Reexpression of epigenetically silenced AML tumor suppressor genes by SUV39H1 inhibition
Bibliographic record
Abstract
Reexpression of hypermethylated tumor suppressor genes using DNA methyltransferase (DNMT) and histone deacetylase inhibitors occurs by a mechanism whereby promoter demethylation is the dominant event. In support of this model, we found in acute myeloid leukemia cells with hypermethylated p15INK4B and E-cadherin promoters that the DNMT inhibitor, 5-aza-2'-deoxycytidine, induced p15INK4B and E-cadherin expression, and decreased levels of DNA methylation, histone H3 lysine 9 (H3K9) methylation and SUV39H1 associated with p15INK4B and E-cadherin promoters. On the basis of these observations, we examined whether promoter demethylation was dominant to H3K9 demethylation in p15INK4B and E-cadherin reexpression. We observed that SUV39H1 short hairpin RNA and chaetocin, a SUV39H1 inhibitor, induced p15INK4B and E-cadherin expression and H3K9 demethylation without promoter demethylation. Reexpression of hypermethylated p15INK4B and E-cadherin required histone H3K9 demethylation that was achieved directly by inhibiting SUV39H1 expression or activity, or indirectly by decreasing the amount of SUV39H1 associated with the p15INK4B and E-cadherin promoters using 5-aza-2'-deoxycytidine. The results from this study highlight the potential of H3K9 methyltransferases as therapeutic targets for reactivating expression of hypermethylated genes.
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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".