Curcumin-Induced Apoptosis in PC3 Prostate Carcinoma Cells Is Caspase-Independent and Involves Cellular Ceramide Accumulation and Damage to Mitochondria
Bibliographic record
Abstract
Curcumin, the principal curcuminoid of tumeric, has potent anticancer activity. To determine the mechanism of curcumin-induced cytotoxicity in prostate cancer cells, we exposed PC3 prostate carcinoma cells to 25 to 100 microM curcumin for 24 to 72 h. Curcumin treatment of PC3 cells caused time- and dose-dependent induction of apoptosis and depletion of cellular reduced glutathione (GSH). Exogenous GSH and its precursor N-acetyl-cysteine, but not ascorbic acid (AA) or ebselen, decreased curcumin accumulation in PC3 cells and also prevented curcumin-induced DNA fragmentation. The failure of AA and ebselen to protect PC3 cells from curcumin-induced apoptosis argued against the involvement of reactive oxygen species; rather, GSH-mediated inhibition of curcumin-induced cytotoxicity was due to reduced curcumin accumulation in PC3 cells. Curcumin-treated PC3 cells showed apoptosis-inducing cellular ceramide accumulation and activation of p38 mitogen-activated protein kinase (MAPK) and c-jun N-terminal kinase (JNK). Caspase-3, caspase-8, and caspase-9 were activated, and cytochrome c and apoptosis-inducing factor (AIF) were released from mitochondria following curcumin treatment. Interestingly, curcumin-induced apoptosis was not prevented by p38 MAPK, JNK, or caspase inhibition. We conclude that curcumin-induced cytotoxicity was due to cellular ceramide accumulation and damage to mitochondria that resulted in apoptosis mediated by AIF and other caspase-independent processes.
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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 | 0.000 | 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 | 0.001 |
| 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".