ArticleCell cycle (Georgetown, Tex.)
c-Jun and Fra-2 pair up to Myc-anistically drive HCC.
Article in Cell cycle (Georgetown, Tex.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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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Who cites it
1 citing paper in PubMed.
- Validation of signature molecular profiles of advanced HCV liver disease in hepatocellular carcinoma patients.Virus research · 2025Article
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2 authors.
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Abstract
Hepatocellular carcinoma (HCC), a leading cause of cancer-related death with limited therapies, is a complex disease developing in a background of Hepatitis Virus infection or systemic conditions, such as the metabolic syndrome. Investigating HCC pathogenesis in model organisms is therefore crucial for developing novel diagnostic and therapeutic tools. Genetically engineered mouse models (GEMMs) have been instrumental in recapitulating the local and systemic features of HCC. Early studies using GEMMs and patient material implicated members of the dimeric Activator Protein-1 (AP-1) transcription factor family, such as c-Jun and c-Fos, in HCC formation. In a recent report, we described how switchable, hepatocyte-restricted expression of a single-chain c-Jun~Fra-2 protein, functionally mimicking the c-Jun/Fra-2 AP-1 dimer, results in spontaneous and largely reversible liver tumors in GEMMs. Dysregulated cell cycle, inflammation, and dyslipidemia are observed at early stages and tumors display molecular HCC signatures. We demonstrate that increased c-Myc expression is an essential molecular determinant of tumor formation that can be therapeutically targeted using the BET inhibitor JQ1. Here, we discuss these findings with additional results illustrating how AP-1 GEMMs can foster preclinical research on liver diseases with novel perspectives offered by the constantly increasing wealth of HCC-related datasets.
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