CFTR protein expression in human primary cells

Abstract

Subjects with cystic fibrosis (CF) display a great variability in clinical manifestations, even when they share the same cystic fibrosis transmembrane conductance regulator (CFTR) genotype. CFTR genotyping has enabled the stratification of subjects associated with mild or severe CF disease. However, environmental and non-CFTR genetic factors also influence CF phenotype, thereby making accurate predictions of disease severity for individuals more difficult. This is also shown in clinical trials with novel drugs targeting the mutant CFTR protein, that show variable efficacy. Reasons for this are still unknown, indicating a need for additional insights that contribute to disease severity and response to therapy at the level of the individual. We aimed to explore whether individual CFTR protein measurements in primary cells of subjects with CF may help in stratifying for disease severity. Various methods of CFTR protein expression analysis on different, easily accessible, primary cells of subjects with CF were developed and compared. By immunofluorescent techniques such as, flow cytometry and confocal microscopy, we analyzed CFTR expression levels in airway epithelial cells. We observed that apical CFTR expression is variable in nasal epithelium of subjects with the most common CFTR mutation. Higher apical expression appears correlated with better lung function.Furthermore, subjects with CF show an extended inflammatory response in their airways, suggested to be partially explained by an intrinsic CFTR-related defect in their immune cells. Therefore, we analyzed CFTR protein expression levels in various peripheral blood cells. In our studies we show that CFTR protein expression levels were generally low in immune cells and not as discriminative as the measurements in nasal epithelium. Typing individual CFTR protein expression characteristics may help to better understand variations between subjects that occur independent of the CFTR genotype, and may show associations with disease severity.