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Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen

Sherene Loi1,2* email, Benjamin Haibe-Kains1,3* email, Christine Desmedt1 email, Pratyaksha Wirapati4 email, Françoise Lallemand1 email, Andrew M Tutt5 email, Cheryl Gillet5 email, Paul Ellis5 email, Kenneth Ryder5 email, James F Reid6,8 email, Maria G Daidone8 email, Marco A Pierotti6,8 email, Els MJJ Berns7 email, Maurice PHM Jansen7 email, John A Foekens7 email, Mauro Delorenzi4 email, Gianluca Bontempi3 email, Martine J Piccart1 email and Christos Sotiriou1 email

Functional Genomics Unit, Jules Bordet Institute, Brussels, Belgium

Peter MacCallum Cancer Center, East Melbourne, Victoria, Australia

Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium

NCCR Molecular Oncology, Swiss Institute of Cancer Research and Swiss Institute of Bioinformatics, Epalinges, Switzerland

Guys Hospital, London, UK

Molecular Cancer Genetics, Fondazione Istituto FIRC di Oncologia Molecolare (IFOM), Milan, Italy

Erasmus MC-Daniel-JNI, Rotterdam, The Netherlands

Department of Experimental Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

author email corresponding author email* Contributed equally

BMC Genomics 2008, 9:239doi:10.1186/1471-2164-9-239

Published: 22 May 2008

Additional files

Additional file 1:

Training dataset characteristics. Summary of patient and tumor characteristics of the 255 patients used in the development of the classifier.

Format: XLS Size: 36KB Download file

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Additional file 2:

Probe clusters. (a) Full annotated gene list of all clusters (probe clusters; "pclust") used for classifier development after preliminary clustering and filtering on the separate dataset of 137 samples. (b) Full annotated gene list of probe clusters (pclust) used in final classifier and global model.

Format: XLS Size: 320KB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional file 3:

Independent validation datasets characteristics. Summary of patient and tumor characteristics of the four independent validation sets.

Format: XLS Size: 80KB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional file 4:

Signature size stability. Evolution of Stab criterion with respect to the signature size using multiple 10-fold cross-validation. The vertical dashed line represents the stability of the ranking using 13 pclusts.

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Additional file 5:

Signature size performance. Evolution of the log2 hazard ratio with respect to the signature size using multiple 10-fold cross-validation. The vertical dashed line represents the performance of the classifier using 13 pclusts. The horizontal red dashed line represents the limit of statistical significance.

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Additional file 6:

External validation of the classifier (Ma, Reid and Jansen datasets). (a) Kaplan Meier curves for Ma et al. The risk group was defined by the classifier using a 50:50 cutoff. The two survival curves were not significantly different according to the logrank test (p-value of 0.1). (b) Kaplan Meier curves for Reid et al. The risk group was defined by the classifier using a 50:50 cutoff. The two survival curves were significantly different according to the logrank test (p-value of 0.05). (c) Kaplan Meier curves for Jansen et al. The risk group was defined by the classifier using a 50:50 cutoff. The two survival curves were significantly different according to the logrank test (p-value of 0.25).

Format: PDF Size: 116KB Download file

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Additional file 7:

Simplified classifiers. Top correlated "simplified" classifiers of 13 genes (one probe set per cluster) and histogram displaying correlation between "simple" classifiers and final model.

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