AMPK‐Dependent Epigenetic Regulation of Metabolism Mediates the Anti‐Cancer Action of Pterostilbene in Hepatocellular Carcinoma
Bibliographic record
Abstract
Disrupted metabolism, often implicated in hepatocellular carcinoma (HCC), is linked to aberrant epigenetic patterns. Dietary polyphenols, including pterostilbene (PTS), have been demonstrated to remodel epigenetic landscapes and restore metabolic homeostasis by regulating the activity of AMP-activated protein kinase (AMPK), a protein recently shown to orchestrate a diverse set of networks to epigenetically mediate transcription. We therefore explored the mechanistic involvement of AMPK in the epigenetic effects of PTS in HCC. We incorporated PTS into a choline-deficient amino acid defined HCC-inducing diet (CDAA) in male Fisher-344 rats and found significant attenuation in HCC development compared to CDAA alone. Transcriptomics by RNA-sequencing revealed PTS-upregulated targets, that were enriched in key metabolic processes, including the folate (Aldh1l1), methionine (Bhmt), and sarcosine (Dmdgh) cycles. PTS-mediated gene upregulation was linked to lower levels of histone H3-methylation at lysine 27 (H3K27me3) at gene promoters. Mechanistic studies in HCC HepG2 cells revealed that AMPK inhibition abolished epigenetic gene activation in response to PTS, which was accompanied by diminished binding of H3K27me3-demethylase KDM6A at promoters of PTS-target genes. Our findings provide evidence for new disease vulnerabilities that arise from epigenetic/metabolic changes and constitute novel opportunities for preventative and therapeutic success in HCC.
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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) | 0.001 | 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".