About the efficacy of anti-fibrotic compounds in human 3D MASH Model
Background
Metabolic dysfunction-associated steatohepatitis (MASH) is a severe liver disease characterized by lipid accumulation, inflammation, and fibrosis. The development of MASH therapies has been hindered by the lack of human translational models and limitations of analysis techniques for fibrosis. Here, we aimed to establish an algorithm for automated phenotypic quantification of fibrosis of Sirius Red stained histology sections of InSphero’s 3D InSight™ Human liver MASH (MASH LiMT) model using a digital pathology quantitative single-fiber artificial intelligence FibroNest image analysis platform.
Method
The MASH hLiMT model consists of primary human hepatocytes, Kupffer cells, liver endothelial cells, and hepatic stellate cells. Upon exposure to defined lipotoxic and inflammatory stimuli such as free fatty acids and LPS in media containing high levels of sugar and insulin, the 3D MASH model displayed key disease pathophysiological features within 10 days of treatment. Quantifiable markers were established for drug efficacy testing, such as secretion of pro-collagen type I/III and TIMPs/MMPs, as well as quantification of fibrosis using the FibroNest platform based on the Sirius Red staining of histology slides. Next-generation sequencing was used to assess the changes in gene expression.
Results
The FibroNest algorithm for MASH hLiMTs was validated using anti-fibrotic reference compounds with different therapeutic modalities - ALK5i and anti-TGF-beta antibody. The phenotypic quantification of fibrosis demonstrated that both reference compounds decreased the deposition of fibrillated collagen in alignment with effects on the secretion of pro-collagen type I/III, tissue inhibitor of metalloproteinases-1 and matrix metalloproteinase-3 and pro-fibrotic gene expression. In contrast, several clinical MASH compounds, alone and in combination, showed strong anti-fibrotic effects on the deposition of collagen fibers; however, they were less pronounced on the secretion of pro-fibrotic biomarkers.
Conclusion
In summary, the phenotypic quantification of fibrosis of MASH hLiMTs combined with the secretion of pro-fibrotic biomarkers and transcriptomics represents a promising drug discovery tool for assessing anti-fibrotic compounds.
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