Total particulate matter concentration skews cigarette smoke’s gene expression profile

Abstract

Exposure of small animals to cigarette smoke is widely used as a model to study the pathogenesis of chronic obstructive pulmonary disease. However, protocols and exposure systems utilised vary substantially and it is unclear how these different systems compare. We analysed the gene expression profile of six publically available murine datasets from different cigarette smoke-exposure systems and related the gene signatures to three clinical cohorts. 234 genes significantly regulated by cigarette smoke in at least one model were used to construct a 55-gene network containing 17 clusters. Increasing numbers of differentially regulated clusters were associated with higher total particulate matter concentrations in the different datasets. Low total particulate matter induced genes mainly related to xenobiotic/detoxification responses, while higher total particulate matter activated immune/inflammatory processes in addition to xenobiotic/detoxification responses. To translate these observations to the clinic, we analysed the regulation of the revealed network in three human cohorts. Similar to mice, we observed marked differences in the number of regulated clusters between the cohorts. These differences were not determined by pack-year. Although none of the experimental models exhibited a complete alignment with any of the human cohorts, some exposure systems showed higher resemblance. Thus, depending on the cohort, clinically observed changes in gene expression may be mirrored more closely by specific cigarette smoke exposure systems. This study emphasises the need for careful validation of animal models.