The hepatotoxic potential of a mixture of toluene, styrene and ethanol: in silico toxicogenomic data-mining

Nina Umićević; Katarina  Baralić; Danijela Djukić-Ćosić; Evica Antonijević Miljaković; Aleksandra  Buha Djordjević; Marijana Ćurčić; Zorica Bulat; Biljana Antonijević

Nina Umićević University of Banja Luka – Faculty of Medicine, Department of Toxicology
Katarina Baralić University of Belgrade – Faculty of Pharmacy, Department of Toxicology „Akademik Danilo Soldatović“
Danijela Djukić-Ćosić University of Banja Luka – Faculty of Medicine, Department of Toxicology; University of Belgrade – Faculty of Pharmacy, Department of Toxicology „Akademik Danilo Soldatović“
Evica Antonijević Miljaković University of Belgrade – Faculty of Pharmacy, Department of Toxicology „Akademik Danilo Soldatović“
Aleksandra Buha Djordjević University of Belgrade – Faculty of Pharmacy, Department of Toxicology „Akademik Danilo Soldatović“
Marijana Ćurčić University of Belgrade – Faculty of Pharmacy, Department of Toxicology „Akademik Danilo Soldatović“
Zorica Bulat University of Belgrade – Faculty of Pharmacy, Department of Toxicology „Akademik Danilo Soldatović“
Biljana Antonijević University of Banja Luka – Faculty of Medicine, Department of Toxicology; University of Belgrade – Faculty of Pharmacy, Department of Toxicology „Akademik Danilo Soldatović“

Abstract

Organic solvents are still widely used in various industries and considered the most common chemicals associated with liver injury in workers. For research into the relationships between these chemicals and genes, interactions among chemicals, molecular pathways and biological processes, a significant place in toxicity testing has been taken by in silico methodologies. This study aims to provide evidence for the involvement of a selected mixture of organic solvents (toluene, styrene, ethanol) in liver disease development and show the potential of in silico toxicogenomic data-mining in determining possible mechanisms of mixture toxicity. The Comparative Toxicogenomics Database (CTD), GeneMania and ToppGene Suite were used for data-mining. The results showed that there were 17 genes connected with liver injury common for all the tested solvents. Co-expression (61.73%) was the most prominent interaction between the genes, while physical interactions were present at 14.56%, co-localization at 12.54% and interactions predicted by the server at 6.62%. Gene ontology analysis revealed biological processes affected by the investigated mixture (reactive oxygen species metabolic and biosynthetic process, response to oxidative stress, and response to organic cyclic compound). Oxidative stress response, antioxidant and oxidoreductase activity, vitamin B12 metabolism were noted as the key molecular pathways contributing to liver disease development. Our results emphasize the role of oxidative stress as one of the mechanisms of organic solvents' mixture toxicity and provide new insights into molecular mechanisms involved in hepatotoxicity.