Epigenetic therapy of acute myeloid leukemia using 5-aza-2'-deoxycytidine (decitabine) in combination with inhibitors of histone methylation and deacetylation
Bibliographic record
Abstract
BACKGROUND: The silencing of tumor suppressor genes (TSGs) by aberrant DNA methylation occurs frequently in acute myeloid leukemia (AML). This epigenetic alteration can be reversed by 5-aza-2'-deoxcytidine (decitabine, 5-AZA-CdR). Although 5-AZA-CdR can induce complete remissions in patients with AML, most patients relapse. The effectiveness of this therapy may be limited by the inability of 5-AZA-CdR to reactivate all TSGs due to their silencing by other epigenetic mechanisms such as histone methylation or chromatin compaction. EZH2, a subunit of the polycomb repressive complex 2, catalyzes the methylation of histone H3 lysine 27 (H3K27) to H3K27me3. 3-Deazaneplanocin-A (DZNep), an inhibitor of methionine metabolism, can reactivate genes silenced by H3K27me3 by its inhibition of EZH2. In a previous report, we observed that 5-AZA-CdR, in combination with DZNep, shows synergistic antineoplastic action against AML cells. Gene silencing due to chromatin compaction is attributable to the action of histone deacetylases (HDAC). This mechanism of epigenetic gene silencing can be reversed by HDAC inhibitors such as trichostatin-A (TSA). Silent TSGs that cannot be reactivated by 5-AZA-CdR or DZNep have the potential to be reactivated by TSA. This provides a rationale for the use of HDAC inhibitors in combination with 5-AZA-CdR and DZNep to treat AML. RESULTS: The triple combination of 5-AZA-CdR, DZNep, and TSA induced a remarkable synergistic antineoplastic effect against human AML cells as demonstrated by an in vitro colony assay. This triple combination also showed a potent synergistic activation of several key TSGs as determined by real-time PCR. The triple combination was more effective than the combination of two agents or a single agent. Microarray analysis showed that the triple combination generated remarkable changes in global gene expression. CONCLUSIONS: Our data suggest that it may be possible to design a very effective therapy for AML using agents that target the reversal of the following three epigenetic "lock" mechanisms that silence gene expression: DNA methylation, histone methylation, and histone deacetylation. This approach merits serious consideration for clinical investigation in patients with advanced AML.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".