Literature DB >> 18355885

Gene expression profiling in rat liver treated with compounds inducing phospholipidosis.

Mitsuhiro Hirode1, Atsushi Ono, Toshikazu Miyagishima, Taku Nagao, Yasuo Ohno, Tetsuro Urushidani.   

Abstract

We have constructed a large-scale transcriptome database of rat liver treated with various drugs. In an effort to identify a biomarker for diagnosis of hepatic phospholipidosis, we extracted 78 probe sets of rat hepatic genes from data of 5 drugs, amiodarone, amitriptyline, clomipramine, imipramine, and ketoconazole, which actually induced this phenotype. Principal component analysis (PCA) using these probes clearly separated dose- and time-dependent clusters of treated groups from their controls. Moreover, 6 drugs (chloramphenicol, chlorpromazine, gentamicin, perhexiline, promethazine, and tamoxifen), which were reported to cause phospholipidosis but judged as negative by histopathological examination, were designated as positive by PCA using these probe sets. Eight drugs (carbon tetrachloride, coumarin, tetracycline, metformin, hydroxyzine, diltiazem, 2-bromoethylamine, and ethionamide), which showed phospholipidosis-like vacuolar formation in the histopathology, could be distinguished from the typical drugs causing phospholipidosis. Moreover, the possible induction of phospholipidosis was predictable by the expression of these genes 24 h after single administration in some of the drugs. We conclude that these identified 78 probe sets could be useful for diagnosis of phospholipidosis, and that toxicogenomics would be a promising approach for prediction of this type of toxicity.

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Year:  2008        PMID: 18355885     DOI: 10.1016/j.taap.2008.01.036

Source DB:  PubMed          Journal:  Toxicol Appl Pharmacol        ISSN: 0041-008X            Impact factor:   4.219


  11 in total

1.  Glucosylceramide and lysophosphatidylcholines as potential blood biomarkers for drug-induced hepatic phospholipidosis.

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2.  Human skin-derived stem cells as a novel cell source for in vitro hepatotoxicity screening of pharmaceuticals.

Authors:  Robim M Rodrigues; Joery De Kock; Steven Branson; Mathieu Vinken; Kesavan Meganathan; Umesh Chaudhari; Agapios Sachinidis; Olivier Govaere; Tania Roskams; Veerle De Boe; Tamara Vanhaecke; Vera Rogiers
Journal:  Stem Cells Dev       Date:  2013-09-21       Impact factor: 3.272

3.  Interaction of gentamicin with phosphatidylserine/phosphatidylcholine mixtures in adsorption monolayers and thin liquid films: morphology and thermodynamic properties.

Authors:  Georgi D Georgiev; Georgi As Georgiev; Z Lalchev
Journal:  Eur Biophys J       Date:  2010-03-04       Impact factor: 1.733

4.  Predicting drug-induced hepatotoxicity using QSAR and toxicogenomics approaches.

Authors:  Yen Low; Takeki Uehara; Yohsuke Minowa; Hiroshi Yamada; Yasuo Ohno; Tetsuro Urushidani; Alexander Sedykh; Eugene Muratov; Viktor Kuz'min; Denis Fourches; Hao Zhu; Ivan Rusyn; Alexander Tropsha
Journal:  Chem Res Toxicol       Date:  2011-07-21       Impact factor: 3.739

Review 5.  Practical application of toxicogenomics for profiling toxicant-induced biological perturbations.

Authors:  Naoki Kiyosawa; Sunao Manabe; Takashi Yamoto; Atsushi Sanbuissho
Journal:  Int J Mol Sci       Date:  2010-09-20       Impact factor: 5.923

6.  Predicting the mechanism of phospholipidosis.

Authors:  Robert Lowe; Hamse Y Mussa; Florian Nigsch; Robert C Glen; John Bo Mitchell
Journal:  J Cheminform       Date:  2012-01-26       Impact factor: 5.514

7.  Toxicogenomic biomarkers for liver toxicity.

Authors:  Naoki Kiyosawa; Yosuke Ando; Sunao Manabe; Takashi Yamoto
Journal:  J Toxicol Pathol       Date:  2009-04-06       Impact factor: 1.628

8.  Model steatogenic compounds (amiodarone, valproic acid, and tetracycline) alter lipid metabolism by different mechanisms in mouse liver slices.

Authors:  Ewa Szalowska; Bart van der Burg; Hai-Yen Man; Peter J M Hendriksen; Ad A C M Peijnenburg
Journal:  PLoS One       Date:  2014-01-29       Impact factor: 3.240

9.  Open TG-GATEs: a large-scale toxicogenomics database.

Authors:  Yoshinobu Igarashi; Noriyuki Nakatsu; Tomoya Yamashita; Atsushi Ono; Yasuo Ohno; Tetsuro Urushidani; Hiroshi Yamada
Journal:  Nucleic Acids Res       Date:  2014-10-13       Impact factor: 16.971

10.  Whole genome transcript profiling of drug induced steatosis in rats reveals a gene signature predictive of outcome.

Authors:  Nishika Sahini; Saravanakumar Selvaraj; Jürgen Borlak
Journal:  PLoS One       Date:  2014-12-03       Impact factor: 3.240

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