Prediction of metabolism-induced hepatotoxicity on three-dimensional hepatic cell culture and enzyme microarrays
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Human liver contains various oxidative and conjugative enzymes that can convert nontoxic parent compounds to toxic metabolites or, conversely, toxic parent compounds to nontoxic metabolites. Unlike primary hepatocytes, which contain myriad drug-metabolizing enzymes (DMEs), but are difficult to culture and maintain physiological levels of DMEs, immortalized hepatic cell lines used in predictive toxicity assays are easy to culture, but lack the ability to metabolize compounds. To address this limitation and predict metabolism-induced hepatotoxicity in high-throughput, we developed an advanced miniaturized three-dimensional (3D) cell culture array (DataChip 2.0) and an advanced metabolizing enzyme microarray (MetaChip 2.0). The DataChip is a functionalized micropillar chip that supports the Hep3B human hepatoma cell line in a 3D microarray format. The MetaChip is a microwell chip containing immobilized DMEs found in the human liver. As a proof of concept for generating compound metabolites in situ on the chip and rapidly assessing their toxicity, 22 model compounds were dispensed into the MetaChip and sandwiched with the DataChip. The IC50 values obtained from the chip platform were correlated with rat LD50 values, human C max values, and drug-induced liver injury categories to predict adverse drug reactions in vivo. As a result, the platform had 100% sensitivity, 86% specificity, and 93% overall predictivity at optimum cutoffs of IC50 and C max values. Therefore, the DataChip/MetaChip platform could be used as a high-throughput, early stage, microscale alternative to conventional in vitro multi-well plate platforms and provide a rapid and inexpensive assessment of metabolism-induced toxicity at early phases of drug development.
KeywordsMetabolism-induced hepatotoxicity Three-dimensional (3D) cell culture array Metabolizing enzyme microarray DataChip/MetaChip High-throughput toxicity screening
We acknowledge support from the National Institute of Environmental Health Sciences (ES018022, ES012619, and ES025779) and National Science Foundation (IIP-0740592). This work was partly supported by Samsung Electro-Mechanics Co. (SEMCO), Ltd. The authors are grateful to Dr. Byeong-Cheon Koh (former Executive Vice President) and members of the cell chip research group in SEMCO for helpful suggestions and assistance with chip fabrication.
Compliance with ethical standards
Conflict of interest
The research was partly supported by Samsung Electro-Mechanics Co. (SEMCO). Thus, the authors declare that there might be potential conflict of interest.
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