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  • Oncogenomics
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A gene-expression signature to predict survival in breast cancer across independent data sets

Oncogene volume 26, pages 1507–1516 (2007)Cite this article

Abstract

Prognostic signatures in breast cancer derived from microarray expression profiling have been reported by two independent groups. These signatures, however, have not been validated in external studies, making clinical application problematic. We performed microarray expression profiling of 135 early-stage tumors, from a cohort representative of the demographics of breast cancer. Using a recently proposed semisupervised method, we identified a prognostic signature of 70 genes that significantly correlated with survival (hazard ratio (HR): 5.97, 95% confidence interval: 3.0–11.9, P=2.7e−07). In multivariate analysis, the signature performed independently of other standard prognostic classifiers such as the Nottingham Prognostic Index and the ‘Adjuvant!’ software. Using two different prognostic classification schemes and measures, nearest centroid (HR) and risk ordering (D-index), the 70-gene classifier was also found to be prognostic in two independent external data sets. Overall, the 70-gene set was prognostic in our study and the two external studies which collectively include 715 patients. In contrast, we found that the two previously described prognostic gene sets performed less optimally in external validation. Finally, a common prognostic module of 29 genes that associated with survival in both our cohort and the two external data sets was identified. In spite of these results, further studies that profile larger cohorts using a single microarray platform, will be needed before prospective clinical use of molecular classifiers can be contemplated.

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Acknowledgements

Research in the Cancer Genomics Program is funded by grants from Cancer Research UK, Cambridge MIT Institute and Isaac Newton Trust. JDB is a CR-UK Senior Clinical Research Fellow. We thank Dr Patrick Royston for advice on survival analysis and Ms Claire Paish, Nottingham City Hospital for collecting the tissue samples. NLB-M is the recipient of a Praxis XXI doctoral fellowship from FCT, Ministry of Science, Portugal.

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Author notes

  1. A Naderi and A E Teschendorff: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Oncology, Cancer Genomics Program, Hutchison/MRC Research Center, University of Cambridge, Cambridge, UK

    A Naderi, A E Teschendorff, N L Barbosa-Morais, S Aparicio, J D Brenton & C Caldas

  2. Department of Pathology, Hutchison/MRC Research Center, University of Cambridge, Cambridge, UK

    S E Pinder

  3. Department of Molecular Medical Sciences, Nottingham City Hospital NHS Trust and University of Nottingham, Nottingham, UK

    A R Green & D G Powe

  4. Department of Medical and Surgical Sciences, Nottingham City Hospital NHS Trust and University of Nottingham, Nottingham, UK

    J F R Robertson

  5. Department of Histopathology, Nottingham City Hospital NHS Trust and University of Nottingham, Nottingham, UK

    I O Ellis

  6. Faculty of Medicine, Institute of Molecular Medicine, University of Lisbon, Lisbon, Portugal

    N L Barbosa-Morais

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  1. A Naderi
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  2. A E Teschendorff
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  8. S Aparicio
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  9. I O Ellis
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  10. J D Brenton
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  11. C Caldas
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Corresponding authors

Correspondence to J D Brenton or C Caldas.

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Supplementary Information accompanies the paper on the Oncogene website (http://www.nature.com/onc).

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Naderi, A., Teschendorff, A., Barbosa-Morais, N. et al. A gene-expression signature to predict survival in breast cancer across independent data sets. Oncogene 26, 1507–1516 (2007). https://doi.org/10.1038/sj.onc.1209920

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