Literature DB >> 24161236

A metabolomics investigation of non-genotoxic carcinogenicity in the rat.

Zsuzsanna Ament1, Claire L Waterman, James A West, Catherine Waterfield, Richard A Currie, Jayne Wright, Julian L Griffin.   

Abstract

Non-genotoxic carcinogens (NGCs) promote tumor growth by altering gene expression, which ultimately leads to cancer without directly causing a change in DNA sequence. As a result NGCs are not detected in mutagenesis assays. While there are proposed biomarkers of carcinogenic potential, the definitive identification of non-genotoxic carcinogens still rests with the rat and mouse long-term bioassay. Such assays are expensive and time-consuming and require a large number of animals, and their relevance to human health risk assessments is debatable. Metabolomics and lipidomics in combination with pathology and clinical chemistry were used to profile perturbations produced by 10 compounds that represented a range of rat non-genotoxic hepatocarcinogens (NGC), non-genotoxic non-hepatocarcinogens (non-NGC), and a genotoxic hepatocarcinogen. Each compound was administered at its maximum tolerated dose level for 7, 28, and 91 days to male Fisher 344 rats. Changes in liver metabolite concentration differentiated the treated groups across different time points. The most significant differences were driven by pharmacological mode of action, specifically by the peroxisome proliferator activated receptor alpha (PPAR-α) agonists. Despite these dominant effects, good predictions could be made when differentiating NGCs from non-NGCs. Predictive ability measured by leave one out cross validation was 87% and 77% after 28 days of dosing for NGCs and non-NGCs, respectively. Among the discriminatory metabolites we identified free fatty acids, phospholipids, and triacylglycerols, as well as precursors of eicosanoid and the products of reactive oxygen species linked to processes of inflammation, proliferation, and oxidative stress. Thus, metabolic profiling is able to identify changes due to the pharmacological mode of action of xenobiotics and contribute to early screening for non-genotoxic potential.

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Year:  2013        PMID: 24161236      PMCID: PMC3980845          DOI: 10.1021/pr4007766

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  62 in total

Review 1.  Genotoxic and nongenotoxic carcinogens: mechanisms of action and testing strategies.

Authors:  C Ramel
Journal:  IARC Sci Publ       Date:  1992

2.  Interlaboratory evaluation of genomic signatures for predicting carcinogenicity in the rat.

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Authors:  R S Chhabra
Journal:  Toxic Rep Ser       Date:  2000-04

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Authors:  J E Le Belle; N G Harris; S R Williams; K K Bhakoo
Journal:  NMR Biomed       Date:  2002-02       Impact factor: 4.044

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Authors:  Alex Y Nie; Michael McMillian; J Brandon Parker; Angelique Leone; Stewart Bryant; Lynn Yieh; Anton Bittner; Jay Nelson; Andrew Carmen; Jackson Wan; Peter G Lord
Journal:  Mol Carcinog       Date:  2006-12       Impact factor: 4.784

7.  Bioassay of N,N'-diethylthiourea for possible carcinogenicity.

Authors: 
Journal:  Natl Cancer Inst Carcinog Tech Rep Ser       Date:  1979

8.  An in vivo-in vitro replicative DNA synthesis (RDS) test using rat hepatocytes as an early prediction assay for nongenotoxic hepatocarcinogens screening of 22 known positives and 25 noncarcinogens.

Authors:  Y Uno; H Takasawa; M Miyagawa; Y Inoue; T Murata; K Yoshikawa
Journal:  Mutat Res       Date:  1994-02       Impact factor: 2.433

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