Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database

Takeki Uehara, Yohsuke Minowa, Yuji Morikawa, Chiaki Kondo, Toshiyuki Maruyama, Ikuo Kato, Noriyuki Nakatsu, Yoshinobu Igarashi, Atsushi Ono, Hitomi Hayashi, Kunitoshi Mitsumori, Hiroshi Yamada, Yasuo Ohno, Tetsuro Urushidani

Research output: Contribution to journalArticlepeer-review

83 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)297-306
Number of pages10
JournalToxicology and Applied Pharmacology
Issue number3
Publication statusPublished - Sep 15 2011
Externally publishedYes


  • Hepatocarcinogenicity
  • Microarray
  • Non-genotoxic hepatocarcinogens
  • TG-GATEs
  • Toxicogenomics

ASJC Scopus subject areas

  • Toxicology
  • Pharmacology


Dive into the research topics of 'Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database'. Together they form a unique fingerprint.

Cite this