Quantcast

Evaluating the Toxicity of Cigarette Whole Smoke Solutions in an Air-liquid-interface Human in vitro Airway Tissue Model.

Research paper by Xuefei X Cao, Levan L Muskhelishvili, John J Latendresse, Patricia P Richter, Robert H RH Heflich

Indexed on: 25 Jan '17Published on: 25 Jan '17Published in: Toxicological sciences : an official journal of the Society of Toxicology



Abstract

Exposure to cigarette smoke causes a multitude of pathological changes leading to tissue damage and disease. Quantifying such changes in highly differentiated in vitro human tissue models may assist in evaluating the toxicity of tobacco products. In this methods development study, well-differentiated human air-liquid-interface (ALI) in vitro airway tissue models were used to assess toxicological endpoints relevant to tobacco smoke exposure. Whole mainstream smoke solutions (WSSs) were prepared from two commercial cigarettes (R60 and S60) that differ in smoke constituents when machine-smoked under International Organization for Standardization (ISO) conditions. The airway tissue models were exposed apically to WSSs 4-h per day for one to five days. Cytotoxicity, tissue barrier integrity, oxidative stress, mucin secretion, and matrix metalloproteinase (MMP) excretion were measured. The treatments were not cytotoxic and had marginal effects on tissue barrier properties; however, other endpoints responded in time- and dose-dependent manners, with the R60 resulting in higher levels of response than the S60 for many endpoints. Based on the lowest effective dose, differences in response to the WSSs were observed for mucin induction and MMP secretion. Mitigation of mucin induction by co-treatment of cultures with N-acetylcysteine suggests that oxidative stress contributes to mucus hypersecretion. Overall, these preliminary results suggest that quantifying disease-relevant endpoints using ALI airway models is a potential tool for tobacco product toxicity evaluation. Additional research using tobacco samples generated under smoking machine conditions that more closely approximate human smoking patterns will inform further methods development.