EGFR Tyrosine Kinase Inhibition Worsens Acute Lung Injury in Mice with Repairing Airway Epithelium
Bibliographic record
Abstract
RATIONALE: Epidermal growth factor receptor (EGFR) and its ligands play important roles in the regeneration of damaged epithelium and proliferation of various epithelial tumors. Although the EGFR-tyrosine kinase inhibitor gefitinib is effective against advanced non-small cell lung cancer with EGFR mutations, some patients treated with this agent develop severe acute interstitial pneumonia. Characteristics of patients who develop interstitial pneumonia include older age, smoking history, and preexisting interstitial pneumonia suggesting a connection between airway injury and alveolar dysfunction. OBJECTIVES: The purpose of this study was to investigate the effects of gefitinib on airway repair after injury. METHODS: C57BL/6J mice received intraperitoneally naphthalene at Day 0. Gefitinib (20, 90, or 200 mg/kg) was given daily at Days--1 to 13 after naphthalene administration. Bronchoalveolar lavage fluid and lung tissue were obtained at Days 7 and 14. Terminal bronchial epithelial cells from Days 7 and 14 were retrieved with laser capture microdissection, and gene expression analyzed using microarray. MEASUREMENTS AND MAIN RESULTS: Gefitinib treatment after naphthalene prolonged neutrophil sequestration and worsened acute lung injury. We found 17 genes with more than a threefold increase in bronchiolar epithelial cells from mice treated with 200 mg/kg of gefitinib after naphthalene at Day 14 compared with those treated with naphthalene alone. Up-regulated genes included S100A8, S100A6, and StefinA3. These genes are known to participate in neutrophil sequestration, acute inflammation, and airway remodeling. CONCLUSIONS: EGFR inhibition in repairing airway epithelial cells modulated significant expression of genes involved in the airway microenvironment, prolonged inflammation, and potentiated acute lung injury.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".