Testosterone and prolactin increase carboxypeptidase‐D and nitric oxide levels to promote survival of prostate cancer cells
Bibliographic record
Abstract
BACKGROUND: Plasma-membrane carboxypeptidase-D (CPD) releases arginine from extracellular substrates. Arginine is converted intracellularly to nitric oxide (NO). This study determined the effects of testosterone (T) and prolactin (PRL) on CPD expression, and the role(s) of CPD in NO production and survival of prostate cancer (PCa) cells. METHODS: LNCaP cells were treated with T and/or PRL. CPD expression was measured. Regulation by T (low doses) was determined using transfected cells overexpressing 5α-reductase type-1 (5αR1), which converts T to the more potent dihydrotestosterone. The effects of siRNAs targeting CPD (siCPDs) on NO production, cell viability, and apoptosis were determined using DAF2-DA, MTS, and Annexin-V assays. The effects of PRL/T on CPD/NO levels in PC-3, MDA-PCa-2b, and 22Rv1 cells were also evaluated. RESULTS: In LNCaP cells, 10 nM T and 10 ng/ml PRL-upregulated CPD mRNA/protein levels. In pTRE-transfectants, 1 nM T-upregulated CPD mRNA levels by ∼2-fold over controls, whereas 0.1 nM T caused similar upregulation in pTRE-5αR1-transfectants. In LNCaP cells cultured in arginine-free medium, addition of furylacryloyl-Ala-Arg (FAR; CPD substrate) increased NO levels. NO production, with FAR, was enhanced by PRL and/or T. siCPDs decreased NO production and cell viability, but increased apoptosis. QPCR analysis showed T/PRL-upregulation of CPD in 22Rv1, MDA-PCa-2b, and PC-3 cells. NO production was doubled by T/PRL in 22Rv1 cells, tripled by T in MDA-PCa-2b cells, and marginally increased by PRL in MDA-PCa-2b and PC-3 cells. CONCLUSIONS: T and PRL upregulate CPD and NO levels in PCa cells. CPD increases NO production to promote PCa cell survival.
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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 | 0.000 |
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".