Valproate induces widespread epigenetic reprogramming which involves demethylation of specific genes
Why this work is in the frame
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Bibliographic record
Abstract
Valproate (VPA)(1) has been used for decades in the treatment of epilepsy, and is also effective as a mood stabilizer and in migraine therapy. It has been shown that VPA is also a histone deacetylase (HDAC) inhibitor. We have previously shown that VPA could trigger active demethylation of ectopically methylated transiently transfected DNA in HEK 293 cells. We therefore tested whether VPA treatment could bring about stable changes in the epigenome by causing changes in the state of DNA methylation of genomic DNA. Using a microarray gene expression analysis we identified the genes whose expression is induced by VPA treatment in HEK 293 cells. We found that a subset of these genes could also be induced by the classical DNA methylation inhibitor 5-aza-2'-deoxy-cytidine (5-aza-CdR) suggesting that VPA can alter the state of expression of genes, which are stably suppressed by DNA methylation. We mapped the state of methylation of three of these genes, MELANOMA ANTIGEN B2 GENE (MAGEB2), METALLOPROTEINASE 2 (MMP2) and WIF1, which are involved in tumor growth and metastasis. A chromatin immunoprecipitation (ChIP) assay revealed that VPA treatment caused as expected a change in the state of acetylation of these genes. Our data supports the concept that chromatin acetylation and DNA methylation are found in a dynamic interrelation and that the consequences of HDAC inhibitors are not limited to changes in histone acetylation but that they also bring about a change in the state of modification of DNA. The implications of our results on the future therapeutic utilities of VPA in cancer will be discussed.
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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 it