Establishment and Validation of Classifiers to Predict Genotoxic and Non-Genotoxic Carcinogens
L Jian-jun1, LI Yao-ting1,3, ZHOU Shu-ya2, FAN Chang-fa2, ZENG Xue-zhen3, LI Bao-wen2, WANG Ju-feng1, HUANG Zhi-ying3*, LI Bo4*
1. Beijing Key Laboratory, National Center for Safety Evaluation of Drugs, National Institutes for Food and Drug Control, Beijing 100176, China; 2. Institute for Laboratory Animal Resources, National Institutes for Food and Drug Control, Beijing 100079, China; 3. School of Pharmaceutical Science, Sun Yat-sen University, Guangzhou 510006, China; 4. National Institutes for Food and Drug Control, Beijing 100050, China
Abstract��OBJECTIVE To establish classifiers to predict genotoxic and non-genotoxic carcinogens using toxicogenomics methods, explore the effect of exposure time and validated the prediction performance of the classifiers. METHODS The primary mouse hepatocyte model was treated for 24 and 48 h with two genotoxic carcinogens, aflatoxin B1(AFB1), benzo(a)pyrene (BAP) and two non-genotoxic carcinogens, thioacetamide (TAA), wyeth-14643 (WY). The differentially expressed genes were input to prediction analysis for microarray (PAM) software to screen out classifiers. The functions and interrelations of genes in classifiers were studied by gene set enrichment analysis (GSEA) and the protein-protein interactions were predicted using STRING database. Two additional carcinogens to validate the prediction performance of the classifiers were used. Finally, the experiment of QuantiGene Multiplex assay (Q-GP) to validate the microarray data was used. RESULTS Forty-eight h classifiers had a better predicted capability than that of 24 h classifiers. p53 pathway, TNF-�� signaling pathway, fatty acid metabolism, PPAR signaling pathway involved in the classifires were enriched by GSEA. Carcinogenic protein-protein interaction network and metabolism-related protein-protein interaction network are obtained using STRING database. The predicted probability of the two additional carcinogens using 48 h classifiers was nearly 100% and data between QuantiGene Multiplex assay and microarray assay had a high conformity. CONCLUSION The classifiers which could be used to discriminate the potential genotoxic carcinogens and non-genotoxic carcinogens and to predict modes of action for unknown compounds, are successfully established and validated. This might be a promising candidate in vitro method for carcinogenicity study in the field of nonclinical safety evaluation of drugs.
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L Jian-jun, LI Yao-ting, ZHOU Shu-ya, FAN Chang-fa, ZENG Xue-zhen, LI Bao-wen, WANG Ju-feng, HUANG Zhi-ying, LI Bo. Establishment and Validation of Classifiers to Predict Genotoxic and Non-Genotoxic Carcinogens. Chinese Pharmaceutical Journal, 2016, 51(20): 1753-1764.
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2016, Vol. 51 
