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Prediction of doxorubicin sensitivity in breast tumors based on gene expression profiles of drug-resistant cell lines correlates with patient survival

Oncogene volume 24, pages 7542–7551 (2005)Cite this article

Abstract

Up to date clinical tests for predicting cancer chemotherapy response are not available and individual markers have shown little predictive value. We hypothesized that gene expression patterns attributable to chemotherapy-resistant cells can predict response and cancer prognosis. We contrasted the expression profiles of 13 different human tumor cell lines of gastric (EPG85–257), pancreatic (EPP85–181), colon (HT29) and breast (MCF7 and MDA-MB-231) origin and their counterparts resistant to the topoisomerase inhibitors daunorubicin, doxorubicin or mitoxantrone. We interrogated cDNA arrays with 43 000 cDNA clones (∼30 000 unique genes) to study the expression pattern of these cell lines. We divided gene expression profiles into two sets: we compared the expression patterns of the daunorubicin/doxorubicin-resistant cell lines and the mitoxantrone-resistant cell lines independently to the parental cell lines. For identifying predictive genes, the Prediction Analysis for Mircorarrays algorithm was used. The analysis revealed 79 genes best correlated with doxorubicin resistance and 70 genes with mitoxantrone resistance. In an independent classification experiment, we applied our model of resistance for predicting the sensitivity of 44 previously characterized breast cancer samples. The patient group characterized by the gene expression profile similar to those of doxorubicin-sensitive cell lines exhibited longer survival (49.7±26.1 months, n=21, P=0.034) than the resistant group (32.9±18.7 months, n=23). The application of gene expression signatures derived from doxorubicin-resistant and -sensitive cell lines allowed to predict effectively clinical survival after doxorubicin monotherapy. Our approach demonstrates the significance of in vitro experiments in the development of new strategies for cancer response prediction.

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Acknowledgements

Violeta Serra and Balazs Györffy are supported by Marie Curie fellowships (HPMD-CT-2000-00001). Violeta Serra's work at Stanford University was supported by the Berliner Krebsgesellschaft. We would like to thank Mrs Schütze, Mrs Schaefer and Mrs Pacyna-Gengelbach for technical help.

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Author notes

  1. Balázs Györffy and Violeta Serra: These authors contributed equally to this work

Authors and Affiliations

  1. Charité, Institute of Pathology, Humboldt University, Schumannstr. 20/21, Berlin, D-10117, Germany

    Balázs Györffy, Violeta Serra, Karsten Jürchott, Rula Abdul-Ghani, Iver Petersen, Hermann Lage, Manfred Dietel & Reinhold Schäfer

  2. 2nd Department of Internal Medicine, Semmelweis University Budapest, Szentkirályi u. 46, Budapest, H-1088, Hungary

    Balázs Györffy

  3. Centro Nacional de Investigaciones Oncologicas (CNIO), Melchor Fernández Almagro 3, Madrid, E-28029, Spain

    Violeta Serra

  4. Departments of Genetics, Stanford University School of Medicine, Stanford, 94305, California, CA, USA

    Mitch Garber

  5. Max-Delbrück-Center for Molecular Medicine, Robert-Rössle-Strasse 10, Berlin, 13092, Germany

    Ulrike Stein

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Correspondence to Balázs Györffy.

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Györffy, B., Serra, V., Jürchott, K. et al. Prediction of doxorubicin sensitivity in breast tumors based on gene expression profiles of drug-resistant cell lines correlates with patient survival. Oncogene 24, 7542–7551 (2005). https://doi.org/10.1038/sj.onc.1208908

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