Improved identification of human hepatotoxic potential by summary variables of gene expression
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Abstract
Prediction of hepatotoxicity in humans remains an unresolved challenge. Recently, an in-vitro/in-silico-method was established to predict blood concentrations of test compounds with an increased risk of causing human hepatotoxicity. In the present study, we addressed the question whether gene expression data can improve the quality of hepatotoxicity prediction compared to cytotoxicity analysis alone. A particular challenge is that high-dimensional gene expression data must be summarized into variables that allow for the determination of the lowest test compound concentration that causes altered gene expression. To address this challenge, we analyzed 60 hepatotoxic and non-hepatotoxic substances in a concentration dependent manner for cytotoxicity and expression of 3,524 probes, whose expression were previously reported to be influenced by hepatotoxicants. The toxicity separation index (TSI) was applied to quantify how well specific summary variables of gene expression are able to differentiate between the set of hepatotoxic and non-hepatotoxic substances. The best TSI was obtained when the lowest concentration of a test compound was considered positive that led to differential expression of two genes when compared to vehicle controls. Furthermore, the best gene expression-based summary variable was superior to cytotoxicity-based variables alone, and the combination of the best summary variables of gene expression and cytotoxicity data further improved the TSI compared to each category alone. In conclusion, the method used to derive summary variables of gene expression is critical and the best summary variables improve the prediction of hepatotoxic substances in relation to oral doses and blood concentrations in humans.
Plain language summary
Liver injury is a relevant side effect of many drugs. It represents the most common cause of acute liver failure in Western countries as well as the most common reason for late-stage drug development failure or withdrawal of drugs from the market. We show that genome-wide gene expression analysis of drug-exposed cultured human hepatocytes can differentiate between hepatotoxic and non-hepatotoxic substances. A precondition, is that the multivariate gene expression variables are summarized by the here described technique to a single variable that indicates the lowest concentration where a test substances begins to influence gene expression. A second precondition is that testing includes the plasma peak concentration of the test compounds for therapeutic doses of the respective compounds. The here presented in vitro/in silico procedure can reduce the number of animals needed in pre-clinical safety studies as liver damaging drug candidates would be detected prior to the studies in rodents.
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