Mevalonate Cascade Inhibition by Simvastatin Induces the Intrinsic Apoptosis Pathway via Depletion of Isoprenoids in Tumor Cells
Bibliographic record
Abstract
The mevalonate (MEV) cascade is responsible for cholesterol biosynthesis and the formation of the intermediate metabolites geranylgeranylpyrophosphate (GGPP) and farnesylpyrophosphate (FPP) used in the prenylation of proteins. Here we show that the MEV cascade inhibitor simvastatin induced significant cell death in a wide range of human tumor cell lines, including glioblastoma, astrocytoma, neuroblastoma, lung adenocarcinoma, and breast cancer. Simvastatin induced apoptotic cell death via the intrinsic apoptotic pathway. In all cancer cell types tested, simvastatin-induced cell death was not rescued by cholesterol, but was dependent on GGPP- and FPP-depletion. We confirmed that simvastatin caused the translocation of the small Rho GTPases RhoA, Cdc42, and Rac1/2/3 from cell membranes to the cytosol in U251 (glioblastoma), A549 (lung adenocarcinoma) and MDA-MB-231(breast cancer). Simvastatin-induced Rho-GTP loading significantly increased in U251 cells which were reversed with MEV, FPP, GGPP. In contrast, simvastatin did not change Rho-GTP loading in A549 and MDA-MB-231. Inhibition of geranylgeranyltransferase I by GGTi-298, but not farnesyltransferase by FTi-277, induced significant cell death in U251, A549, and MDA-MB-231. These results indicate that MEV cascade inhibition by simvastatin induced the intrinsic apoptosis pathway via inhibition of Rho family prenylation and depletion of GGPP, in a variety of different human cancer cell lines.
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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 | 0.001 |
| 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".