Antineoplastic action of 5-aza-2′-deoxycytidine and phenylbutyrate on human lung carcinoma cells
Bibliographic record
Abstract
Current chemotherapy of advanced non-small cell lung cancer produces only a modest increase in survival time. New approaches are needed to improve its effectiveness. During tumorigenesis, silencing of tumor suppressor genes can occur by aberrant methylation. The DNA methylation inhibitor, 5-aza-2'-deoxycytidine (5-AZA-CdR), can reactivate the expression of these genes. Nucleosomes containing unacetylated positively charged histones bind tightly to DNA producing a compact configuration, which inhibits transcription. Phenylbutyrate (PB), an inhibitor of histone deacetylase (HDAC), increases histone acetylation, neutralizing its positive charge and resulting in DNA with a more open structure, which favors transcription. It has been reported that 5-AZA-CdR in combination with HDAC inhibitor can increase the expression of silent tumor suppressor genes. The objective of our study was to determine if these agents, in combination, produce an enhancement of their antitumor activity. We evaluated the antineoplastic activity of 5-AZA-CdR and PB alone or in combination on human A549 and Calu-6 lung carcinoma cell lines by inhibition of DNA synthesis and clonogenic assays. 5-AZA-CdR and PB in combination produced a greater inhibition of DNA synthesis than either agent alone. Also, in a clonogenic assay the combination of these drugs showed a significant synergistic antitumor effect. These results provide a rationale to investigate the combination of 5-AZA-CdR and PB in patients with advanced lung 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) | 0.001 | 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) | 0.002 | 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".