Abstract A83: Inhibiting mitochondrial ATP synthase with Oligomycin A enhances the kinetics of oncolytic reovirus-induced apoptosis in vitro
Notice bibliographique
Résumé
Abstract Introduction: Here we consider a role for metabolic activity in regulating the efficiency of oncolytic reovirus infection in cancer cells. It is well established that (i) many cancer cells show metabolic dysfunction compared to non-transformed cells and (ii) oncolytic reovirus demonstrates strong selectivity toward cancer cells. How reovirus attains this selectivity and what underlies the efficiency of oncolysis is not fully elucidated. Oncolytic reovirus (Reolysin®) is currently in phase III clinical trials and targeted application of this therapy could benefit significantly from a better determination of prognostic indicators of therapeutic success. Methods: We used chemical inhibitors of glycolysis (2-deoxyglucose [2DG]-Hexokinase), respiration (Rotenone [RN]-Complex I; Antimycin A [AA]-Complex III; Sodium Azide [AZ]-Complex IV; ), and oxidative phosphorylation (Oligomycin A- mitochondrial FO-F1 ATP Synthase) to treat HCT116 colon cancer cells concurrently infected with reovirus, and cell morphology and viability were assessed. Viral plaque assays, flow cytometry for caspase activity and cell viability, Western Blots, caspase inhibition (z-VAD-fmk [ZVAD]- pan-caspase inhibitor) and BAX/BAK double knockout [DKO] HCT116 cells were used to assess the influence of Oligomycin A on reovirus replication and cytolysis. A panel of other cancer cell lines of various tissue origins was used to assess more broadly how Oligomycin A influences cell killing by reovirus. Results: Chemical inhibition of mitochondrial ATP synthase using Oligomycin A , but not general inhibition of respiration or glycolysis, significantly enhanced the speed of reovirus-induced cell killing, as assessed by observing cell morphology and viability in HCT116 cancer cells. Oligomycin A promoted earlier and more substantial caspase activation in reovirus infected cancer cells and corresponding increases in markers of caspase-dependent apoptosis such as cleaved poly-ADP-ribose polymerase (PARP). Reovirus-induced apoptosis was responsible for the enhanced cytolysis observed in the presence of Oligomycin A because the pan-caspase inhibitor ZVAD abolished the observed cell death. Reovirus replication paradoxically appeared to decrease in the presence of Oligomycin A despite, or possibly because of, the increased kinetics of cell death. Reovirus infection is known to induce apoptosis in an atypical manner that is independent of the pro-apoptotic proteins BAX and BAK. Using BAX/BAK double knockout HCT116 cells we determined that the enhancement of cell death induced by reovirus in the presence of Oligomycin was retained, consistent with the atypical mechanism of reovirus-induced apoptosis. Finally, combining Oligomycin A with reovirus in multiple cancer cell lines led to improved cell death, suggesting a generalized mechanism of enhanced cell death that might have therapeutic relevance. Conclusions: This work is the first to investigate whether manipulation of energy metabolism can modulate reovirus infection of cancer cells. We found that inhibition of mitochondrial ATP synthase with Oligomycin A, but not inhibition of certain other steps in cellular energy metabolism, enhanced the kinetics of induction of caspase-dependent apoptosis and cell death during reovirus infection in cancer cells. Furthermore, combining Oligomycin A with reovirus infection led to enhanced killing of various types of cancer cell lines, suggesting this may be a widely applicable strategy for improving reovirus oncolysis. Our data suggest for the first time that mitochondrial metabolism might regulate and be exploited to modulate reovirus infection and provide a framework for future study. Citation Format: Matthew Clarkson, Siyuan Yin, Mio Tsutsui, David Andrews, Randal Johnston. Inhibiting mitochondrial ATP synthase with Oligomycin A enhances the kinetics of oncolytic reovirus-induced apoptosis in vitro. [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr A83.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».