Inflammatory Cytokines IL-32 and IL-17 Have Common Signaling Intermediates despite Differential Dependence on TNF-Receptor 1
Bibliographic record
Abstract
Cytokines IL-32 and IL-17 are emerging as critical players in the pathophysiology of immune-mediated chronic inflammatory diseases. It has been speculated that the molecular mechanisms governing IL-32- and IL-17-mediated cellular responses are differentially dependent on the TNF pathway. In this study, kinome analysis demonstrated that following stimulation with cytokine IL-32, but not IL-17, there was increased phosphorylation of a peptide target corresponding to TNF-R1. Consistent with this observation, blocking TNF-R1 resulted in a suppression of IL-32-induced downstream responses, indicating that IL-32-mediated activity may be dependent on TNF-R1. In contrast, blocking TNF-R1 did not affect IL-17-induced downstream responses. Kinome analysis also implicated p300 (transcriptional coactivator) and death-associated protein kinase-1 (DAPK-1) as signaling intermediates for both IL-32 and IL-17. Phosphorylation of p300 and DAPK-1 upon stimulation with either IL-32 or IL-17 was confirmed by immunoblots. The presence of common targets was supported by results demonstrating similar downstream responses induced in the presence of IL-32 and IL-17, such as transcriptional responses and the direct activation of NF-κB. Furthermore, knockdown of p300 and DAPK-1 altered downstream responses induced by IL-32 and IL-17, and impacted certain cellular responses induced by TNF-α and IL-1β. We hypothesize that p300 and DAPK-1 represent nodes where the inflammatory networks of IL-32 and IL-17 overlap, and that these proteins would affect both TNF-R1-dependent and -independent pathways. Therefore, p300 and DAPK-1 are viable potential therapeutic targets for chronic inflammatory diseases.
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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) | 0.001 | 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 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".