The sesquiterpene lactone parthenolide in combination with docetaxel reduces metastasis and improves survival in a xenograft model of breast cancer
Bibliographic record
Abstract
Parthenolide, a sesquiterpene lactone, shows antitumor activity in vitro, which correlates with its ability to inhibit the DNA binding of the antiapoptotic transcription factor nuclear factor kappaB (NF-kappaB) and activation of the c-Jun NH(2)-terminal kinase. In this study, we investigated the chemosensitizing activity of parthenolide in vitro as well as in MDA-MB-231 cell-derived xenograft metastasis model of breast cancer. HBL-100 and MDA-MB-231 cells were used to measure the antitumor and chemosensitizing activity of parthenolide in vitro. Parthenolide was effective either alone or in combination with docetaxel in reducing colony formation, inducing apoptosis and reducing the expression of prometastatic genes IL-8 and the antiapoptotic gene GADD45beta1 in vitro. In an adjuvant setting, animals treated with parthenolide and docetaxel combination showed significantly enhanced survival compared with untreated animals or animals treated with either drug. The enhanced survival in the combination arm was associated with reduced lung metastases. In addition, nuclear NF-kappaB levels were lower in residual tumors and lung metastasis of animals treated with parthenolide, docetaxel, or both. In the established orthotopic model, there was a trend toward slower growth in the parthenolide-treated animals but no statistically significant findings were seen. These results for the first time reveal the significant in vivo chemosensitizing properties of parthenolide in the metastatic breast cancer setting and support the contention that metastases are very reliant on activation of NF-kappaB.
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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) | 0.001 | 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".