Sulforaphane covalently interacts with the transglutaminase 2 cancer maintenance protein to alter its structure and suppress its activity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Type 2 transglutaminase (TG2) functions as an important cancer cell survival protein in a range of cancers including epidermal squamous cell carcinoma. TG2 exists in open and closed conformations each of which has a distinct and mutually exclusive activity. The closed conformation has GTP-binding/GTPase activity while the open conformation functions as a transamidase to catalyze protein-protein crosslinking. GTP-binding/GTPase activity is required for TG2 maintenance of the aggressive cancer phenotype. Thus, identifying agents that convert TG2 from the closed to the open GTP-binding/GTPase inactive conformation is an important cancer prevention/treatment strategy. Sulforaphane (SFN) is an important diet-derived cancer prevention agent that is known to possess a reactive isothiocyanate group and has potent anticancer activity. Using a biotin-tagged SFN analog (Biotin-ITC) and kinetic analysis we show that SFN covalently and irreversibly binds to recombinant TG2 to inhibit transamidase activity and shift TG2 to an open/extended conformation, leading to a partial inhibition of GTP binding. We also show that incubation of cancer cells or cancer cell extract with Biotin-ITC results in formation of a TG2/Biotin-ITC complex and that SFN treatment of cancer cells inhibits TG2 transamidase activity and shifts TG2 to an open/extended conformation. These findings identify TG2 as a direct SFN anticancer target in epidermal squamous cell carcinoma.
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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 | 0.000 |
| 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 it