PubMed

Metabolites. 2023 Oct 17;13(10):1088. doi: 10.3390/metabo13101088.ABSTRACTThe Animal Metabolite Database (AMDB, https://amdb.online) is a freely accessible database with built-in statistical analysis tools, allowing one to browse and compare quantitative metabolomics data and raw NMR and MS data, as well as sample metadata, with a focus on the metabolite concentrations rather than on the raw data itself. AMDB also functions as a platform for the metabolomics community, providing convenient deposition and exchange of quantitative metabolomic data. To date, the majority of the data in AMDB relate to the metabolite content of the eye lens and blood of vertebrates, primarily wild species from Siberia, Russia and laboratory rodents. However, data on other tissues (muscle, heart, liver, brain, and more) are also present, and the list of species and tissues is constantly growing. Typically, every sample in AMDB contains concentrations of 60-90 of the most abundant metabolites, provided in nanomoles per gram of wet tissue weight (nmol/g). We believe that AMDB will become a widely used tool in the community, as typical metabolite baseline concentrations in tissues of animal models will aid in a wide variety of fundamental and applied scientific fields, including, but not limited to, animal modeling of human diseases, assessment of medical formulations, and evolutionary and environmental studies.PMID:37887413 | DOI:10.3390/metabo13101088

Metabolites. 2023 Oct 17;13(10):1086. doi: 10.3390/metabo13101086.ABSTRACTGrowing evidence indicates that metabolites and energy metabolism play an active rather than consequential role in regulating cellular fate. Cardiac development requires dramatic metabolic remodeling from relying primarily on glycolysis in pluripotent stem cells (PSCs) to oxidizing a wide array of energy substrates to match the high bioenergetic demands of continuous contraction in the developed heart. However, a detailed analysis of how remodeling of energy metabolism contributes to human cardiac development is lacking. Using dynamic multiple reaction monitoring metabolomics of central carbon metabolism, we evaluated temporal changes in energy metabolism during human PSC 3D cardiac lineage specification. Significant metabolic remodeling occurs during the complete differentiation, yet temporal analysis revealed that most changes occur during transitions from pluripotency to mesoderm (day 1) and mesoderm to early cardiac (day 5), with limited maturation of cardiac metabolism beyond day 5. Real-time metabolic analysis demonstrated that while hPSC cardiomyocytes (hPSC-CM) showed elevated rates of oxidative metabolism compared to PSCs, they still retained high glycolytic rates, confirming an immature metabolic phenotype. These observations support the opportunity to metabolically optimize the differentiation process to support lineage specification and maturation of hPSC-CMs.PMID:37887411 | DOI:10.3390/metabo13101086

Metabolites. 2023 Oct 13;13(10):1079. doi: 10.3390/metabo13101079.ABSTRACTIn this investigation, we outline the applications of a data mining technique known as Subgroup Discovery (SD) to the analysis of a sample size-limited metabolomics-based dataset. The SD technique utilized a supervised learning strategy, which lies midway between classificational and descriptive criteria, in which given the descriptive property of a dataset (i.e., the response target variable of interest), the primary objective was to discover subgroups with behaviours that are distinguishable from those of the complete set (albeit with a differential statistical distribution). These approaches have, for the first time, been successfully employed for the analysis of aromatic metabolite patterns within an NMR-based urinary dataset collected from a small cohort of patients with the lysosomal storage disorder Niemann-Pick class 1 (NPC1) disease (n = 12) and utilized to distinguish these from a larger number of heterozygous (parental) control participants. These subgroup discovery strategies discovered two different NPC1 disease-specific metabolically sequential rules which permitted the reliable identification of NPC1 patients; the first of these involved 'normal' (intermediate) urinary concentrations of xanthurenate, 4-aminobenzoate, hippurate and quinaldate, and disease-downregulated levels of nicotinate and trigonelline, whereas the second comprised 'normal' 4-aminobenzoate, indoxyl sulphate, hippurate, 3-methylhistidine and quinaldate concentrations, and again downregulated nicotinate and trigonelline levels. Correspondingly, a series of five subgroup rules were generated for the heterozygous carrier control group, and 'biomarkers' featured in these included low histidine, 1-methylnicotinamide and 4-aminobenzoate concentrations, together with 'normal' levels of hippurate, hypoxanthine, quinolinate and hypoxanthine. These significant disease group-specific rules were consistent with imbalances in the combined tryptophan-nicotinamide, tryptophan, kynurenine and tyrosine metabolic pathways, along with dysregulations in those featuring histidine, 3-methylhistidine and 4-hydroxybenzoate. In principle, the novel subgroup discovery approach employed here should also be readily applicable to solving metabolomics-type problems of this nature which feature rare disease classification groupings with only limited patient participant and sample sizes available.PMID:37887404 | DOI:10.3390/metabo13101079

Metabolites. 2023 Oct 13;13(10):1075. doi: 10.3390/metabo13101075.ABSTRACTThe untargeted metabolomics analysis of biological samples with nuclear magnetic resonance (NMR) provides highly complex data containing various signals from different molecules. To use these data for classification, e.g., in the context of food authentication, machine learning methods are used. These methods are usually applied as a black box, which means that no information about the complex relationships between the variables and the outcome is obtained. In this study, we show that the random forest-based approach surrogate minimal depth (SMD) can be applied for a comprehensive analysis of class-specific differences by selecting relevant variables and analyzing their mutual impact on the classification model of different truffle species. SMD allows the assignment of variables from the same metabolites as well as the detection of interactions between different metabolites that can be attributed to known biological relationships.PMID:37887402 | DOI:10.3390/metabo13101075

Metabolites. 2023 Oct 12;13(10):1073. doi: 10.3390/metabo13101073.ABSTRACTHepatocellular carcinoma (HCC) is one of the most refractory cancers with a high rate of recurrence. Iron is an essential trace element, and iron chelation has garnered attention as a novel therapeutic strategy for cancer. Since intracellular metabolism is significantly altered by inhibiting various proteins by iron chelation, we investigated combination anticancer therapy targeting metabolic changes that are forcibly modified by iron chelator administration. The deferoxamine (DFO)-resistant cell lines were established by gradually increasing the DFO concentration. Metabolomic analysis was conducted to evaluate the metabolic alterations induced by DFO administration, aiming to elucidate the resistance mechanism in DFO-resistant strains and identify potential novel therapeutic targets. Metabolom analysis of the DFO-resistant Huh7 cells revealed enhanced glycolysis and salvage cycle, alternations in glutamine metabolism, and accumulation of dipeptides. Huh7 cultured in the absence of glutamine showed enhanced sensitivity to DFO, and glutaminase inhibitor (CB839) showed a synergistic effect with DFO. Furthermore, the effect of DFO was enhanced by an autophagy inhibitor (chloroquine) in vitro. DFO-induced metabolic changes are specific targets for the development of efficient anticancer combinatorial therapies using DFO. These findings will be useful for the development of new cancer therapeutics in refractory liver cancer.PMID:37887398 | DOI:10.3390/metabo13101073

Metabolites. 2023 Oct 12;13(10):1071. doi: 10.3390/metabo13101071.ABSTRACTThe Omega-3 Index (O3I) reflects eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content in erythrocytes. While the O3I is associated with numerous health outcomes, its widespread use is limited. We investigated whether urinary metabolites could be used to non-invasively monitor the O3I in an exploratory analysis of a previous placebo-controlled, parallel arm randomized clinical trial in males and females (n = 88) who consumed either ~3 g/d olive oil (OO; control), EPA, or DHA for 12 weeks. Fasted blood and first-void urine samples were collected at baseline and following supplementation, and they were analyzed via gas chromatography and multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS), respectively. We tentatively identified S-carboxypropylcysteamine (CPCA) as a novel urinary biomarker reflecting O3I status, which increased following both EPA and DHA (p < 0.001), but not OO supplementation, and was positively correlated to the O3I (R = 0.30, p < 0.001). Additionally, an unknown dianion increased following DHA supplementation, but not EPA or OO. In ROC curve analyses, CPCA outperformed all other urinary metabolites in distinguishing both between OO and EPA or DHA supplementation groups (AUC > 80.0%), whereas the unknown dianion performed best in discriminating OO from DHA alone (AUC = 93.6%). Candidate urinary biomarkers of the O3I were identified that lay the foundation for a non-invasive assessment of omega-3 status.PMID:37887396 | DOI:10.3390/metabo13101071

Metabolites. 2023 Oct 10;13(10):1069. doi: 10.3390/metabo13101069.ABSTRACTIdiopathic pulmonary fibrosis (IPF) is a chronic and progressive condition characterized by the impairment of alveolar epithelial cells. Despite continued research efforts, the effective therapeutic medication is still absent due to an incomplete understanding of the underlying etiology. It has been shown that rhythmic alterations are of significant importance in the pathophysiology of IPF. However, a comprehensive understanding of how metabolite level changes with circadian rhythms in individuals with IPF is lacking. Here, we constructed an extensive metabolite database by utilizing an unbiased reference system culturing with 13C or 15N labeled nutrients. Using LC-MS analysis via ESI and APCI ion sources, 1300 potential water-soluble metabolites were characterized and applied to evaluate the metabolic changes with rhythm in the lung from both wild-type mice and mice with IPF. The metabolites, such as glycerophospholipids and amino acids, in WT mice exhibited notable rhythmic oscillations. The concentrations of phospholipids reached the highest during the fast state, while those of amino acids reached their peak during fed state. Similar diurnal variations in the metabolite rhythm of amino acids and phospholipids were also observed in IPF mice. Although the rhythmic oscillation of metabolites in the urea cycle remained unchanged, there was a significant up-regulation in their levels in the lungs of IPF mice. 15N-ammonia in vivo isotope tracing further showed an increase in urea cycle activity in the lungs of mice with IPF, which may compensate for the reduced efficiency of the hepatic urea cycle. In sum, our metabolomics database and method provide evidence of the periodic changes in lung metabolites, thereby offering valuable insights to advance our understanding of metabolic reprogramming in the context of IPF.PMID:37887394 | DOI:10.3390/metabo13101069

Metabolites. 2023 Oct 9;13(10):1061. doi: 10.3390/metabo13101061.ABSTRACTThe gut microbiome is of tremendous relevance to human health and disease, so it is a hot topic of omics-driven biomedical research. However, a valid identification of gut microbiota-associated molecules in human blood or urine is difficult to achieve. We hypothesize that bowel evacuation is an easy-to-use approach to reveal such metabolites. A non-targeted and modifying group-assisted metabolomics approach (covering 40 types of modifications) was applied to investigate urine samples collected in two independent experiments at various time points before and after laxative use. Fasting over the same time period served as the control condition. As a result, depletion of the fecal microbiome significantly affected the levels of 331 metabolite ions in urine, including 100 modified metabolites. Dominating modifications were glucuronidations, carboxylations, sulfations, adenine conjugations, butyrylations, malonylations, and acetylations. A total of 32 compounds, including common, but also unexpected fecal microbiota-associated metabolites, were annotated. The applied strategy has potential to generate a microbiome-associated metabolite map (M3) of urine from healthy humans, and presumably also other body fluids. Comparative analyses of M3 vs. disease-related metabolite profiles, or therapy-dependent changes may open promising perspectives for human gut microbiome research and diagnostics beyond analyzing feces.PMID:37887386 | DOI:10.3390/metabo13101061

Metabolites. 2023 Oct 8;13(10):1059. doi: 10.3390/metabo13101059.ABSTRACTHepatocellular carcinoma (HCC) is the main liver malignancy and has a high mortality rate. The discovery of novel biomarkers for early diagnosis, prognosis, and stratification purposes has the potential to alleviate its disease burden. Mass spectrometry (MS) is one of the principal technologies used in metabolomics, with different experimental methods and machine types for different phases of the biomarker discovery process. Here, we review why MS applications are useful for liver cancer, explain the MS technique, and briefly summarise recent findings from metabolomic MS studies on HCC. We also discuss the current challenges and the direction for future research.PMID:37887384 | DOI:10.3390/metabo13101059

Metabolites. 2023 Oct 7;13(10):1058. doi: 10.3390/metabo13101058.ABSTRACTAnkylosing spondylitis (AS) is a type of chronic rheumatic immune disease, and the crucial point of AS treatment is identifying the correct stage of the disease. However, there is a lack of effective diagnostic methods for AS staging. The primary objective of this study was to perform an untargeted metabolomic approach in AS patients in an effort to reveal metabolic differences between patients in remission and acute stages. Serum samples from 40 controls and 57 AS patients were analyzed via gas chromatography-mass spectrometry (GC-MS). Twenty-four kinds of differential metabolites were identified between the healthy controls and AS patients, mainly involving valine/leucine/isoleucine biosynthesis and degradation, phenylalanine/tyrosine/tryptophan biosynthesis, glutathione metabolism, etc. Furthermore, the levels of fatty acids (linoleate, dodecanoate, hexadecanoate, and octadecanoate), amino acids (serine and pyroglutamate), 2-hydroxybutanoate, glucose, etc., were lower in patients in the acute stage than those in the remission stage, which may be associated with the aggravated inflammatory response and elevated oxidative stress in the acute stage. Multiple stage-specific metabolites were significantly correlated with inflammatory indicators (CRP and ESR). In addition, the combination of serum 2-hydroxybutanoate and hexadecanoate plays a significant role in the diagnosis of AS stages. These metabolomics-based findings provide new perspectives for AS staging, treatment, and pathogenesis studies.PMID:37887383 | DOI:10.3390/metabo13101058

Metabolites. 2023 Oct 7;13(10):1057. doi: 10.3390/metabo13101057.ABSTRACTAlcoholic liver disease (ALD) represents a significant global health concern, yet the available treatment options remain limited. Numerous studies have shown that gut microbiota is a critical target for the treatment of ALD. Additionally, there is increasing evidence that host metabolism also plays a crucial role in the development of ALD. Akkermansia muciniphila has been demonstrated to ameliorate experimental ALD through its modulatory effects on the intestinal vascular barrier, enhancement of mucus layer thickness, and promotion of intestinal tight junction proteins. Nevertheless, there is a dearth of studies investigating the impact of A. muciniphila on host metabolism and gut microbiota. Here, C57BL/6 mice were utilized to establish a modified NIAAA model in order to investigate the impact of the oral administration of A. muciniphila during the development of ALD. Furthermore, we employed targeted metabolomics to analyze the serum metabolomic profiles of the mice and 2bRAD-M sequencing to comprehensively examine the underlying mechanisms of the efficacy of A. muciniphila on ALD. Our results illustrated that the oral administration of A. muciniphila alleviated alcohol-induced liver injury in conjunction with encouraged serum levels of ornithine and diminished the elevation of oxalic acid levels induced by alcohol intake. In addition, A. muciniphila also inhibited the proliferation of harmful bacteria, such as Escherichia coli and Helicobacter hepaticus, induced by alcohol consumption while promoting the growth of butyrate-producing and commensal bacteria, including Paramuribaculum intestinale and Bacteroides ovatus. In conclusion, this study suggests that A. muciniphila restores ALD by regulating the gut microbiota, and this corrective effect is associated with alterations in the serum metabolism. Our research supplies a theoretical basis for developing A. muciniphila as an innovative generation of probiotic for preventing and managing ALD.PMID:37887381 | DOI:10.3390/metabo13101057

Metabolites. 2023 Oct 7;13(10):1055. doi: 10.3390/metabo13101055.ABSTRACTWe developed a machine-learning system for the selective diagnostics of adenocarcinoma (AD), squamous cell carcinoma (SQ), and small-cell carcinoma lung (SC) cancers based on their metabolomic profiles. The system is organized as two-stage binary classifiers. The best accuracy for classification is 92%. We used the biomarkers sets that contain mostly metabolites related to cancer development. Compared to traditional methods, which exclude hierarchical classification, our method splits a challenging multiclass task into smaller tasks. This allows a two-stage classifier, which is more accurate in the scenario of lung cancer classification. Compared to traditional methods, such a "divide and conquer strategy" gives much more accurate and explainable results. Such methods, including our algorithm, allow for the systematic tracking of each computational step.PMID:37887380 | DOI:10.3390/metabo13101055

Metabolites. 2023 Oct 5;13(10):1052. doi: 10.3390/metabo13101052.ABSTRACTCellular metabolomics provides insights into the metabolic processes occurring within cells and can help researchers understand how these processes are regulated and how they relate to cellular function, health, and disease. In this technical note, we investigated the effects of solvent evaporation equipment and storage condition on high-coverage cellular metabolomics. We previously introduced a robust CIL LC-MS-based cellular metabolomics workflow that encompasses various steps, including cell harvest, metabolic quenching, cell lysis, metabolite extraction, differential chemical isotope labeling, and LC-MS analysis. This workflow has consistently served as the cornerstone of our collaborative research and service projects. As a core facility catering to users with diverse research needs and financial resources, we have encountered scenarios requiring short-term sample storage. For example, the need often arises to transport samples at room temperature from user sites to our core facility. Herein, we present a study in which we compared different solvent evaporation methods (specifically, the nitrogen blowdown evaporator, SpeedVac concentrator, and lyophilizer) and diverse storage conditions (including dried samples stored in a freezer, samples stored in a freezer with methanol, dried samples stored at room temperature, and samples stored at room temperature with methanol). Our findings indicate that the choice of solvent evaporation equipment did not significantly impact the cellular metabolome. However, we observed a noteworthy change in the metabolome after 7 days of storage when cells were stored with methanol, regardless of whether they were kept at -80 °C or room temperature, in contrast to cells that were dried and frozen. Importantly, we detected no significant alterations in cells that were dried and stored at room temperature. In conclusion, to ensure the production of high-quality CIL LC-MS metabolomics results, we strongly recommend that, in situations where low-temperature storage is not feasible, cell samples should be thoroughly dried before storage or shipment at room temperature.PMID:37887377 | DOI:10.3390/metabo13101052

Metabolites. 2023 Oct 4;13(10):1051. doi: 10.3390/metabo13101051.ABSTRACTThe application of metabolomics to the study of plants is growing because of the current development of analytical techniques. The most commonly used analytical technology driving plant metabolomics studies is Mass Spectrometry (MS) coupled to liquid chromatography (LC). In recent years, Nuclear Magnetic Resonance (NMR) spectroscopy, not requiring a previous chromatographic separation, has been receiving growing attention for metabolite fingerprinting of natural extracts. Herein, an integrated LC-MS and 1H NMR metabolomic approach provided a comprehensive phytochemical characterization of Symphytum anatolicum whole plant, taking into account both primary and specialized metabolites. Moreover, the NMR analyses provided direct quantitative information. Species belonging to the Symphytum genus, known as comfrey, have shown several biological activities including anti-inflammatory, analgesic, hepatoprotective, antifungal, and antibacterial. The LC-MS profile showed the presence of 21 main specialized metabolites, belonging to the classes of flavonoids, phenylpropanoids, salvianols, and oxylipins. The 1H NMR spectrum revealed the occurrence of metabolites including organic acids, phenolics, flavonoids, sugars, and amino acids. A quantitative analysis of these metabolites was performed and their concentration was obtained with respect to the known concentration of TSP, by means of the software package Chenomx which allows quantification of individual components in the NMR spectra. Furthermore, the phenolic content, antioxidant activity, glucosidase, and tyrosinase inhibitory activity of S. anatolicum extract were evaluated. The resulting bioactivity profile suggests how S. anatolicum represents a source of metabolites with health-promoting activity.PMID:37887376 | DOI:10.3390/metabo13101051

Metabolites. 2023 Oct 3;13(10):1050. doi: 10.3390/metabo13101050.ABSTRACTDoliocarpus dentatus is thought to have a wide variety of therapeutic phytochemicals that allegedly improve libido and cure impotence. Although a few biomarkers have been identified with potential antinociceptive and cytotoxic properties, an untargeted mass spectrometry-based metabolomics approach has never been undertaken to identify therapeutic biofingerprints for conditions, such as erectile dysfunction, in men. This study executes a preliminary phytochemical screening of the woody vine of two ecotypes of D. dentatus with renowned differences in therapeutic potential for erectile dysfunction. Liquid chromatography-mass spectrometry-based metabolomics was used to screen for flavonoids, terpenoids, and other chemical classes found to contrast between red and white ecotypes. Among the metabolite chemodiversity found in the ecotype screens, using a combination of GNPS, MS-DIAL, and SIRIUS, approximately 847 compounds were annotated at levels 2 to 4, with the majority of compounds falling under lipid and lipid-like molecules, benzenoids and phenylpropanoids, and polyketides, indicative of the contributions of the flavonoid, shikimic acid, and terpenoid biosynthesis pathways. Despite the extensive annotation, we report on 138 tentative compound identifications of potentially therapeutic compounds, with 55 selected compounds at a level-2 annotation, and 22 statistically significant therapeutic biomarkers, the majority of which were polyphenols. Epicatechin methyl gallate, catechin gallate, and proanthocyanidin A2 had the greatest significant differences and were also relatively abundant among the red and white ecotypes. These putatively identified compounds reportedly act as antioxidants, neutralizing damaging free radicals, and lowering cell oxidative stress, thus aiding in potentially preventing cellular damage and promoting overall well-being, especially for treating erectile dysfunction (ED).PMID:37887375 | DOI:10.3390/metabo13101050

Metabolites. 2023 Oct 2;13(10):1047. doi: 10.3390/metabo13101047.ABSTRACTHepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is the third leading cause of mortality globally. Patients with HCC have a poor prognosis due to the fact that the emergence of symptoms typically occurs at a late stage of the disease. In addition, conventional biomarkers perform suboptimally when identifying HCC in its early stages, heightening the need for the identification of new and more effective biomarkers. Using metabolomics and lipidomics approaches, this study aims to identify serum biomarkers for identification of HCC in patients with liver cirrhosis (LC). Serum samples from 20 HCC cases and 20 patients with LC were analyzed using ultra-high-performance liquid chromatography-Q Exactive mass spectrometry (UHPLC-Q-Exactive-MS). Metabolites and lipids that are significantly altered between HCC cases and patients with LC were identified. These include organic acids, amino acids, TCA cycle intermediates, fatty acids, bile acids, glycerophospholipids, sphingolipids, and glycerolipids. The most significant variability was observed in the concentrations of bile acids, fatty acids, and glycerophospholipids. In the context of HCC cases, there was a notable increase in the levels of phosphatidylethanolamine and triglycerides, but the levels of fatty acids and phosphatidylcholine exhibited a substantial decrease. In addition, it was observed that all of the identified metabolites exhibited a superior area under the receiver operating characteristic (ROC) curve in comparison to alpha-fetoprotein (AFP). The pathway analysis of these metabolites revealed fatty acid, lipid, and energy metabolism as the most impacted pathways. Putative biomarkers identified in this study will be validated in future studies via targeted quantification.PMID:37887372 | DOI:10.3390/metabo13101047

Metabolites. 2023 Oct 1;13(10):1046. doi: 10.3390/metabo13101046.ABSTRACTThe zebra mussel, Dreissena polymorpha, is extensively used as a sentinel species for biosurveys of environmental contaminants in freshwater ecosystems and for ecotoxicological studies. However, its metabolome remains poorly understood, particularly in light of the potential molecular sexual dimorphism between its different tissues. From an ecotoxicological point of view, inter-sex and inter-organ differences in the metabolome suggest variability in responsiveness, which can influence the analysis and interpretation of data, particularly in the case where males and females would be analyzed indifferently. This study aimed to assess the extent to which the molecular fingerprints of functionally diverse tissues like the digestive glands, gonads, gills, and mantle of D. polymorpha can reveal tissue-specific molecular sexual dimorphism. We employed a non-targeted metabolomic approach using liquid chromatography high-resolution mass spectrometry and revealed a significant sexual molecular dimorphism in the gonads, and to a lesser extent in the digestive glands, of D. polymorpha. Our results highlight the critical need to consider inter-sex differences in the metabolome of D. polymorpha to avoid confounding factors, particularly when investigating environmental effects on molecular regulation in the gonads, and to a lesser extent in the digestive glands.PMID:37887371 | DOI:10.3390/metabo13101046

Metabolites. 2023 Sep 26;13(10):1038. doi: 10.3390/metabo13101038.ABSTRACTVolumetric absorptive microsampling (VAMS) has arisen as a relevant tool in biological analysis, offering simplified sampling procedures and enhanced stability. Most of the attention VAMS has received in the past decade has been from pharmaceutical research, with most of the published work employing VAMS targeting drugs or other exogenous compounds, such as toxins and pollutants. However, biomarker analysis by employing blood microsampling has high promise. Herein, a comprehensive review on the applicability of VAMS devices for the analysis of endogenous metabolites/biomarkers was performed. The study presents a full overview of the analysis process, incorporating all the steps in sample treatment and validation parameters. Overall, VAMS devices have proven to be reliable tools for the analysis of endogenous analytes with biological importance, often offering improved analyte stability in comparison with blood under ambient conditions as well as a convenient and straightforward sample acquisition model.PMID:37887363 | DOI:10.3390/metabo13101038

Metabolites. 2023 Sep 26;13(10):1037. doi: 10.3390/metabo13101037.ABSTRACTLung cancer is the leading cause of cancer-related death worldwide. Metabolic reprogramming is a fundamental trait associated with lung cancer development that fuels tumor proliferation and survival. Monitoring such metabolic pathways and their intermediate metabolites can provide new avenues concerning treatment strategies, and the identification of prognostic biomarkers that could be utilized to monitor drug responses in clinical practice. In this review, recent trends in the analytical techniques used for metabolome mapping of lung cancer are capitalized. These techniques include nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and imaging mass spectrometry (MSI). The advantages and limitations of the application of each technique for monitoring the metabolite class or type are also highlighted. Moreover, their potential applications in the analysis of many biological samples will be evaluated.PMID:37887362 | DOI:10.3390/metabo13101037

Metabolites. 2023 Sep 26;13(10):1035. doi: 10.3390/metabo13101035.ABSTRACTMetastatic soft-tissue sarcomas (mSTS) encompass a highly heterogeneous group of rare tumours characterized by different clinical behaviours and outcomes. Currently, prognostic factors for mSTS are very limited, posing significant challenges in predicting patient survival. Within a cohort of 39 mSTS patients undergoing trabectedin treatment, it was remarkable to find one patient who underwent 73 cycles of trabectedin achieving an unforeseen clinical outcome. To identify contributing factors to her exceptional long-term survival, we have explored circulation metabolomics and biohumoral biomarkers to uncover a potential distinct host biochemical phenotype. The long-term survival patient compared with the other mSTS patients exhibited a distinctive metabolic profile characterized by remarkably higher levels of ursodeoxycholic acid (UDCA) derivatives and vitamin D and lower levels of lithocholic acid (LCA) derivatives, as well as reduced levels of inflammatory C-Reactive Protein 4 (C-RP4) biomarker. Despite its exploratory nature, this study reveals a potential association between specific bile acid metabolic profiles and mSTS patients' prognosis. Enhanced clinical understanding of the interplay between bile acid metabolism and disease progression could pave the way for new targeted therapeutic interventions which may improve the overall survival of mSTS patients.PMID:37887360 | DOI:10.3390/metabo13101035