Detection of polyol accumulation in a new ovarian carcinoma cell line, CABA I: a1H NMR study

Ovarian carcinomas represent a major form of gynaecological malignancies, whose treatment consists mainly of surgery and chemotherapy. Besides the difficulty of prognosis, therapy of ovarian carcinomas has reached scarce improvement, as a consequence of lack of efficacy and development of drug-resistance. The need of different biochemical and functional parameters has grown, in order to obtain a larger view on processes of biological and clinical significance. In this paper we report novel metabolic features detected in a series of different human ovary carcinoma lines, by 1H NMR spectroscopy of intact cells and their extracts. Most importantly, a new ovarian adenocarcinoma line CABA I, showed strong signals in the spectral region between 3.5 and 4.0 p.p.m., assigned for the first time to the polyol sorbitol (39±11 nmol/106 cells). 13C NMR analyses of these cells incubated with [1-13C]-D-glucose demonstrated labelled-sorbitol formation. The other ovarian carcinoma cell lines (OVCAR-3, IGROV 1, SK-OV-3 and OVCA432), showed, in the same spectral region, intense resonances from other metabolites: glutathione (up to 30 nmol/106 cells) and myo-inositol (up to 50 nmol/106 cells). Biochemical and biological functions are suggested for these compounds in human ovarian carcinoma cells, especially in relation to their possible role in cell detoxification mechanisms during tumour progression

Whole genome association mapping by incompatibilities and local perfect phylogenies

BACKGROUND: With current technology, vast amounts of data can be cheaply and efficiently produced in association studies, and to prevent data analysis to become the bottleneck of studies, fast and efficient analysis methods that scale to such data set sizes must be developed. RESULTS: We present a fast method for accurate localisation of disease causing variants in high density case-control association mapping experiments with large numbers of cases and controls. The method searches for significant clustering of case chromosomes in the "perfect" phylogenetic tree defined by the largest region around each marker that is compatible with a single phylogenetic tree. This perfect phylogenetic tree is treated as a decision tree for determining disease status, and scored by its accuracy as a decision tree. The rationale for this is that the perfect phylogeny near a disease affecting mutation should provide more information about the affected/unaffected classification than random trees. If regions of compatibility contain few markers, due to e.g. large marker spacing, the algorithm can allow the inclusion of incompatibility markers in order to enlarge the regions prior to estimating their phylogeny. Haplotype data and phased genotype data can be analysed. The power and efficiency of the method is investigated on 1) simulated genotype data under different models of disease determination 2) artificial data sets created from the HapMap ressource, and 3) data sets used for testing of other methods in order to compare with these. Our method has the same accuracy as single marker association (SMA) in the simplest case of a single disease causing mutation and a constant recombination rate. However, when it comes to more complex scenarios of mutation heterogeneity and more complex haplotype structure such as found in the HapMap data our method outperforms SMA as well as other fast, data mining approaches such as HapMiner and Haplotype Pattern Mining (HPM) despite being significantly faster. For unphased genotype data, an initial step of estimating the phase only slightly decreases the power of the method. The method was also found to accurately localise the known susceptibility variants in an empirical data set – the ΔF508 mutation for cystic fibrosis – where the susceptibility variant is already known – and to find significant signals for association between the CYP2D6 gene and poor drug metabolism, although for this dataset the highest association score is about 60 kb from the CYP2D6 gene. CONCLUSION: Our method has been implemented in the Blossoc (BLOck aSSOCiation) software. Using Blossoc, genome wide chip-based surveys of 3 million SNPs in 1000 cases and 1000 controls can be analysed in less than two CPU hours

EVALUATION OF S9788 AS A POTENTIAL MODULATOR OF DRUG-RESISTANCE AGAINST HUMAN TUMOR SUBLINES EXPRESSING DIFFERING RESISTANCE MECHANISMS IN-VITRO

Significant activity has been identified using S9788, a triazineaminopiperidine derivative, as a new modulator of multidrug resistance against a series of drug-resistant human tumour-cell lines in vitro. Maximal non-cytotoxic concentrations (i.e., those resulting in less-than-or-equal-to 10% cytotoxicity) of S9788 or verapamil were tested in combination with vinblastine, Adriamycin or vincristine and cytotoxicity was evaluated using a clonogenic assay, or the metabolic dye reduction MTT assay, or by monitoring growth inhibition. Under these conditions, the extent of resistance modulation by verapamil and by S9788 was comparable in the various tumour cell lines tested, although a definite concentration-dependent modulation was noted with both compounds. The highest dose-modification factors were noted in the highly vinblastine-resistant classic multi-drug-resistant subline CEM/VLB100, although resistance reversal was only partial. Resistance modulation by both verapamil and S9788 was noted in 4 drug-selected resistant sublines and 4 ''intrinsically'' resistant human tumour cell lines, which all exhibited significant P-glycoprotein expression. In contrast, in 2 drug-resistant human tumour sublines (GLC4/ADR and CEM/VM-1) characterized by altered topoisomerase-II activity and proving to be P-glycoprotein-negative, no resistance modulation relative to parental cells was observed. These data are consistent with the proposal that resistance modulation is mediated by interaction between S9788 and P-glycoprotein and support its clinical evaluation in patients with P-glycoprotein-positive tumours. (C) 1993 Wiley-Liss, Inc

Opioid antagonists and the A118G polymorphism in the μ-opioid receptor gene: effects of GSK1521498 and naltrexone in healthy drinkers stratified by OPRM1 genotype

The A118G single-nucleotide polymorphism (SNP rs1799971) in the μ-opioid receptor gene, OPRM1, has been much studied in relation to alcohol use disorders. The reported effects of allelic variation at this SNP on alcohol-related behaviors, and on opioid receptor antagonist treatments, have been inconsistent. We investigated the pharmacogenetic interaction between A118G variation and the effects of two μ-opioid receptor antagonists in a clinical lab setting. Fifty-six overweight and moderate–heavy drinkers were prospectively stratified by genotype (29 AA homozygotes, 27 carriers of at least 1 G allele) in a double-blind placebo-controlled, three-period crossover design with naltrexone (NTX; 25 mg OD for 2 days, then 50 mg OD for 3 days) and GSK1521498 (10 mg OD for 5 days). The primary end point was regional brain activation by the contrast between alcohol and neutral tastes measured using functional magnetic resonance imaging (fMRI). Secondary end points included other fMRI contrasts, subjective responses to intravenous alcohol challenge, and food intake. GSK1521498 (but not NTX) significantly attenuated fMRI activation by appetitive tastes in the midbrain and amygdala. GSK1521498 (and NTX to a lesser extent) significantly affected self-reported responses to alcohol infusion. Both drugs reduced food intake. Across all end points, there was less robust evidence for significant effects of OPRM1 allelic variation, or for pharmacogenetic interactions between genotype and drug treatment. These results do not support strong modulatory effects of OPRM1 genetic variation on opioid receptor antagonist attenuation of alcohol- and food-related behaviors. However, they do support further investigation of GSK1521498 as a potential therapeutic for alcohol use and eating disorders

A coding polymorphism in the CYSLT2 receptor with reduced affinity to LTD4 is associated with asthma

Background Cysteinyl leukotrienes (CYSLTR) are potent biological mediators in the pathophysiology of asthma for which two receptors have been characterized, CYSLTR1 and CYSLTR2. The leukotriene modifying agents currently used to control bronchoconstriction and inflammation in asthmatic patients are CYSLTR1-specific leukotriene receptor antagonists. In this report, we investigated a possible role for therapeutic modulation of CYSLTR2 in asthma by investigating genetic association with asthma and further characterization of the pharmacology of a coding polymorphism