JNK inhibition reduces lung remodeling and pulmonary fibrotic systemic markers
Bibliographic record
Abstract
BACKGROUND: Lung remodeling and pulmonary fibrosis are serious, life-threatening conditions resulting from diseases such as chronic severe asthma and idiopathic pulmonary fibrosis (IPF). Preclinical evidence suggests that JNK enzyme function is required for key steps in the pulmonary fibrotic process. However, a selective JNK inhibitor has not been investigated in translational models of lung fibrosis with clinically relevant biomarkers, or in IPF patients. METHODS: The JNK inhibitor CC-930 was evaluated in the house dust mite-induced fibrotic airway mouse model, in a phase I healthy volunteer pharmacodynamic study, and subsequently in a phase II multicenter study of mild/moderate IPF (n = 28), with a 4-week, placebo-controlled, double-blind, sequential ascending-dose period (50 mg QD, 100 mg QD, 100 mg BID) and a 52-week open-label treatment-extension period. RESULTS: In the preclinical model, CC-930 attenuated collagen 1A1 gene expression, peribronchiolar collagen deposition, airway mucin MUC5B expression in club cells, and MMP-7 expression in lung, bronchoalveolar lavage fluid, and serum. In the phase I study, CC-930 reduced c-Jun phosphorylation induced by UV radiation in skin. In the phase II IPF study, there was a CC-930 dose-dependent trend in reduction of MMP-7 and SP-D plasma protein levels. The most commonly reported adverse events were increased ALT, increased AST, and upper respiratory tract infection (six subjects each, 21.4 %). A total of 13 subjects (46.4 %) experienced adverse events that led to discontinuation of study drug. Nine out of 28 subjects experienced progressive disease in this study. The mean FVC (% predicted) declined after 26-32 weeks at doses of 100 mg QD and 100 mg BID. Changes in MMP-7, SP-D, and tenascin-C significantly correlated with change in FVC (% predicted). CONCLUSIONS: These results illustrate JNK enzymatic activity involvement during pulmonary fibrosis, and support systemic biomarker use for tracking disease progression and the potential clinical benefit of this novel intervention in IPF. Trial registration ClinicalTrials.gov NCT01203943.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".