Abstract 3532: P-glycoprotein downregulation using RNAi decreases cholesterol efflux from human renal cancer cells
Bibliographic record
Abstract
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.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".