Defective HNF4alpha-dependent gene expression as a driver of hepatocellular failure in alcoholic hepatitis

Alcoholic hepatitis (AH) is a life-threatening condition characterized by profound hepatocellular dysfunction for which targeted treatments are urgently needed. Identification of molecular drivers is hampered by the lack of suitable animal models. By performing RNA sequencing in livers from patients with different phenotypes of alcohol-related liver disease (ALD), we show that development of AH is characterized by defective activity of liver-enriched transcription factors (LETFs). TGFβ1 is a key upstream transcriptome regulator in AH and induces the use of HNF4α P2 promoter in hepatocytes, which results in defective metabolic and synthetic functions. Gene polymorphisms in LETFs including HNF4α are not associated with the development of AH. In contrast, epigenetic studies show that AH livers have profound changes in DNA methylation state and chromatin remodeling, affecting HNF4α-dependent gene expression. We conclude that targeting TGFβ1 and epigenetic drivers that modulate HNF4α-dependent gene expression could be beneficial to improve hepatocellular function in patients with AH

The epidermal growth factor receptor ligand amphiregulin is a negative regulator of hepatic acute-phase gene expression

BACKGROUND/AIMS: The modulation of the hepatic acute-phase reaction (APR) that occurs during inflammation and liver regeneration is important for allowing normal hepatocellular proliferation and the restoration of homeostasis. Activation of acute-phase protein (APP) gene expression by interleukin-6 (IL-6)-type cytokines is thought to be counteracted by growth factors released during hepatic inflammation and regeneration. The epidermal growth factor receptor (EGFR) ligand amphiregulin (AR) is readily induced by inflammatory signals and plays a nonredundant protective role during liver injury. In this paper, we investigated the role of AR as a modulator of liver APP gene expression. METHODS: Expression of APP genes was measured in the livers of AR(+/+) and AR(-/-)mice during inflammation and regeneration and in cultured liver cells treated with AR and oncostatin M (OSM). Crosstalk between AR and OSM signalling was studied. RESULTS: APP genes were overexpressed in the livers of AR(-/-) mice during inflammation and hepatocellular regeneration. In cultured AR-null hepatocytes and human hepatocellular carcinoma (HCC) cells after AR knockdown, APP gene expression is enhanced. AR counteracts OSM-triggered signal transducer and activator of transcription 3 signalling in hepatocytes and attenuates APP gene transcription. CONCLUSIONS: Our data support the relevance of EGFR-mediated signalling in the modulation of cytokine-activated pathways. We have identified AR as a key regulator of hepatic APP gene expression during inflammation and liver regeneration

Defective HNF4alpha-dependent gene expression as a driver of hepatocellular failure in alcoholic hepatitis

Alcoholic hepatitis (AH) is a life-threatening condition characterized by profound hepatocellular dysfunction for which targeted treatments are urgently needed. Identification of molecular drivers is hampered by the lack of suitable animal models. By performing RNA sequencing in livers from patients with different phenotypes of alcohol-related liver disease (ALD), we show that development of AH is characterized by defective activity of liver-enriched transcription factors (LETFs). TGFβ1 is a key upstream transcriptome regulator in AH and induces the use of HNF4α P2 promoter in hepatocytes, which results in defective metabolic and synthetic functions. Gene polymorphisms in LETFs including HNF4α are not associated with the development of AH. In contrast, epigenetic studies show that AH livers have profound changes in DNA methylation state and chromatin remodeling, affecting HNF4α-dependent gene expression. We conclude that targeting TGFβ1 and epigenetic drivers that modulate HNF4α-dependent gene expression could be beneficial to improve hepatocellular function in patients with AH

Pilot multi-omic analysis of human bile from benign and malignant biliary strictures: A machine-learning approach

Cholangiocarcinoma (CCA) and pancreatic adenocarcinoma (PDAC) may lead to the development of extrahepatic obstructive cholestasis. However, biliary stenoses can also be caused by benign conditions, and the identification of their etiology still remains a clinical challenge. We performed metabolomic and proteomic analyses of bile from patients with benign (n = 36) and malignant conditions, CCA (n = 36) or PDAC (n = 57), undergoing endoscopic retrograde cholangiopancreatography with the aim of characterizing bile composition in biliopancreatic disease and identifying biomarkers for the differential diagnosis of biliary strictures. Comprehensive analyses of lipids, bile acids and small molecules were carried out using mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (1H-NMR) in all patients. MS analysis of bile proteome was performed in five patients per group. We implemented artificial intelligence tools for the selection of biomarkers and algorithms with predictive capacity. Our machine-learning pipeline included the generation of synthetic data with properties of real data, the selection of potential biomarkers (metabolites or proteins) and their analysis with neural networks (NN). Selected biomarkers were then validated with real data. We identified panels of lipids (n = 10) and proteins (n = 5) that when analyzed with NN algorithms discriminated between patients with and without cancer with an unprecedented accurac

Pilot multi-omic analysis of human bile from benign and malignant biliary strictures: A machine-learning approach

Cholangiocarcinoma (CCA) and pancreatic adenocarcinoma (PDAC) may lead to the development of extrahepatic obstructive cholestasis. However, biliary stenoses can also be caused by benign conditions, and the identification of their etiology still remains a clinical challenge. We performed metabolomic and proteomic analyses of bile from patients with benign (n = 36) and malignant conditions, CCA (n = 36) or PDAC (n = 57), undergoing endoscopic retrograde cholangiopancreatography with the aim of characterizing bile composition in biliopancreatic disease and identifying biomarkers for the differential diagnosis of biliary strictures. Comprehensive analyses of lipids, bile acids and small molecules were carried out using mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (1H-NMR) in all patients. MS analysis of bile proteome was performed in five patients per group. We implemented artificial intelligence tools for the selection of biomarkers and algorithms with predictive capacity. Our machine-learning pipeline included the generation of synthetic data with properties of real data, the selection of potential biomarkers (metabolites or proteins) and their analysis with neural networks (NN). Selected biomarkers were then validated with real data. We identified panels of lipids (n = 10) and proteins (n = 5) that when analyzed with NN algorithms discriminated between patients with and without cancer with an unprecedented accurac

Activation of the unfolded protein response (UPR) is associated with cholangiocellular injury, fibrosis and carcinogenesis in an experimental model of fibropolycystic liver disease

Polycystic liver disease (PLD) is a group of rare disorders that result from structural changes in the biliary tree development in the liver. In the present work, we studied alterations in molecular mechanisms and signaling pathways that might be responsible for these pathologies. We found that activation of the unfolded protein response, a process that occurs in response to an accumulation of unfolded or misfolded proteins in the lumen of the endoplasmic reticulum, as well as the scarring of the liver tissue, contribute to the pathogenesis of PLD and the development of cancer. As a preclinical animal model we have used mutant mice of a specific signaling pathway, the c-Jun N-terminal kinase 1/2 (Jnk1/2). These mice resemble a perfect model for the study of PLD and early cancer development

Activation of the unfolded protein response (UPR) is associated with cholangiocellular injury, fibrosis and carcinogenesis in an experimental model of fibropolycystic liver disease

Polycystic liver disease (PLD) is a group of rare disorders that result from structural changes in the biliary tree development in the liver. In the present work, we studied alterations in molecular mechanisms and signaling pathways that might be responsible for these pathologies. We found that activation of the unfolded protein response, a process that occurs in response to an accumulation of unfolded or misfolded proteins in the lumen of the endoplasmic reticulum, as well as the scarring of the liver tissue, contribute to the pathogenesis of PLD and the development of cancer. As a preclinical animal model we have used mutant mice of a specific signaling pathway, the c-Jun N-terminal kinase 1/2 (Jnk1/2). These mice resemble a perfect model for the study of PLD and early cancer development

Defective HNF4alpha-dependent gene expression as a driver of hepatocellular failure in alcoholic hepatitis

Alcoholic hepatitis (AH) is a life-threatening condition characterized by profound hepatocellular dysfunction for which targeted treatments are urgently needed. Identification of molecular drivers is hampered by the lack of suitable animal models. By performing RNA sequencing in livers from patients with different phenotypes of alcohol-related liver disease (ALD), we show that development of AH is characterized by defective activity of liver-enriched transcription factors (LETFs). TGFβ1 is a key upstream transcriptome regulator in AH and induces the use of HNF4α P2 promoter in hepatocytes, which results in defective metabolic and synthetic functions. Gene polymorphisms in LETFs including HNF4α are not associated with the development of AH. In contrast, epigenetic studies show that AH livers have profound changes in DNA methylation state and chromatin remodeling, affecting HNF4α-dependent gene expression. We conclude that targeting TGFβ1 and epigenetic drivers that modulate HNF4α-dependent gene expression could be beneficial to improve hepatocellular function in patients with AH