Inhibition of DNA Methyltransferase Activates Tumor Necrosis Factor α–Induced Monocytic Differentiation in Acute Myeloid Leukemia Cells
Bibliographic record
Abstract
Transcriptional silencing via promoter methylation of genes important for cell growth and differentiation plays a key role in myeloid leukemogenesis. We find that clinically achievable levels of 5-aza-2'-deoxycytidine (5-AZA-dC), a potent inhibitor of DNA methylation, can modify chromatin and restore the ability of tumor necrosis factor alpha (TNFalpha) to induce monocytic differentiation of the acute myeloid leukemia cells NB4 and U937. Although 5-AZA-dC cannot fully induce differentiation, we show that 5-AZA-dC acts directly on TNFalpha-responsive promoters to facilitate TNFalpha-induced transcriptional pathways leading to differentiation. 5-AZA-dC regulates the expression of Dif-2, a TNFalpha target gene, by deacetylating chromatin domains in a methylation-dependent manner. Chromatin immunoprecipitation analyses of the Dif-2 promoter show histone hyperacetylation and a recruitment of the nuclear factor-kappaB transcription factor in response to 5-AZA-dC. Furthermore, 5-AZA-dC plus TNFalpha enhances the level of phosphorylated RNA Pol II at the Dif-2 promoter via synergistic recruitment of TFIIH. We conclude that nonspecific changes in chromatin can allow a specific transcriptional inducer to overcome blocks in leukemic cell differentiation. Our results support the concept of low doses of 5-AZA-dC acting in combination with other agents to target epigenetic changes that drive malignant growth in leukemic cells. [Cancer Res 2009;69(1):55-64].
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".