title: In vivo murine hepatic microRNA and mRNA expression signatures predicting the (non-)genotoxic carcinogenic potential of chemicals.
abstract: There is a high need to improve the assessment of, especially non-genotoxic, carcinogenic features of chemicals. We therefore explored a toxicogenomics-based approach using genome-wide microRNA and mRNA expression profiles upon short-term exposure in mice. For this, wild-type mice were exposed for seven days to three different classes of chemicals, i.e., four genotoxic carcinogens (GTXC), seven non-genotoxic carcinogens (NGTXC), and five toxic non-carcinogens. Hepatic expression patterns of mRNA and microRNA transcripts were determined after exposure and used to assess the discriminative power of the in vivo transcriptome for GTXC and NGTXC. A final classifier set, discriminative for GTXC and NGTXC, was generated from the transcriptomic data using a tiered approach. This appeared to be a valid approach, since the predictive power of the final classifier set in three different classifier algorithms was very high for the original training set of chemicals. Subsequent validation in an additional set of chemicals revealed that the predictive power for GTXC remained high, in contrast to NGTXC, which appeared to be more troublesome. Our study demonstrated that the in vivo microRNA-ome has less discriminative power to correctly identify (non-)genotoxic carcinogen classes. The results generally indicate that single mRNA transcripts do have the potential to be applied in risk assessment, but that additional (genomic) strategies are necessary to correctly predict the non-genotoxic carcinogenic potential of a chemical.
authors.affiliation: Center for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA, Bilthoven, The Netherlands.
authors.forename: Joost P M
authors.initials: JP
authors.lastname: Melis
authors.forename: Kasper W J
authors.initials: KW
authors.lastname: Derks
authors.forename: Tessa E
authors.initials: TE
authors.lastname: Pronk
authors.forename: Paul
authors.initials: P
authors.lastname: Wackers
authors.forename: Mirjam M
authors.initials: MM
authors.lastname: Schaap
authors.forename: Edwin
authors.initials: E
authors.lastname: Zwart
authors.forename: Wilfred F J
authors.initials: WF
authors.lastname: van Ijcken
authors.forename: Martijs J
authors.initials: MJ
authors.lastname: Jonker
authors.forename: Timo M
authors.initials: TM
authors.lastname: Breit
authors.forename: Joris
authors.initials: J
authors.lastname: Pothof
authors.forename: Harry
authors.initials: H
authors.lastname: van Steeg
authors.forename: Mirjam
authors.initials: M
authors.lastname: Luijten
mesh_terms: D000465:Algorithms; D000818:Animals; D002273:Carcinogens / Q000145:classification / Q000633:toxicity*; D016002:Discriminant Analysis; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation / Q000187:drug effects; D005819:Genetic Markers; D008099:Liver / Q000187:drug effects* / Q000378:metabolism; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D035683:MicroRNAs / Q000378:metabolism*; D009153:Mutagens / Q000145:classification / Q000633:toxicity*; D012333:RNA, Messenger / Q000378:metabolism*; D015203:Reproducibility of Results; D018570:Risk Assessment; D013997:Time Factors; D043922:Toxicogenetics / Q000379:methods*
chemical_list: D002273:Carcinogens; D005819:Genetic Markers; D035683:MicroRNAs; D009153:Mutagens; D012333:RNA, Messenger