- The environmental health science community recognizes polycyclic aromatic hydrocarbons (PAHs) as a re-emerging class of environmental pollutants due to their persistence and prominence in mixtures of concern. Due to their widespread distribution in the environment, exposure to PAHs often occur as complex chemical mixtures. Exposures are linked to numerous adverse health outcomes in humans, with cancer as the greatest concern. Current assessment of cancer risk for PAHs involves testing individual compounds in a two-year rodent bioassay. These studies are time and resource-intensive, and often lack reproducibility or concordance. Furthermore, they require extrapolation of effects to humans, leading to further uncertainties regarding species-specific biology and chemical mode of action (MOA). The primary method for estimating cancer risk of PAH mixtures is the relative potency factor (RPF) approach in which mixtures are evaluated based on a subset of individual component PAHs compared to benzo[a]pyrene (BAP) as a surrogate or reference. However, we and others have found this approach has proved to be inadequate for predicting carcinogenicity of PAH mixtures and certain individual PAHs, particularly those that function through alternate pathways or exhibit greater promotional capacity compared to BAP. Furthermore, the specific mechanisms by which environmental exposures to
PAHs may cause cardio-respiratory diseases and increase cancer risk remains poorly understood. In this dissertation, we employed a 3D, organotypic human in vitro bronchial epithelial culture (HBEC) model to address these gaps in knowledge. First, a comparative transcriptomic evaluation was conducted to assess potential differences in mechanism of toxicity for two PAHs, benzo[a]pyrene (BAP) and dibenzo[def,p]chrysene (DBC), compared to a complex PAH mixture based on short-term biosignatures identified from global gene expression profiling. Comparison of BAP and DBC gene signatures showed that a majority of genes (~60%) were uniquely regulated by treatment, including those enriched for cell cycle, hypoxia, oxidative stress, and inflammation. Gene networks involved in NRF2-mediated oxidative stress detoxification were upregulated by BAP, while DBC downregulated these same targets, suggesting a chemical-specific pattern in transcriptional regulation involved in antioxidant response, potentially contributing to differences in PAH potency. These findings support research scrutinizing the applicability of the RPF, where assumptions of similar MOA are necessary for quantitative PAH cancer risk assessment. Next, we developed and refined an approach to utilize chemical-specific transcriptional patterns towards accurate classification of carcinogenic potency of PAHs and PAH mixtures. Systems biology information was collected from a human in vitro airway epithelial model exposed to a range of non-carcinogenic and carcinogenic PAHs and PAH mixtures. These transcriptional changes were evaluated for differentially enriched biological functions. Individual pathway-based gene sets were tested for optimal classification performance. Posterior probabilities of best performing gene sets were selected and integrated via Bayesian integration resulting in a 91% accurate classifier with four gene sets, including aryl hydrocarbon receptor signaling, regulation of epithelial mesenchymal transition, regulation of angiogenesis, and cell cycle G2-M. In addition, transcriptional benchmark dose modeling of (BAP) showed that the most sensitive gene sets were largely dissimilar from those that best classified
PAH carcinogenicity challenging current assumptions that BAP carcinogenicity (and subsequent mode of action) is reflective of overall PAH carcinogenicity. Lastly, we evaluated molecular mechanisms related to PAH cancer risk through a two-tiered weighted gene co-expression network analysis (WGCNA) two-tiered approach, first to identify gene sets co-modulated to RPF cancer risk and then to link genes to a more comprehensive list of regulatory values, including inhalation-specific risk values. Over 3,000 genes associated with processes of cell cycle regulation, inflammation, DNA damage, and cell adhesion processes were found to be co-modulated with increasing RPF with pathways for cell cycle S phase and cytoskeleton actin identified as the most significantly enriched biological networks correlated to RPF. These gene sets represent potential biomarkers that can be used to evaluate cancer risk associated with PAH mixtures. In this study, the results illustrated the utility of systems toxicology approaches in analyzing global gene expression towards chemical hazard assessment, and information obtained from these analyses could be used towards future predictive model development. This work expanded current understanding of early mechanisms involved in PAH toxicity and provided novel applications utilizing toxicogenomics and organotypic cell culture models for classification, modelling, and biomarker identification. Together, these advances support further development of alternative approaches for use in predictive and mechanistic toxicology towards chemical hazard assessment.