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Genomic signatures to guide the use of chemotherapeutics

A Retraction to this article was published on 07 January 2011

A Corrigendum to this article was published on 01 August 2008

A Corrigendum to this article was published on 01 November 2007

This article has been updated


Using in vitro drug sensitivity data coupled with Affymetrix microarray data, we developed gene expression signatures that predict sensitivity to individual chemotherapeutic drugs. Each signature was validated with response data from an independent set of cell line studies. We further show that many of these signatures can accurately predict clinical response in individuals treated with these drugs. Notably, signatures developed to predict response to individual agents, when combined, could also predict response to multidrug regimens. Finally, we integrated the chemotherapy response signatures with signatures of oncogenic pathway deregulation to identify new therapeutic strategies that make use of all available drugs. The development of gene expression profiles that can predict response to commonly used cytotoxic agents provides opportunities to better use these drugs, including using them in combination with existing targeted therapies.

NOTE: In the version of this article initially published online, the affiliations of some authors were incorrectly listed. R.S. and J.C. should be affiliation 4, and the correct address for this affiliation should be Division of Gynecologic Surgical Oncology, H. Lee Moffitt Cancer Center & Research Institute, University of South Florida, 12902 Magnolia Drive, Tampa, Florida 33612, USA. Also, "Center for Applied Genomics and Technology" should be omitted from affiliation 1. The error has been corrected for all versions of the article.

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Figure 1: A gene expression signature that predicts sensitivity to docetaxel.
Figure 2: Development of a panel of gene expression signatures that predict sensitivity to chemotherapeutic drugs.
Figure 3: Prediction of response to combination therapy.
Figure 4: Patterns of predicted sensitivity to common chemotherapeutic drugs in human cancers.
Figure 5: Relationship between predicted chemotherapeutic sensitivity and oncogenic pathway deregulation.
Figure 6

Accession codes


Gene Expression Omnibus

Change history

  • 27 October 2006

    In the version of this article initially published online, the affiliations of some authors were incorrectly listed. R.S. and J.C. should be affiliation 4, and the correct address for this affiliation should be Division of Gynecologic Surgical Oncology, H. Lee Moffitt Cancer Center & Research Institute, University of South Florida, 12902 Magnolia Drive, Tampa, Florida 33612, USA. Also, "Center for Applied Genomics and Technology" should be omitted from affiliation 1. The error has been corrected for all versions of the article.

  • 21 July 2008

    Nature Medicine 11, 1294-1300 (2006); published online 22 October 2006; corrected online 27 October 2006 and corrected after print 21 July 2008. In the version of this article initially published, of the 122 samples assayed for sensitivity to daunorubicin for which the authors applied a predictor of adriamycin sensitivity (Fig. 2c), 27 samples were replicated owing to the fact that the same samples were included in several separate series files in the Gene Expression Omnibus generated in 2004 and 2005, which were the source of the data provided for the study. The authors have reanalyzed the prediction of adriamycin sensitivity using only the 95 unique samples and find a revised accuracy of 74%. Additionally, the authors have added two more accession numbers (GSE2351 and GSE649) to more clearly identify the sources of the samples. The errors have been corrected in the HTML and PDF versions of the article.

  • 07 January 2011

    This Article has been retracted. See the full retraction notice for details.


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The authors would like to acknowledge and thank L. Pusztai for providing us with the clinical and expression data on the samples studied from the M.D. Anderson Cancer Center. Funding for this work was supplied in part by research grants from the US National Institutes of Health (NCI-U54 CA112952-02 (J.R.N.) and R01CA106520 (J.R.N.)). A.P. is an American Association for Cancer Research Translational Research Grant awardee, J.L. receives research support from Glaxo-Smith-Kline and Sanofi-Aventis Pharmaceuticals and Orthobiotech, and P.F. is a Damon Runyon Cancer Research Investigator. Additional sources of funding included the Ovarian Cancer Research Fund and the Hearing the Ovarian Cancer Whisper Jacquie Liggett Fellowship.

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Correspondence to Joseph R Nevins.

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Competing interests

J.L. reports receiving research support from Glaxo-Smith-Kline, Sanofi-Aventis and Orthobiotech. There are no other competing financial interests.

Supplementary information

Supplementary Fig. 1

A patient-derived docetaxel gene expression signature predicts response to docetaxel in cancer cell lines (PDF 227 kb)

Supplementary Fig. 2

Development of gene expression signatures that predict sensitivity to a panel of commonly used chemotherapeutic drugs (PDF 379 kb)

Supplementary Fig. 3

Specificity of chemotherapy response predictors (PDF 184 kb)

Supplementary Fig. 4

Relationships in predicted probability of response to chemotherapies in breast (Panel A), lung (Panel B) and ovarian cancer (Panel C) (PDF 279 kb)

Supplementary Fig. 5

Integrating prediction of oncogenic pathway deregulation with chemotherapeutic sensitivity (PDF 370 kb)

Supplementary Table 1

The genes constituting the individual chemosensitivity predictors developed on the NCI-60 cell line panel and the genes constituting the PI3 kinase pathway predictor (PDF 452 kb)

Supplementary Table 2

A summary of the chemotherapy response predictors: validations in cell line and patient data sets (PDF 49 kb)

Supplementary Table 3

An enrichment analysis showing that a genomic-guided response prediction increases the probability of a clinical response in the different data sets studied; a comparison of this data to previously reported predictors of response (PDF 50 kb)

Supplementary Methods (PDF 154 kb)

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Potti, A., Dressman, H., Bild, A. et al. Genomic signatures to guide the use of chemotherapeutics. Nat Med 12, 1294–1300 (2006).

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