Patient personalized translational tools in cystic fibrosis to transform data from bench to bed-side and back

Cystic fibrosis is a deadly multiorgan disorder caused by loss of function mutations in the gene that encodes for the cystic fibrosis transmembrane conductance regulator (CFTR) chloride/bicarbonate ion channel. More than 1,700 CFTR genetic variants exist that can cause CF, and majority of these are extremely rare. Because of genetic and environmental influences, CF patients exhibit large phenotypic variation. These factors make clinical trials difficult and largely impractical due to limited and heterogeneous patient pools. Also, the benefit of approved small-molecule CF modulators in a large number of rare mutation patients remains unknown. The goal of this study is to perform a comprehensive bench-side study using in vitro patient enteroids and in vivo mice implanted human intestinal organoids (HIOs) to test CF modulator-Ivacaftor response for a rare CF mutation patient. Based on the positive Ivacaftor response in the enteroids, the patient was enrolled in a (N = 1) clinical trial and showed improved clinical outcomes upon Ivacaftor treatment. HIO implantation model allowed in vivo modulator dosing and provided an elegant human organ-based demonstration of bench-to-bedside testing of modulator effects. Additionally, using the CF HIO model the role of CFTR function in the maturation of human intestine was reported for the first time. In all, we demonstrate that these models effectively serve to translate data from the lab to the clinic and back so that patient-specific therapies could be easily identified and disease-relevant developmental abnormalities in CF organs could be studied and addressed. NEW & NOTEWORTHY In this study, we report an example of laboratory models informing clinical care for rare CF mutation patient, with subsequent recapitulation of clinical benefit in a unique and disease relevant, human-derived in vivo model, effectively translating data from the lab to the clinic and back. This extensive work outlines a potential platform to identify patient-specific therapies and to understand relevant developmental abnormalities associated with CF disease.