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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.
“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.
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.
Ethnopharmacological relevance: Berberis orthobotrys (BORM) is a medical plant with a long history in traditional usage for the treatment of wounds, cancer, gastrointestinal malady and several other diseases. Our previous studies identified the endemic Pakistani plant Berberis orthobotrys Bien. ex Aitch. as promising source for the treatment of breast cancer and osteosarcoma.
Aim of the study: The present study was aimed to evaluate the anti-cancer properties of 26 plant derived extracts and compounds including the methanolic root extract of Berberis orthobotrys (BORM) on pediatric alveolar rhabdomyosarcoma (RMA), which is known to develop drug resistance, metastatic invasion and potential Tumor progression.
Materials and methods: The main anti-tumor activity of BORM was verified by focusing on morphological, cell structural and metabolic alterations via metabolic profiling, cell viability measurements, flow cytometry, western blotting and diverse microscopy-based methods using the human RMA cell line Rh30.
Results: Exposure of 25 μg/ml BORM exerts an influence on the cell stability, the degradation of oncosomes as well as the shutdown of the metabolic activity of RMA cells, primarily by downregulation of the energy metabolism.
Therefore glycyl-aspartic acid and N-acetyl serine decreased moderately, and uracil increased intracellularly. On healthy, non-transformed muscle cells BORM revealed very low metabolic alterations and nearly no cytotoxic impact. Furthermore, BORM is also capable to reduce Rh30 cell migration (~50%) and proliferation (induced G2/M cycle arrest) as well as to initiate apoptosis confirmed by reduced Bcl-2, Bax and PCNA expression and induced PARP-1 cleavage.
Conclusions: The study provides the first evidence, that BORM treatment is effective against RMA cells with low side effects on healthy cells.
Cancer cell lipid class homeostasis is altered under nutrient-deprivation but stable under hypoxia
(2019)
Background: Cancer cells modify the balance between fatty acid (FA) synthesis and uptake under metabolic stress, induced by oxygen/nutrient deprivation. These modifications were shown to alter the levels of individual triglyceride (TG) or phospholipid sub-species. To attain a holistic overview of the lipidomic profiles of cancer cells under stress we performed a broad lipidomic assay, comprising 244 lipids from six major classes. This assay allowed us to perform robust analyses and assess the changes in averages of broader lipid-classes, stratified on the basis of saturation index of their fatty-acyl side chains.
Methods: Global lipidomic profiling using Liquid Chromatography-Mass Spectrometry was performed to assess lipidomic profiles of biologically diverse cancer cell lines cultivated under metabolically stressed conditions.
Results: Neutral lipid compositions were markedly modified under serum-deprived conditions and, strikingly, the cellular level of triglyceride subspecies decreased with increasing number of double bonds in their fatty acyl chains.
In contrast and unexpectedly, no robust changes were observed in lipidomic profiles of hypoxic (2% O2) Cancer cells despite concurrent changes in proliferation rates and metabolic gene expression.
Conclusions: Serum-deprivation significantly affects lipidomic profiles of cancer cells. Although, the levels of individual lipid moieties alter under hypoxia (2% O2), the robust averages of broader lipid classes remain unchanged.
The knowledge of transformation pathways and identification of transformation products (TPs) of veterinary drugs is important for animal health, food, and environmental matters. The active agent Monensin (MON) belongs to the ionophore antibiotics and is widely used as a veterinary drug against coccidiosis in broiler farming. However, no electrochemically (EC) generated TPs of MON have been described so far. In this study, the online coupling of EC and mass spectrometry (MS) was used for the generation of oxidative TPs. EC-conditions were optimized with respect to working electrode material, solvent, modifier, and potential polarity. Subsequent LC/HRMS (liquid chromatography/high resolution mass spectrometry) and MS/MS experiments were performed to identify the structures of derived TPs by a suspected target analysis. The obtained EC-results were compared to TPs observed in metabolism tests with microsomes and hydrolysis experiments of MON.
Five previously undescribed TPs of MON were identified in our EC/MS based study and one TP, which was already known from literature and found by a microsomal assay, could be confirmed.
Two and three further TPs were found as products in microsomal tests and following hydrolysis, respectively. We found decarboxylation, O-demethylation and acid-catalyzed ring-opening reactions to be the major mechanisms of MON transformation.
Cancer cell lipid class homeostasis is altered under nutrient-deprivation but stable under hypoxia
(2019)
Background: Cancer cells modify the balance between fatty acid (FA) synthesis and uptake under metabolic stress, induced by oxygen/nutrient deprivation. These modifications were shown to alter the levels of individual triglyceride (TG) or phospholipid sub-species. To attain a holistic overview of the lipidomic profiles of cancer cells under stress we performed a broad lipidomic assay, comprising 244 lipids from six major classes. This assay allowed us to perform robust analyses and assess the changes in averages of broader lipid-classes, stratified on the basis of saturation index of their fatty-acyl side chains.
Methods: Global lipidomic profiling using Liquid Chromatography-Mass Spectrometry was performed to assess lipidomic profiles of biologically diverse cancer cell lines cultivated under metabolically stressed conditions.
Results: Neutral lipid compositions were markedly modified under serum-deprived conditions and, strikingly, the cellular level of triglyceride subspecies decreased with increasing number of double bonds in their fatty acyl chains.
In contrast and unexpectedly, no robust changes were observed in lipidomic profiles of hypoxic (2% O2) cancer cells despite concurrent changes in proliferation rates and metabolic gene expression.
Conclusions: Serum-deprivation significantly affects lipidomic profiles of cancer cells. Although, the levels of individual lipid moieties alter under hypoxia (2% O2), the robust averages of broader lipid classes remain unchanged.
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.
Cancer cells are often exposed to a metabolically challenging environment with scarce availability of oxygen and nutrients. This metabolic stress leads to changes in the balance between the endogenous synthesis and exogenous uptake of fatty acids, which are needed by cells for membrane biogenesis, energy production and protein modification. Alterations in lipid metabolism and, consequently, lipid composition have important therapeutic implications, as they affect the survival, membrane dynamics and therapy response of cancer cells. In this article, we provide an overview of recent insights into the regulation of lipid metabolism in cancer cells under metabolic stress and discuss how this metabolic adaptation helps cancer cells thrive in a harsh tumour microenvironment.
Multiple works have studied possible associations between human leukocyte antigen (HLA) alleles and end stage renal disease (ESRD) showing, however, contradictory and inconsistent results. Here, we revisit the association between ESRD and HLA antigens, comparing HLA polymorphism (at HLA-A, -B, -C, -DRB1, -DQB1 and DQA1 loci) in ESRD patients (n = 497) and controls (n = 672). Our data identified several HLA alleles that displayed a significant positive or negative association with ESRD. We also determined whether heterozygosity or homozygosity of the ESRD-associated HLA alleles at different loci could modify the prevalence of the disease. Few HLA allele combinations displayed significant associations with ESRD, among which A*3_26 combination showed the highest strength of association (OR = 4.488, P≤ 0.05) with ESRD. Interestingly, the age of ESRD onset was not affected by HLA allele combinations at different loci. We also performed an extensive literature analysis to determine whether the association of HLA to ESRD can be similar across different ethnic groups. Our analysis showed that at least certain HLA alleles, HLA-A*11, HLA-DRB1*11, and HLA-DRB1*4, display a significant association with ESRD in different ethnic groups. The findings of our study will help in determining possible protective or susceptible roles of various HLA alleles in ESRD.