TY - GEN
T1 - Prediction of non-genotoxic hepatocarcinogenicity using chemical-protein interactions
AU - Tung, Chun Wei
PY - 2013/8/1
Y1 - 2013/8/1
N2 - 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.
AB - 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.
KW - Chemical-Protein Interaction
KW - Decision Tree
KW - Interpretable Rule
KW - Non-Genotoxic Hepatocarcinogenicity
KW - Toxicology
UR - http://www.scopus.com/inward/record.url?scp=84880727780&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84880727780&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-39159-0-21
DO - 10.1007/978-3-642-39159-0-21
M3 - Conference contribution
AN - SCOPUS:84880727780
SN - 9783642391583
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 231
EP - 241
BT - Pattern Recognition in Bioinformatics - 8th IAPR International Conference, PRIB 2013, Proceedings
T2 - 8th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2013
Y2 - 17 June 2013 through 20 June 2013
ER -