EGFR activation suppresses respiratory virus-induced IRF1-dependent CXCL10 production
Bibliographic record
Abstract
Airway epithelial cells are the primary cell type involved in respiratory viral infection. Upon infection, airway epithelium plays a critical role in host defense against viral infection by contributing to innate and adaptive immune responses. Influenza A virus, rhinovirus, and respiratory syncytial virus (RSV) represent a broad range of human viral pathogens that cause viral pneumonia and induce exacerbations of asthma and chronic obstructive pulmonary disease. These respiratory viruses induce airway epithelial production of IL-8, which involves epidermal growth factor receptor (EGFR) activation. EGFR activation involves an integrated signaling pathway that includes NADPH oxidase activation of metalloproteinase, and EGFR proligand release that activates EGFR. Because respiratory viruses have been shown to activate EGFR via this signaling pathway in airway epithelium, we investigated the effect of virus-induced EGFR activation on airway epithelial antiviral responses. CXCL10, a chemokine produced by airway epithelial cells in response to respiratory viral infection, contributes to the recruitment of lymphocytes to target and kill virus-infected cells. While respiratory viruses activate EGFR, the interaction between CXCL10 and EGFR signaling pathways is unclear, and the potential for EGFR signaling to suppress CXCL10 has not been explored. Here, we report that respiratory virus-induced EGFR activation suppresses CXCL10 production. We found that influenza virus-, rhinovirus-, and RSV-induced EGFR activation suppressed IFN regulatory factor (IRF) 1-dependent CXCL10 production. In addition, inhibition of EGFR during viral infection augmented IRF1 and CXCL10. These findings describe a novel mechanism that viruses use to suppress endogenous antiviral defenses, and provide potential targets for future therapies.
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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 | 0.001 |
| 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".