Lovastatin Induces Multiple Stress Pathways Including LKB1/AMPK Activation That Regulate Its Cytotoxic Effects in Squamous Cell Carcinoma Cells
Bibliographic record
Abstract
BACKGROUND: Cellular stress responses trigger signaling cascades that inhibit proliferation and protein translation to help alleviate the stress or if the stress cannot be overcome induce apoptosis. In recent studies, we demonstrated the ability of lovastatin, an inhibitor of mevalonate synthesis, to induce the Integrated Stress Response as well as inhibiting epidermal growth factor receptor (EGFR) activation. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we evaluated the effects of lovastatin on the activity of the LKB1/AMPK pathway that is activated upon cellular energy shortage and can interact with the above pathways. In the squamous cell carcinoma (SCC) cell lines SCC9 and SCC25, lovastatin treatment (1-25 µM, 24 hrs) induced LKB1 and AMPK activation similar to metformin (1-10 mM, 24 hrs), a known inducer of this pathway. Lovastatin treatment impaired mitochondrial function and also decreased cellular ADP/ATP ratios, common triggers of LKB1/AMPK activation. The cytotoxic effects of lovastatin were attenuated in LKB1 null MEFs indicating a role for this pathway in regulating lovastatin-induced cytotoxicity. Of clinical relevance, lovastatin induces synergistic cytotoxicity in combination with the EGFR inhibitor gefitinib. In LKB1 deficient (A549, HeLa) and expressing (SCC9, SCC25) cell lines, metformin enhanced gefitinib cytotoxicity only in LKB1 expressing cell lines while both groups showed synergistic cytotoxic effects with lovastatin treatments. Furthermore, the combination of lovastatin with gefitinib induced a potent apoptotic response without significant induction of autophagy that is often induced during metabolic stress inhibiting cell death. CONCLUSION/SIGNIFICANCE: Thus, targeting multiple metabolic stress pathways including the LKB1/AMPK pathway enhances lovastatin's ability to synergize with gefitinib in SCC cells.
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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".