Identification of a novel set of biomarkers for evaluating phospholipidosis-inducing potential of compounds using rat liver microarray data measured 24-h after single dose administration

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• 作者：Henrik T. Yudate^a ; ¹ ; Toshihiro Kai^a ; ¹ ; ^{tkai@m.u-tokyo.ac.jp} ; Mikio Aoki^a ; Yohsuke Minowa^b ; Toru Yamada^a ; Toru Kimura^a ; Atsushi Ono^c ; Hiroshi Yamada^b ; Yasuo Ohno^d ; Tetsuro Urushidani^b ; ^e
• 关键词：Biomarker ; Phospholipidosis ; Microarray ; Gene expression ; Toxicogenomics ; Liver
• 刊名：Toxicology
• 出版年：2012
• 期刊代码：47_0300483x
• 类别：pha
• 出版时间：16 May, 2012
• 卷：295
• 期：1-3
• 页码：1-7
• 文件大小：393 K

摘要

Phospholipid accumulation manifests as an adverse effect of cationic amphiphilic drugs in particular. Detection, however, by histopathology examination is time-consuming and may require repeated administration of compounds for several weeks. To eliminate compounds with potential for inducing phospholipidosis from the discovery pipeline, we have identified and validated a set of biomarkers for predicting the phospholipidosis-inducing potential utilizing a comprehensive rat transcriptome microarray database created by the Japanese Toxicogenomics and Toxicogenomics Informatics Projects (TGP/TGP2) together with in-house data. The set of biomarkers comprising 25 Affymetrix GeneChip probe sets was identified using genetic algorithm optimization on 24-h time-point microarray data from rats treated with single doses of hepatotoxic compounds including amiodarone, clomipramine, haloperidol, hydroxyzine, imipramine, and perhexiline. The set of novel biomarkers represents an early time-point gene-expression pattern characteristic for a condition eventually leading to phospholipidosis. This implies significant advantages in terms of time and resources over currently published biomarkers derived using repeated-dosing late time-point data. The biomarker set was validated by 11 independent compounds. Accuracy, sensitivity, and specificity values were 82%, 67%, and 100%, respectively and the area under the receiver operating characteristic curve was 0.97. These results show that the biomarker set possesses a high classification accuracy for novel compounds. Pathway analysis was carried out for the biomarkers and the detection of pathways related to lipid-metabolism was statistically significant. These pathways most probably reflect lipid metabolism changes associated with phospholipidosis supporting the validity of our novel biomarkers.