THG-1/TSC22D4 Promotes IL-1 Signaling through Stabilization of TRAF6 in Squamous Cell Carcinoma
Bibliographic record
Abstract
Malignant neoplasms arise within a region of chronic inflammation, which is a key factor in all aspects of tumorigenesis including initiation, proliferation, invasion, angiogenesis, and metastasis. IL-1 plays critical functions in tumor development by influencing the tumor microenvironment and promoting cancer progression. However, the mechanism of continuous activation of the IL-1-mediated inflammatory pathway in tumors has not been fully elucidated. This study provides a novel mechanism of the autocrine activation of IL-1 signaling in squamous cell carcinoma (SCC) through a novel oncoprotein, TSC-22 homologous gene-1 (THG-1, also known as TSC22D4). The RNA sequencing analysis revealed that THG-1 overexpression enhances the transcription of NF-κB targets including IL1A, IL1B, TNFA, and IL8. Furthermore, THG-1 knockdown reduced the responsiveness to IL-1 through the suppression of NF-κB nuclear translocation. To elucidate the mechanism, we focused on a THG-1 interacting protein, NRBP1. We found that NRBP1 facilitates the degradation of TNF receptor-associated factor 6 (TRAF6) through its E3 ubiquitin ligase activity. THG-1 bound to NRBP1 and suppressed the degradation of TRAF6. Furthermore, THG-1 knockdown reduced TRAF6 abundance and NF-κB activity in SCC cells. Public database analyses of head and neck SCC revealed that high expression of THG-1 is associated with the activation of the IL-1 and TNF pathways, which share TRAF6 in the signal transductions. Finally, THG-1 abundance in laryngeal SCC specimens is elevated in patients with recurrence. These results indicated that THG-1 drives the self-sufficiency of IL-1-mediated inflammatory pathway, which could contribute to the future diagnosis and immunotherapy of SCCs. Implications: An oncoprotein, THG-1/TSC22D4 activates the IL-1-mediated inflammatory pathway through the suppression of TRAF6 degradation, which mediates the continuous inflammation in tumors.
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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 | 0.001 |
| 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) | 0.000 | 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".