A novel transcriptomics based in vitro method to compare and predict hepatotoxicity based on mode of action.

摘要: Abstract High-content data have the potential to inform mechanism of action for toxicants. However, most support this notion been generated in vivo. Because many cell lines and primary cells maintain a differentiated phenotype, it is possible that grown culture may also be useful predictive toxicology via high-content approaches such as whole-genome microarray. We evaluated global changes gene expression rat hepatocytes exposed two concentrations ten hepatotoxicants: acetaminophen (APAP), β-naphthoflavone (BNF), chlorpromazine (CPZ), clofibrate (CLO), bis(2-ethylhexyl)phthalate (DEHP), diisononyl phthalate (DINP), methapyrilene (MP), valproic acid (VPA), phenobarbital (PB) WY14643 at separate time points. These compounds were selected cover range mechanisms toxicity, with some overlap expected address question how analysis is, given mode action. Gene microarray was performed on after 24 h 48 h exposure each chemical using Affymetrix microarrays. Cluster suggests hepatocyte model capable responding these hepatotoxicants, appear action-specific. Among different methods used data, combination method pathways (MOAs) filter total probesets provided robust analysis. The resulted phthalates clustering closely together, other peroxisome proliferators, CLO WY14643, eliciting similar responses pathway levels. Cyp inducers PB, MP, CPZ BNF clustered together. VPA APAP had profiles unique. A externally available (TG-GATES) vivo 6 chemicals (APAP, CLO, CPZ, MP WY14643) compared vitro result. results indicate transcription profiling an assay offer pertinent biological predictions hepatotoxicity potential.