Systems and chemical biology approaches to study cell function and response to toxins

Toxicity is one of the main causes of failure during drug discovery, and of withdrawal once drugs reached the market. Prediction of potential toxicities in the early stage of drug development has thus become of great interest to reduce such costly failures. Since toxicity results from chemical perturbation of biological systems, we combined biological and chemical strategies to help understand and ultimately predict drug toxicities. First, we proposed a systematic strategy to predict and understand the mechanistic interpretation of drug toxicities based on chemical fragments. Fragments frequently found in chemicals with certain toxicities were defined as structural alerts for use in prediction. Some of the predictions were supported with mechanistic interpretation by integrating fragmentchemical, chemical-protein, protein-protein interactions and gene expression data. Next, we systematically deciphered the mechanisms of drug actions and toxicities by analyzing the associations of drugs’ chemical features, biological features and their gene expression profiles from the TG-GATEs database. We found that in vivo (rat liver) and in vitro (rat hepatocyte) gene expression patterns were poorly overlapped and gene expression responses in different species (rat and human) and different tissues (liver and kidney) varied widely. Eventually, for further understanding of individual differences in drug responses, we reviewed how genetic polymorphisms influence the individual's susceptibility to drug toxicity by deriving chemical-protein interactions and SNP variations from Mechismo database. Such a study is also essential for personalized medicine. Overall, this study showed that, integrating chemical and biological in addition to genetic data can help assess and predict drug toxicity at system and population levels

Metabolic biomarker responses in acute cerebral events

Aims The aims of this study were to identify a potential blood biomarker for acute stroke and additionally to identify biomarkers capable of differentiating hyper-acute ischaemic from haemorrhagic stroke using metabonomic techniques. Methodology Following ethical approval participants were recruited from the hyper-acute stroke unit at Charing Cross Hospital and acute blood samples taken from patients who were suspected of having an acute stroke. Serum was extracted and frozen prior to MS and NMR analysis. Sub-acute TIA patients were used as a comparative group and patients with known atherosclerotic disease as a non-acute control group. A total of 90 participants were recruited for analysis. Positive and negative mode reverse phase UPLC-MS and additionally 1H-NMR spectroscopy were used to analyse prepared serum samples. Modelling was performed using OPLS-DA and CA-PLS techniques where appropriate following permutation analysis to detect discriminatory metabolites between participant groups. Results Positive mode mass spectrometry detected metabolites that could differentiate between participants who had suffered an acute cerebral ischaemic event (inclusive of stroke and acute TIA) and those participants that were known to have established atherosclerotic disease. The metabolites detected include phosphatidylcholines, sphingomyelins and a ganglioside. Unfortunately, due to a relatively small sample size the CA-PLS false discovery rate analysis found the initial results to lack statistical significance (Q value = 0.95). It was not possible to metabolically differentiate between acute ischaemic and haemorrhagic strokes. Conclusion Despite the relatively small sample size leading to a confirmed false discovery rate analysis the initial findings of elevated phosphatidylcholines, sphingomyelins and the peripheral detection of a ganglioside in relation to acute cerebral ischaemia is promising and follows a trend in the published literature. Further studies with a larger sample size, rigorous follow up and temporal trend analysis using dedicated lipidomic techniques may find a sensitive diagnostic serological biomarker for hyper-acute stroke and transient ischaemic attack.Open Acces

Applications of Mass Spectrometry in Proteomics and Pharmacokinetics

Tremendous technology improvements of the last decades has given mass spectrometry a more and more expanding role in the study of a wide range of molecules: from the identification and quantification of small molecular weight molecules to the structural determination of biomacromolecules. Many are the fields of application for this technique and the various versions of it. In the present study three different applications have been explored. The first application is a pharmacokinetics study of anticancer drug Gemcitabine and its principal metabolite, where the role of the LC-MS/MS is essential both for the selectivity of the detection of the small analytes and the sensitivity enhanced by multi-reaction monitoring experiments. The design of the study involved the collection of several blood samples at selected times and from patients that would have met certain eligibility criteria. The ESI demonstrated to be the most suitable approach and it provided the necessary data to conclude that toxicity of Gemcitabine did not increase when administered at FDR (Fixed Dose Rate) infusion in patients with impaired hepatic function. The second application describes an example of how MS represents a powerful tool in cancer research, from serum profiling study with high resolution MALDITOF and bioinformatic analysis, to the identification of potential biomarker through peak identification. Almost 400 serum sample – homogeneously distributed between biopsy confirmed ovarian cancer and high risk serum samples – were analyzed on a high resolution MALDI-TOF instrument after automated reverse phase magnetic beads separation. The high throughput data have undergone sophisticated bioinformatic procedures that lead to a list of upand down-regulated peaks, although identification studies were possible only for those peaks that showed a good reproducibility. One down-regolated peak has been identified using the LC-MS/MS technique. The identified peak confirmed a basic role of fibrinogen in the ovarian cancer; the other four peaks that have been identified as down-regulated showed an absolutely not satisfactory ionization in electro-spray, therefore further analysis will be performed on these analytes in order to determinate their amino acidic sequence. The most suitable technique seems to be MALDI-TOF/TOF mass spectrometry, since the peptides already showed a good degree of ionization in MALDI. The third and last study belongs to a quite new field, which is the combination of immuno precipitation assays with MALDI-TOF (Immuno Precipitation Mass Spectrometry, IPMS) experiments in order to evaluate the specificity of a series of monoclonal antibodies to specific antigen. The automated assay that has been developed provides structural information about the antigen that binds the monoclonal antibody to be tested and previously conjugated to the surface of magnetic beads, ideal support for robotic automation. IPMS showed its potential as a complementary tool of crucial importance in the selection of the monoclonal antibody for the development of ELISA based assay to be applied in the screening of a consistent number of human specimens for the clinical validation of proteins indicated in literature as potential biomarkers. Mass spectrometry in association with fractionation techniques, such as liquid or magnetic beads chromatography, is a very flexible tool in the cancer research field. Further improvement in the instrumentation and in the technology will bring always more and more results to be confident in