Journal
TOXICOLOGICAL SCIENCES
Volume 173, Issue 1, Pages 32-40Publisher
OXFORD UNIV PRESS
DOI: 10.1093/toxsci/kfz214
Keywords
artificial intelligence; AOP-helpFinder; integrative systems toxicology; adverse outcome pathway network; HBM4EU
Categories
Funding
- European Union's Horizon 2020 research and innovation programme [733032 HBM4EU]
- Universite de Paris
- Assistance Publique-Hopitaux-de-Paris
- INSERM
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Bisphenol F (BPF) is one of several Bisphenol A (BPA) substituents that is increasingly used in manufacturing industry leading to detectable human exposure. Whereas a large number of studies have been devoted to decipher BPA effects, much less is known about its substituents. To support decision making on BPF's safety, we have developed a new computational approach to rapidly explore the available data on its toxicological effects, combining text mining and integrative systems biology, and aiming at connecting BPF to adverse outcome pathways (AOPs). We first extracted from different databases BPF-protein associations that were expanded to protein complexes using protein-protein interaction datasets. Over-representation analysis of the protein complexes allowed to identify the most relevant biological pathways putatively targeted by BPF. Then, automatic screening of scientific abstracts from literature using the text mining tool, AOP-helpFinder, combined with data integration from various sources (AOP-wiki, CompTox, etc.) and manual curation allowed us to link BPF to AOP events. Finally, we combined all the information gathered through those analyses and built a comprehensive complex framework linking BPF to an AOP network including, as adverse outcomes, various types of cancers such as breast and thyroid malignancies. These results which integrate different types of data can support regulatory assessment of the BPA substituent, BPF, and trigger new epidemiological and experimental studies.
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