Epigenetic activation of MGAT3 and corresponding bisecting GlcNAc shortens the survival of cancer patients.

Bisecting GlcNAc on N-glycoproteins is described in E-cadherin-, EGF-, Wnt- and integrin- cancer-associated signaling pathways. However, the mechanisms regulating bisecting GlcNAc expression are not clear. Bisecting GlcNAc is attached to N-glycans through beta 1-4 N-acetylglucosaminyl transferase III (MGAT3), which is encoded by two exons flanked by high-density CpG islands. Despite a recently described correlation of MGAT3 and bisecting GlcNAc in ovarian cancer cells, it remains unknown whether DNA methylation is causative for the presence of bisecting GlcNAc. Here, we narrow down the regulatory genomic region and show that reconstitution of MGAT3 expression with 5-Aza coincides with reduced DNA methylation at the MGAT3 transcription start site. The presence of bisecting GlcNAc on released N-glycans was detected by mass spectrometry (LC-ESI-qTOF-MS/MS) in serous ovarian cancer cells upon DNA methyltransferase inhibition. The regulatory impact of DNA methylation on MGAT3 was further evaluated in 18 TCGA cancer types (n = 6118 samples) and the results indicate an improved overall survival in patients with reduced MGAT3 expression, thereby identifying long-term survivors of high-grade serous ovarian cancers (HGSOC). Epigenetic activation of MGAT3 was also confirmed in basal-like breast cancers sharing similar molecular and genetic features with HGSOC. These results provide novel insights into the epigenetic regulation of MGAT3/bisecting GlcNAc and demonstrate the importance of N-glycosylation in cancer progression.

Experiments for a systematic comparison between stable-isotope-(deuterium) labeling and radio-((14)C) labeling for the elucidation of the in vitro metabolic pattern of pharmaceutical drugs.

A systematic comparison between two labeling approaches for the investigation of the in vitro metabolic pattern of pharmaceutical drugs was performed by examining the use of (i) radiolabeled drugs analyzed with LC-MS-offline radiodetection and (ii) stable-isotope labeled drugs, used in a defined mixture with the unlabeled drug and analyzed by LC-MS with recognition of the specific isotopic pattern. (14)C was used for the radioisotope-approach and deuterium for the stable-isotope approach. Olanzapine, diclofenac and ketoconazole were chosen as model drugs, as they are commercially available in their non-, radio- and stable-isotope labeled forms. For all three model drugs, liver microsome- and hepatocyte-incubations (both from rat) were performed with various concentrations and incubation times for both, the radio- and the stable-isotope approaches. The metabolic pattern, including structure elucidation of all detected metabolites, was performed independently for all individual compounds and incubations. Subsequently, the metabolic patterns of the radio-, and the stable-isotope approaches were compared. In conclusion, all metabolites found with the radioisotope approach could also be found with the stable-isotope approach. Although the stable-isotope approach does not provide a quantitative result, it can be considered to be a highly suited analytical alternative for early in vitro metabolism investigations, especially when radiolabeled drug analogues are not yet available and quantitative results are not yet necessary.

Contemporary issues in toxicology the role of metabonomics in toxicology and its evaluation by the COMET project.

The role that metabonomics has in the evaluation of xenobiotic toxicity studies is presented here together with a brief summary of published studies. To provide a comprehensive assessment of this approach, the Consortium for Metabonomic Toxicology (COMET) has been formed between six pharmaceutical companies and Imperial College of Science, Technology and Medicine (IC), London, UK. The objective of this group is to define methodologies and to apply metabonomic data generated using (1)H NMR spectroscopy of urine and blood serum for preclinical toxicological screening of candidate drugs. This is being achieved by generating databases of results for a wide range of model toxins which serve as the raw material for computer-based expert systems for toxicity prediction. The project progress on the generation of comprehensive metabonomic databases and multivariate statistical models for prediction of toxicity, initially for liver and kidney toxicity in the rat and mouse, is reported. Additionally, both the analytical and biological variation which might arise through the use of metabonomics has been evaluated. An evaluation of intersite NMR analytical reproducibility has revealed a high degree of robustness. Second, a detailed comparison has been made of the ability of the six companies to provide consistent urine and serum samples using a study of the toxicity of hydrazine at two doses in the male rat, this study showing a high degree of consistency between samples from the various companies in terms of spectral patterns and biochemical composition. Differences between samples from the various companies were small compared to the biochemical effects of the toxin. A metabonomic model has been constructed for urine from control rats, enabling identification of outlier samples and the metabolic reasons for the deviation. Building on this success, and with the completion of studies on approximately 80 model toxins, first expert systems for prediction of liver and kidney toxicity have been generated.