P‐glycoprotein increases the efflux of the androgen dihydrotestosterone and reduces androgen responsive gene activity in prostate tumor cells
Bibliographic record
Abstract
BACKGROUND: P-glycoprotein (P-gp) is commonly associated with multi-drug resistance (MDR) in cancer cells and the efflux of a broad spectrum of chemicals from the cell, including many chemotherapeutics and certain steroid hormones. The impact of P-gp and mechanisms involved in androgen transport and cellular accumulation within normal and malignant prostate cells remains unclear. METHODS: Following incubation of LNCaP, PC-3, HeLa, and HeLa FLAG-androgen receptor (AR) cells with (3)H-dihydrotestosterone (DHT) alone and in combination with P-gp inhibitors, PSC-833 and verapamil, we examined the cellular accumulation and efflux of androgens, as well as gene transcriptional response. RESULTS: Our data reveal that the cellular transport and accumulation of DHT is dependent on the expression of functional AR and modulated by P-gp. P-gp over-expression by both transient transfection and aspirin treatment in LNCaP cells showed decreased intracellular DHT accumulation, further suggesting DHT efflux is P-gp regulated. CONCLUSIONS: Androgen responsiveness may be modulated by P-gp in prostate cancer cells. The biological consequences of increased P-gp expression are decreased androgen accumulation and a corresponding decrease in androgen-regulated transcriptional activity and PSA gene expression.
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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) | 0.002 | 0.000 |
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".