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Metabolic dysfunction-associated steatotic liver disease and steatohepatitis-associated hepatocarcinoma preclinical models

Lookup NU author(s): Dr Jack LeslieORCiD, Professor Fiona OakleyORCiD

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Abstract

© Springer Nature Limited 2026. Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses liver steatosis and metabolic dysfunction-associated steatohepatitis (MASH), which can result in fibrosis and/or cirrhosis and increase the risk of hepatocellular carcinoma (HCC). The latest Clinical Practice Guidelines acknowledge the importance of systemic metabolic dysfunction as a driver of hepatic lipid accumulation and disease progression. To ensure translational relevance of preclinical models, they need to faithfully replicate the key human pathophysiological characteristics of MASLD and its progression to fibrosis and HCC. This Review discusses the strengths and weaknesses of prevalent MASLD and MASH-HCC preclinical models, expanding the discussion to the latest advances in vivo (for example, genetically altered, humanized and large animals) and in vitro (for example, organoids or spheroids, 3D-bioprinted livers, precision-cut liver slices, organs-on-a-chip and decellularized scaffolds). Evidence will be critically re-assessed according to the new MASLD definition, paving a consensus in the field for nomenclature, expected limitations and how to conduct a systematic validation of new models against human-relevant disease outcomes. We also propose a standardized pipeline for preclinical studies in MASLD and MASH-HCC. This Review aims to help researchers make informed decisions when choosing an experimental design that best aligns with the specific requirements of their projects, whilst meaningfully replicating human disease.


Publication metadata

Author(s): Leslie J, Krishnamurthy KA, Gopalsamy IK, Inacio P, Huch M, Gallage S, Oakley F, Vacca M

Publication type: Review

Publication status: Published

Journal: Nature Reviews Gastroenterology and Hepatology

Year: 2026

Pages: Epub ahead of print

Online publication date: 26/01/2026

Acceptance date: 26/11/2025

ISSN (print): 1759-5045

ISSN (electronic): 1759-5053

Publisher: Nature Research

URL: https://doi.org/10.1038/s41575-025-01162-9

DOI: 10.1038/s41575-025-01162-9


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