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Transcriptomic Responses to Ivacaftor and Prediction of Ivacaftor Clinical Responsiveness.

ABSTRACT: Ivacaftor is a drug that was recently approved by the U.S. Food and Drug Administration for the treatment of patients with cystic fibrosis (CF) and at least one copy of the G511D mutation in the CFTR (CF transmembrane conductance regulator) gene. The transcriptomic effect of ivacaftor in patients with CF remains unclear. Here, we sought to examine whether and how the transcriptome of patients is influenced by ivacaftor treatment, and to determine whether these data allow prediction of ivacaftor responsiveness. Our data originated from the G551D Observational Study (GOAL). We performed RNA sequencing (RNA-seq) on peripheral blood mononuclear cells (PBMCs) from 56 patients and compared the transcriptomic changes that occurred before and after ivacaftor treatment. We used consensus clustering to stratify patients into subgroups based on their clinical responses after treatment, and we determined differences between subgroups in baseline gene expression. A random forest model was built to predict ivacaftor responsiveness. We identified 239 genes (false discovery rate < 0.1) that were significantly influenced by ivacaftor in PBMCs. The functions of these genes relate to cell differentiation, microbial infection, inflammation, Toll-like receptor signaling, and metabolism. We classified patients into "good" and "moderate" responder groups based on their clinical response to ivacaftor. We identified a panel of signature genes and built a statistical model for predicting CFTR modulator responsiveness. Despite a limited sample size, adequate prediction performance was achieved with an accuracy of 0.92. In conclusion, for the first time, the present study demonstrates profound transcriptomic impacts of ivacaftor in PBMCs from patients with CF, and provides a pilot statistical model for predicting clinical responsiveness to ivacaftor before treatment.

SUBMITTER: Sun T

PROVIDER: S-EPMC6827069 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Rationale: The cystic fibrosis (CF) modulator drug, elexacaftor/tezacaftor/ivacaftor (ETI), proved highly effective in controlled clinical trials for individuals with at least one F508del allele, which occurs in at least 85% of people with CF. Objectives: PROMISE is a postapproval study to understand the broad effects of ETI through 30 months' clinical use in a more diverse U.S. patient population with planned analyses after 6 months. Methods: Prospective, observational study in 487 people with CF age 12 years or older with at least one F508del allele starting ETI for the first time. Assessments occurred before and 1, 3, and 6 months into ETI therapy. Outcomes included change in percent predicted FEV1 (ppFEV1), sweat chloride concentration, body mass index (BMI), and self-reported respiratory symptoms. Measurements and Main Results: Average age was 25.1 years, and 44.1% entered the study using tezacaftor/ivacaftor or lumacaftor/ivacaftor, whereas 6.7% were using ivacaftor, consistent with F508del homozygosity and G551D allele, respectively. At 6 months into ETI therapy, ppFEV1 improved 9.76 percentage points (95% confidence interval [CI], 8.76 to 10.76) from baseline, cystic fibrosis questionnaire-revised respiratory domain score improved 20.4 points (95% CI, 18.3 to 22.5), and sweat chloride decreased -41.7 mmol/L (95% CI, -43.8 to -39.6). BMI also significantly increased. Changes were larger in those naive to modulators but substantial in all groups, including those treated with ivacaftor at baseline. Conclusions: ETI by clinical prescription provided large improvements in lung function, respiratory symptoms, and BMI in a diverse population naive to modulator drug therapy, using existing two-drug combinations, or using ivacaftor alone. Each group also experienced significant reductions in sweat chloride concentration, which correlated with improved ppFEV1 in the overall study population. Clinical trial registered with www.clinicaltrials.gov (NCT NCT04038047).

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Transcriptomic Responses to Ivacaftor and Prediction of Ivacaftor Clinical Responsiveness.

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