Utility of Toxicogenomics Tools for the Toxicological Assessment of Polycyclic Aromatic Hydrocarbons and Complex Polycyclic Aromatic Hydrocarbon Mixtures

Abstract

Human exposures to polycyclic aromatic hydrocarbons (PAHs) occur as components of complex mixtures. Evaluations of health risks posed by complex mixtures containing PAHs rely on the toxicological knowledge of prioritized PAH mixture components, assuming that these PAHs share a common mode of action and that the sum of the contributions of these PAHs equals the toxic potency of the mixture (i.e., additivity). Traditional toxicity testing methods emphasizing apical endpoints have had limited success at evaluating the validity of these assumptions. Toxicogenomic tools that are able to rapidly generate toxicologically-relevant and mechanistic information have gained acceptance in the regulatory arena for individual chemicals; however, the applicability of these tools for chemical mixtures has been inadequately addressed. This thesis used toxicogenomic tools to (1) improve the understanding of mechanisms underlying the adverse, toxicological responses induced by individual PAHs and (2) evaluate the contention that transcriptional profiles and pathway information can be used to critically examine interactions between individual PAHs in PAH-containing mixtures, and the assumption of additivity. Microarrays were used to profile gene expression changes (transcriptomes) in forestomach, liver, and lung tissues (targets of PAH exposure) from mice orally exposed to three doses of eight individual PAHs, two defined PAH mixtures, and one complex PAH-containing mixture (coal tar). The results revealed that each PAH induced transcriptional changes that were significantly associated with several pathways implicated in carcinogenesis. However, despite a uniform ability to induce DNA damage (i.e., DNA adducts), mutations, and increases in enzyme activity, the pathways differ across PAHs and tissues. A novel strategy that employs single-PAH transcriptome data to models of additivity revealed that the assumption of additivity in PAH mixtures is valid at the pathway level; however, the independent action model of additivity yielded better estimates compared to concentration addition (used in human health risk assessment of PAH mixtures) or generalized concentration addition. Additionally, predicted and observed coal tar-induced transcriptional benchmark doses were comparable to those derived from previously published coal tar-induced murine lung tumour incidence data. Overall, this thesis demonstrates the utility of toxicogenomic data to expand the current understanding regarding the toxic potential of individual PAHs and PAH-containing complex mixtures.