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RESEARCH PRODUCT

A metabolomics cell-based approach for anticipating and investigating drug-induced liver injury

Agustín LahozJuan Carlos García-cañaverasJosé V. CastellM. Teresa Donato

subject

Bioquímica0301 basic medicineDrugmedia_common.quotation_subjectMetaboliteBiologyPharmacologymedicine.disease_causeBioinformaticsModels BiologicalArticleMass Spectrometry03 medical and health scienceschemistry.chemical_compound0302 clinical medicineMetabolomicsmedicineHumansMetabolomicsToxicologiaPhospholipidsmedia_commonPhospholipidosisMultidisciplinaryHep G2 Cellsmedicine.diseaseGlutathioneFatty LiverOxidative Stress030104 developmental biologychemistryDrug development030220 oncology & carcinogenesisToxicityChemical and Drug Induced Liver InjurySteatosisOxidative stress

description

AbstractIn preclinical stages of drug development, anticipating potential adverse drug effects such as toxicity is an important issue for both saving resources and preventing public health risks. Current in vitro cytotoxicity tests are restricted by their predictive potential and their ability to provide mechanistic information. This study aimed to develop a metabolomic mass spectrometry-based approach for the detection and classification of drug-induced hepatotoxicity. To this end, the metabolite profiles of human derived hepatic cells (i.e., HepG2) exposed to different well-known hepatotoxic compounds acting through different mechanisms (i.e., oxidative stress, steatosis, phospholipidosis and controls) were compared by multivariate data analysis, thus allowing us to decipher both common and mechanism-specific altered biochemical pathways. Briefly, oxidative stress damage markers were found in the three mechanisms, mainly showing altered levels of metabolites associated with glutathione and γ-glutamyl cycle. Phospholipidosis was characterized by a decreased lysophospholipids to phospholipids ratio, suggestive of phospholipid degradation inhibition. Whereas, steatosis led to impaired fatty acids β-oxidation and a subsequent increase in triacylglycerides synthesis. The characteristic metabolomic profiles were used to develop a predictive model aimed not only to discriminate between non-toxic and hepatotoxic drugs, but also to propose potential drug toxicity mechanism(s).

https://doi.org/10.1038/srep27239