<scp>DNA</scp>demethylation and invasive cancer: implications for therapeutics
Bibliographic record
Abstract
One of the hallmarks of cancer is aberrant DNA methylation, which is associated with abnormal gene expression. Both hypermethylation and silencing of tumour suppressor genes as well as hypomethylation and activation of prometastatic genes are characteristic of cancer cells. As DNA methylation is reversible, DNA methylation inhibitors were tested as anticancer drugs with the idea that such agents would demethylate and reactivate tumour suppressor genes. Two cytosine analogues, 5-azacytidine (Vidaza) and 5-aza-2'-deoxycytidine, were approved by the Food and Drug Administration as antitumour agents in 2004 and 2006 respectively. However, these agents might cause activation of a panel of prometastatic genes in addition to activating tumour suppressor genes, which might lead to increased metastasis. This poses the challenge of how to target tumour suppressor genes and block cancer growth with DNA-demethylating drugs while avoiding the activation of prometastatic genes and precluding the morbidity of cancer metastasis. This paper reviews current progress in using DNA methylation inhibitors in cancer therapy and the potential promise and challenges ahead.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".