Abstract B02: mTOR/S6K pathway-dependent metabolic reprogramming in cancer cells mediates resistance to glycolytic inhibitors
Notice bibliographique
Résumé
Abstract The targeting of “glycolytic addiction” in cancer has been an attractive proposition since the time the Warburg effect was reported in the 1940s. However this has not been successful in the clinic thus far, as the outcome of numerous clinical trials with glycolytic inhibitors has not been encouraging either due to minimal efficacy at lower tolerable doses or undue toxicity at higher effective doses. We hypothesized that the extensive cross-talk between the glycolytic pathway and other networks of cellular metabolism offers prospective avenues through which cancer cells can escape inhibition of any one node in the glycolytic pathway. By continuously exposing several glycolysis-addicted cancer cell lines to the glycolytic inhibitor 2-deoxyglucose (2-DG), we have generated derivative Glycolysis Independent lines (GIs) lines with substantially reduced glycolytic dependency. We also employed 2-DG innately resistant glycolysis independent lines to compare and contrast with the derivative GI lines. GIs, both acquired and innate, equally exhibit glycolysis independence to the knockdown of the glycolytic enzyme glucose-6-phosphate isomerase (PGI), which is blocked by 2-DG. GIs, but not their parental counterparts, exhibit elevated OX-PHOS rates to compensate for the reduced glycolytic rates. Steady state and targeted flux analyses revealed extensive metabolic reprogramming in GIs: 1. GIs increasingly utilize glutamine to feed the TCA cycle, OXPHOS and pyrimidine synthesis. 2. GIs effectively circumvent 2-DG-induced block downstream of glucose-6 phosphate (G6P) by shunting G6P through the pentose phosphate pathway back into the glycolysis, thereby generating acetyl CoA for the TCA cycle and for fatty acid biosynthesis. We determined that the S6 kinase axis of the mTOR pathway critically underlies the metabolic re-wiring of GIs, both acquired and innate. Pharmacologically targeting either S6K1 or OX-PHOS or glutaminase (the rate-limiting enzyme for glutamine breakdown in the mitochondria) not only re-sensitized GIs to 2-DG, but also pre-empted the acquisition of resistance to glycolytic inhibitors. Interestingly we were also able to re-sensitize GIs (both acquired and innate) to PGI knockdown by pharmacologically targeting either S6K1 or OXPHOS indicating the robustness of our models. Furthermore, the combination of either everolimus (clinically approved mTOR inhibitor) or phenformin (mitochondrial complex I inhibitor) with the inducible knockdown of PGI significantly reduced tumor volumes in both the acquired and innate GI line xenograft models whereas either of the drugs or PGI knockdown alone was ineffective in reducing tumor burden. Taken together, our findings suggest that cancer cells can acquire resistance to glycolytic inhibitors via mTOR/S6K pathway-mediated re-wiring of glycolytic and mitochondrial metabolic networks. Therefore, the combined targeting of glycolysis and mTOR/S6K1 or mitochondrial metabolism may be a viable therapeutic strategy to reduce tumor burden in patients across various indications. Citation Format: Raju Pusapati, Min Gao, Anneleen Daemen, Georgia Hatzivassiliou, Jeffrey Settleman. mTOR/S6K pathway-dependent metabolic reprogramming in cancer cells mediates resistance to glycolytic inhibitors. [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 B02.
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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».