Critical Role for STAT3 in IL-17A-Mediated CCL11 Expression in Human Airway Smooth Muscle Cells
Bibliographic record
Abstract
IL-17A has been shown to be expressed at higher levels in respiratory secretions from asthmatics and to correlate with airway hyperresponsiveness. Although these studies raise the possibility that IL-17A may influence allergic disease, the mechanism remains unknown. We previously demonstrated that IL-17A mediates CC chemokine (CCL11) production from human airway smooth muscle (ASM) cells. In this study, we demonstrate that STAT3 activation is critical in IL-17A-mediated CCL11 expression in ASM cells. IL-17A mediated a rapid phosphorylation of STAT3 but not STAT6 or STAT5 in ASM cells. Interestingly, transient transfection with wild-type or mutated CCL11 promoter constructs showed that IL-17A-mediated CCL11 expression relies on the STAT6 binding site. However, STAT3 but not STAT6 in vivo binding to the CCL11 promoter was detected following IL-17A stimulation of ASM cells. Overexpression of DN STAT3 (STAT3beta) abolishes IL-17A-induced CCL11 promoter activity. This effect was not observed with STAT6 DN or the STAT3 mutant at Ser(727). Interestingly, disruption of STAT3 activity with the SH2 domain binding peptide, but not with control peptide, results in a significant reduction of IL-17A-mediated STAT3 phosphorylation and CCL11 promoter activity. IL-17A-mediated CCL11 promoter activity and mRNA were significantly diminished in STAT3- but not STAT6-silenced ASM cells. Finally, IL-17A-induced STAT3 phosphorylation was sensitive to pharmacological inhibitors of JAK2 and ERK1/2. Taken together, our data provide the first evidence of IL-17A-mediated gene expression via STAT3 in ASM cells. Collectively, our results raise the possibility that the IL-17A/STAT3 signaling pathway may play a crucial role in airway inflammatory responses.
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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) | 0.003 | 0.001 |
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".