TY - CHAP A1 - Lisec, Jan A1 - Jaeger, C. ED - Antonio, C. T1 - Statistical and Multivariate Analysis of MS-Based Plant Metabolomics Data N2 - 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. KW - Mass-Spectrometry KW - Multivariate Statistics PY - 2018 SN - 978-1-4939-7819-9 SN - 978-1-4939-7818-2 U6 - https://doi.org/10.1007/978-1-4939-7819-9_20 SN - 1064-3745 SN - 1940-6029 VL - 1778 SP - Chapter 20, 285 EP - 296 PB - Springer-Verlag AN - OPUS4-45492 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lisec, Jan A1 - Hoffmann, F. A1 - Jaeger, C. A1 - Bhattacharya, A. A1 - Schmitt, C. A. T1 - Nontargeted Identification of Tracer Incorporation in High- Resolution Mass Spectrometry N2 - “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. KW - Fluxomics KW - R package KW - Mass-Spectrometry PY - 2018 U6 - https://doi.org/10.1021/acs.analchem.8b00356 VL - 90 IS - 12 SP - 7253 EP - 7260 PB - ACS Publications AN - OPUS4-45493 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schrezenmeier, E. A1 - Hoffmann, F. A1 - Jaeger, C. A1 - Schrezenmeier, J. A1 - Lisec, Jan A1 - Glander, P. A1 - Algharably, E. A1 - Kreutz, R. A1 - Budde, K. A1 - Duerr, M. A1 - Halleck, F. T1 - Pharmacokinetics of Daclatasvir, Sofosbuvir and GS-331007 in a Prospective Cohort of HCV positive Kidney Transplant Recipients N2 - 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. KW - Mass-Spectrometry PY - 2018 U6 - https://doi.org/10.1097/FTD.0000000000000567 SN - 0163-4356 VL - 41 IS - 1 SP - 53 EP - 58 PB - Wolters Kluwer AN - OPUS4-46647 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Zaimenko, I. A1 - Jaeger, C. A1 - Brenner, H. A1 - Chang-Claude, J. A1 - Hoffmeister, M. A1 - Grötzinger, C. A1 - Detjen, K. A1 - Burock, S. A1 - Schmitt, C.A. A1 - Stein, U. A1 - Lisec, Jan T1 - Non-invasive metastasis prognosis from plasma metabolites in stage II colorectal cancer patients: The DACHS study N2 - 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. KW - Mass-Spectrometry KW - Cancer PY - 2019 U6 - https://doi.org/10.1002/ijc.32076 SN - 1097-0215 VL - 145 IS - 1 SP - 221 EP - 231 PB - Wiley AN - OPUS4-47465 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lisec, Jan A1 - Jaeger, C. A1 - Zaidi, Nousheen T1 - Cancer cell lipid class homeostasis is altered under nutrient-deprivation but stable under hypoxia N2 - 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. KW - Mass-Spectrometry KW - Tumor metabolism KW - Fatty acid metabolism KW - Lipidomic profile KW - Metabolic stress PY - 2018 U6 - https://doi.org/10.1101/382457 SP - 1 EP - 25 PB - Cold Spring Harbor Laboratory CY - Cold Spring Harbor, NY AN - OPUS4-46814 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -