Synergy between Interleukin-1β, Interferon-γ, and Glucocorticoids to Induce TLR2 Expression Involves NF-κB, STAT1, and the Glucocorticoid Receptor
Bibliographic record
Abstract
Glucocorticoids act via the glucocorticoid receptor (GR; NR3C1) to downregulate inflammatory gene expression and are effective treatments for mild-moderate asthma. However, in severe asthma and virus-induced exacerbations, glucocorticoid therapies are less efficacious, possibly due to reduced repressive ability and/or the increased expression of pro-inflammatory genes. In human A549 epithelial and primary human bronchial epithelial cells (pHBECs), toll-like receptor (TLR) 2 mRNA and protein were <i>supra</i>-additively induced by interleukin-1β (IL1B) plus dexamethasone (IL1B+Dex), interferon-γ (IFNG) plus dexamethasone (IFNG+Dex) and IL1B plus IFNG plus dexamethasone (IL1B+IFNG+Dex). Indeed, ~34-2100-fold increases were apparent at 24 h for IL1B+IFNG+Dex and this was greater than for any single or dual treatment. Using the A549 cell model, TLR2 induction by IL1B+IFNG+Dex was antagonized by Org34517, a competitive GR antagonist. Further, when combined with IL1B, IFNG, or IL1B+IFNG, the enhancements by dexamethasone on TLR2 expression required GR. Likewise, inhibitor of κB kinase 2-inhibitors reduced IL1B+IFNG+Dex-induced TLR2 expression, and TLR2 expression induced by IL1B+Dex, with or without IFNG, required the nuclear factor (NF)-κB subunit, p65. Similarly, signal transducer and activator of transcription (STAT) 1 phosphorylation and γ-interferon-activated-sequence-dependent transcription were induced by IFNG. These, along with IL1B+IFNG+Dex-induced TLR2 expression, were inhibited by Janus kinase (JAK) inhibitors. As IL1B+IFNG+Dex-induced TLR2 expression also required STAT1, this study reveals cooperation between JAK-STAT1, NF-κB, and GR to upregulate TLR2 expression. Since TLR2 agonism elicits inflammatory responses, we propose that synergies involving TLR2 may occur within the cytokine milieu present in the immunopathology of glucocorticoid-resistant disease, and this could promote glucocorticoid resistance. <b>Significance Statement</b> This study highlights that in human pulmonary epithelial cells, glucocorticoids, when combined with the inflammatory cytokines, IL1B and IFNG, can synergistically induce the expression of inflammatory genes, such as TLR2. This effect involved positive combinatorial interactions between NF-κB/p65, GR and JAK-STAT1 signalling to synergistically upregulate TLR2 expression. Thus, synergies involving glucocorticoid-enhancement of TLR2 expression may occur in the immunopathology of glucocorticoid-resistant inflammatory diseases, including severe asthma.
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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 | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".