4 research outputs found

    Atorvastatin favorably modulates a clinical hepatocellular carcinoma risk gene signature

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    Lipophilic but not hydrophilic statins have been shown to be associated with reduced risk for hepatocellular carcinoma (HCC) in patients with chronic viral hepatitis. We investigated differential actions of lipophilic and hydrophilic statins and their ability to modulate a clinical prognostic liver signature (PLS) predicting HCC risk in patients with liver disease. Hepatitis C virus (HCV)-infected Huh7.5.1 cells, recently developed as a model to screen HCC chemopreventive agents, were treated with lipophilic statins (atorvastatin and simvastatin) and hydrophilic statins (rosuvastatin and pravastatin), and then analyzed by RNA sequencing and PLS. Lipophilic statins, particularly atorvastatin, more significantly suppressed the HCV-induced high-risk pattern of PLS and genes in YAP and AKT pathway implicated in fibrogenesis and carcinogenesis, compared with the hydrophilic statins. While atorvastatin inhibited YAP activation through the mevalonate pathway, the distinctive AKT inhibition of atorvastatin was mediated by stabilizing truncated retinoid X receptor alpha, which has been known to enhance AKT activation, representing a target for HCC chemoprevention. In addition, atorvastatin modulated the high-risk PLS in an in vitro model of nonalcoholic fatty liver disease (NAFLD). Conclusion: Atorvastatin distinctively inhibits YAP and AKT activation, which are biologically implicated in HCC development, and attenuates a high-risk PLS in an in vitro model of HCV infection and NAFLD. These findings suggest that atorvastatin is the most potent statin to reduce HCC risk in patients with viral and metabolic liver diseases

    Hepatocellular carcinoma chemoprevention by targeting the angiotensin-converting enzyme and EGFR transactivation

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    Hepatocellular carcinoma (HCC) is a leading cause of death among cirrhotic patients, for which chemopreventive strategies are lacking. Recently, we developed a simple human cell-based system modeling a clinical prognostic liver signature (PLS) predicting liver disease progression and HCC risk. In a previous study, we applied our cell-based system for drug discovery and identified captopril, an approved angiotensin converting enzyme (ACE) inhibitor, as a candidate compound for HCC chemoprevention. Here, we explored ACE as a therapeutic target for HCC chemoprevention. Captopril reduced liver fibrosis and effectively prevented liver disease progression toward HCC development in a diethylnitrosamine (DEN) rat cirrhosis model and a diet-based rat model for nonalcoholic steatohepatitis–induced (NASH-induced) hepatocarcinogenesis. RNA-Seq analysis of cirrhotic rat liver tissues uncovered that captopril suppressed the expression of pathways mediating fibrogenesis, inflammation, and carcinogenesis, including epidermal growth factor receptor (EGFR) signaling. Mechanistic data in liver disease models uncovered a cross-activation of the EGFR pathway by angiotensin. Corroborating the clinical translatability of the approach, captopril significantly reversed the HCC high-risk status of the PLS in liver tissues of patients with advanced fibrosis. Captopril effectively prevents fibrotic liver disease progression toward HCC development in preclinical models and is a generic and safe candidate drug for HCC chemoprevention

    A human liver cell-based system modeling a clinical prognostic liver signature for therapeutic discovery

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    International audienceAbstract Chronic liver disease and hepatocellular carcinoma (HCC) are life-threatening diseases with limited treatment options. The lack of clinically relevant/tractable experimental models hampers therapeutic discovery. Here, we develop a simple and robust human liver cell-based system modeling a clinical prognostic liver signature (PLS) predicting long-term liver disease progression toward HCC. Using the PLS as a readout, followed by validation in nonalcoholic steatohepatitis/fibrosis/HCC animal models and patient-derived liver spheroids, we identify nizatidine, a histamine receptor H2 (HRH2) blocker, for treatment of advanced liver disease and HCC chemoprevention. Moreover, perturbation studies combined with single cell RNA-Seq analyses of patient liver tissues uncover hepatocytes and HRH2 + , CLEC5A high , MARCO low liver macrophages as potential nizatidine targets. The PLS model combined with single cell RNA-Seq of patient tissues enables discovery of urgently needed targets and therapeutics for treatment of advanced liver disease and cancer prevention
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