Importance of dose-schedule of 5-aza-2'-deoxycytidine for epigenetic therapy of cancer
Bibliographic record
Abstract
Abstract Background The inactivation of tumor suppressor genes (TSGs) by aberrant DNA methylation plays an important role in the development of malignancy. Since this epigenetic change is reversible, it is a potential target for chemotherapeutic intervention using an inhibitor of DNA methylation, such as 5-aza-2'-deoxycytidine (DAC). Although clinical studies show that DAC has activity against hematological malignancies, the optimal dose-schedule of this epigenetic agent still needs to be established. Methods Clonogenic assays were performed on leukemic and tumor cell lines to evaluate thein vitroantineoplastic activity of DAC. The reactivation of TSGs and inhibition of DNA methylation by DAC were investigated by reverse transcriptase-PCR and Line-1 assays. Thein vivoantineoplastic activity of DAC administered as an i.v. infusion was evaluated in mice with murine L1210 leukemia by measurement of survival time, and in mice bearing murine EMT6 mammary tumor by excision of tumor after chemotherapy for anin vitroclonogenic assay. Results Increasing the DAC concentration and duration of exposure produced a greater loss of clonogenicity for both human leukemic and tumor cell lines. The reactivation of the TSGs (p57KIP2in HL-60 leukemic cells andp16CDKN2Ain Calu-6 lung carcinoma cells) and the inhibition of global DNA methylation in HL-60 leukemic cells increased with DAC concentration. In mice with L1210 leukemia and in mice bearing EMT6 tumors, the antineoplastic action of DAC also increased with the dose. The plasma level of DAC that produced a very potent antineoplastic effect in mice with leukemia or solid tumors was > 200 ng/ml (> 1 μM). Conclusion We have shown that intensification of the DAC dose markedly increased its antineoplastic activity in mouse models of cancer. Our data also show that there is a good correlation between the concentrations of DAC that reducein vitroclonogenicity, reactivate TSGs and inhibit DNA methylation. These results suggest that the antineoplastic action of DAC is related to its epigenetic action. Our observations provide a strong rationale to perform clinical trials using dose intensification of DAC to maximize the chemotherapeutic potential of this epigenetic agent in patients with cancer.
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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) | 0.002 | 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".