Prediction of Non-genotoxic Hepatocarcinogenicity Using Chemical-Protein Interactions

  • Chun-Wei Tung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7986)


The assessment of non-genotoxic hepatocarcinogenicity of chemicals is currently based on 2-year rodent bioassays. It is desirable to develop a fast and effective method to accelerate the identification of potential hepatocarcinogenicity of non-genotoxic chemicals. In this study, a novel method CPI is proposed to predict potential hepatocarcinogenicity of non-genotoxic chemicals. The CPI method is based on chemical-protein interactions and interpretable decision tree classifiers.The interpretable rules generated by the CPI method are analyzed to provide insights into the mechanism and biomarkers of non-genotoxic hepatocarcinogenicity. The CPI method with an independent test accuracy of 86% using only 1 protein biomarker outperforms the state-of-the-art methods of gene expression profile-based toxicogenomics using 90 gene biomarkers. A protein ABCC3 was identified as a potential protein biomarker for further exploration. This study presents the potential application of CPI method for assessing non-genotoxic hepatocarcinogenicity of chemicals.


Non-Genotoxic Hepatocarcinogenicity Decision Tree Chemical-Protein Interaction Interpretable Rule Toxicology 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Chun-Wei Tung
    • 1
    • 2
  1. 1.School of PharmacyKaohsiung Medical UniversityTaiwan
  2. 2.ToxicologyKaohsiung Medical UniversityTaiwan

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