ReviewJournal of hepatocellular carcinoma2026
Etiology-Driven Mouse Models of Hepatocellular Carcinoma: Paving the Way for Precision Oncology.
Review in Journal of hepatocellular carcinoma, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
5 authors.
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Abstract
Background: Hepatocellular carcinoma (HCC) is biologically heterogeneous, and its genomic alterations, inflammatory context, and tumor immune microenvironment are strongly shaped by the underlying etiology, including chronic hepatitis B virus (HBV) infection, metabolic dysfunction-associated steatotic liver disease (MASLD), and alcohol exposure. This etiological diversity complicates the selection and interpretation of preclinical models. Genetically engineered mouse models (GEMMs), particularly when combined with dietary, chemical, viral, or alcohol-related insults, provide useful systems for dissecting how defined genetic drivers interact with disease-specific liver environments in an immunocompetent host. Main Body: This review summarizes etiology-aligned GEMMs and related mouse models for HCC. In HBV-related models, we discuss how viral antigen exposure, HBV-associated genomic instability, Short Conclusion: Etiology-aligned GEMMs can help match biological questions to appropriate preclinical platforms and generate testable hypotheses about therapy response. However, etiology alone should not be treated as a substitute for molecular profiling or clinical validation. Future models should integrate precise genetic engineering with fibrotic or cirrhotic backgrounds, microbiome-aware environmental modulation, and complementary human-relevant systems to better capture the complex evolution of human HCC.
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