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Metastasis is the main cause of death from colorectal cancer (CRC). About 20% of stage II CRC patients develop metastasis during the course of disease. We performed metabolic profiling of plasma samples from non-metastasized and metachronously metastasized stage II CRC patients to assess the potential of plasma metabolites to serve as biomarkers for stratification of stage II CRC patients according to metastasis risk. We compared the metabolic profiles of plasma samples prospectively obtained prior to metastasis formation from non-metastasized vs. metachronously metastasized stage II CRC patients of the German population-based case–control multicenter DACHS study retrospectively. Plasma samples were analyzed from stage II CRC patients for whom follow-up data including the information on metachronous metastasis were available. To identify metabolites distinguishing non-metastasized from metachronously metastasized stage II CRC patients robust supervised classifications using decision trees and support vector machines were performed and verified by 10-fold cross-validation, by nested cross-validation and by traditional validation using training and test sets. We found that metabolic profiles distinguish non-metastasized from metachronously metastasized stage II CRC patients. Classification models from decision trees and support vector machines with 10-fold cross-validation gave average accuracy of 0.75 (sensitivity 0.79, specificity 0.7) and 0.82 (sensitivity 0.85, specificity 0.77), respectively, correctly predicting metachronous metastasis in stage II CRC patients. Taken together, plasma metabolic profiles distinguished non-metastasized and metachronously metastasized stage II CRC patients. The classification models consisting of few metabolites stratify non-invasively stage II CRC patients according to their risk for metachronous metastasis.
Under the auspices of the Protein Analysis Working Group (PAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) a pilot study, CCQM-P216, was coordinated by the Chinese National Institute of Metrology (NIM), National Research Council of Canada (NRC) and the Bureau International des Poids et Mesures (BIPM). Eleven Metrology Institutes or Designated Institutes and the BIPM participated in the first phase of the pilot study (Part 1). The purpose of this pilot study was to develop measurement capabilities for larger proteins using a recombinant humanized IgG monoclonal antibody against Spike glycoprotein of SARS-CoV-2 (Anti-S IgG mAb) in solution. The first phase of the study was designed to employ established methods that had been previously studies by the CCQM Protein Analysis Working Group, involving the digestion of protein down to the peptide or amino acid level. The global coronavirus pandemic has also led to increased focus on antibody quantitation methods. IgG are among the immunoglobulins produced by the immune system to provide protection against SARS-CoV-2. Anti-SARS-CoV-2 IgG can therefore be detected in samples from affected patients. Antibody tests can show whether a person has been exposed to the SARS-CoV-2, and whether or not they potentially show lasting immunity to the disease. With the constant spread of the virus and the high pressure of re-opening economies, antibody testing plays a critical role in the fight against COVID-19 by helping healthcare professionals to identify individuals who have developed an immune response, either via vaccination or exposure to the virus. Many countries have launched large-scale antibody testing for COVID-19. The development of measurement standards for the antibody detection of SARS-CoV-2 is critically important to deal with the challenges of the COVID-19 pandemic. In this study, the SARS-CoV-2 monoclonal antibody is being used as a model system to build capacity in methods that can be used in antibody quantification. Amino acid reference values with corresponding expanded uncertainty of 36.10 ± 1.55 mg/kg, 38.75 ± 1.45 mg/kg, 18.46 ± 0.78 mg/kg, 16.20 ± 0.67 mg/kg and 30.61 ± 1.30 mg/kg have been established for leucine, valine, phenylalanine, isoleucine and proline, respectively. Agreement between nearly all laboratories was achieved for the amino acid analysis within 2 to 2.5 %, with one participant achieving markedly higher results due to a technical issue found in their procedure; this result was thus excluded from the reference value calculations. The relatively good agreement within a laboratory between different amino acids was not dissimilar to previous results for peptides or small proteins, indicating that factors such as hydrolysis conditions and calibration procedures could be the largest sources of variability. Peptide reference values with corresponding expanded uncertainty of 4.99 ± 0.28 mg/kg and 6.83 ± 0.65 mg/kg have been established for ALPAPIEK and GPSVFPLAPSSK, respectively. Not surprisingly due to prior knowledge from previous studies on peptide quantitation, agreement between laboratories for the peptide-based analysis was slightly poorer at 3 to 5 %, with one laboratory's result excluded for the peptide GPSVFPLAPSSK. Again, this level of agreement was not significantly poorer than that achieved in previous studies with smaller or less complex proteins. To reach the main text of this paper, click on Final Report.
“Fluxomics” refers to the systematic analysis of metabolic fluxes in a biological system and may uncover novel dynamic properties of metabolism that remain undetected in conventional metabolomic approaches. In labeling experiments, tracer molecules are used to track changes in the isotopologue distribution of metabolites, which allows one to estimate fluxes in the metabolic network. Because unidentified compounds cannot be mapped on pathways, they are often neglected in labeling experiments. However, using recent developments in de novo annotation may allow to harvest the information present in these compounds if they can be identified. Here, we present a novel tool (HiResTEC) to detect tracer incorporation in high-resolution mass spectrometry data sets. The software automatically extracts a comprehensive, nonredundant list of all compounds showing more than 1% tracer incorporation in a nontargeted fashion. We explain and show in an example data set how mass precision and other filter heuristics, calculated on the raw data, can efficiently be used to reduce redundancy and noninformative signals by 95%. Ultimately, this allows to quickly investigate any labeling experiment for a complete set of labeled compounds (here 149) with acceptable false positive rates. We further re-evaluate a published data set from liquid chromatography-electrospray ionization (LC-ESI) to demonstrate broad applicability of our tool and emphasize importance of quality control (QC) tests. HiResTEC is provided as a package in the open source software framework R and is freely available on CRAN.
To set up recommendations on how to define “reasonable minimum composition thresholds” for CO2 streams to access CO2 pipeline networks, we investigated potential impacts of CO2 streams with different and temporally variable compositions and mass flow rates along the CCS chain. All investigations were based on a generic “CCS cluster scenario” in which CO2 streams captured from a spatial cluster of eleven emitters (seven fossil-fired power plants, two cement plants, one refinery and one steel mill) are collected in a regional pipeline network. The resulting CO2 stream (19.78 Mio t impure CO2 per year) is transported in a trunk line (onshore and offshore) and injected into five generic replicate storage structures (Buntsandstein saline aquifers) offshore. Experimental investigations and modeling of selected impacts revealed beneficial as well as adverse impacts of different impurities and their combinations. Overall, no fundamental technical obstacles for transporting, injecting and storing CO2 streams of the considered variable compositions and mass flow rates were observed. We recommend to define minimum composition thresholds for each specific CCS project through limiting
i) the overall CO2 content,
ii) maximum contents of relevant impurities or elements,
iii) acceptable variability of concentrations of critical impurities, and defining impurity combinations to be avoided.
The collaborative project “Impacts of impurities in CO2 streams captured from different emitters in a regional cluster on transport, injection and storage (CLUSTER)” aimed to set up recommendations on how to define “reasonable minimum composition thresholds” that CO2 streams should meet when accessing CO2 transport pipeline networks. Within CLUSTER, we investigated potential impacts of CO2 streams with different and temporally variable compositions and mass flow rates along the whole CCS chain. Investigations included, amongst others, impacts on: Corrosion of pipeline steel, pipeline network design and related transport costs, alteration of well bore cements, pressure development and rock integrity, geochemical reactions, and petrophysical and geomechanical rock properties.
All investigations are based on a generic CCS chain scenario. In this scenario, CO2 streams are captured from a spatial cluster of eleven emitters and collected in a regional pipeline network. Emitters comprise seven fossil fuel-fired power plants equipped with different capture technologies, two cement plants, one refinery and one integrated iron and steel plant. In total, 19.78 Mio t CO2 (including impurities) are captured in the emitter cluster annually. The combined CO2 stream is transported in a trunk line with a length of 400 km (100 km of these offshore) and is injected into five generic storage structures. The storage reservoirs are saline aquifers of the Buntsandstein.
The investigations revealed beneficial and deteriorating impacts of different impurities and combinations thereof. Overall, no fundamental technical obstacles for transporting, injecting and storing CO2 streams of the modelled variable compositions and mass flow rates were observed. Based on the results, the CLUSTER project team recommends not to define “minimum composition thresholds” for CO2 streams as strict threshold values for each individual impurity in the stream. Instead, CO2 stream compositions and variabilities for specific CCS projects should be constrained with regard to a set of parameters including i) the overall CO2 content, ii) maximum contents of relevant impurities or elements, iii) acceptable variability of CO2 stream composition, and iv) impurity combinations to be avoided.
Cardiolipin (CL) is a major cardiac mitochondrial phospholipid maintaining regular mitochondrial morphology and function in cardiomyocytes. Cardiac CL production includes ist biosynthesis and a CL-remodeling process. Here we studied the impact of CL-biosynthesis and the enzyme Cardiolipin Synthase (CLS) on cardiac function.
CLS and cardiac CL-species were significantly downregulated in cardiomyocytes following catecholamine-induced cardiac damage in mice, accompanied by increased oxygen consumption rates, signs of oxidative stress and mitochondrial uncoupling. RNAi-mediated cardiomyocyte-specific knockdown of CLS in Drosophila melanogaster resulted in marked cardiac dilatation, severe impairment of systolic performance and slower diastolic filling velocity assessed by fluorescence-based heart imaging. Finally, we showed that CL72:8 is significantly decreased in cardiac samples from patients with heart failure with reduced ejection fraction (HFrEF). In summary, we identified CLS as a regulator of cardiac function. Considering the cardiac depletion of CL-species in HFrEF, pharmacological targeting of CLS may be a promising therapeutic approach.zeige mehrzeige weniger
MACC1 is a prognostic and predictive metastasis biomarker for more than 20 solid Cancer entities. However, its role in cancer metabolism is not sufficiently explored. Here, we report on how MACC1 impacts the use of glucose, glutamine, lactate, pyruvate and fatty acids and show the comprehensive analysis of MACC1-driven metabolic networks. We analyzed concentrationdependent changes in nutrient use, nutrient depletion, metabolic tracing employing 13C-labeled substrates, and in vivo studies. We found that MACC1 permits numerous effects on cancer
metabolism. Most of those effects increased nutrient uptake. Furthermore, MACC1 alters metabolic pathways by affecting metabolite production or turnover from metabolic substrates. MACC1 supports use of glucose, glutamine and pyruvate via their increased depletion or altered distribution within metabolic pathways. In summary, we demonstrate that MACC1 is an important regulator of metabolism in cancer cells.
Raw data from metabolomics experiments are initially subjected to peak identification and signal deconvolution to generate raw data matrices m × n, where m are samples and n are metabolites. We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification.
Limited data exist on the pharmacokinetic profile of novel direct acting antivirals in kidney transplant recipients. Daclatasvir is primarily eliminated via the biliary route and sofosbuvir via the renal route; here we report the pharmacokinetic profile of combined treatment with these compounds in a prospective study of hepatitis C virus positive kidney transplant recipients (EudraCT: 2014-004551-32). In this study plasma samples of 16 HCV positive kidney transplant recipients receiving daclatasvir and sofosbuvir were collected at 4 time points at day 1, 7, 14, 21, 56, and 84 after start of treatment. Inclusion criteria were stable graft function and an estimated GFR (eGFR) > 30mL/min/1.73m. Daclatasvir, sofosbuvir and GS-331007 (inactive metabolite of sofosbuvir) plasma concentrations were determined using ultra-performance liquid chromatography quadrupole time of flight mass spectrometry. All patients showed a rapid virological response with HCV RNA below the detection limit 21 days after the start of therapy (medium time to viral clearance). No difference of the areas under the concentration-time curve (AUC) of daclatsavir, sofosbuvir and GS-331007 was observed between patients with an eGFR below or ≥ 60mL/min. For GS-331007, no relevant changes of trough levels were observed over time. Mean GS-331007 trough levels were 339.5±174.9 ng/mL in patients with an eGFR ≥ 60mL/min and 404.3±226 ng/mL in patients with an eGFR < 60mL/min at day 7 (p=0.52). At day 84, GS-331007 trough levels were 357.8±200.8 ng/mL and 404.2±70.2 ng/mL in patients with an eGFR ≥ 60 mL/min and in patients with an eGFR < 60 mL/min, respectively (p=0.51). The accumulation ratios of renally eliminated GS-331007 for AUC and Cmax did not significantly differ between the two eGFR groups at day 7. An impaired eGFR (30-60 mL/min) does not lead to a dose accumulation of daclatasvir, sofosbuvir and GS-331007. This study provides the rationale for future studies investigating the pharmacokinetic profile of sofosbuvir based HCV treatment in kidney transplant recipients with an eGFR < 30 mL/min.
Cancer cell lipid class homeostasis is altered under nutrient-deprivation but stable under hypoxia
(2018)
Under oxygen/nutrient deprivation cancer cells modify the Balance between fatty acid (FA) synthesis and uptake, which alters the levels of individual triglyceride or phospholipid sub-species. These modifications may affect survival and drug-uptake in cancer cells. Here, we aimed to attain a more holistic overview of the lipidomic profiles of cancer cells under stress and assess the changes in Major lipid-classes. First, expressions of markers of FA synthesis/uptake in cancer cells were assessed and found to be differentially regulated under metabolic stress. Next, we performed a broad lipidomics assay, comprising 244 lipids from six major classes, which allowed us to investigate robust stress induced changes in median levels of different lipid classes -additionally stratified by fatty acid side chain saturation status. The lipidomic profiles of cancer cells were predominantly affected by nutrient-deprivation. Neutral lipid compositions were markedly modified under serum-deprivation and, strikingly, the cellular level of triglyceride subspecies decreased with increasing number of double bonds in their fatty acyl chains. In contrast, cancer cells maintained lipid class homeostasis under hypoxic stress. We conclude that although the levels of individual lipid moieties alter under hypoxia, the robust averages of broader lipid class remain unchanged.