Inhibition of NHE-1 Increases Smoke-Induced Proliferative Activity of Barrett’s Esophageal Cell Line

Several clinical studies indicate that smoking predisposes its consumers to esophageal inflammatory and malignant diseases, but the cellular mechanism is not clear. Ion transporters protect esophageal epithelial cells by maintaining intracellular pH at normal levels. In this study, we hypothesized that smoking affects the function of ion transporters, thus playing a role in the development of smoking-induced esophageal diseases. Esophageal cell lines were treated with cigarettesmoke extract (CSE), and the viability and proliferation of the cells, as well as the activity, mRNA and protein expression of the Na(+)/H(+) exchanger-1 (NHE-1), were studied. NHE-1 expression was also investigated in human samples. For chronic treatment, guinea pigs were exposed to tobacco smoke, and NHE-1 activity was measured. Silencing of NHE-1 was performed by using specific siRNA. CSE treatment increased the activity and protein expression of NHE-1 in the metaplastic cells and decreased the rate of proliferation in a NHE-1-dependent manner. In contrast, CSE increased the proliferation of dysplastic cells independently of NHE-1. In the normal cells, the expression and activity of NHE-1 decreased due to in vitro and in vivo smoke exposure. Smoking enhances the function of NHE-1 in Barrett’s esophagus, and this is presumably a compensatory mechanism against this toxic agent

Mouse organoid culture is a suitable model to study esophageal ion transport mechanisms

Altered esophageal ion transport mechanisms play a key role in inflammatory and cancerous diseases of the esophagus, but epithelial ion processes have been less studied in the esophagus because of the lack of a suitable experimental model. In this study, we generated 3D esophageal organoids (EOs) from two different mouse strains and characterized the ion transport processes of the EOs. EOs form a cell-filled structure with a diameter of 250-300 µm and generated from epithelial stem cells as shown by FACS analysis. Using conventional PCR and immunostaining, the presence of Slc26a6 Cl-/HCO3- anion exchanger (AE), Na+/H+ exchanger (NHE), Na+/HCO3- cotransporter (NBC), cystic fibrosis transmembrane conductance regulator (CFTR) and anoctamin 1 Cl- channels were detected in EOs. Microfluorimetric techniques revealed high NHE, AE, and NBC activities, whereas that of CFTR was relatively low. In addition, inhibition of CFTR led to functional interactions between the major acid-base transporters and CFTR. We conclude that EOs provide a relevant and suitable model system for studying the ion transport mechanisms of esophageal epithelial cells, and they can be also used as preclinical tools to assess the effectiveness of novel therapeutic compounds in esophageal diseases associated with altered ion transport processes

Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation - A meta-analysis

Although interest in the role of extracellular vesicles (EV) in oncology is growing, not all potential aspects have been investigated. In this meta-analysis, data regarding (i) the EV proteome and (ii) the invasion and proliferation capacity of the NCI-60 tumor cell lines (60 cell lines from nine different tumor types) were analyzed using machine learning methods.On the basis of the entire proteome or the proteins shared by all EV samples, 60 cell lines were classified into the nine tumor types using multiple logistic regression. Then, utilizing the Least Absolute Shrinkage and Selection Operator, we constructed a discriminative protein panel, upon which the samples were reclassified and pathway analyses were performed. These panels were validated using clinical data (n = 4,665) from Human Protein Atlas.Classification models based on the entire proteome, shared proteins, and discriminative protein panel were able to distinguish the nine tumor types with 49.15%, 69.10%, and 91.68% accuracy, respectively. Invasion and proliferation capacity of the 60 cell lines were predicted with R2 = 0.68 and R2 = 0.62 (p < 0.0001). The results of the Reactome pathway analysis of the discriminative protein panel suggest that the molecular content of EVs might be indicative of tumor-specific biological processes.Integrating in vitro EV proteomic data, cell physiological characteristics, and clinical data of various tumor types illuminates the diagnostic, prognostic, and therapeutic potential of EVs. Video Abstract