Targeting Epigenetics through Histone Deacetylase Inhibitors in Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
Epigenetics play a critical role in controlling normal gene expression and altered epigenetics can lead to abnormal cellular differentiation, proliferation and survival. Acute lymphoblastic leukemia (ALL) is the most common malignancy in children and is characterized by numerous epigenetic abnormalities. These epigenetic changes correspond to repressed activity of some genes and inappropriate activation of others. In contrast to genetic alterations stemming from mutations, deletions or translocation, epigenetic changes are relatively reversible when treated with certain small molecule-based anticancer agents. Histone deacetylase inhibitors (HDI) are a class of drugs capable of modifying the epigenetic status of ALL cells. Several recent preclinical and clinical studies have demonstrated the potential of HDI as therapeutic agents in ALL. This review summarizes recent studies on (1) the principles of epigenetics and their importance in ALL tumorigenesis; (2) the structure, mechanism of action and anti-tumor activity of HDI; (3) the first comprehensive summary of data from preclinical and clinical studies for HDI as the therapeutic agents for ALL; and (4) novel directions for future research on HDI and ALL.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".