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Pancreatic ductal adenocarcinoma cancer (PDAC) is a highly lethal malignancy requiring efficient detection when the primary tumor is still resectable. We previously developed the MxPancreasScore comprising 9 analytes and serum carbohydrate antigen 19-9 (CA19-9), achieving an accuracy of 90.6%. The necessity for 5 different analytical platforms and multiple analytical runs, however, hindered clinical applicability. We therefore aimed to develop a simpler single-analytical run, single-platform diagnostic signature.We evaluated 941 patients (PDAC, 356; chronic pancreatitis [CP], 304; nonpancreatic disease, 281) in 3 multicenter independent tests, and identification (ID) and validation cohort 1 (VD1) and 2 (VD2) were evaluated. Targeted quantitative plasma metabolite analysis was performed on a liquid chromatography-tandem mass spectrometry platform. A machine learning-aided algorithm identified an improved (i-Metabolic) and minimalistic metabolic (m-Metabolic) signatures, and compared them for performance.The i-Metabolic Signature, (12 analytes plus CA19-9) distinguished PDAC from CP with area under the curve (95% confidence interval) of 97.2% (97.1%-97.3%), 93.5% (93.4%-93.7%), and 92.2% (92.1%-92.3%) in the ID, VD1, and VD2 cohorts, respectively. In the VD2 cohort, the m-Metabolic signature (4 analytes plus CA19-9) discriminated PDAC from CP with a sensitivity of 77.3% and specificity of 89.6%, with an overall accuracy of 82.4%. For the subset of 45 patients with PDAC with resectable stages IA-IIB tumors, the sensitivity, specificity, and accuracy were 73.2%, 89.6%, and 82.7%, respectively; for those with detectable CA19-92 U/mL, 81.6%, 88.7%, and 84.5%, respectively; and for those with CA19-937 U/mL, 39.7%, 94.1%, and 76.3%, respectively.The single-platform, single-run, m-Metabolic signature of just 4 metabolites used in combination with serum CA19-9 levels is an innovative accurate diagnostic tool for PDAC at the time of clinical presentation, warranting further large-scale evaluation.

Summary Mycotoxin‐producing Fusarium graminearum and related species cause Fusarium head blight on cultivated grasses, such as wheat and barley. However, these Fusarium species may have had a longer evolutionary history with North American grasses than with cultivated crops and may interact with the ancestral hosts in ways which are biochemically distinct.We assayed 25 species of asymptomatic native grasses for the presence of Fusarium species and confirmed infected grasses as hosts using re‐inoculation tests. We examined seed from native grasses for the presence of mycotoxin‐producing Fusarium species and evaluated the ability of these fungi to produce mycotoxins in both native grass and wheat hosts using biochemical analysis.Mycotoxin‐producing Fusarium species were shown to be prevalent in phylogenetically diverse native grasses, colonizing multiple tissue types, including seeds, leaves and inflorescence structures. Artificially inoculated grasses accumulated trichothecenes to a much lesser extent than wheat, and naturally infected grasses showed little to no accumulation.Native North American grasses are commonly inhabited by Fusarium species, but appear to accommodate these toxigenic fungi differently from cultivated crops. This finding highlights how host identity and evolutionary history may influence the outcome of plant–fungal interactions and may inform future efforts in crop improvement., See also the Commentary on this article by Selosse et al., 217: 968–972.

We describe here the agreed upon first development steps and priority objectives of a community engagement effort to address current challenges in quality assurance (QA) and quality control (QC) in untargeted metabolomic studies. This has included (1) a QA and QC questionnaire responded to by the metabolomics community in 2015 which recommended education of the metabolomics community, development of appropriate standard reference materials and providing incentives for laboratories to apply QA and QC; (2) a 2-day 'Think Tank on Quality Assurance and Quality Control for Untargeted Metabolomic Studies' held at the National Cancer Institute's Shady Grove Campus and (3) establishment of the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) to drive forward developments in a coordinated manner.

Integrated analysis of metabolomics, transcriptomics and immunohistochemistry can contribute to a deeper understanding of biological processes altered in cancer and possibly enable improved diagnostic or prognostic tests. In this study, a set of 254 metabolites was determined by gas-chromatography/liquid chromatography-mass spectrometry in matched malignant and non-malignant prostatectomy samples of 106 prostate cancer (PCa) patients. Transcription analysis of matched samples was performed on a set of 15 PCa patients using Affymetrix U133 Plus 2.0 arrays. Expression of several proteins was immunohistochemically determined in 41 matched patient samples and the association with clinico-pathological parameters was analyzed by an integrated data analysis. These results further outline the highly deregulated metabolism of fatty acids, sphingolipids and polyamines in PCa. For the first time, the impact of the ERG translocation on the metabolome was demonstrated, highlighting an altered fatty acid oxidation in TMPRSS2-ERG translocation positive PCa specimens. Furthermore, alterations in cholesterol metabolism were found preferentially in high grade tumors, enabling the cells to create energy storage. With this integrated analysis we could not only confirm several findings from previous metabolomic studies, but also contradict others and finally expand our concepts of deregulated biological pathways in PCa.

Metabolomics is a powerful technology with broad applications in life science that, like other -omics approaches, requires high-quality samples to achieve reliable results and ensure reproducibility. Therefore, along with quality assurance, methods to assess sample quality regarding pre-analytical confounders are urgently needed. In this study, we analyzed the response of the human serum metabolome to pre-analytical variations comprising prolonged blood incubation and extended serum storage at room temperature by using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) -based metabolomics. We found that the prolonged incubation of blood results in a statistically significant 20% increase and 4% decrease of 225 tested serum metabolites. Extended serum storage affected 21% of the analyzed metabolites (14% increased, 7% decreased). Amino acids and nucleobases showed the highest percentage of changed metabolites in both confounding conditions, whereas lipids were remarkably stable. Interestingly, the amounts of taurine and O-phosphoethanolamine, which have both been discussed as biomarkers for various diseases, were 1.8- and 2.9-fold increased after 6 h of blood incubation. Since we found that both are more stable in ethylenediaminetetraacetic acid (EDTA) blood, EDTA plasma should be the preferred metabolomics matrix.

High-quality biological samples are required for the favorable outcome of research studies, and valid data sets are crucial for successful biomarker identification. Prolonged storage of biospecimens may have an artificial effect on compound levels. In order to investigate the potential effects of long-term storage on the metabolome, human ethylenediaminetetraacetic acid (EDTA) plasma samples stored for up to 16 years were analyzed by gas and liquid chromatography-tandem mass spectrometry-based metabolomics. Only 2% of 231 tested plasma metabolites were altered in the first seven years of storage. However, upon longer storage periods of up to 16 years and more time differences of few years significantly affected up to 26% of the investigated metabolites when analyzed within subject age groups. Ontology classes that were most affected included complex lipids, fatty acids, energy metabolism molecules, and amino acids. In conclusion, the human plasma metabolome is adequately stable to long-term storage at &minus, 80 &deg, C for up to seven years but significant changes occur upon longer storage. However, other biospecimens may display different sensitivities to long-term storage. Therefore, in retrospective studies on EDTA plasma samples, analysis is best performed within the first seven years of storage.

The metabolome offers real time detection of the adaptive, multi-parametric response of the organisms to environmental changes, pathophysiological stimuli or genetic modifications and thus rationalizes the optimization of cell cultures in bioprocessing. In bioprocessing the measurement of physiological intracellular metabolite levels is imperative for successful applications. However, a sampling method applicable to all cell types with little to no validation effort which simultaneously offers high recovery rates, high metabolite coverage and sufficient removal of extracellular contaminations is still missing. Here, quenching, centrifugation and fast filtration were compared and fast filtration in combination with a stabilizing washing solution was identified as the most promising sampling method. Different influencing factors such as filter type, vacuum pressure, washing solutions were comprehensively tested. The improved fast filtration method (MxP® FastQuench) followed by routine lipid/polar extraction delivers a broad metabolite coverage and recovery reflecting well physiological intracellular metabolite levels for different cell types, such as bacteria (Escherichia coli) as well as mammalian cells chinese hamster ovary (CHO) and mouse myeloma cells (NS0).The proposed MxP® FastQuench allows sampling, i.e. separation of cells from medium with washing and quenching, in less than 30 seconds and is robustly designed to be applicable to all cell types. The washing solution contains the carbon source respectively the 13C-labeled carbon source to avoid nutritional stress during sampling. This method is also compatible with automation which would further reduce sampling times and the variability of metabolite profiling data.

Objective The objective of the current study was to find a metabolic signature associated with the early manifestations of type-2 diabetes mellitus. Research Design and Method Modern metabolic profiling technology (MxP™ Broad Profiling) was applied to find early alterations in the plasma metabolome of type-2 diabetic patients. The results were validated in an independent study. Eicosanoid and single inon monitoring analysis (MxP™ Eicosanoid and MxP™ SIM analysis) were performed in subsets of samples. Results A metabolic signature including significantly increased levels of glyoxylate as a potential novel marker for early detection of type-2 diabetes mellitus was identified in an initial study (Study1). The signature was significantly altered in fasted diabetic and pre-diabetic subjects and in non-fasted subjects up to three years prior to the diagnosis of type-2 diabetes; most alterations were also consistently found in an independent patient group (Study 2). In Study 2 diabetic and most control subjects suffered from heart failure. In Study 1 a subgroup of diabetic subjects, with a history of use of anti-hypertensive medication further showed a more pronounced increase of glyoxylate levels, compared to a non-diabetic control group when tested in a hyperglycemic state. In the context of a prior history of anti-hypertensive medication, alterations in hexosamine and eicosanoid levels were also found. Conclusion A metabolic signature including glyoxylate was associated with type-2 diabetes mellitus, independent of the fasting status and of occurrence of another major disease. The same signature was also found to be associated with pre-diabetic subjects. Glyoxylate levels further showed a specifically strong increase in a subgroup of diabetic subjects. It could represent a new marker for the detection of medical subgroups of diabetic subjects.

BACKGROUND Metabolomics is a valuable tool with applications in almost all life science areas. There is an increasing awareness of the essential need for high-quality biospecimens in studies applying omics technologies and biomarker research. Tools to detect effects of both blood and plasma processing are a key for assuring reproducible and credible results. We report on the response of the human plasma metabolome to common preanalytical variations in a comprehensive metabolomics analysis to reveal such high-quality markers. METHODS Human EDTA blood was subjected to preanalytical variations while being processed to plasma: microclotting, prolonged processing times at different temperatures, hemolysis, and contamination with buffy layer. In a second experiment, EDTA plasma was incubated at different temperatures for up to 16 h. Samples were subjected to GC-MS and liquid chromatography–tandem mass spectrometry–based metabolite profiling (MxP™ Broad Profiling) complemented by targeted methods, i.e., sphingoids (as part of MxP™ Lipids), MxP™ Catecholamines, and MxP™ Eicosanoids. RESULTS Short-term storage of blood, hemolysis, and short-term storage of noncooled plasma resulted in statistically significant increases of 4% to 19% and decreases of 8% to 12% of the metabolites. Microclotting, contamination of plasma with buffy layer, and short-term storage of cooled plasma were of less impact on the metabolome (0% to 11% of metabolites increased, 0% to 8% decreased). CONCLUSIONS The response of the human plasma metabolome to preanalytical variation demands implementation of thorough quality assurance and QC measures to obtain reproducible and credible results from metabolomics studies. Metabolites identified as sensitive to preanalytics can be used to control for sample quality.

The concentrations of bromocyclen were determined in the water and muscle tissue of trout and bream from the river Stor (northern Germany), to locate the source of this contaminant. The concentrations in water varied between n.d. and 261 pg/L, while in the fish samples concentrations between 0.01 and 0.24 mg/kg fat were determined. In addition, remarkably high concentrations of bromocyclen were found in waste water from sewage plants discharging into the river Stor and at the city of Hamburg. Sewage plants can be, therefore, assumed to be the main source of bromocyclen contamination. This is the first report about the contamination of river water and waste water with bromocyclen. Determination by chiral capillary gas chromatography using a modified cyclodextrin phase showed no significant enantiomeric excess in the water samples, but a preferential degradation of (+)-bromocyclen in the fish muscle tissue of breams.

The study presented here describes the application of metabolite profiling of highly polar, intracellular metabolites after incubation of a mammalian fibroblast cell line with inhibitors of mitochondrial function. A metabolomics approach was used to assess the complex response of the cellular energy metabolism. Metabolic profiles of phosphorylated and carboxylated intracellular metabolites were assessed by UPLC-MS/MS and used to predict the mode of mitochondrial toxicity. Based on distinct metabolic patterns, multivariate data analysis allowed for the discrimination of two groups of toxins: inhibitors of the electron transport in mitochondrial membranes (complex IV inhibitors) and uncouplers of oxidative phosphorylation. Beyond these known interferences, metabolic profiling was able to reveal additional inhibitory effects on the cellular energy metabolism. Most prominently, for three of the toxins, metabolic patterns also disclosed an enhanced activity of the glycerol phosphate shuttle inferring the inhibition of NADH dehydrogenase at complex I. Secondly, inhibition of the electron transport was accompanied by a limiting availability of citric acid cycle intermediates and aspartate. Concomitantly, specific perturbations of the purine nucleotide cycle were observed. We have shown here that metabolomic approaches may assist to predict complex modes of action of toxic compounds on cellular level as well as to unravel specific dysfunctions in the energy metabolism.

Sarcosine in prostate cancer tissue samples was recently reported to be increased during prostate cancer progression to metastasis and suggested to be a key metabolite of cancer cell invasion and aggressiveness. We reevaluated sarcosine in prostate cancer tissue samples as a potential indicator of tumor aggressiveness, and as a predictor of recurrence-free survival.Sarcosine in matched samples of malignant and nonmalignant tissue from 92 patients with prostate cancer after radical prostatectomy was measured in the framework of a global metabolite profiling study of prostate cancer by gas chromatography/mass spectrometry. We related results to age, prostate volume, tumor stage, Gleason score, preoperative prostate specific antigen and biochemical recurrence, defined as a persistent prostate specific antigen increase of greater than 0.2 ng/ml. Nonparametric statistical tests, ROC curves and Kaplan-Meier analyses were done.Median sarcosine content in tissue was about 7% higher in matched malignant vs nonmalignant samples, which was significantly. Sarcosine values were not associated with tumor stage (pT2 vs pT3), tumor grade (Gleason score less than 7 vs 7 or greater) or biochemical recurrence. The lack of metastatic tissue samples was a study limitation.Sarcosine in prostate cancer tissue samples cannot be considered a suitable predictor of tumor aggressiveness or biochemical recurrence.

The environmental pollutant alpha-HCH was analysed in seawater, air and bulk deposition samples from the North Sea. Enantioselective analyses of the sample extracts gave evidence of the change of the direction of net air-water gas transfer of the contaminant in dependence on the season. Due to warmer water surface temperatures during late summer to early autumn the equilibrium of alpha-HCH between air and water is dominated rather by volatilisation than deposition. The volatilisation of non-racemic alpha-HCH, as known to occur from seawater, changes the enantiomeric ratio in air, which is reflected in the observed ratio in rain that passes the air column.

Background and objective: Metabolomic research offers a deeper insight into biochemical changes in cancer metabolism and is a promising tool for identifying novel biomarkers. We aimed to evaluate the diagnostic and prognostic potential of metabolites in prostate cancer (PCa) tissue after radical prostatectomy. Material and methods: 107 matched-paired tissue samples collected after radical prostatectomy were subjected to the MxPTM Broad Profiling by gas chromatography- mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (Patent WO 2010/139711 A1: "Means and methods for diagnosing prostate carcinomas"). Aminoadipic acid, cerebronic acid, gluconic acid, glycerophosphoethanolamine, 2- hydroxybehenic acid, isopentenyl pyrophosphate, maltotriose, 7-methylguanine, and tricosanoic acid were related to clinicopathological variables like prostate volume, tumor stage, Gleason score, preoperative prostate-specific antigen (PSA), and disease recurrence in the follow-up. Non-parametric statistical tests, receiver- operating characteristics (ROC) and univariate and multivariate analyses (Kaplan- Meier curve; Cox regression) were performed. Results: All metabolites showed higher concentrations in malignant than in non- malignant samples except for gluconic acid and maltotriose, which had lower levels in tumors. ROC analyses showed a clear differentiation for all metabolites with a maximal area under the curve of 0.86 for tricosanoic acid. However, the metabolites were not related to tumor stage and Gleason grade. "Aminoadipic acid, gluconic acid, and maltotriose levels were associated with tumor recurrence (Kaplan-Meier analysis) and were, together with tumor stage and Gleason score, a successful metabolite combination in the multivariate Cox regression model for the prediction of tumor recurrence." Conclusions: This exemplary study performed with selected metabolites from a global metabolic profiling investigation proves that metabolites in prostate carcinoma tissue can be used, in combination with traditional pathological and histomorphological parameters, as promising diagnostic and prognostic tools. Citation Format: Glen Kristiansen, Regina Reszka, Beate Kamlage, Bianca Bethan, Michael Lein, Carsten Stephan, Klaus Jung. Metabolite profiling as tool for the identification of differentiating and prognostic markers of prostate carcinoma. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3224. doi:10.1158/1538-7445.AM2013-3224