Comprehensive plasma steroidomics reveals subtle alterations of systemic steroid profile in patients at different stages of prostate cancer disease

The steroid submetabolome, or steroidome, is of particular interest in prostate cancer (PCa) as the dependence of PCa growth on androgens is well known and has been routinely exploited in treatment for decades. Nevertheless, the community is still far from a comprehensive understanding of steroid involvement in PCa both at the tissue and at systemic level. In this study we used liquid chromatography/high resolution mass spectrometry (LC/HRMS) backed by a dynamic retention time database DynaSTI to obtain a readout on circulating steroids in a cohort reflecting a progression of the PCa. Hence, 60 relevant compounds were annotated in the resulting LC/HRMS data, including 22 unknown steroid isomers therein. Principal component analysis revealed only subtle alterations of the systemic steroidome in the study groups. Next, a supervised approach allowed for a differentiation between the healthy state and any of the stages of the disease. Subsequent clustering of steroid metabolites revealed two groups responsible for this outcome: one consisted primarily of the androgens, whereas another contained corticosterone and its metabolites. The androgen data supported the currently established involvement of a hypothalamic-pituitary–gonadal axis in the development of PCa, whereas biological role of corticosterone remained elusive. On top of that, current results suggested a need for improvement in the dynamic range of the analytical methods to better understand the role of low abundant steroids, as the analysis revealed an involvement of estrogen metabolites. In particular, 2-hydroxyestradiol-3-methylether, one of the compounds present in the disease phenotype, was annotated and reported for the first time in men

Characterization and Detection of Erythropoietin Fc Fusion Proteins Using Liquid Chromatography–Mass Spectrometry

Erythropoietin Fc (EPO-Fc) fusion proteins are potential drug candidates that have been designed for the treatment of anemia in humans by stimulating erythrocyte production. Such compounds can be considered performance-enhancing agents that may be used by athletes in endurance sports. This study describes the primary structure of commercially available EPO-Fc based on comprehensive liquid chromatography coupled with mass spectrometry (LC–MS) analysis. A bottom-up approach and the intact molecular weight (MW) measurement of deglycosylated protein and its IdeS proteolytic fractions was used to determine the amino acid sequence of EPO-Fc. Using multiple proteases, peptides covering unknown fusion breakpoints (spacer peptides) were identified. We demonstrated that “spacer peptides” can be used in the determination of EPO-Fc fusion proteins in biological samples using common LC–tandem MS methods

Pharmacokinetic Properties of the Novel Synthetic Cannabinoid 5F-APINAC and Its Influence on Metabolites Associated with Neurotransmission in Rabbit Plasma

The strong psychoactive effects of synthetic cannabinoids raise the need for the deeper studying of their neurometabolic effects. The pharmacokinetic properties of 5F-APINAC and its influence on metabolomics profiles associated with neurotransmission were investigated in rabbit plasma. Twelve rabbits divided into three groups received 1-mL 5F-APINAC at 0.1, 1 and 2 mg/kg. The intervention groups were compared with the controls. Sampling was performed at nine time points (0–24 h). Ultra-high-performance liquid chromatography–tandem mass spectrometry was used. The pharmacokinetics were dose-dependent (higher curve at a higher dose) with a rapid biotransformation, followed by gradual elimination within 24 h. The tryptophan concentrations abruptly decreased (p < 0.05) in all tested groups, returning to the basal levels after 6 h. 5-hydroxylindole acetic acid increased (p < 0.05) in the controls, but this trend was absent in the treated groups. The aspartic acid concentrations were elevated (p < 0.001) in the treated groups. L-kynurenine was elevated (p < 0.01) in the intervention groups receiving 1 mg/kg to 2 mg/kg. Dose-dependent elevations (p < 0.01) were found for kynurenic acid, xanthurenic acid and quinolinic acid (p < 0.01), whereas the anthranilic acid trends were decreased (p < 0.01). The indole-3-propionic acid and indole-3-carboxaldehyde trends were elevated (p < 0.05), whereas the indole-3-lactic acid trajectories were decreased (p < 0.01) in the intervention groups. 5F-APINAC administration had a rapid biotransformation and gradual elimination. The metabolites related to the kynurenine and serotonergic system/serotonin pathways, aspartic acid innervation system and microbial tryptophan catabolism were altered

Short- and medium-term exposures of diazepam induce metabolomic alterations associated with the serotonergic, dopaminergic, adrenergic and aspartic acid neurotransmitter systems in zebrafish (Danio rerio) embryos/larvae

Introduction: Diazepam is a well-known psychoactive drug widely used worldwide for the treatment of anxiety, seizures, alcohol withdrawal syndrome, muscle spasms, sleeplessness, agitation, and pre/post-operative sedation. It is part of the benzodiazepine family, substances known to primarily act by binding and enhancing gamma-aminobutyric acid (GABA(A)) receptors. The objective of the present work was to investigate the influence of short and medium-term diazepam exposures on neurotransmitters measured through targeted metabolomics using a zebrafish embryo model.Methods: Short-term (2.5 h) and medium-term (96 h) exposures to diazepam were performed at drug concentrations of 0.8, 1.6, 16, and 160 mu g/L. Intervention groups were compared with a vehicle control group. Each group consisted of 20 zebrafish eggs/larvae. Metabolites related with neurotransmission were determined by ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS).Results: Thirty-six compounds were quantified. Significantly increased tryptophan and serotonin concentrations were found in the intervention groups receiving higher doses of diazepam in 2.5 h exposure (p < 0.05 control versus intervention groups). Tyrosine concentrations were higher (p < 0.05) at higher concentrations in 2.5 h exposure, but lower (p < 0.05) at higher concentrations in 96 h exposure. Both phenylalanine and aspartic acid concentrations were higher (p < 0.05) at higher doses in 2.5 h and 96 h exposure.Conclusions: Short- and medium-term exposures to diazepam induce dose- and time-dependent metabolomic alterations associated with the semtonergic, dopaminergic/adrenergic, and aspartic acid neurotransmitter systems in zebrafish

Misdiagnosis of diabetic foot ulcer in patients with undiagnosed skin malignancies

A growing number of studies report dermal malignancies mimicking diabetic foot ulcers (DFUs). We reviewed clinical cases reporting malignant tumours misdiagnosed to be DFU aiming to identify factors contributing to misdiagnosis. We systematically searched in PubMed for clinical cases reporting on misdiagnosis of DFU in patients with cancer. A chi-square analysis was conducted to show the link between the incidence of initial DFU misdiagnosis and patient age, gender and wound duration. Lesions misdiagnosed to be DFU were subsequently diagnosed as melanoma (68% of the cases), Kaposi's sarcoma (14%), squamous cell carcinoma (11%), mantle cell lymphoma, and diffuse B-cell lymphoma (both by 4%). Older age (≥65 years) was associated with a significantly increased risk of malignancy masked as DFU (OR: 2.452; 95% CI: 1.132 to 5.312; P value = .019). The risk of such suspicion in older patients (age ≥ 65 years) was 145% higher than in younger patients (age < 65 years). Clinicians should maintain a high level of awareness towards potentially malignant foot lesions in elderly patients with diabetes (age ≥ 65)

Alkylresorcinols as New Modulators of the Metabolic Activity of the Gut Microbiota

Alkylresorcinols (ARs) are polyphenolic compounds with a wide spectrum of biological activities and are potentially involved in the regulation of host metabolism. The present study aims to establish whether ARs can be produced by the human gut microbiota and to evaluate alterations in content in stool samples as well as metabolic activity of the gut microbiota of C57BL, db/db, and LDLR (−/−) mice according to diet specifications and olivetol (5-n-pentylresorcinol) supplementation to estimate the regulatory potential of ARs. Gas chromatography with mass spectrometric detection was used to quantitatively analyse AR levels in mouse stool samples; faecal microbiota transplantation (FMT) from human donors to germ-free mice was performed to determine whether the intestinal microbiota could produce AR molecules; metagenome sequencing analysis of the mouse gut microbiota followed by reconstruction of its metabolic activity was performed to investigate olivetol’s regulatory potential. A significant increase in the amounts of individual members of AR homologues in stool samples was revealed 14 days after FMT. Supplementation of 5-n-Pentylresorcinol to a regular diet influences the amounts of several ARs in the stool of C57BL/6 and LDLR (−/−) but not db/db mice, and caused a significant change in the predicted metabolic activity of the intestinal microbiota of C57BL/6 and LDLR (−/−) but not db/db mice. For the first time, we have shown that several ARs can be produced by the intestinal microbiota. Taking into account the dependence of AR levels in the gut on olivetol supplementation and microbiota metabolic activity, AR can be assumed to be potential quorum-sensing molecules, which also influence gut microbiota composition and host metabolism

Pharmacokinetics, quorum-sensing signal molecules and tryptophan-related metabolomics of the novel anti-virulence drug Fluorothiazinon in a Pseudomonas aeruginosa-induced pneumonia murine model

Pseudomonas aeruginosa (PA) infection is commonly associated with hospital-acquired infections in patients with immune deficiency and/or severe lung diseases. Managing this bacterium is complex due to drug resistance and high adaptability. Fluorothiazinon (FT) is an anti-virulence drug developed to suppress the virulence of bacteria as opposed to bacterial death increasing host's immune response to infection and improving treatment to inhibit drug resistant bacteria. We aimed to evaluate FT pharmacokinetics, quorum sensing signal molecules profiling and tryptophan-related metabolomics in blood, liver, kidneys, and lungs of mice. Study comprised three groups: a group infected with PA that was treated with 400 mg/kg FT ("infected treated group"); a non-infected group, but also treated with the same single drug dose ("non-infected treated group"); and an infected group that received a vehicle ("infected non-treated group"). PA-mediated infection blood pharmacokinetics profiling was indicative of increased drug concentrations as shown by increased Cmax and AUCs. Tissue distribution in liver, kidneys, and lungs, showed that liver presented the most consistently higher concentrations of FT in the infected versus non-infected mice. FT showed that HHQ levels were decreased at 1 h after dosing in lungs while PQS levels were lower across time in lungs of infected treated mice in comparison to infected non-treated mice. Metabolomics profiling performed in lungs and blood of infected treated versus infected non-treated mice revealed drug-associated metabolite alterations, especially in the kynurenic and indole pathways

Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer

Abstract Lung cancer is referred to as the second most common cancer worldwide and is mainly associated with complex diagnostics and the absence of personalized therapy. Metabolomics may provide significant insights into the improvement of lung cancer diagnostics through identification of the specific biomarkers or biomarker panels that characterize the pathological state of the patient. We performed targeted metabolomic profiling of plasma samples from individuals with non-small cell lung cancer (NSLC, n = 100) and individuals without any cancer or chronic pathologies (n = 100) to identify the relationship between plasma endogenous metabolites and NSLC by means of modern comprehensive bioinformatics tools, including univariate analysis, multivariate analysis, partial correlation network analysis and machine learning. Through the comparison of metabolomic profiles of patients with NSCLC and noncancer individuals, we identified significant alterations in the concentration levels of metabolites mainly related to tryptophan metabolism, the TCA cycle, the urea cycle and lipid metabolism. Additionally, partial correlation network analysis revealed new ratios of the metabolites that significantly distinguished the considered groups of participants. Using the identified significantly altered metabolites and their ratios, we developed a machine learning classification model with an ROC AUC value equal to 0.96. The developed machine learning lung cancer model may serve as a prototype of the approach for the in-time diagnostics of lung cancer that in the future may be introduced in routine clinical use. Overall, we have demonstrated that the combination of metabolomics and up-to-date bioinformatics can be used as a potential tool for proper diagnostics of patients with NSCLC

Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults

Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors in patients diagnosed with arterial hypertension (HTA) (n = 61), coronary artery disease (CAD) (n = 48), and non-cardiovascular disease (CVD) individuals (n = 27). In total, almost all significantly different acylcarnitines, amino acids, methylarginines, and intermediates of the kynurenic and indolic tryptophan conversion pathways presented increased (p< 0.05) in concentration levels during the progression of CVD, indicating an association of inflammation, mitochondrial imbalance, and oxidative stress with early stages of CVD. Additionally, the random forest algorithm was found to have the highest prediction power in multiclass and binary classification patients with CAD, HTA, and non-CVD individuals and globally between CVD and non-CVD individuals (accuracy equal to 0.80 and 0.91, respectively). Thus, the present study provided a complex approach for the risk stratification of patients with CAD, patients with HTA, and non-CVD individuals using targeted metabolomics profiling