Abstract 3532: P-glycoprotein downregulation using RNAi decreases cholesterol efflux from human renal cancer cells
Notice bibliographique
Résumé
Abstract Background: Renal cancer is responsible for an estimated 55,000 new cases and 13,000 deaths per year in the United States (2008). Human renal cancer tissue contains eight times more cholesterol than adjacent normal kidney tissue indicating that cholesterol may be important for cancer. Increased cholesterol levels have also been found to protect kidneys from ischemia. Interestingly, a p-glycoprotein (Pgp) knockout mouse model has been found to be protective against ischemic renal injury suggesting a link between Pgp and increased renal cholesterol. Our objectives were to investigate cholesterol accumulation, biosynthesis and efflux in 3 models: a) a human embryonic kidney cell line (293T) where Pgp expression is reduced by RNA interference (RNAi), b) kidneys from a murine Pgp knockout model and c) a canine kidney cell line (MDCKII) overexpressing human Pgp. Methods: All cell culture studies were performed in DMEM. The 293T cells were transfected with 3 Pgp specific RNAi oligos and compared to a scrambled RNAi control; protein analysis was performed 72h post-transfection. Cellular cholesterol concentrations were determined using the Amplex Red cholesterol assay. Cholesterol synthesis was evaluated by immunoblotting of HMG CoA reductase, the rate limiting enzyme in the biosynthesis pathway. Cholesterol efflux to high density lipoprotein (HDL) acceptors over 6h was measured after a 24h incubation with 3H-cholesterol. Male Pgp knockout and FVB control (wild type) mice were maintained 12 weeks on a controlled chow diet (25% of calories coming from fat and 0.02% cholesterol). Cells were lysed in RIPA buffer with protease inhibitors and analyzed for HMG CoA reductase and actin expression by immunoblotting. Lipids from kidney tissues were extracted by Folch method and cholesterol levels were determined using an enzymatic assay. Results: Pgp protein expression was downregulated 80-90% with this RNAi system. Despite reduced HMG CoA reductase levels in both Pgp knockdown cells (29%) and the kidneys from the Pgp knockout (35%) there was no change in cholesterol levels suggesting either uptake was increased or efflux was reduced in these samples. When cholesterol efflux was analyzed in the Pgp knockdown cells, we found a 31-46% reduction in cholesterol efflux to HDL. In the case of the MDR1-MDCKII cells overexpressing Pgp, we found a 100% increase in HMG CoA reductase expression with no changes in cholesterol cellular levels, further suggesting that cholesterol efflux is increased in these cells. Conclusions: The reduced cholesterol efflux in Pgp knockdown cells suggests a role for Pgp in cholesterol efflux. This finding is supported by the observation that Pgp over-expression causes compensatory changes to the levels of the cholesterol synthesis enzyme, HMG CoA reductase. ACKNOWLEDGEMENTS: Funding for this project was provided by the Canadian Institutes of Health Research (CIHR). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3532.
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 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) | 0,001 | 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) | 0,003 | 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 ».