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Updated: Mar 31, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Genome-wide gene expression profiling to predict resistance to anthracyclines in breast cancer patients
B Haibe-Kains1, C Desmedt2, A Di Leo3
1Institut Jules Bordet, Brussels, Belgium ; Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium ; Ontario Cancer Institute, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Abstract:
Validated biomarkers predictive of response/resistance to anthracyclines in breast cancer are currently lacking. The neoadjuvant Trial of Principle (TOP) study, in which patients with estrogen receptor (ER)-negative tumors were treated with anthracycline (epirubicin) monotherapy, was specifically designed to evaluate the predictive value of topoisomerase II-alpha (TOP2A) and develop a gene expression signature to identify those patients who do not benefit from anthracyclines. Here we describe in details the contents and quality controls for the gene expression and clinical data associated with the study published by Desmedt and colleagues in the Journal of Clinical Oncology in 2011 (Desmedt et al., 2011). We also provide R code to easily access the data and perform the quality controls and basic analyses relevant to this dataset.

