. In multivariate analyses, the association remained significant for the 78-gene profile and the 21-gene set after adjusting for ER and PgR. Conclusion The 78-gene tamoxifen response profile, the 21-gene set and the HOXB13-IL17BR ratio were all significantly associated with TTP in an independent patient series treated with tamoxifen. The addition of multigene assays to ER (IHC) improves the prediction of outcome in tamoxifen treated patients and deserves incorporation in future clinical studies.

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Acknowledgments

We are indepted to Maxime Look and Marion Meijer-van Gelder for advice regarding data analyses and to Sjoerd Rodenhuis, Fabien Reyal and Stella Mook for critically reading the manuscript. The authors would like to thank Renate de Groot for the construction of the tissue microarray and Donne Majoor and Jacinta Aantjes for their help with the immunohistochemistry. The authors would like to commemorate Hans Peterse, an excellent surgical pathologist and a highly estimated colleague who passed away unexpectedly during the course of this project.

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Authors and Affiliations

  1. Department of Pathology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands

    Marleen Kok, Johannes L. Peterse & Laura J. Van’t Veer

  2. Department of Medical Oncology and Molecular Biology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands

    Sabine C. Linn & Teun M. van den Berg

  3. Agendia BV, Amsterdam, The Netherlands

    Ryan K. Van Laar, Leonie J. M. J. Delahaye & Annuska M. Glas

  4. Department of Medical Oncology of the Erasmus MC, Josephine Nefkens Institute and Daniel den Hoed, Rotterdam, The Netherlands

    Maurice P. H. M. Jansen, John A. Foekens, Jan G. M. Klijn & Els M. J. J. Berns

  5. Department of Molecular Biology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands

    Michael Hauptmann & Lodewyk F. A. Wessels

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  1. Marleen Kok
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  2. Sabine C. Linn
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  3. Ryan K. Van Laar
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  4. Maurice P. H. M. Jansen
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  8. Johannes L. Peterse
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  9. Michael Hauptmann
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  10. John A. Foekens
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  11. Jan G. M. Klijn
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  13. Laura J. Van’t Veer
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  14. Els M. J. J. Berns
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Correspondence to Laura J. Van’t Veer.

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Kok, M., Linn, S.C., Van Laar, R.K. et al. Comparison of gene expression profiles predicting progression in breast cancer patients treated with tamoxifen. Breast Cancer Res Treat 113, 275–283 (2009). https://doi.org/10.1007/s10549-008-9939-y

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  • DOI: https://doi.org/10.1007/s10549-008-9939-y

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