Insights into cancer and neurodegenerative diseases through selenoproteins and the connection with gut microbiota : current analytical methodologies

Introduction: Selenium plays many key roles in health especially in connection with cancer and neurodegenerative diseases. However, it needs to be appreciated that the essentiality/toxicity of selenium depends on both, a narrow range of concentration and the chemical specie involved. In this context, selenoproteins are essential biomolecules against these disorders, mainly due to its antioxidant action. To this end, analytical methodologies may allow identifying and quantifying individual selenospecies in human biofluids and tissues. Areas covered: This review focus on the role of selenoproteins in medicine, with special emphasis in cancer and neurodegenerative diseases, considering the possible link with gut microbiota. In particular, this article reviews the analytical techniques and procedures recently developed for the absolute quantification of selenoproteins and selenometabolites in human biofluids and tissues. Expert commentary: The beneficial role of selenium in human health has been extensively studied and reviewed. However, several challenges remain unsolved as discussed in this article: (i) speciation of selenium (especially selenoproteins) in cancer and neurodegenerative disease patients; (ii) supplementation of selenium in humans using functional foods and nutraceuticals; (iii) the link between selenium and selenoproteins expression and the gut microbiota and (iv) analytical methods and pitfalls for the absolute quantification of selenoproteins and selenometabolites

Loss of Smell and Taste Can Accurately Predict COVID-19 Infection: A Machine-Learning Approach.

The COVID-19 outbreak has spread extensively around the world. Loss of smell and taste have emerged as main predictors for COVID-19. The objective of our study is to develop a comprehensive machine learning (ML) modelling framework to assess the predictive value of smell and taste disorders, along with other symptoms, in COVID-19 infection. A multicenter case-control study was performed, in which suspected cases for COVID-19, who were tested by real-time reverse-transcription polymerase chain reaction (RT-PCR), informed about the presence and severity of their symptoms using visual analog scales (VAS). ML algorithms were applied to the collected data to predict a COVID-19 diagnosis using a 50-fold cross-validation scheme by randomly splitting the patients in training (75%) and testing datasets (25%). A total of 777 patients were included. Loss of smell and taste were found to be the symptoms with higher odds ratios of 6.21 and 2.42 for COVID-19 positivity. The ML algorithms applied reached an average accuracy of 80%, a sensitivity of 82%, and a specificity of 78% when using VAS to predict a COVID-19 diagnosis. This study concludes that smell and taste disorders are accurate predictors, with ML algorithms constituting helpful tools for COVID-19 diagnostic prediction

Statistical Assessment of Toxic and Essential Metals in the Serum of Female Patients with Lung Carcinoma from Pakistan

Lung cancer (LC) is the number one cancer killer of women both in the USA and around the world. Besides cigarette smoking, an important feature in the etiology of LC is its strong association with exposure of toxic metals. The primary objective of the present investigation was to assess the concentrations of toxic/essential elements (Ni, Ca, Se, Zn, Co, K, Cr, As, Cu, Na, Fe, Hg, Cd, Mg, Mn, and Pb) in the serum samples of LC female patients with female controls by atomic absorption spectrometry after wet-acid digestion procedure. Carcinoembryonic antigen (CEA) was also measured in the serum of the patients using immunoradiometric method. Comparative appraisal of the data revealed that concentrations of Cr, Mg, Cd, Pb, Hg, As, and Ni were noted to be high significantly in serum of LC female patients, while the average Fe, Co, Mn, Na, K, Zn, Ca, and Se were observed at higher levels in female controls (p < 0.05). The correlation study revealed significantly different mutual associations among the elements in the both donor groups. Markedly, variations in the elemental levels were also noted for different types (non-small cell lung cancer and small cell lung cancer) and stages (I, II, III, & IV) of LC patients. Multivariate analyses showed substantially diverse apportionment of the metals in the female patients and female controls. Hence, present findings suggest that the toxic and essential metals accumulated in the body may pose a high risk for LC progression in Pakistani females. © 2019, Springer Science+Business Media, LLC, part of Springer Nature

Metabolomics reveals tepotinib-related mitochondrial dysfunction in MET activating mutations-driven models.

Genetic aberrations in the hepatocyte growth factor receptor tyrosine kinase MET induce oncogenic addiction in various types of human cancers, advocating MET as a viable anticancer target. Here, we report that MET signaling plays an important role in conferring a unique metabolic phenotype to cellular models expressing MET-activating mutated variants that are either sensitive or resistant towards MET small molecule inhibitors. MET phosphorylation downregulated by the specific MET inhibitor tepotinib resulted in markedly decreased viability and increased apoptosis in tepotinib-sensitive cells. Moreover, prior to the induction of MET inhibition-dependent cell death, tepotinib also led to an altered metabolic signature, characterized by a prominent reduction of metabolite ions related to amino sugar metabolism, gluconeogenesis, glycine and serine metabolism and of numerous TCA cycle-related metabolites such as succinate, malate and citrate. Functionally, a decrease in oxygen consumption rate, a reduced citrate synthase activity, a drop in membrane potential and an associated misbalanced mitochondrial function were observed exclusively in MET inhibitor-sensitive cells. These data imply that interference with metabolic state can be considered an early indicator of efficient MET inhibition and particular changes reported here could be explored in the future as markers of efficacy of anti-MET therapies. This article is protected by copyright. All rights reserved