Evaluating Anti-Fibrotic Therapies within a 3D Human MASH Model

Advancing MASH Research with AI-Driven Fibrosis Quantification

Metabolic dysfunction-associated steatohepatitis (MASH) is a severe liver disease characterized by lipid accumulation, inflammation, and fibrosis.

Progress in MASH therapy development has been hindered by the absence of human translational models and advanced fibrosis analysis techniques.

This study developed an algorithm for automated phenotypic quantification of fibrosis in Sirius Red-stained histology sections from InSphero’s 3D InSight™ Human Liver MASH (MASH LiMT) model using the AI-powered FibroNest digital pathology image analysis platform.

Process Flow of the MASH hLiMT Model for Drug Testing and Disease Analysis

The MASH hLiMT model comprises primary human hepatocytes, Kupffer cells, liver endothelial cells, and hepatic stellate cells.

Following exposure to defined lipotoxic and inflammatory stimuli (e.g., free fatty acids and LPS) in a high-sugar, high-insulin medium, the 3D model exhibited key pathophysiological features of MASH within 10 days.

Quantifiable markers for drug efficacy included pro-collagen type I/III secretion, TIMPs/MMPs levels, and fibrosis assessment using the FibroNest platform with Sirius Red-stained histology.

Gene expression changes were analyzed via next-generation sequencing.

Validation of FibroNest Algorithm in MASH LiMT Models

The FibroNest algorithm for MASH LiMT models was validated using anti-fibrotic reference compounds targeting distinct therapeutic pathways, including ALK5 inhibitors and anti-TGF-beta antibodies.

Phenotypic fibrosis quantification revealed that both compounds significantly reduced fibrillated collagen deposition, consistent with decreases in pro-collagen type I/III secretion, TIMP-1, MMP-3, and pro-fibrotic gene expression.

Comparatively, several clinical MASH compounds, either alone or in combination, showed strong anti-fibrotic effects on collagen fiber deposition but had a lesser impact on pro-fibrotic biomarker secretion.

Key Insight

Integrating phenotypic fibrosis quantification in MASH hLiMT models with pro-fibrotic biomarker secretion analysis and transcriptomics provides a robust and promising platform for assessing anti-fibrotic compounds in drug discovery.

By - Eeshan Aggarwal

Reference: Hepatology. Volume 80, Issue S1. Abstract Supplement for The Liver Meeting by the American Association for the Study of Liver Diseases (AASLD), November 15-19, 2024, San Diego, CA.