Transglutaminase 2 Maintains Hepatocyte Growth Factor Signaling to Enhance the Cancer Cell Phenotype
Bibliographic record
Abstract
Transglutaminase 2 (TG2) is a key epidermal squamous cell carcinoma cancer cell survival protein. However, how TG2 maintains the aggressive cancer phenotype is not well understood. The present studies show that TG2, which is highly expressed in epidermal cancer stem-like cells (ECS cells), maintains hepatocyte growth factor (HGF) signaling to drive an aggressive ECS cell cancer phenotype. Inhibiting TG2 reduces MET tyrosine kinase receptor expression and activity and attenuates the cancer cell phenotype. Moreover, inhibition of TG2 or HGF/MET function reduces downstream MEK1/2 and ERK1/2 activity, and this is associated with reduced cancer cell spheroid formation, invasion, and migration, and reduced stem and EMT marker expression. Treatment of TG2 knockdown cells with HGF partially restores the aggressive cancer phenotype, confirming that MET signaling is downstream of TG2. MET knockout reduces ERK1/2 signaling, doubles the time to initial tumor appearance, and reduces overall tumor growth. These findings suggest that TG2 maintains HGF/MET and MAPK (MEK1/2 and ERK1/2) signaling to drive the aggressive ECS cell cancer phenotype and tumor formation, and that TG2-dependent MET signaling may be a useful anti-cancer target. IMPLICATIONS: TG2 is an important epidermal squamous cell carcinoma stem cell survival protein. We show that TG2 activates an HGF/MET, MEK1/2 ERK1/2 signaling cascade that maintains the aggressive cancer phenotype.
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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 | 0.001 |
| 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) | 0.001 | 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".