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

Area of Science:

• Toxicology
• Genomics
• Biotechnology

Background:

• High-content data can inform toxicant mechanisms of action, but most studies use in vivo data.
• Differentiated cells in culture may offer predictive toxicology potential via high-content approaches like whole-genome microarray.
• Primary rat hepatocytes were used to evaluate global gene expression changes in response to hepatotoxicants.

Purpose of the Study:

• To evaluate global gene expression changes in primary rat hepatocytes exposed to ten hepatotoxicants.
• To determine if gene expression analysis can predict toxicant mechanisms of action.
• To compare in vitro gene expression data with existing in vivo data.

Main Methods:

• Primary rat hepatocytes were exposed to two concentrations of ten hepatotoxicants for 24h and 48h.
• Whole-genome gene expression analysis was performed using Affymetrix microarrays.
• Cluster analysis and pathway-based filtering were used to analyze the data.

Main Results:

• Primary hepatocytes showed mode of action-specific gene expression changes in response to hepatotoxicants.
• Phthalates clustered together, as did other peroxisome proliferators (CLO, WY14643).
• Cytochrome P450 inducers (PB, MP, CPZ, BNF) also clustered together, while VPA and APAP showed unique profiles.
• In vitro results showed similarities to in vivo data for six tested chemicals.

Conclusions:

• Primary rat hepatocytes are a viable model for high-content screening in toxicology.
• Gene expression profiling in vitro can provide pertinent biological data for predicting in vivo hepatotoxicity.
• Pathway-based analysis enhances the robustness of gene expression data for toxicological predictions.