Effects of sustained and intermittent paclitaxel therapy on tumor repopulation in ovarian cancer
Bibliographic record
Abstract
Tumor repopulation between cycles of chemotherapy likely has a negative effect on clinical outcome in ovarian cancer patients. Thus, avoiding treatment-free periods when tumor cells proliferate by providing sustained chemotherapy regimens may improve clinical response. We investigated the effect of sustained versus intermittent paclitaxel administration on tumor repopulation in ovarian cancer. Growth, clonogenic survival, and apoptosis were followed in SKOV3 and A2780 cells after equivalent exposure to intermittent and sustained levels of paclitaxel. In vivo tumor repopulation in response to sustained and intermittent paclitaxel therapy was investigated in an i.p. xenograft model of human ovarian cancer. Tumor growth, proliferation, and apoptosis were evaluated at different intervals during and after the course of treatment using 5-bromo-2-deoxyuridine uptake, caspase-3, and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling immunoassays. Sustained treatment significantly reduced survival in vitro in both cell lines, whereas an increase in clonogenic survival was observed in the intermittent group with each treatment gap, indicating a gradual acceleration in repopulation rates. Similarly, in vivo, sustained therapy resulted in a significant reduction of tumor growth and proliferation. Intermittent therapy resulted in increased tumor proliferation and no efficacy. The percentage of apoptotic tumor cells significantly increased in the sustained group, whereas no significant changes were seen in the control and intermittent groups. Intermittent administration of paclitaxel significantly augmented both in vitro and in vivo tumor repopulation rates, whereas sustained delivery inhibited tumor growth and repopulation. Sustained administration of paclitaxel may increase chemoresponsiveness and clinical response in ovarian cancer by attenuating tumor repopulation.
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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 | 0.000 | 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 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".