Abstract 2332: Repurposing simvastatin to inhibit the mevalonate pathway as a therapeutic strategy to treat high-grade serous ovarian cancer
Notice bibliographique
Résumé
Abstract Introduction: Epithelial ovarian cancer (EOC) is the most lethal gynecological cancer, and its five-year survival rate has not changed appreciably in decades. As such, there is an imperative need for new and innovative therapies. Our lab has previously discovered that metastatic ascites-derived tumor cells have acquired a gain-of-function p53 mutation following interaction with the ovarian microenvironment in our orthotopic murine model of EOC. This p53 mutation is associated with an upregulation of the mevalonate pathway, which is known for its vital role in producing cholesterol. Tumor cells upregulate metabolic pathways as a survival advantage to fuel their rapid growth and metastasis. Simvastatin, a statin therapy, specifically targets HMG-CoA reductase, the rate-limiting enzyme of this pathway, and inhibits its activity. As such, simvastatin may serve as a potential therapeutic opportunity for EOC. Gain-of-function p53 mutations in the epithelial cells of the distal fallopian tube is now widely accepted as the origin of high-grade serous ovarian cancer. Thus, the purpose of our study was to investigate the relationship between p53 status and the mevalonate pathway in oviductal epithelial (OVE) cells as well as evaluate the effect of simvastatin treatment on OVE cell viability. Methods/Results: OVE cells were isolated from the distal oviducts of FVB/N mice with a p53 wildtype status, and we either deleted the Trp53 gene or introduced a gain-of-function R175H p53 mutation using CRISPR/Cas9. Cell viability was measured following treatment with varying doses of simvastatin and p53 mutant cells showed the greatest sensitivity (IC50: 5.48 uM) compared to p53 wildtype (IC50: 14.80 uM) and p53 knockout (IC50:9.78 uM) cells. For subsequent experiments, OVE cells were treated with 10 uM simvastatin or DMSO and subjected to Resazurin, Transwell migration, CyQUANT proliferative and Caspase-Glo 3/7 assays. Simvastatin significantly decreased resazurin reduction to resorufin in a time-dependent manner over 48 hours, regardless of p53 status, demonstrating reduced metabolic activity. Additionally, OVE cell invasion was significantly reduced in simvastatin treated p53 mutant cells, compared to p53 wildtype or p53 knockout cells. Simvastatin treatment diminished cell proliferation and enhanced apoptotic activity in all simvastatin treated OVE cells. Conclusion: Overall, simvastatin appears to inhibit tumorigenic processes in vitro. The next steps of this project are to test simvastatin’s effect on disease regression in a novel murine oviductal cell injection model of EOC recently developed by our lab. In light of these results, repurposing simvastatin as a therapy for ovarian cancer may significantly improve the way we treat this vicious disease. Citation Format: Madison Pereira, Kathy Matuszewska, Jacob Haagsma, Alice Glogova, Trevor G. Shepherd, Jim Petrik. Repurposing simvastatin to inhibit the mevalonate pathway as a therapeutic strategy to treat high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2332.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».