Valproic Acid Inhibits Proliferation and Reduces Invasiveness in Glioma Stem Cells Through Wnt/β Catenin Signalling Activation
Bibliographic record
Abstract
Glioblastoma is the most common malignant brain tumour in adults. The failure of current therapies can be ascribed to glioma stem cells (GSCs), which can rapidly repopulate the tumour following the initial treatment. The study of histone deacetylase inhibitors, such as valproic acid (VPA), is becoming an attractive field in cancer research. However, the exact mechanisms underlying its anti-cancer effect remain to be elucidated due to its pleiotropic effects on several cell-signalling pathways. Ingenuity Pathway Analysis (IPA) bioinformatics analysis was performed on genome-wide data regarding GSCs methylome to identify the signalling pathways mainly affected by methylation changes induced by VPA. Real time PCR and luciferase reporter assay were used to better investigate VPA effects on Wnt/β-catenin signalling pathway. VPA effect on GSC proliferation was evaluated by 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) and Trypan blue assays. Finally, VPA impact on GSC motility was demonstrated by Boyden chamber assay and further confirmed evaluating the expression levels or localisation, through western blot or immunofluorescence, of Twist1, Snail1, E-Cadherin and N-Cadherin. The bioinformatics analyses performed on GSCs methylome highlighted that Wnt/β-catenin signalling was affected by the methylation changes induced by VPA, which could influence its activation status. In particular, we pointed out a general activation of this pathway after VPA exposure, which was accompanied by an inhibitory potential on GSCs proliferation. Finally, we also proved VPA's ability to inhibit GSCs invasion through Snail1 and Twist1 downregulation and E-Cadherin relocalisation. VPA treatment may represent a new, interesting therapeutic approach to affect GSC proliferation and motility, but further investigations are certainly needed.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".