Development and evaluation of a genomic signature for the prediction and mechanistic assessment of nongenotoxic hepatocarcinogens in the rat - PubMed (original) (raw)

doi: 10.1093/toxsci/kfr202. Epub 2011 Aug 2.

Alex Adai, Robert T Dunn 2nd, Andrew Olaharski, George Searfoss, Joe Sina, Jiri Aubrecht, Eric Boitier, Paul Nioi, Scott Auerbach, David Jacobson-Kram, Nandini Raghavan, Yi Yang, Andrew Kincaid, Jon Sherlock, Shen-Jue Chen, Bruce Car; Predictive Safety Testing Consortium, Carcinogenicity Working Group

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Development and evaluation of a genomic signature for the prediction and mechanistic assessment of nongenotoxic hepatocarcinogens in the rat

Mark R Fielden et al. Toxicol Sci. 2011 Nov.

Abstract

Evaluating the risk of chemical carcinogenesis has long been a challenge owing to the protracted nature of the pathology and the limited translatability of animal models. Although numerous short-term in vitro and in vivo assays have been developed, they have failed to reliably predict the carcinogenicity of nongenotoxic compounds. Extending upon previous microarray work (Fielden, M. R., Nie, A., McMillian, M., Elangbam, C. S., Trela, B. A., Yang, Y., Dunn, R. T., II, Dragan, Y., Fransson-Stehen, R., Bogdanffy, M., et al. (2008). Interlaboratory evaluation of genomic signatures for predicting carcinogenicity in the rat. Toxicol. Sci. 103, 28-34), we have developed and extensively evaluated a quantitative PCR-based signature to predict the potential for nongenotoxic compounds to induce liver tumors in the rat as a first step in the safety assessment of potential nongenotoxic carcinogens. The training set was derived from liver RNA from rats treated with 72 compounds and used to develop a 22-gene signature on the TaqMan array platform, providing an economical and standardized assay protocol. Independent testing on over 900 diverse samples (66 compounds) confirmed the interlaboratory precision of the assay and its ability to predict known nongenotoxic hepatocarcinogens (NGHCs). When tested under different experimental designs, strains, time points, dose setting criteria, and other preanalytical processes, the signature sensitivity and specificity was estimated to be 67% (95% confidence interval [CI] = 38-88%) and 59% (95% CI = 44-72%), respectively, with an area under the receiver operating characteristic curve of 0.65 (95% CI = 0.46-0.83%). Compounds were best classified using expression data from short-term repeat dose studies; however, the prognostic expression changes appeared to be preserved after longer term treatment. Exploratory evaluations also revealed that different modes of action for nongenotoxic and genotoxic compounds can be discriminated based on the expression of specific genes. These results support a potential early preclinical testing paradigm to catalyze broader understanding of putative NGHCs.

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