TY - JOUR
T1 - Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database
AU - Uehara, Takeki
AU - Minowa, Yohsuke
AU - Morikawa, Yuji
AU - Kondo, Chiaki
AU - Maruyama, Toshiyuki
AU - Kato, Ikuo
AU - Nakatsu, Noriyuki
AU - Igarashi, Yoshinobu
AU - Ono, Atsushi
AU - Hayashi, Hitomi
AU - Mitsumori, Kunitoshi
AU - Yamada, Hiroshi
AU - Ohno, Yasuo
AU - Urushidani, Tetsuro
N1 - Funding Information:
These studies were supported by a grant from the Ministry of Health, Labour and Welfare of Japan ( H14-Toxico-001 and H19-Toxico-001 ).
PY - 2011/9/15
Y1 - 2011/9/15
N2 - The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificity in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing.
AB - The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificity in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing.
KW - Hepatocarcinogenicity
KW - Microarray
KW - Non-genotoxic hepatocarcinogens
KW - TG-GATEs
KW - Toxicogenomics
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U2 - 10.1016/j.taap.2011.07.001
DO - 10.1016/j.taap.2011.07.001
M3 - Article
C2 - 21784091
AN - SCOPUS:80052356895
VL - 255
SP - 297
EP - 306
JO - Toxicology and Applied Pharmacology
JF - Toxicology and Applied Pharmacology
SN - 0041-008X
IS - 3
ER -