Prohibitin silencing reverses stabilization of mitochondrial integrity and chemoresistance in ovarian cancer cells by increasing their sensitivity to apoptosis
Bibliographic record
Abstract
Current approaches to the treatment of ovarian cancer are limited because of the development of resistance to chemotherapy. Prohibitin (Phb1) is a possible candidate protein that contributes to development of drug resistance, which could be targeted in neoplastic cells. Phb1 is a highly conserved protein that is associated with a block in the G0/G1 phase of the cell cycle and also with cell survival. Our study was designed to determine the role of Phb1 in regulating cellular growth and apoptosis in ovarian cancer cells. Our results showed that Phb1 content is differentially overexpressed in papillary serous ovarian carcinoma and endometrioid ovarian adenocarcinoma when compared to normal ovarian epithelium and was inversely related to Ki67 expression. Immunofluorescence microscopy and Western analyses revealed that Phb1 is primarily associated with the mitochondria in ovarian cancer cells. Over-expression of Phb1 by adenoviral Phb1 infection resulted in an increase in the percentage of ovarian cancer cells accumulating at G0/G1 phase of the cell cycle. Treatment of ovarian cancer cells with staurosporine (STS) induced apoptosis in a time-dependent manner. Phb1 over-expression induced cellular resistance to STS via the intrinsic apoptotic pathway. In contrast, silencing of Phb1 expression by adenoviral small interfering RNA (siRNA) sensitized ovarian cancer cells to STS-induce apoptosis. Taken together, these results suggest that Phb1 induces block at G0/G1 phase of the cell cycle and promotes survival of cancer cells. Furthermore, silencing of the Phb1 gene expression may prove to be a valuable therapeutic approach for chemoresistant ovarian cancer by increasing sensitivity of cancer cells to apoptosis.
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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 | 0.001 |
| 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".