Enhancement of Antineoplastic Action of 5-Aza-2′-deoxycytidine by Phenylbutyrate on L1210 Leukemic Cells
Bibliographic record
Abstract
Epigenetic changes, such as aberrant DNA methylation that silences tumor suppressor genes (TSGs), can play an important role in the development of leukemia. The DNA methylation inhibitor, 5-aza-2'-deoxycytidine (5-AZA-CdR), can reactivate these silent TSGs and is an interesting agent to investigate for therapy of leukemia. It has been reported that the effectiveness of 5-AZA-CdR to reactivate TSG can be enhanced by inhibitors of histone deacetylase (HDIs). HDIs can convert a compact chromatin structure to an open configuration that facilitates gene expression. An interesting HDI is phenylbutyrate (PB), which has shown some clinical activity for the therapy of leukemia. In this report we have investigated the antineoplastic activity of 5-AZA-CdR and PB alone and in combination on murine L1210 lymphoid leukemic cells. The in vitro treatment of 5-AZA-CdR and PB in combination produced a greater inhibition of growth, DNA synthesis, and also a greater reduction on colony formation on both L1210 and human HL-60 leukemic cells as compared to either drug alone. The combination also produced a synergistic activation of the TSG, p15CDN2B, in the L1210 cells. In mice with L1210 leukemia the combination showed enhanced antineoplastic activity. We also observed an enhancement of the antineoplastic activity of this combination in mice with L1210 leukemia. These data provide a rationale to investigate 5-AZA-CdR and PB in patients with advanced leukemia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".