Curcumin-induced apoptosis in ovarian carcinoma cells is p53-independent and involves p38 mitogen-activated protein kinase activation and downregulation of Bcl-2 and survivin expression and Akt signaling
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Bibliographic record
Abstract
New cytotoxic agents are urgently needed for the treatment of advanced ovarian cancer because of the poor long-term response of this disease to conventional chemotherapy. Curcumin, obtained from the rhizome of Curcuma longa, has potent anticancer activity; however, the mechanism of curcumin-induced cytotoxicity in ovarian cancer cells remains a mystery. In this study we show that curcumin exhibited time- and dose-dependent cytotoxicity against monolayer cultures of ovarian carcinoma cell lines with differing p53 status (wild-type p53: HEY, OVCA429; mutant p53: OCC1; null p53: SKOV3). In addition, p53 knockdown or p53 inhibition did not diminish curcumin killing of HEY cells, confirming p53-independent cytotoxicity. Curcumin also killed OVCA429, and SKOV3 cells grown as multicellular spheroids. Nuclear condensation and fragmentation, as well as DNA fragmentation and poly (ADP-ribose) polymerase-1 cleavage in curcumin-treated HEY cells, indicated cell death by apoptosis. Procaspase-3, procaspase-8, and procaspase-9 cleavage, in addition to cytochrome c release and Bid cleavage into truncated Bid, revealed that curcumin activated both the extrinsic and intrinsic pathways of apoptosis. Bax expression was unchanged but Bcl-2, survivin, phosphorylated Akt (on serine 473), and total Akt were downregulated in curcumin-treated HEY cells. Curcumin also activated p38 mitogen-activated protein kinase (MAPK) without altering extracellular signal-regulated kinase 1/2 activity. We conclude that p53-independent curcumin-induced apoptosis in ovarian carcinoma cells involves p38 MAPK activation, ablation of prosurvival Akt signaling, and reduced expression of the antiapoptotic proteins Bcl-2 and survivin. These data provide a mechanistic rationale for the potential use of curcumin in the treatment of ovarian cancer.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it