PRIMA-1 increases cisplatin sensitivity in chemoresistant ovarian cancer cells with p53 mutation: a requirement for Akt down-regulation
Bibliographic record
Abstract
BACKGROUND: Since ovarian cancer is associated with high frequency of p53 mutation, the availability of p53 reactivation and induction of massive apoptosis (PRIMA-1) offers a possible new therapeutic strategy for overcoming this devastating disease. Although Akt activation is believed to be a determinant in chemoresistance in ovarian cancer, whether Akt plays a role in regulating the effectiveness of PRIMA-1 in sensitizing chemoresistant ovarian cancer cells with p53 mutation to cisplatin (CDDP), remains to be determined. METHODS: In the present studies, we examined the influence of Akt down-regulation following dominant-negative (DN-Akt) expression on the ability of PRIMA-1 (0-10 μM) to facilitate CDDP (0-10 μM)-induced apoptosis in p53-mutated chemoresistant ovarian cancer cells (A2780cp). RESULTS: Apoptosis rate was significantly higher at the combined treatment of low PRIMA-1 concentrations (0.156 - 0.938 μM) plus CDDP (10 μM) in the DN-Akt groups than control (p<0.001). Apoptosis in cells treated with PRIMA-1 (0.156 μM) and CDDP treatment (10 μM) was significantly suppressed by p53-siRNA. PRIMA-1 increased phospho-p53 (Ser15) content in Akt down-regulated cells treated with CDDP. CONCLUSIONS: These results demonstrate that PRIMA-1 can sensitize chemoresistant ovarian cancer cells with p53 mutation to CDDP when Akt is down-regulated, and the action of PRIMA-1 is associated with p53 activation. Our findings raise the possibility that PRIMA-1 may be useful candidate for adjuvant therapy with CDDP in chemoresistant ovarian cancer with p53 mutation when Akt is down-regulated.
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How this classification was reachedexpand
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 | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".