Targeting transglutaminase 2 mediated exostosin glycosyltransferase 1 signaling in liver cancer stem cells with acyclic retinoid
Bibliographic record
Abstract
Abstract Transglutaminase 2 (TG2) is a multifunctional protein that promotes or suppresses tumorigenesis, depending on intracellular location and conformational structure. Acyclic retinoid (ACR) is an orally administered vitamin A derivative that prevents hepatocellular carcinoma (HCC) recurrence by targeting liver cancer stem cells (CSCs). In this study, we examined the subcellular location-dependent effects of ACR on TG2 activity at a structural level and characterized the functional role of TG2 and its downstream molecular mechanism in the selective depletion of liver CSCs. A binding assay with high-performance magnetic nanobeads and structural dynamic analysis with native gel electrophoresis and size-exclusion chromatography-coupled multi-angle light scattering or small-angle X-ray scattering showed that ACR binds directly to TG2, induces oligomer formation of TG2, and inhibits the transamidase activity of cytoplasmic TG2 in HCC cells. The loss-of-function of TG2 suppressed the expression of stemness-related genes, spheroid proliferation and selectively induced cell death in an EpCAM+ liver CSC subpopulation in HCC cells. Proteome analysis revealed that TG2 inhibition suppressed the gene and protein expression of exostosin glycosyltransferase 1 (EXT1) and heparan sulfate biosynthesis in HCC cells. In contrast, high levels of ACR increased intracellular Ca 2+ concentrations along with an increase in apoptotic cells, which probably contributed to the enhanced transamidase activity of nuclear TG2. This study demonstrates that ACR could act as a novel TG2 inhibitor; TG2-mediated EXT1 signaling is a promising therapeutic target in the prevention of HCC by disrupting liver CSCs.
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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 | 0.000 |
| 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".