Androgen‐mediated cholesterol metabolism in LNCaP and PC‐3 cell lines is regulated through two different isoforms of acyl‐coenzyme A: Cholesterol Acyltransferase (ACAT)
Bibliographic record
Abstract
BACKGROUND: The objective of this work was to determine the effect of an androgen agonist, R1881, on intracellular cholesterol synthesis and esterification in androgen-sensitive (AS) prostate cancer (LNCaP) cells. METHODS: We investigated the activity and expression of cholesterol metabolism enzymes, HMG-CoA-reductase and ACAT in the LNCaP and PC-3 (androgen-independent control) models. RESULTS: Microsomal PC-3 HMG-CoA-reductase activity was increased with R1881 despite having similar cholesterol levels while increased cholesterol levels in microsomes from LNCaPs treated with R1881 (L+) were associated with increased HMG-CoA reductase activity. Increased intracellular cholesteryl esters (CE) found in (L+) were not associated with an increased ACAT1 activity. There was no effect from androgen treatment on ACAT1 protein expression in theses cells; however, ACAT2 expression was induced upon R1881 treatment. In contrast, we found an increase in the in vitro ACAT1 activity in PC-3 cells treated with androgen (P+). Only ACAT1 expression was induced in P+. We further assessed the expression of STAT1 alpha, a transcriptional activator that modulates ACAT1 expression. STAT1 alpha expression and phosphorylation were induced in P+. To determine the role of the AR on ACAT1 expression and esterification, we treated PC-3 cells overexpressing the androgen receptor with R1881 (PAR+). AR expression was decreased in PAR+ cells; ACAT1 protein expression and cholesterol ester levels were also decreased, however, ACAT2 remained unchanged. STAT1 alpha expression was decreased in PAR+. CONCLUSIONS: Overall, these findings support the importance of cholesterol metabolism regulation within prostate cancer cells and unravel a novel role for STAT1 alpha in prostate cancer metabolism.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".