Prediction of Non-Genotoxic Carcinogenicity Based on Genetic Profiles of Short Term Exposure Assays

PEREZ, O; PERAL GARCIA, P; GONZÁLEZ JOSÉ, ROLANDO

Toxicological Research

Korean Society of Toxicology

Lugar: Cheongpa-ro; Año: 2016 vol. 32 p. 289 - 300

1976-8257

Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms andlong term rodent bioassays are required to identify them. Recent studies have shown that transcription profilingcan be applied to develop early identifiers for long term phenotypes. In this study, we used rat liverexpression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrixDatabase to construct a gene classifier that can distinguish between non-genotoxic carcinogens and otherchemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidativestressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performedon independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics AssistedToxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together witha recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functionalinterpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictorof 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased withincreasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses.Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism.The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis,we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposureassays. In this approach, dose level is critical when evaluating chemicals at early time points.