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.
Аннотация
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.
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Обработка статьи · этапы, ошибки и управление
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История · было → стало
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