Objective: Fibroblast growth factor 15/19 (FGF15/19), an enterokine that regulates synthesis of hepatic bile acids (BA), has been proposed to influence fat metabolism. Without FGF15/19, mouse liver regeneration after partial hepatectomy (PH) is severely impaired. We studied the role of FGF15/19 in response to a high fat diet (HFD) and its regulation by saturated fatty acids. We developed a fusion molecule encompassing FGF19 and apolipoprotein A-I, termed Fibapo, and evaluated its pharmacological properties in fatty liver regeneration. Design: Fgf15^−/− mice were fed a HFD. Liver fat and the expression of fat metabolism and endoplasmic reticulum (ER) stress-related genes were measured. Influence of palmitic acid (PA) on FGF15/19 expression was determined in mice and in human liver cell lines. In vivo half-life and biological activity of Fibapo and FGF19 were compared. Hepatoprotective and proregenerative activities of Fibapo were evaluated in obese db/db mice undergoing PH. Results: Hepatosteatosis and ER stress were exacerbated in HFD-fed Fgf15^−/− mice. Hepatic expression of Pparγ2 was elevated in Fgf15^−/− mice, being reversed by FGF19 treatment. PA induced FGF15/19 expression in mouse ileum and human liver cells, and FGF19 protected from PA-mediated ER stress and cytotoxicity. Fibapo reduced liver BA and lipid accumulation, inhibited ER stress and showed enhanced half-life. Fibapo provided increased db/db mice survival and improved regeneration upon PH. Conclusions: FGF15/19 is essential for hepatic metabolic adaptation to dietary fat being a physiological regulator of Pparγ2 expression. Perioperative administration of Fibapo improves fatty liver regeneration.

Genome instability is related to disease development and carcinogenesis. DNA lesions are caused by genotoxic compounds but also by the dysregulation of fundamental processes like transcription, DNA replication and mitosis. Recent evidence indicates that impaired expression of RNA-binding proteins results in mitotic aberrations and the formation of transcription-associated RNA–DNA hybrids (R-loops), events strongly associated with DNA injury. We identify the splicing regulator SLU7 as a key mediator of genome stability. SLU7 knockdown results in R-loops formation, DNA damage, cell-cycle arrest and severe mitotic derangements with loss of sister chromatid cohesion (SCC). We define a molecular pathway through which SLU7 keeps in check the generation of truncated forms of the splicing factor SRSF3 (SRp20) (SRSF3-TR). Behaving as dominant negative, or by gain-of-function, SRSF3-TR impair the correct splicing and expression of the splicing regulator SRSF1 (ASF/SF2) and the crucial SCC protein sororin. This unique function of SLU7 was found in cancer cells of different tissue origin and also in the normal mouse liver, demonstrating a conserved and fundamental role of SLU7 in the preservation of genome integrity. Therefore, the dowregulation of SLU7 and the alterations of this pathway that we observe in the cirrhotic liver could be involved in the process of hepatocarcinogenesis.

Intrahepatic accumulation of bile acids (BAs) causes hepatocellular injury. Upon liver damage, a potent protective response is mounted to restore the organ’s function. Epidermal growth factor receptor (EGFR) signaling is essential for regeneration after most types of liver damage, including cholestatic injury. However, EGFR can be activated by a family of growth factors induced during liver injury and regeneration. We evaluated the role of the EGFR ligand, amphiregulin (AREG), during cholestatic liver injury and regulation of AREG expression by BAs. First, we demonstrated increased AREG levels in livers from patients with primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC). In two murine models of cholestatic liver injury, bile duct ligation (BDL) and alpha‐naphthyl‐isothiocyanate (ANIT) gavage, hepatic AREG expression was markedly up‐regulated. Importantly, Areg–/– mice showed aggravated liver injury after BDL and ANIT administration compared to Areg+/+ mice. Recombinant AREG protected from ANIT and BDL‐induced liver injury and reduced BA‐triggered apoptosis in liver cells. Oral BA administration induced ileal and hepatic Areg expression, and, interestingly, cholestyramine feeding reduced postprandial Areg up‐regulation in both tissues. Most interestingly, Areg–/– mice displayed high hepatic cholesterol 7 α‐hydroxylase (CYP7A1) expression, reduced serum cholesterol, and high BA levels. Postprandial repression of Cyp7a1 was impaired in Areg–/– mice, and recombinant AREG down‐regulated Cyp7a1 mRNA in hepatocytes. On the other hand, BAs promoted AREG gene expression and protein shedding in hepatocytes. This effect was mediated through the farnesoid X receptor (FXR), as demonstrated in Fxr–/– mice, and involved EGFR transactivation. Finally, we show that hepatic EGFR expression is indirectly induced by BA‐FXR through activation of suppressor of cytokine signaling‐3 (SOC3). Conclusion: AREG‐EGFR signaling protects from cholestatic injury and participates in the physiological regulation of BA synthesis.

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 accuracy.