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Prediction of metastatic relapse in node-positive breast cancer: establishment of a clinicogenomic model after FEC100 adjuvant regimen

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Abstract

Breast cancer is a very heterogeneous disease, and markers for disease subtypes and therapy response remain poorly defined. For that reason, we employed a retrospective study in node-positive breast cancer to identify molecular signatures of gene expression correlating with metastatic free survival. Patients were primarily included in FEC100 (5-fluorouracil 500 mg/m2, epirubicin 100 mg/m2 and cyclophosphamide 500 mg/m2) arms of two multicentric prospective adjuvant clinical trials (PACS01 and PEGASE01—FNCLCC cooperative group). Data from nylon microarrays containing 8,032 cDNA unique sequences, representing 5,776 distinct genes, have been used to develop a predictive model for treatment outcome. We obtained the gene expression profiles for 150 of these patients, and used stringent univariate selection techniques based on Cox regression combined with principal component analysis to identify a genomic signature of metastatic relapse after adjuvant FEC100 regimen. Most of the 14 selected genes have a clear role in breast cancer, carcinogenesis or chemotherapy resistance. Six genes have been previously described in other genomic studies (UBE2C, CENPF, C16orf61 [DC13], STMN1, CCT5 and BCL2A1). Furthermore, we showed the interest of combining transcriptomic data with clinical data into a clinicogenomic model for patients subtyping. The described model adds predictive accuracy to that provided by the well-established Nottingham prognostic index or by our genomic signature alone.

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Abbreviations

AIC:

Akaike information criterion

CGM:

clinicogenomic model

CI:

confidence interval

GS:

genomic signature

HR:

hazard ratio

NPI:

Nottingham prognostic index

MFS:

metastatic free survival

MR:

metastatic relapse

PCA:

principal component analysis

SBR:

Scarff–Bloom–Richardson

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Acknowledgements

We thank M. Martin, E. Ollivier and N. Roi for technical assistance.

This work was supported by funds from PFIZER-France pharmaceutical company, the Ligue Régionale contre le Cancer de Loire Atlantique, Cancéropôle Grand Ouest and by generous gifts from Lyon’s Clubs-La Baule/Pays Guérandais and Nantes Pays de Loire, and different regional associations of bowls players. A part of the tissues used in this publication was provided by IRCNA tumor bank, Nantes, funded by the Institut National du Cancer and the Cancéropôle Grand Ouest.

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Authors and Affiliations

  1. Service d’Oncologie Médicale, Centre de Lutte Contre le Cancer René Gauducheau, Bd J. Monod, 44805, Nantes—Saint Herblain Cedex, France

    Mario Campone

  2. Unité de Biostatistique, Centre de Lutte Contre le Cancer René Gauducheau, Bd J. Monod, 44805, Nantes—Saint Herblain Cedex, France

    Loïc Campion, Wilfried Gouraud & Catherine Charbonnel

  3. INSERM U601, Institut de Biologie, 9 quai Moncousu, 44035, Nantes Cedex, France

    Loïc Campion, Wilfried Gouraud, Catherine Charbonnel, Florence Magrangeas & Stéphane Minvielle

  4. Service d’Oncologie Médicale, Institut Claudius Regaud, 20–24 rue du Pont Saint Pierre, 31052, Toulouse Cedex, France

    Henry Roché

  5. Unité Mixte de Génomique du Cancer, Hôpital Laennec, Bd J. Monod, 44805, Nantes—Saint Herblain Cedex, France

    Wilfried Gouraud, Catherine Charbonnel, Florence Magrangeas, Stéphane Minvielle & Pascal Jézéquel

  6. Fédération Nationale des Centres de Lutte Contre le Cancer (FNCLCC), 101 rue de Tolbiac, 75654, Paris Cedex 13, France

    Jean Genève & Anne-Laure Martin

  7. Département de Biologie Oncologique, Centre de Lutte Contre le Cancer René Gauducheau, Bd J. Monod, 44805, Nantes—Saint Herblain Cedex, France

    Régis Bataille & Pascal Jézéquel

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  1. Mario Campone
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Correspondence to Pascal Jézéquel.

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Campone, M., Campion, L., Roché, H. et al. Prediction of metastatic relapse in node-positive breast cancer: establishment of a clinicogenomic model after FEC100 adjuvant regimen. Breast Cancer Res Treat 109, 491–501 (2008). https://doi.org/10.1007/s10549-007-9673-x

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  • DOI: https://doi.org/10.1007/s10549-007-9673-x

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