RT Journal Article
SR Electronic
T1 Identification of toxicologically predictive gene sets using cDNA microarrays
JF Molecular Pharmacology
JO Mol Pharmacol
FD American Society for Pharmacology and Experimental Therapeutics
SP 1189
OP 1194
DO 10.1124/mol.60.6.1189
VO 60
IS 6
A1 Russell S. Thomas
A1 David R. Rank
A1 Sharron G. Penn
A1 Gina M. Zastrow
A1 Kevin R. Hayes
A1 Kalyan Pande
A1 Edward Glover
A1 Tomi Silander
A1 Mark W. Craven
A1 Janardan K. Reddy
A1 Stevan B. Jovanovich
A1 Christopher A. Bradfield
YR 2001
UL http://molpharm.aspetjournals.org/content/60/6/1189.abstract
AB We have developed an approach to classify toxicants based upon their influence on profiles of mRNA transcripts. Changes in liver gene expression were examined after exposure of mice to 24 model treatments that fall into five well-studied toxicological categories: peroxisome proliferators, aryl hydrocarbon receptor agonists, noncoplanar polychlorinated biphenyls, inflammatory agents, and hypoxia-inducing agents. Analysis of 1200 transcripts using both a correlation-based approach and a probabilistic approach resulted in a classification accuracy of between 50 and 70%. However, with the use of a forward parameter selection scheme, a diagnostic set of 12 transcripts was identified that provided an estimated 100% predictive accuracy based on leave-one-out cross-validation. Expansion of this approach to additional chemicals of regulatory concern could serve as an important screening step in a new era of toxicological testing.