Decellularized liver scaffolds for constructing drug-metabolically functional <i>ex vivo</i> human liver models.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 39386220.
- Also identified by DOI 10.1016/j.bioactmat.2024.09.029 and PMC identifier 11462156.
- Licence recorded as CC BY-NC-ND.
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Abstract
The creation of <i>ex vivo</i> human liver models has long been a critical objective in academic, clinical, and pharmaceutical research, particularly for drug development, where accurate evaluation of hepatic metabolic dynamics is crucial. We have developed a bioengineered, perfused, organ-level human liver model that accurately replicates key liver functions, including metabolic activities, and protein synthesis, thus addressing some of the limitations associated with traditional liver monolayers, organoids, and matrix-embedded liver cells. Our approach utilizes liver-specific biomatrix scaffolds, prepared using an innovative protocol and fortified with matrix components that facilitate cellular interactions. These scaffolds, when seeded with human fetal liver cells or co-seeded with liver parenchymal and endothelial cell lines, enable the formation of three-dimensional (3D) human livers with enhanced cellular organization. The "recellularized tissue-engineered livers" (RCLs) have undergone various analyses, demonstrating the capability for establishing liver microenvironments <i>ex vivo</i>. Within 7-14 days, the RCLs exhibit evidence of liver differentiation and metabolic capabilities, underscoring the potential for use in drug metabolism and toxicity studies. Although our study represents a significant step forward, we acknowledge the need for direct comparisons with existing models and further research to fully elucidate the spectrum of regenerative responses. The high drug-metabolizing enzyme activity of RCLs, as demonstrated in our study, provides a promising avenue for investigating drug-induced liver injury mechanisms, contributing to a more detailed understanding of early drug discovery processes.