AMP-activated protein kinase (AMPK) beyond metabolism
Bibliographic record
Abstract
AMP-activated protein kinase (AMPK), an established metabolic stress sensor, has gained popularity in cancer biology due to its ability to control cellular growth and mediate cell cycle checkpoints in cancer cells in response to low energy levels. AMPK is a key effector of the tumor suppressor liver kinase B 1 (LKB1) which inhibits the cellular growth mediator mammalian target of rapamycin (mTOR) and activates checkpoint mediators such as p53 and the cyclin dependent kinase inhibitors p21(cip1) and p27(kip1). However, recent work describes a novel function for AMPK as a sensor of genomic stress and a participant of the DNA damage response (DDR) pathway. Ionizing radiation and chemotherapy activate AMPK in cancer cells to mediate signal transduction downstream of ataxia telangiectasia mutated (ATM) to activate p53- p21(cip1)/p27(kip1) and inhibit mTOR. We discuss evidence on the transcriptional and post-translational regulation of AMPK by ionizing radiation and the role of the enzyme as a mediator of chemo- and radiation sensitivity in epithelial cancer cells. Furthermore, we review data on the participation of AMPK in cytokinesis and observations suggesting a physical association of this enzyme with the mitotic apparatus. The evidence available to date suggests that AMPK is a point of convergence of metabolic and genomic stress signals, which (1) control the activity of growth mediators, (2) propagate DDR, and (3) mediate the anti-proliferative effects of common cytotoxic cancer therapy such as radiation and chemotherapy. This highlights the importance of targeting AMPK with novel cancer therapeutics.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".