Oxidative stress-mediated epidermal growth factor receptor activation by cigarette smoke or heated tobacco aerosol in human primary bronchial epithelial cells from multiple donors.

The epidermal growth factor receptor (EGFR) signaling pathway has essential roles in maintaining homeostasis of various tissues by regulating cell proliferation and differentiation. Deregulation of the EGFR signaling pathway is associated with various chronic diseases including chronic obstructive pulmonary disease. Cigarette smoke (CS) is known to activate EGFR, which is linked to chronic obstructive pulmonary disease. The biological sequence from CS exposure to EGFR activation is initiated by oxidative stress caused by intracellular reactive oxygen species (ROS) and the depletion of glutathione, which led to EGFR ligand secretion and EGFR activation. We hypothesized that reducing exposure to CS constituents contributes to preventing CS-inducible EGFR activation. Therefore, we examined the aerosol from heated tobacco products (HTPs) because the aerosol contains fewer chemical constituents at lower levels than CS. We exposed primary human bronchial epithelial cells from four donors to the extracts of CS from a 1R6F reference cigarette or HTP aerosol from three in-market products, including our DT3.0a. The biological sequence from ROS to EGFR activation was assessed. CS induced all the tested endpoints although inter-donor differences were observed, whereas HTPs elicited most of the biological events at higher concentrations; however, EGFR phosphorylation was not observed even at fivefold higher concentration than CS. Overall, our results indicate that HTPs are less effective than CS to elicit ROS-induced EGFR activation. The reduced-risk potential of HTPs on EGFR-related diseases should be investigated further. In addition, testing with multiple donors is warranted when considering the individual differences in responses of primary cells to stimuli.

Proof of concept for quantitative adverse outcome pathway modeling of chronic toxicity in repeated exposure.

Adverse Outcome Pathway (AOP) is a useful tool to glean mode of action (MOE) of a chemical. However, in order to use it for the purpose of risk assessment, an AOP needs to be quantified using in vitro or in vivo data. Majority of quantitative AOPs developed so far, were for single exposure to progressively higher doses. Limited attempts were made to include time in the modeling. Here as a proof-of concept, we developed a hypothetical AOP, and quantified it using a virtual dataset for six repeated exposures using a Bayesian Network Analysis (BN) framework. The virtual data was generated using realistic assumptions. Effects of each exposure were analyzed separately using a static BN model and analyzed in combination using a dynamic BN (DBN) model. Our work shows that the DBN model can be used to calculate the probability of adverse outcome when other upstream KEs were observed earlier. These probabilities can help in identification of early indicators of AO. In addition, we also developed a data driven AOP pruning technique using a lasso-based subset selection, and show that the causal structure of AOP is itself dynamic and changes over time. This proof-of-concept study revealed the possibility for expanding the applicability of the AOP framework to incorporate biological dynamism in toxicity appearance by repeated insults.