Valproic acid and butyrate induce apoptosis in human cancer cells through inhibition of gene expression of Akt/protein kinase B
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In eukaryotic cells, the genomic DNA is packed with histones to form the nucleosome and chromatin structure. Reversible acetylation of the histone tails plays an important role in the control of specific gene expression. Mounting evidence has established that histone deacetylase inhibitors selectively induce cellular differentiation, growth arrest and apoptosis in variety of cancer cells, making them a promising class of anticancer drugs. However, the molecular mechanisms of the anti-cancer effects of these inhibitors have yet to be understood. RESULTS: Here, we report that a key determinant for the susceptibility of cancer cells to histone deacetylase inhibitors is their ability to maintain cellular Akt activity in response to the treatment. Also known as protein kinase B, Akt is an essential pro-survival factor in cell proliferation and is often deregulated during tumorigenesis. We show that histone deacetylase inhibitors, such as valproic acid and butyrate, impede Akt1 and Akt2 expression, which leads to Akt deactivation and apoptotic cell death. In addition, valproic acid and butyrate induce apoptosis through the caspase-dependent pathway. The activity of caspase-9 is robustly activated upon valproic acid or butyrate treatment. Constitutively active Akt is able to block the caspase activation and rescues cells from butyrate-induced apoptotic cell death. CONCLUSION: Our study demonstrates that although the primary target of histone deacetylase inhibitors is transcription, it is the capacity of cells to maintain cellular survival networks that determines their fate of survival.
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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