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Article
Nature Medicine - 12, 1294 - 1300 (2006)
Published online: 22 October 2006; Corrected online: 27 October 2006; Corrected online: 21 July 2008; Retracted: 07 January 2011 | doi:10.1038/nm1491


There is a Corrigendum (November 2007) associated with this Article.

There is a Corrigendum (August 2008) associated with this Article.

There is a Retraction (January 2011) associated with this Article.

Genomic signatures to guide the use of chemotherapeutics

Anil Potti1, 2, Holly K Dressman1, 3, Andrea Bild1, 3, Richard F Riedel1, 2, Gina Chan4, Robyn Sayer4, Janiel Cragun4, Hope Cottrill4, Michael J Kelley2, Rebecca Petersen5, David Harpole5, Jeffrey Marks5, Andrew Berchuck1, 6, Geoffrey S Ginsburg1, 2, Phillip Febbo1, 2, 3, Johnathan Lancaster4 & Joseph R Nevins1, 2, 3

1  Duke Institute for Genome Sciences and Policy, Duke University, Box 3382, Durham, North Carolina 27710, USA

2  Department of Medicine, Duke University Medical Center, Box 31295, Durham, North Carolina 27710, USA

3  Department of Molecular Genetics and Microbiology, Duke University Medical Center, Box 3054, Durham, North Carolina 27710, USA

4  Division of Gynecologic Surgical Oncology, H. Lee Moffitt Cancer Center & Research Institute, University of South Florida, 12902 Magnolia Drive, Tampa, Florida 33612, USA

5  Department of Surgery, Duke University Medical Center, Box 3627, Durham, North Carolina 27710, USA

6  Department of Obstetrics and Gynecology, Duke University Medical Center, Box 3079, Durham, North Carolina 27710, USA

Correspondence should be addressed to Joseph R Nevins nevin001@mc.duke.edu

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NOTE: This Article has been retracted.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

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ISSN: 1078-8956
EISSN: 1546-170X
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