Untargeted metabolomics coupled with genomics in the study of sucrose and xylose metabolism in Pectobacterium betavasculorum.

Introduction: Pectobacterium betavasculorum is a member of the Pectobacerium genus that inhabits a variety of niches and is found in all climates. Bacteria from the Pectobacterium genus can cause soft rot disease on various plants due to the secretion of plant cell wall degrading enzymes (PCWDEs). The species P. betavasculorum is responsible for the vascular necrosis of sugar beet and soft rot of many vegetables. It also infects sunflowers and artichokes. The main sugar present in sugar beet is sucrose while xylose is one of the main sugars in artichoke and sunflower. Methods: In our work, we applied metabolomic studies coupled with genomics to investigate the metabolism of P. betavasculorum in the presence of xylose and sucrose as the only carbon source. The ability of the strains to use various sugars as the only carbon source were confirmed by the polypyridyl complex of Ru(II) method in 96-well plates. Results: Our studies provided information on the metabolic pathways active during the degradation of those substrates. It was observed that different metabolic pathways are upregulated in the presence of xylose in comparison to sucrose. Discussion: The presence of xylose enhances extracellular metabolism of sugars and glycerol as well as stimulates EPS and IPS synthesis. In contrast, in the presence of sucrose the intensive extracellular metabolism of amines and amino acids is promoted.

Metabolomics Meets Clinics: A Multivariate Analysis of Plasma and Urine Metabolic Signatures in Pulmonary Arterial Hypertension.

Pulmonary arterial hypertension (PAH) is a severe, multifactorial, and frequently misdiagnosed disorder. The aim of this observational study was to compare the plasma and urine metabolomic profiles of PAH patients and healthy control subjects. Plasma and urine metabolomic profiles were analyzed using the GC-MS technique. Correlations between metabolite levels and clinical parameters among PAH patients, as well as the between-group differences, were evaluated. The linear discriminant analysis model, which allows for subject classification in terms of PAH with the highest possible precision, was developed and proposed. Plasma pyruvic acid, cholesterol, threonine, urine 3-(3-hydroxyphenyl)-3-hydroxypropanoic acid, butyric acid, 1,2-benzenediol, glucoheptonic acid, and 2-oxo-glutaric acid were found to build a relatively accurate classification model for PAH patients. The model reached an accuracy of 91% and significantly improved subject classification (OR = 119 [95% CI: 20.3-698.3], p < 0.0001). Five metabolites were detected in urine that provide easily available and noninvasive tests as compared to right heart catheterization. The selected panel of metabolites has potential for early recognition of patients with dyspnea and faster referral to a reference center.

Plasma untargeted metabolomics with proteinase K discloses phospholipid signature associated with pulmonary arterial hypertension.

Pulmonary arterial hypertension is a rare but life-threatening and clinically heterogeneous disease. The diagnostic schedule of this disorder is complex, and no specific indicator of the arterial etiology has been explored. In this study, untargeted plasma metabolomics was applied to evaluate the metabolic fingerprints of pulmonary arterial hypertension patients. Plasma samples were prepared using a new approach, which applies proteinase K during the sample preparation procedure to increase the metabolite coverage. The metabolic fingerprints were determined via LC-MS and subsequently analyzed with the use of both uni- and multivariate statistics. A total of 21 metabolites were discovered to be significantly altered in pulmonary arterial hypertensive patients. The metabolites were mainly related to the phospholipid metabolic pathways. In this study, decreases were found in the phosphatidylcholines (PCs) [PC(32:0), PC(40:7), PC(42:7)], phosphatidylethanolamine PE(18:0/18:2), lysophosphatidylethanolamines (LPEs) [LPE(22:6), LPE(18:2), LPE(18:0), LPE(20:4), LPE(20:1), LPE(20:0)], lysophosphatidylcholine LPC(20:4) and lysophosphatidylserine LPS(19:0), as well as increase of sphingomyelin SM(36:2), in the plasma samples of pulmonary arterial hypertensive patients in comparison to the control group. Besides their function as components of the biological membranes, these metabolites are also involved in the intracellular signaling pathways that are related to cell proliferation and apoptosis. The results obtained during this study confirm the potential of (untargeted) metabolomics to identify the molecular characteristics of the pathophysiology of pulmonary arterial hypertension. The clinical relevance of this study constitutes the selection of a metabolic panel that can potentially detect and properly diagnose the disease.

Searching for the primary metabolic alterations of polycystic ovary syndrome by application of the untargeted metabolomics approach.

Despite a large number of studies, the pathogenesis of polycystic ovary syndrome (PCOS) still remains unexplained. In light of ambiguous observations reported in metabolomics, there is a need to carry out studies focusing on confirming the discriminating power of the proposed metabolomics biomarkers. Our research aimed to perform a validation study of metabolites detected in our previous study from serum samples, on the new set of samples obtained from PCOS women and healthy controls to confirm previously selected compounds. Additionally, the second biological matrix - urine - was used to get a more comprehensive insight into metabolic alterations. We applied two analytical techniques - gas chromatography and liquid chromatography coupled with mass spectrometry to analyze both serum and urine samples obtained from 35 PCOS patients and 35 healthy women. Thank to our approach, we identified and described a comprehensive set of metabolites altered in PCOS patients. Results of our study indicate increased steroid hormone synthesis, alteration in sphingo- and phospholipids metabolism, and disturbed fatty acids metabolism. Moreover, the citric acid cycle, γ-glutamyl cycle, vitamin B metabolism, and a few primary amino acids like tryptophan, phenylalanine, histidine, and alanine are altered.

Molecular signature of renal cell carcinoma by means of a multiplatform metabolomics analysis.

Renal cell carcinoma (RCC) is a disease with no specific diagnostic method or treatment. Thus, the evaluation of novel diagnostic tools or treatment possibilities is essential. In this study, a multiplatform untargeted metabolomics analysis of urine was applied to search for a metabolic pattern specific for RCC, which could enable comprehensive assessment of its biochemical background. Thirty patients with diagnosed RCC and 29 healthy volunteers were involved in the first stage of the study. Initially, the utility of the application of the selected approach was checked for RCC with no differentiation for cancer subtypes. In the second stage, this approach was used to study clear cell renal cell carcinoma (ccRCC) in 38 ccRCC patients and 38 healthy volunteers. Three complementary analytical platforms were used: reversed-phase liquid chromatography coupled with time-of-flight mass spectrometry (RP-HPLC-TOF/MS), capillary electrophoresis coupled with time-of-flight mass spectrometry (CE-TOF/MS), and gas chromatography triple quadrupole mass spectrometry (GC-QqQ/MS). As a result of urine sample analyses, two panels of metabolites specific for RCC and ccRCC were selected. Disruptions in amino acid, lipid, purine, and pyrimidine metabolism, the TCA cycle and energetic processes were observed. The most interesting differences were observed for modified nucleosides. This is the first time that the levels of these compounds were found to be changed in RCC and ccRCC patients, providing a framework for further studies. Moreover, the application of the CE-MS technique enabled the determination of statistically significant changes in symmetric dimethylarginine (SDMA) in RCC.

Comprehensive Metabolic Signature of Renal Dysplasia in Children. A Multiplatform Metabolomics Concept.

Renal dysplasia is a severe congenital abnormality of the kidney parenchyma, which is an important cause of end-stage renal failure in childhood and early adulthood. The diagnosis of renal dysplasia relies on prenatal or postnatal ultrasounds as children show no specific clinical symptoms before chronic kidney disease develops. Prompt diagnosis is important in terms of early introduction of nephroprotection therapy and improved long-term prognosis. Metabolomics was applied to study children with renal dysplasia to provide insight into the changes in biochemical pathways underlying its pathology and in search of early indicators for facilitated diagnosis. The studied cohort consisted of 72 children, 39 with dysplastic kidneys and 33 healthy controls. All subjects underwent comprehensive urine metabolic profiling with the use of gas chromatography and liquid chromatography coupled to mass spectrometry, with two complementary separation modes of the latter. Univariate and multivariate statistical calculations identified a total of nineteen metabolites, differentiating the compared cohorts, independent of their estimated glomerular filtration rate. Seven acylcarnitines, xanthine, and glutamine were downregulated in the urine of renal dysplasia patients. Conversely, renal dysplasia was associated with higher urinary levels of dimethylguanosine, threonic acid or glyceric acid. This is the first metabolomic study of subjects with renal dysplasia. The authors define a characteristic urine metabolic signature in children with dysplastic kidneys, irrespective of renal function, linking the condition with altered fatty acid oxidation, amino acid and purine metabolisms.

Metabolic Evaluation of Urine from Patients Diagnosed with High Grade (HG) Bladder Cancer by SPME-LC-MS Method.

Bladder cancer (BC) is a common malignancy of the urinary system and a leading cause of death worldwide. In this work, untargeted metabolomic profiling of biological fluids is presented as a non-invasive tool for bladder cancer biomarker discovery as a first step towards developing superior methods for detection, treatment, and prevention well as to further our current understanding of this disease. In this study, urine samples from 24 healthy volunteers and 24 BC patients were subjected to metabolomic profiling using high throughput solid-phase microextraction (SPME) in thin-film format and reversed-phase high-performance liquid chromatography coupled with a Q Exactive Focus Orbitrap mass spectrometer. The chemometric analysis enabled the selection of metabolites contributing to the observed separation of BC patients from the control group. Relevant differences were demonstrated for phenylalanine metabolism compounds, i.e., benzoic acid, hippuric acid, and 4-hydroxycinnamic acid. Furthermore, compounds involved in the metabolism of histidine, beta-alanine, and glycerophospholipids were also identified. Thin-film SPME can be efficiently used as an alternative approach to other traditional urine sample preparation methods, demonstrating the SPME technique as a simple and efficient tool for urinary metabolomics research. Moreover, this study's results may support a better understanding of bladder cancer development and progression mechanisms.

GC-MS-based untargeted metabolomics of plasma and urine to evaluate metabolic changes in prostate cancer.

Prostate cancer (CaP) is a common cancer in men. Its late detection and inefficient diagnosis are a challenge for researchers who are currently searching for new cancer-related indicators that would facilitate better detectability of CaP and explain its pathogenesis. In the present preliminary study, endogenous volatile metabolites were detected in plasma and urine samples by using the metabolic fingerprinting approach. The analyses were performed using the GC-QqQ/MS technique in the scan mode. The detected and putatively identified metabolites were statistically analyzed using advanced univariate and multivariate statistical methods. Eleven urinary and three plasma metabolites were selected as statistically significant in patients with CaP as compared to those in healthy controls. Supervised methods such as logistic regression and quadratic support vector machine were applied to obtain the classification models. The accuracy, sensitivity, and specificity of the models were above 83%, 85%, and 81%, respectively. The putatively identified metabolites were associated with biochemical pathways such as tricarboxylic acid cycle, glycolysis, carbohydrate conversion, and steroidal lipid metabolism that are mainly involved in energy production for cell growth and proliferation.

The Luminescence of 1,8-Diazafluoren-9-One/Titanium Dioxide Composite Thin Films for Optical Application.

The investigation of innovative label-free α-amino acids detection methods represents a crucial step for the early diagnosis of several diseases. While 1,8-diazafluoren-9-one (DFO) is known in forensic application because of the fluorescent products by reacting with the amino acids present in the papillary exudate, its application for diagnostic purposes has not been fully investigated. The stabilization of DFO over a transparent substrate allows its complexation with biomolecules for the detection of α-amino acids. In this study, DFO was immobilized into a titanium dioxide (TiO2) matrix for the fluorescence detection of glycine, as a target α-amino acid (a potential marker of the urogenital tract cancers). The DFO/TiO2 composite was characterized by atomic force microscopy, spectroscopic ellipsometry, fluorescence spectroscopy and fluorescence microscopy. The performed fluorescent studies indicate spectacular formation of aggregates at higher concentration. The measurements performed using various fluorescence and microscopic techniques together with the suitable analysis show that the aggregates are able to emit short-lived fluorescence.

Metabolomic Signature of Early Vascular Aging (EVA) in Hypertension.

Arterial stiffening is a hallmark of early vascular aging (EVA) syndrome and an independent predictor of cardiovascular morbidity and mortality. In this case-control study we sought to identify plasma metabolites associated with EVA syndrome in the setting of hypertension. An untargeted metabolomic approach was used to identify plasma metabolites in an age-, BMI-, and sex-matched groups of EVA (n = 79) and non-EVA (n = 73) individuals with hypertension. After raw data processing and filtration, 497 putative compounds were characterized, out of which 4 were identified as lysophosphaditylcholines (LPCs) [LPC (18:2), LPC (16:0), LPC (18:0), and LPC (18:1)]. A main finding of this study shows that identified LPCs were independently associated with EVA status. Although LPCs have been shown previously to be positively associated with inflammation and atherosclerosis, we observed that hypertensive individuals characterized by 4 down-regulated LPCs had 3.8 times higher risk of EVA compared to those with higher LPC levels (OR = 3.8, 95% CI 1.7-8.5, P < 0.001). Our results provide new insights into a metabolomic phenotype of vascular aging and warrants further investigation of negative association of LPCs with EVA status. This study suggests that LPCs are potential candidates to be considered for further evaluation and validation as predictors of EVA in patients with hypertension.

Urinary metabolomic signature of muscle-invasive bladder cancer: A multiplatform approach.

Bladder cancer (BCa) is ninth amongst the most common types of cancer in the human population worldwide. The statistics of incidence and mortality of BCa are alarming and the currently applied diagnostic methods are still not sensitive enough. This leads to a large number of undiagnosed BCa cases, usually among patients in the early stages of the disease. Despite the fact that many risk factors of BCa have been recognized, the pathomechanism of development of bladder cancer has not been fully explained yet. Therefore, in the present study, multiplatform urinary metabolomics has been implemented in order to scrutinize potential diagnostic indicators of BCa that might help to explain its pathomechanism and be potentially useful in diagnosis and determination of stage of the disease. Urine samples collected from muscle-invasive high grade BCa patients (n = 24) and healthy volunteers (n = 24) were matched in terms of most common BCa risk factors i.e. gender, age, BMI and smoking status. They were analyzed by high performance liquid chromatography coupled with time of flight mass spectrometry detection (HPLC-TOF/MS) using RP and HILIC chromatography, gas chromatography hyphenated with triple quadruple mass spectrometry detection (GC-QqQ/MS) in scan mode, and proton nuclear magnetic resonance (1H NMR). The six datasets obtained were submitted to univariate and multivariate statistical analyses. 17 metabolites significantly discriminated urinary profiles of BCa patients from urinary profiles of healthy volunteers. These metabolites are mainly involved in amino acid metabolism, pyrimidine and purine metabolism, as well as energy metabolism and might play a crucial role in the pathogenesis of BCa.

Multiplatform metabolomics provides insight into the molecular basis of chronic kidney disease.

Changes in metabolites composition can reflect currently present pathological processes in a living organism and constitute a basis for diagnosis and treatment improvements. Thus, the multiplatform metabolomics approach was applied for the investigation of molecular mechanisms of chronic kidney disease (CKD) progression. The high-performance liquid chromatography coupled with time-of-flight mass spectrometry (HPLC-TOF-MS) and gas chromatography coupled with triple quadrupole mass spectrometry (GC-QqQ/MS) serum metabolic fingerprinting followed by uni- and multivariate statistical analysis was carried out to determine metabolic pattern differentiating CKD patients and healthy controls. Furthermore, metabolites changes between stage 3 and 4 of the disease, as well as health status were investigated. The progression of the disease was found to be related to alterations in acylcarnitine, amino acid, lysophospholipid and carbohydrate metabolism. Elevated levels of serum acylcarnitines, sugar alcohols, and organic acids, as well as decreased levels of lysophospholipids, and amino acids, were found to be statistically significant for CKD progression. The obtained results confirm the utility of metabolomics approach as a tool for an explanation of molecular processes underlying CKD development.

Identification of the metabolic fingerprints in women with polycystic ovary syndrome using the multiplatform metabolomics technique.

In addition to chronic anovulation and clinical signs of hyperandrogenism women with polycystic ovary syndrome (PCOS) are insulin resistant and therefore, develop central obesity with its long term consequences such as dyslipidaemia, hypertension, atherosclerosis and type 2 diabetes mellitus (T2DM), which all lead to the development of cardiovascular disease (CVD). Due to the polysymptomatic nature of this syndrome and lack of consensus on its diagnostic criteria there is a strong need of finding a reliable biochemical or molecular marker, which would facilitate making the accurate diagnosis of PCOS. Therefore, the aim of our study was to perform a metabolomics analysis with the use of two complementary techniques: gas chromatography and liquid chromatography coupled with mass spectrometry, of the serum samples from women with PCOS (n = 30) and to compare them with healthy age and BMI matched controls (n = 30). Obtained results were subjected to one-dimensional statistical analysis (student's t-test or its non-parametric equivalent U Mann-Whitney test) and multivariate statistical analysis (the principal component analysis [PCA], variable importance into projection [VIP] and selectivity ratio [SR]). The results of our study showed that women with PCOS are characterised by metabolic disorders of the amino acids, carbohydrates, steroid hormones, lipids and purines. Compared to control subjects, women with PCOS had increased serum levels of phospholipids, aromatic amino acids, organic acids, hormones and sphinganine and decreased total cholesterol. Among the identified compounds, total cholesterol, phenylalanine and dehydroepiandrosterone sulfate, uric and lactic acid were the compounds with the strongest discriminating power.

Metabolomic Heterogeneity of Urogenital Tract Cancers Analyzed by Complementary Chromatographic Techniques Coupled with Mass Spectrometry.

BACKGROUND: In regard to urogenital tract cancer studies, an estimated 340,650 new cases and 58,360 deaths from genital system cancer and about 141,140 new cases and 29330 deaths from urinary system were projected to occur in the United States in 2012. The main drawbacks of currently available diagnostic tests constitute the low specificity, costliness and quite high invasiveness. OBJECTIVE: The main goal of this pilot study was to determine and compare urine metabolic fingerprints in urogenital tract cancer patients and healthy controls. METHOD: A comparative analysis of the metabolic profile of urine from 30 patients with cancer of the genitourinary system (bladder (n=10), kidney (n=10) and prostate (n=10)) and 30 healthy volunteers as a control group was provided by LC-TOF/MS and GCQqQ/ MS. The data analysis was performed by the use of U-Mann Whitney test or Student's t-test, principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). RESULTS: As a result, 33, 43, and 22 compounds were identified as statistically significant in bladder, prostate and kidney cancer, respectively, compared to healthy groups. CONCLUSION: Diverse compounds such as purine, sugars, amino acids, nucleosides, organic acids which play a role in purine metabolism, in tricarboxylic acid cycle, in amino acid metabolism or in gut microbiota metabolism were identified. Only two metabolites namely glucocaffeic acid and lactic acid were found to be in common in studied three types of cancer.

Untargeted Metabolomics Provides Insight into the Mechanisms Underlying Resistant Hypertension.

BACKGROUND: Resistant hypertension (RH) affects about 15-20% of treated hypertensive patients worldwide. RH increases the risk of cardiovascular events such as myocardial infarction and stroke by 50%. The pathological mechanisms underlying resistance to treatment are still poorly understood. OBJECTIVE: The main goal of this pilot study was to determine and compare plasma metabolomic profiles in resistant and non-resistant hypertensive patients. METHODS: We applied untargeted metabolomic profiling in plasma samples collected from 69 subjects with RH and 81 subjects with controlled hypertension. To confirm patients' compliance to antihypertensive treatment, levels of selected drugs and their metabolites were determined in plasma samples with the LC-ESI-TOF/MS technique. RESULTS: The results showed no statistically significant differences in the administration of antihypertensive drug in the compared groups. We identified 19 up-regulated and 13 downregulated metabolites in the RH. CONCLUSION: The metabolites altered in RH are linked to oxidative stress and inflammation, endothelium dysfunction, vasoconstriction and cell proliferation. Our results may generate new hypothesis about RH development and progression.

Targeted metabolomics in bladder cancer: From analytical methods development and validation towards application to clinical samples.

Bladder cancer constitutes the ninth most common cancer worldwide and, despite continuous development of new diagnostic approaches, the thirteenth leading cause of global cancer mortality. In our previous untargeted urine metabolomic investigation, seventeen metabolites were found to be statistically differentiating bladder cancer patients and healthy volunteers. Therefore, the main goal of this study was to develop and validate an analytical method for simultaneous quantitative determination of those metabolites using reversed phase high-performance liquid chromatography coupled with triple quadrupole mass spectrometry technique (RP-HPLC-QQQ/MS). Different chromatographic conditions, as well as various sample treatment procedures were tested in order to provide the best separation and the lowest limit of quantification (LOQ) values for studied compounds. The validation was performed according to the Food and Drug Administration guidelines (FDA). The limit of determination (LOD) and the LOQ values were in the range of 0.21-10.51 ng/ml and 0.69-35.02 ng/ml, respectively. The concentration range of compounds was developed between 2.5 and 12500 ng/ml. Only one compound (trimethyllysine) showed a significant matrix effect (61%) and consequently low process efficiency (64%). Overall, developed method presented recovery and precision values within the ranges proposed by FDA guidelines. The optimized and validated method was applied to urine samples obtained from 40 patients with bladder cancer and 40 healthy volunteers matched according to ones of the most important risk factors for developing urinary bladder tumors, e.i. age, gender and BMI. Afterwards, statistical analysis was provided by the use of Student's t-test or U-Mann Whitney test. The developed method was sensitive, selective and reproducible to be applied for the quantification of metabolites in the investigation of urine samples. As a consequence, ten out of previously chosen seventeen compounds, participating in different metabolites' pathways (gut floral metabolism, RNA degradation, purine metabolism, etc.), were found to be statistically significantly different in the urine concentration (p < 0.05) between cancer and control groups.

New plasma preparation approach to enrich metabolome coverage in untargeted metabolomics: plasma protein bound hydrophobic metabolite release with proteinase K.

Plasma untargeted metabolomics is a common method for evaluation of the mechanisms underlying human pathologies and identification of novel biomarkers. The plasma proteins provide the environment for transport of hydrophobic metabolites. The current sample preparation protocol relies on the immediate precipitation of proteins and thus leads to co-precipitation of a significant fraction of hydrophobic metabolites. Here we present a new simple procedure that overcomes the co-precipitation problem and improves metabolome coverage. Introducing an additional step preceding the protein precipitation, namely limited digestion with proteinase K, allows release of associated metabolites through the relaxation of the native proteins tertiary structure. The modified protocol allows clear detection of hydrophobic metabolites including fatty acids and phospholipids. Considering the potential involvement of the hydrophobic metabolites in human cardiovascular and cancer diseases, the method may constitute a novel approach in plasma untargeted metabolomics.

Comparative pharmacodynamic analysis of imidazoline compounds using rat model of ocular mydriasis with a test of quantitative structure-activity relationships.

Imidazol(in)e derivatives, having the chemical structure similar to clonidine, exert diverse pharmacological activities connected with their interactions with alpha2-adrenergic receptors, e.g. hypotension, bradycardia, sedation as well as antinociceptive, anxiolytic, antiarrhythmic, muscle relaxant and mydriatic effects. The mechanism of pupillary dilation observed after systemic administration of imidazol(in)es to rats, mice and cats depends on the stimulation of postsynaptic alpha2-adrenoceptors within the brain. It was proved that the central nervous system (CNS)-localized I1-imidazoline receptors are not engaged in those effects. It appeared interesting to analyze the CNS-mediated pharmacodynamics of imidazole(in)e agents in terms of their chromatographic and calculation chemistry-derived parameters. In the present study a systematic determination and comparative pharmacometric analysis of mydriatic effects in rats were performed on a series of 20 imidazol(in)e agents, composed of the well-known drugs and of the substances used in experimental pharmacology. The eye pupil dilatory activities of the compounds were assessed in anesthetized Wistar rats according to the established Koss method. Among twenty imidazol(in)e derivatives studied, 18 produced diverse dose-dependent mydriatic effects. In the quantitative structure-activity relationships (QSAR) analysis, the pharmacological data (half maximum mydriatic effect - ED50 in µmol/kg) were considered along with the structural parameters of the agents from molecular modeling. The theoretically calculated lipophilicity parameters, CLOGP, of imidazol(in)es, as well as their lipophilicity parameters from HPLC, logkw, were also considered. The attempts to derive statistically significant QSAR equations for a full series of the agents under study were unsuccessful. However, for a subgroup of eight apparently structurally related imidazol(in)es a significant relationship between log(1/ED50) and logkw values was obtained. The lack of "predictive" QSAR for the whole series of the structurally diverse agents is probably due to a complex mechanism of the ligand-alpha2-adrenergic receptor interactions, which are predominantly of a highly structurally specific polar nature. Such interactions are difficult to quantify with the established chemical structural descriptors, contrary to the less specific, molecular bulkiness-related interactions.

Volatile organic compounds in gastrointestinal stromal tumour tissue originating from patient-derived xenografts.

Gastrointestinal stromal tumours (GISTs) are the most common mesenchymal neoplasms of the gastrointestinal tract and localize mainly in the stomach or small intestine. The metabolomic signatures of GISTs driven by different KIT gene mutations remain undiscovered and unexplored. The main aim of this pilot study was to determine and compare metabolomic profiles in GIST xenograft models with different genetic backgrounds. Metabolomic profiling using gas chromatography coupled with mass spectrometry followed by univariate and multivariate statistical analyses was applied to select metabolites that differentiated the GIST models studied. The significant differences observed in the metabolites were mainly derived from glycolysis, the citric acid cycle and glutamine and lipid metabolism. The obtained results may suggest variable metabolomic signatures of tumours, possibly related to the different underlying, specific KIT gene mutations and with potential implications for the biological behaviour and natural course of this rare disease. This study constitutes a proof of concept in GISTs and reveals the potential of the metabolomic approach in orphan malignancies.