Alterations in cholesterol regulation contribute to the production of intratumoral androgens during progression to castration‐resistant prostate cancer in a mouse xenograft model
Bibliographic record
Abstract
BACKGROUND: Emerging evidence suggests that androgens and the androgen receptor (AR) are important mediators of castration-resistant prostate cancer (CRPC) progression. Increased expression of several enzymes responsible for cholesterol synthesis and conversion into downstream androgens has been documented in human CRPC tumors in comparison to primary tumors. Based on these observations it is hypothesized that cholesterol and its overall regulation within the cell are altered, thus modifying precursor levels for de novo androgen synthesis within the castrate tumoral environment. METHODS: Tumoral steroid levels were assessed by LC-MS. Free and esterified cholesterol was quantified by LC-MS and a fluorescent assay. Gene and protein expression were assessed by RT-PCR and immunoblotting. RESULTS: Herein, using a prostate cancer xenograft mouse model it is demonstrated by Western blot analysis that proteins responsible for cholesterol regulation (LDL-r, SR-B1, HMG-CoA reductase, ACAT1,2, ABCA1) are altered during disease progression to increase influx and synthesis of cholesterol as well as free cholesterol formation from cholesteryl ester stores. In turn this can provide increased amounts of precursor for intratumoral steroidogenesis after castration. Androgens- testosterone and dihydrotestosterone- coincidently increase at CRPC to physiologically relevant levels leading to the induction of AR expression and PSA production. Furthermore, cellular cholesterol homeostasis is maintained by increased cholesterol efflux at CRPC so that excess free cholesterol does not cause toxicity to the tumor cells. CONCLUSIONS: Cellular cholesterol regulation processes are altered during progression to CRPC. Free cholesterol from increased biosynthesis or uptake is likely a precursor for intratumoral de novo androgen synthesis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".