Blocking the Raf/MEK/ERK Pathway Sensitizes Acute Myelogenous Leukemia Cells to Lovastatin-Induced Apoptosis
Bibliographic record
Abstract
The statin family of drugs are well-established inhibitors of 3-hydroxy-3-methylglutaryl-CoA reductase and are used clinically in the control of hypercholesterolemia. Recent evidence, from ourselves and others, shows that statins can also trigger tumor-specific apoptosis by blocking protein geranylgeranylation. We and others have proposed that statins disrupt localization and function of geranylgeranylated proteins responsible for activating signal transduction pathways essential for the growth and/or survival of transformed cells. To explore this further, we have investigated whether the mitogen-activated protein kinase (MAPK) signaling cascades play a role in regulating statin-induced apoptosis. Cells derived from acute myelogenous leukemia (AML) are used as our model system. We show that p38 and c-Jun NH2-terminal kinase/stress-activated kinase MAPK pathways are not altered during lovastatin-induced apoptosis. By contrast, exposure of primary and established AML cells to statins results in significant disruption of basal extracellular signal-regulated kinase (ERK) 1/2 phosphorylation. Addition of geranylgeranyl PPi reverses statin-induced loss of ERK1/2 phosphorylation and apoptosis. By establishing and evaluating the inducible Raf-1:ER system in AML cells, we show that constitutive activation of the Raf/MAPK kinase (MEK)/ERK pathway significantly represses but does not completely block lovastatin-induced apoptosis. Our results strongly suggest statins trigger apoptosis by regulating several signaling pathways, including the Raf/MEK/ERK pathway. Indeed, down-regulation of the Raf/MEK/ERK pathway potentiates statin-induced apoptosis because exposure to the MEK1 inhibitor PD98059 sensitizes AML cells to low, physiologically achievable concentrations of lovastatin. Our study suggests that lovastatin, alone or in combination with a MEK1 inhibitor, may represent a new and immediately available therapeutic approach to combat tumors with activated ERK1/2, such as AML.
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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) | 0.001 | 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 | 0.001 |
| 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 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".