Growth Inhibitory, Antiandrogenic, and Pro-apoptotic Effects of Punicic Acid in LNCaP Human Prostate Cancer Cells
Bibliographic record
Abstract
Prostate cancer is a commonly diagnosed cancer in men, and dietary chemoprevention by pomegranate (Punica granatum) extracts has shown noticeable benefits. In this study, we investigated the growth inhibitory, antiandrogenic, and pro-apoptotic effects of 13 pure compounds found in the pomegranate in androgen-dependent LNCaP human prostate cancer cells. Cells deprived of steroid hormones were exposed to increasing concentrations (1-100 μM) of pomegranate compounds in the presence of 0.1 nM dihydrotestosterone (DHT), and the inhibition of cell growth was measured by WST-1 colorimetric assay after a 4 day exposure. Four compounds, epigallocatechin gallate (EGCG), delphinidin chloride, kaempferol, and punicic acid, were found to inhibit DHT-stimulated cell growth at concentrations of 10 μM and above. These four pomegranate compounds inhibited DHT-stimulated androgen receptor nuclear accumulation and the expression of the androgen receptor-dependent genes prostate specific antigen and steroid 5α-reductase type 1 at concentrations ≥10 μM. We determined the possible contribution of apoptosis to the observed decrease in cell growth and found that three compounds, EGCG, kaempferol, and, in particular, punicic acid, induced DNA fragmentation after a 24 h treatment, at concentrations in the 10-100 μM range. Punicic acid, an important fatty acid in pomegranate seeds, was further found to induce intrinsic apoptosis via a caspase-dependent pathway. In conclusion, punicic acid, the main constituent of pomegranate seed (70-80%), exhibited potent growth inhibitory activities in androgen-dependent LNCaP cells, which appear to be mediated by both antiandrogenic and pro-apoptotic mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".