ArticleScientific reports2026
Temporal proteomic profiling of iPSC-derived human liver organoids reveals optimal maturation for drug metabolism and toxicology.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Liver Organoids: From Disease Modelling to Regenerative Medicine.Cell proliferation · 2026Review
- Recent advances and expanding applications of organoid models in unveiling drug ADME profiles.Journal of pharmaceutical analysis · 2026Review
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Authors and funding
4 authors.
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Abstract
Liver organoids have emerged as an innovative three-dimensional model system that effectively recapitulates the structural and functional complexities of human liver tissue, addressing limitations of traditional two-dimensional culture systems. This study presents a comprehensive temporal proteomic characterization of iPSC-derived human liver organoids (iHLOs) by profiling 5,736 proteins across their four developmental stages, Days 7, 15, 30, and 45, to identify optimal timepoints for drug metabolism and toxicological applications. The analysis revealed that Day 30 represents the peak of functional maturity, marked by the highest expression of key-metabolizing enzymes, such as cytochrome P450 3A4 (CYP3A4), along with cholangiocyte-specific proteins and hepatic metabolic enzymes. Functional validation of CYP3A4 activity through rifampicin induction and ketoconazole inhibition demonstrated metabolic competence comparable to existing in vitro liver models, including HepaRG cells and primary human hepatocytes. Interestingly, Day 45 organoids exhibited a shift toward a mesenchymal cell profile, with increased markers of hepatic stellate cells, suggesting utility for disease modeling applications. These findings indicate Day 30 of liver organoids as the optimal stage for drug metabolism and toxicological investigations, providing a proteomic framework that enhances their utility of iHLOs as physiologically relevant liver models.
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