BiofabricationBioengineeringPeer-reviewed journal article
A microvascularized in vitro liver model for disease modeling and drug discovery
Flavio BonaniniiD, Roelof Dinkelberg, Manuel Caro TorregrosaiD, Nienke Kortekaas, Tessa M. S. HagensiD, Stéphane TreillardiD, Dorota KurekiD, Vincent van DuineniD, Paul VultoiD, Kristin M. BircsakiD
Abstract
Drug discovery for complex liver diseases faces alarming attrition rates. The lack of non-clinical models that recapitulate key aspects of liver (patho)-physiology is likely contributing to the inefficiency of developing effective treatments. Of particular notice is the common omission of an organized microvascular component despite its importance in maintaining liver function and its involvement in the development of several pathologies. Increasing the complexity of in vitro models is usually associated with a lack of scalability and robustness which hinders their implementation in drug development pipelines. Here, we describe a comprehensive liver MPS model comprising stellates, liver-derived endothelial cells and hepatocytes conceived within a scalable and automated platform. We show that endothelial cells self-organize in a microvascular network when co-cultured with stellates in a hydrogel. In a tri-culture, hepatocytes polarize accordingly, with a basolateral side facing blood vessels and an apical side facing bile-canaliculi-like structures. Stellates interact and surround the hollow microvessels. Steatosis was induced by exogenous administration of fatty acids which could be prevented by co-administration of firsocostat. Administration of TGF-{beta} resulted in an activated stellate cells phenotype which could be prevented by the co-administration of SB-431542. The model was implemented on a microtiter plate format comprising 64 chips which enabled the development of a fully automated, multiplexed fibrosis assay with a robust Z factor suitable for high-throughput applications.
- assay: organoid / primary culture
- research focus: drug response / drug discovery
- research focus: differential expression
- research focus: cell-cell communication
- approach: experimental assay
- Citations
- 18
- FWCI
- 1.72
- Field percentile
- top 16%
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