Synergistic antineoplastic action of DNA methylation inhibitor 5‐AZA‐2′‐deoxycytidine and histone deacetylase inhibitor depsipeptide on human breast carcinoma cells
Bibliographic record
Abstract
During tumorigenesis, cancer-related genes can be silenced by aberrant DNA methylation and by changes in chromatin structure. It has been reported that 5-aza-2'-deoxycytidine, a potent inhibitor of DNA methylation, in combination with histone deacetylase inhibitors, can produce a synergistic reactivation of these genes. The aim of our study was to investigate the in vitro antineoplastic activity of 5-aza-2'-deoxycytidine in combination with depsipeptide, a potent histone deacetylase inhibitor, against MDA-MB-231 and MDA-MB-435 human breast carcinoma cell lines. We observed that the combination of 5-aza-2'-deoxycytidine and depsipeptide produced a synergistic antineoplastic effect against these tumor cells as compared to either agent administered alone. We also investigated the effect of this drug combination on the activation of maspin and gelsolin expression. These 2 genes whose function is to suppress tumor metastasis have been reported to be silenced by epigenetic events in breast cancer. Using semi-quantitative RT-PCR, we observed that 5-aza-2'-deoxycytidine in combination with depsipeptide produced a greater reactivation of both maspin and gelsolin as compared to each agent alone. The synergistic interaction between 5-aza-2'-deoxycytidine and depsipeptide on breast carcinoma cell lines provides a rationale to investigate this interesting drug combination in future clinical trials on patients with advanced breast cancer.
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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".