Cell-Cycle Gene Expression in Lovastatin-Induced Medulloblastoma Apoptosis
Bibliographic record
Abstract
Background: 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase is a key rate-limiting enzyme in the mevalonate pathway, which generates precursors both for cholesterol biosynthesis and for the production of nonsteroidal mevalonate derivatives that are involved in a number of growth-regulatory processes. We have reported that lovastatin, a competitive inhibitor of HMG-CoA reductase, not only inhibits medulloblastoma proliferationin vitro, but also induces near-complete cell death via apoptosis. The mechanism of this phenomenon is unclear. Possible involvement of changes in expression of certain cell-cycle related genes led us to study some of them in more detail. Methods: Medulloblastoma cell lines were exposedin vitroto lovastatin, and the effects of gene expression changes were studied using RT-PCR, antisense oligonucleotide, DNA electrophoresis and Western blotting analysis. Results: 1) Levels of totalRasgene mRNA and individualRasgene mRNA are stable in lovastatin treatment in all examined medulloblastoma cell lines. 2) Blockingc-mycgene over-expression does not enhance medulloblastoma cell sensitivity to lovastatin. 3) Following lovastatin treatment,p16expression exhibits no change, but pronounced increases of p27KIP1protein are observed in all examined cell lines. Lovastatin induces pronounced increases of p21WAF1protein only in Daoy and UW228, but not in D283 Med and D341 Med. 4) Following lovastatin treatment, increased p53 protein is detected only in D341 Med, and bax protein is unchanged in all cell lines. Conclusion: Lovastatin-induced growth inhibition and apoptosis in medulloblastoma are not dependent on the regulation ofRasandc-mycgene expression, but may be mediated byp27KIP1gene expression. Lovastatin-induced apoptosis in medulloblastoma is probably p53 independent, butp53andp21WAF1gene expression may also mediate anti-proliferative effects of lovastatin on specific medulloblastoma 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 | 0.000 |
| 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".