Rescue of multiple class II CFTR mutations by elexacaftor+tezacaftor+ivacaftor mediated in part by the dual activities of elexacaftor as both corrector and potentiator
Bibliographic record
Abstract
Positive results in pre-clinical studies of the triple combination of elexacaftor, tezacaftor and ivacaftor, performed in airway epithelial cell cultures obtained from patients harbouring the class II cystic fibrosis transmembrane conductance regulator (CFTR) mutation F508del-CFTR, translated to impressive clinical outcomes for subjects carrying this mutation in clinical trials and approval of Trikafta.Encouraged by this correlation, we were prompted to evaluate the effect of the elexacaftor, tezacaftor and ivacaftor triple combination on primary nasal epithelial cultures obtained from individuals with rare class II CF-causing mutations (G85E, M1101K and N1303K) for which Trikafta is not approved.Cultures from individuals homozygous for M1101K responded better than cultures harbouring G85E and N1303K after treatment with the triple combination with respect to improvement in regulated channel function and protein processing. A similar genotype-specific effect of the triple combination was observed when the different mutations were expressed in HEK293 cells, supporting the hypothesis that these modulators may act directly on the mutant proteins. Detailed studies in nasal cultures and HEK293 cells showed that the corrector, elexacaftor, exhibited dual activity as both corrector and potentiator, and suggested that the potentiator activity contributes to its pharmacological activity.These pre-clinical studies using nasal epithelial cultures identified mutation genotypes for which elexacaftor, tezacaftor and ivacaftor may produce clinical responses that are comparable to, or inferior to, those observed for F508del-CFTR.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".