Levels of Cyclooxygenase-2 Are Increased in the Oral Mucosa of Smokers: Evidence for the Role of Epidermal Growth Factor Receptor and Its Ligands
Bibliographic record
Abstract
Cyclooxygenase-2 (COX-2) is a promising pharmacologic target for preventing aerodigestive malignancies. In this study, we investigated the effects of tobacco smoke on the expression of COX-2 in oral mucosa. An approximately 4-fold increase in amount of COX-2 mRNA was observed in the oral mucosa of active smokers versus never smokers. Thus, a series of in vitro studies were carried out to elucidate the mechanism by which tobacco smoke induced COX-2. Treatment of a nontumorigenic oral epithelial cell line (MSK-Leuk1) with a saline extract of tobacco smoke (TS) stimulated COX-2 transcription, resulting in increased amounts of COX-2 mRNA, COX-2 protein, and prostaglandin E(2) (PGE(2)) synthesis. Exposure of cells to TS also caused an increase in epidermal growth factor receptor (EGFR) tyrosine kinase activity. Both an inhibitor of EGFR tyrosine kinase activity and a neutralizing anti-EGFR antibody blocked TS-mediated induction of COX-2. To define the mechanism by which TS activated EGFR, the release of amphiregulin and transforming growth factor alpha, two ligands of the EGFR, was measured. Exposure to TS caused a rapid increase in the release of both ligands. TS also markedly induced the expression of mRNAs for amphiregulin and transforming growth factor alpha. Importantly, increased expression of both ligands was also detected in the oral mucosa of active smokers. Taken together, these results suggest that activation of EGFR signaling contributes to the elevated levels of COX-2 found in the oral mucosa of smokers. Moreover, these findings strengthen the rationale for determining whether inhibitors of COX-2 or EGFR tyrosine kinase activity can reduce the risk of tobacco smoke-related malignancies of the aerodigestive tract.
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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".