Fine mapping the spatial distribution and concentration of unlabeled drugs within tissue micro-compartments using imaging mass spectrometry.

Readouts that define the physiological distributions of drugs in tissues are an unmet challenge and at best imprecise, but are needed in order to understand both the pharmacokinetic and pharmacodynamic properties associated with efficacy. Here we demonstrate that it is feasible to follow the in vivo transport of unlabeled drugs within specific organ and tissue compartments on a platform that applies MALDI imaging mass spectrometry to tissue sections characterized with high definition histology. We have tracked and quantified the distribution of an inhaled reference compound, tiotropium, within the lungs of dosed rats, using systematic point by point MS and MS/MS sampling at 200 microm intervals.

Essential tactics of tissue preparation and matrix nano-spotting for successful compound imaging mass spectrometry.

The ultimate goal of MALDI-Imaging Mass Spectrometry (MALDI-IMS) is to achieve spatial localization of analytes in tissue sections down to individual tissue compartments or even at the level of a few cells. With compound tissue imaging, it is possible to track the transportation of an unlabelled, inhaled reference compound within lung tissue, through the application of MALDI-IMS. The procedure for isolation and preparation of lung tissues is found to be crucial in order to preserve the anatomy and structure of the pulmonary compartments.

Proteomic analysis of phospholipidosis in citalopram treated U937 cells--support for the cholesterol biosynthesis hypothesis.

Excessive accumulation of phospholipids leads to phospholipidosis (PL), which disrupts cellular functions, in extreme cases leading to acute or chronic disease. Citalopram and many other cationic amphiphilic drugs (CADs) have been shown to cause PL both in vitro and in vivo. Recent toxicogenomic studies suggest four hypothetical mechanisms for PL (lysosomal enzyme transport decrease, lysosomal phospholipase activity decrease, phospholipids biosynthesis increase or cholesterol biosynthesis increase).

Correlation network analysis for data integration and biomarker selection.

High-throughput biomolecular profiling techniques such as transcriptomics, proteomics and metabolomics are increasingly being used in in vivo studies to recognize and characterize effects of xenobiotics on organs and systems. Of particular interest are biomarkers of treatment-related effects which are detectable in easily accessible biological fluids such as blood. A fundamental challenge in such biomarker studies is selecting among the plethora of biomolecular changes induced by a compound and revealed by molecular profiling, to identify biomarkers which are exclusively or predominantly due to specific processes.

Prediction of drug-induced liver injury in humans by using in vitro methods: the case of ximelagatran.

Objective: To investigate the possible mechanisms underlying the liver enzyme elevations seen during clinical studies of long-term treatment (>35 days) with ximelagatran, and investigate the usefulness of pre-clinical in vitro systems to predict drug-induced liver effects.

Methods: Ximelagatran and its metabolites were tested for effects on cell viability, mitochondrial function, formation of reactive metabolites and reactive oxygen species, protein binding, and induction of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) gene expression or nuclear orphan receptors. Experimental systems included fresh and cryopreserved hepatocytes, human hepatoma cell lines (HepG2 and HuH-7) and subcellular human liver fractions.

Protein biomarkers of nephrotoxicity; a review and findings with cyclosporin A, a signal transduction kinase inhibitor and N-phenylanthranilic acid.

Biomarkers of nephrotoxicity range from plasma and urine biochemistry, enzymic assays for brush border and lysosomal markers plus new protein markers by immunoassay. Because of the complexity of the nephron and regional sensitivity to xenobiotics, it is important to co-localise sites of marker release with pathological lesions. Han Wistar rats were treated p.

Identification of end points relevant to detection of potentially adverse drug reactions.

Expectations are high that the use of proteomics, gene arrays and metabonomics will improve risk assessment and enable prediction of toxicity early in drug development. These molecular profiling techniques may be used to classify compounds and to identify predictive markers that can be used to screen large numbers of chemicals. One of the challenges for the scientific community is to discriminate between changes in gene/protein expression and metabolic profiles reflecting physiological/adaptive responses, and changes related to pathology and toxicology.