Development of an approach for ab initio estimation of compound-induced liver injury based on global gene transcriptional profiles.
Toxicity is a major cause of failure in drug development. A toxicogenomic approach may provide a powerful tool for better assessing the potential toxicity of drug candidates. Several approaches have been reported for predicting hepatotoxicity based on reference compounds with well-studied toxicity mechanisms. We developed a new approach for assessing compound-induced liver injury without prior knowledge of a compound's mechanism of toxicity. Using samples from rodents treated with 49 known liver toxins and 10 compounds without known liver toxicity, we derived a hepatotoxicity score as a single quantitative measurement for assessing the degree of induced liver damage. Combining the sensitivity of the hepatotoxicity score and the power of a machine learning algorithm, we then built a model to predict compound-induced liver injury based on 212 expression profiles. As estimated in an independent data set of 54 expression profiles, the built model predicted compound-induced liver damage with 90.9% sensitivity and 88.4% specificity. Our findings illustrate the feasibility of ab initio estimation of liver toxicity based on transcriptional profiles.
Dai
Xudong
X
Rosetta Inpharmatics LLC, Merck & Co., Inc., Seattle, WA 98109, USA. xudong_dai@merck.com
He
Yudong D
YD
Dai
Hongyue
H
Lum
Pek Y
PY
Roberts
Christopher J
CJ
Waring
Jeffrey F
JF
Ulrich
Roger G
RG
D000410:Alanine Transaminase / Q000097:blood; D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D001219:Aspartate Aminotransferases / Q000097:blood; D001663:Bilirubin / Q000097:blood; D002624:Chemistry, Clinical / Q000379:methods; D002784:Cholesterol / Q000097:blood; D016000:Cluster Analysis; D004305:Dose-Response Relationship, Drug; D064420:Drug-Related Side Effects and Adverse Reactions / Q000139:chemically induced / Q000145:classification / Q000378:metabolism; D005240:Feasibility Studies; D020869:Gene Expression Profiling; D008099:Liver / Q000187:drug effects* / Q000201:enzymology / Q000473:pathology; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000145:classification; D051381:Rats; D017207:Rats, Sprague-Dawley; D012680:Sensitivity and Specificity; D043922:Toxicogenetics / Q000379:methods*; D014158:Transcription, Genetic
D004364:Pharmaceutical Preparations; D002784:Cholesterol; D001219:Aspartate Aminotransferases; D000410:Alanine Transaminase; D001663:Bilirubin