Fibroblast growth factors 19 and 21 in acute liver damage

Currently there are very few pharmacological options available to treat acute liver injury. Because its natural exposure to noxious stimuli the liver has developed a strong endogenous hepatoprotective capacity. Indeed, experimental evidence exposed a variety of endogenous hepatic and systemic responses naturally activated to protect the hepatic parenchyma and to foster liver regeneration, therefore preserving individual’s survival. The fibroblast growth factor (FGF) family encompasses a range of polypeptides with important effects on cellular differentiation, growth survival and metabolic regulation in adult organisms. Among these FGFs, FGF19 and FGF21 are endocrine hormones that profoundly influence systemic metabolism but also exert important hepatoprotective activities. In this review, we revisit the biology of these factors and highlight their potential application for the clinical management of acute liver injur

FOSL1 promotes cholangiocarcinoma via transcriptional effectors that could be therapeutically targeted

Understanding the molecular mechanisms involved in cholangiocarcinoma (bile duct cancer) development and progression stands as a critical step for the development of novel therapies. Through an inter-species approach, this study provides evidence of the clinical and functional role of the transcription factor FOSL1 in cholangiocarcinoma. Moreover, we report that downstream effectors of FOSL1 are susceptible to pharmacological inhibition, thus providing new opportunities for therapeutic intervention

Epigenetic mechanisms in gastric cancer: Potential new therapeutic opportunities

Gastric cancer (GC) is one of the deadliest malignancies worldwide. Complex disease heterogeneity, late diagnosis, and suboptimal therapies result in the poor prognosis of patients. Besides genetic alterations and environmental factors, it has been demonstrated that alterations of the epigenetic machinery guide cancer onset and progression, representing a hallmark of gastric malignancies. Moreover, epigenetic mechanisms undergo an intricate crosstalk, and distinct epigenomic profiles can be shaped under different microenvironmental contexts. In this scenario, targeting epigenetic mechanisms could be an interesting therapeutic strategy to overcome gastric cancer heterogeneity, and the efforts conducted to date are delivering promising results. In this review, we summarize the key epigenetic events involved in gastric cancer development. We conclude with a discussion of new promising epigenetic strategies for gastric cancer treatment

Fibroblast growth factors 19 and 21 in acute liver damage

Currently there are very few pharmacological options available to treat acute liver injury. Because its natural exposure to noxious stimuli the liver has developed a strong endogenous hepatoprotective capacity. Indeed, experimental evidence exposed a variety of endogenous hepatic and systemic responses naturally activated to protect the hepatic parenchyma and to foster liver regeneration, therefore preserving individual’s survival. The fibroblast growth factor (FGF) family encompasses a range of polypeptides with important effects on cellular differentiation, growth survival and metabolic regulation in adult organisms. Among these FGFs, FGF19 and FGF21 are endocrine hormones that profoundly influence systemic metabolism but also exert important hepatoprotective activities. In this review, we revisit the biology of these factors and highlight their potential application for the clinical management of acute liver injur

Fragile X mental retardation protein in intrahepatic cholangiocarcinoma: regulating the cancer cell behavior plasticity at the leading edge.

Intrahepatic cholangiocarcinoma (iCCA) is a rare malignancy of the intrahepatic biliary tract with a very poor prognosis. Although some clinicopathological parameters can be prognostic factors for iCCA, the molecular prognostic markers and potential mechanisms of iCCA have not been well investigated. Here, we report that the Fragile X mental retardation protein (FMRP), a RNA binding protein functionally absent in patients with the Fragile X syndrome (FXS) and also involved in several types of cancers, is overexpressed in human iCCA and its expression is significantly increased in iCCA metastatic tissues. The silencing of FMRP in metastatic iCCA cell lines affects cell migration and invasion, suggesting a role of FMRP in iCCA progression. Moreover, we show evidence that FMRP is localized at the invasive front of human iCCA neoplastic nests and in pseudopodia and invadopodia protrusions of migrating and invading iCCA cancer cells. Here FMRP binds several mRNAs encoding key proteins involved in the formation and/or function of these protrusions. In particular, we find that FMRP binds to and regulates the expression of Cortactin, a critical regulator of invadopodia formation. Altogether, our findings suggest that FMRP could promote cell invasiveness modulating membrane plasticity and invadopodia formation at the leading edges of invading iCCA cells

FOSL1 promotes cholangiocarcinoma via transcriptional effectors that could be therapeutically targeted

Understanding the molecular mechanisms involved in cholangiocarcinoma (bile duct cancer) development and progression stands as a critical step for the development of novel therapies. Through an inter-species approach, this study provides evidence of the clinical and functional role of the transcription factor FOSL1 in cholangiocarcinoma. Moreover, we report that downstream effectors of FOSL1 are susceptible to pharmacological inhibition, thus providing new opportunities for therapeutic intervention

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