Abstract LB-296: Synergistic anticancer action of inhibitor of DNA methylation 5-aza-2-deocycytidine and EZH2 histone methylase inhibitor 3-deazaneplanocin A
Bibliographic record
Abstract
Abstract The purpose of this study was to investigate the antineoplastic action of epigenetic therapy using 5-aza-2′-deoxycytidine (5-AZA-CdR) in combination with 3-deazaneplanocin A (DZNep). Aberrant epigenetic modifications play an important role in oncogenesis. DNA hypermethylation, which can silence tumor suppressor genes (TSGs), can be reversed by treatment with 5-AZA-CdR, a potent inhibitor of DNA methylation. Overexpression of EZH2 methyltransferase (HMT) can also contribute to neoplastic transformation by silencing differentiation genes and TSGs. Recent studies have shown that DZNep, an inhibitor of HMT, can reactivate certain TSGs and has activity as an antineoplastic agent. Inhibitors of DNA methylation and histone deacetylation are reported to produce synergistic reactivation of silent TSGs and synergistic anticancer activity. Our objective was to determine if this type of “cross-talk” also exists between inhibitors of DNA methylation and inhibitors of HMT. Our experimental approach was to treat leukemic and tumor cells with 5-AZA-CdR and/or DZNep and determine cell survival by in vitro colony assays. Treatment of human HL-60 myeloid leukemic cells for 24 h with 50 nM 5-AZA-CdR or 500 nM DZNep produced a loss of clonogenity (LC) of 50.0 ± 5.8% and 75.6 ± 4.15, respectively. 5-AZA-CdR in combination with DZNep at the same concentrations of each agent produced a LC of 99 ± 1% (n =3). The interaction between these two different types of epigenetic agents was clearly synergistic. We also performed colony assays with 5-AZA-CdR plus DZNep on human A549 lung carcinoma cells. These epigenetic agents in combination also produced a synergistic LC on these tumor cells. The epigenetic action of 5-AZA-CdR plus DZNep on malignant cells of different phenotype suggests that this type of treatment may show effectiveness in most types of cancer. Our current objective is to verify the synergistic interaction between inhibitors of DNA methylation and HMT in mouse models with cancer. We are also investigating action of these agents alone and in combination on expression of cancer-related genes in order to understand the molecular basis of the synergistic anticancer activity. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-296.
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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 | 0.000 |
| 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".