Mutation-specific downregulation of CFTR2 variants by gating potentiators
Bibliographic record
Abstract
Approximately 50% of cystic fibrosis (CF) patients are heterozygous with a rare mutation on at least one allele. Several mutants exhibit functional defects, correctable by gating potentiators. Long-term exposure (≥24 h) to the only available potentiator drug, VX-770, leads to the biochemical and functional downregulation of F508del-CFTR both in immortalized and primary human airway cells, and possibly other CF mutants, attenuating its beneficial effect. Based on these considerations, we wanted to determine the effect of chronic VX-770 exposure on the functional and biochemical expression of rare CF processing/gating mutants in human airway epithelia. Expression of CFTR2 mutants was monitored in the human bronchial epithelial cell line (CFBE41o-) and in patient-derived conditionally reprogrammed bronchial and nasal epithelia by short-circuit current measurements, cell surface ELISA and immunoblotting in the absence or presence of CFTR modulators. The VX-770 half-maximal effective (EC50) concentration for G551D-CFTR activation was ∼0.63 μM in human nasal epithelia, implying that comparable concentration is required in the lung to attain clinical benefit. Five of the twelve rare CFTR2 mutants were susceptible to ∼20-70% downregulation by chronic VX-770 exposure with an IC50 of ∼1-20 nM and to destabilization by other investigational potentiators, thereby diminishing the primary functional gain of CFTR modulators. Thus, chronic exposure to VX-770 and preclinical potentiators can destabilize CFTR2 mutants in human airway epithelial models in a mutation and compound specific manner. This highlights the importance of selecting potentiator drugs with minimal destabilizing effects on CF mutants, advocating a precision medicine approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".