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ToxSci Advance Access published online on February 20, 2007
Toxicological Sciences, doi:10.1093/toxsci/kfm023
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© The Author 2007. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Application of Genomic Biomarkers to Predict Increased Lung Tumor Incidence in Two-Year Rodent Cancer Bioassays

Russell S. Thomas*,{ddagger}, Linda Pluta*, Longlong Yang* and Thomas A. Halsey*,{dagger}

* The Hamner Institutes for Health Sciences, 6 Davis Drive, Research Triangle Park, NC 27709-2137 {dagger} Present address: Almac Diagnostics, 801-1 Capitola Drive, Durham, NC 27713

{ddagger} Corresponding Author Phone: (919) 558-1311, Fax: (919) 558-1300, Email: rthomas{at}thehamner.org

Received December 23, 2006; revision received February 9, 2007; accepted February 14, 2007


  Abstract

Rodent cancer bioassays are part of a legacy of safety testing that has not changed significantly over the past 30 years. The bioassays are expensive, time-consuming, and use hundreds of animals. Fewer than 1,500 chemicals have been tested in a rodent cancer bioassay compared to the thousands of environmental and industrial chemicals that remain untested for carcinogenic activity. In this study, we used existing data generated by the National Toxicology Program (NTP) to identify gene expression biomarkers that can predict results from a rodent cancer bioassay. A set of 13 diverse chemicals were selected from those tested by the NTP. Seven chemicals were positive for increased lung tumor incidence in female B6C3F1 mice and six were negative. Female mice were exposed subchronically to each of the 13 chemicals and microarray analysis was performed on the lung. Statistical classification analysis using the gene expression profiles identified a set of 8 probe sets corresponding to 6 genes whose expression correctly predicted the increase in lung tumor incidence with 93.9% accuracy. The sensitivity and specificity were 95.2% and 91.8%, respectively. Among the six genes in the predictive signature, most were enzymes involved in endogenous and xenobiotic metabolism and one gene was a growth factor receptor involved in lung development. The results demonstrate increases in chemically-induced lung tumor incidence in female mice can be predicted using gene biomarkers from a subchronic exposure and may form the basis of a more efficient and economical approach for evaluating the carcinogenic activity of chemicals.

Key Words: genomics; biomarkers; rodent cancer bioassays.


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