Inhibition of tumor angiogenesis by oral etoposide
Bibliographic record
Abstract
The chemotherapeutic agent etoposide is a topoisomerase II inhibitor widely used for cancer therapy. Low-dose oral etoposide, administered at close regular intervals, has potent anti-tumor activity in patients who are refractory to intravenous etoposide; however, the mechanism remains unclear. Since endothelial cells may be more sensitive than tumor cells to chemotherapy agents, we determined the effects of etoposide alone and in combination with oral cyclooxygenase-2 inhibitors and peroxisome-proliferator activated receptor γ ligands on angiogenesis and tumor growth in xenograft tumor models. Optimal anti-angiogenic (metronomic) and anti-tumor doses of etoposide on angiogenesis, primary tumor growth and metastasis were established alone and in combination therapy. Etoposide inhibited endothelial and tumor cell proliferation, decreased vascular endothelial growth factor (VEGF) production by tumor cells and suppressed endothelial tube formation at non-cytotoxic concentrations. In our in vivo studies, oral etoposide inhibited fibroblast growth factor 2 and VEGF-induced corneal neovascularization, VEGF-induced vascular permeability and increased levels of the endogenous angiogenesis inhibitor endostatin in mice. In addition, etoposide inhibited Lewis lung carcinoma (LLC) and human glioblastoma (U87) primary tumor growth as well as spontaneous lung metastasis in a LLC resection model. Furthermore, etoposide had synergistic anti-tumor activity in combination with celecoxib and rosiglitazone, which are also oral anti-angiogenic and anti-tumor agents. Etoposide inhibits angiogenesis in vitro and in vivo by indirect and direct mechanisms of action. Combining etoposide with celecoxib and rosiglitazone increases its efficacy and merits further investigation in future clinical trials to determine the potential usefulness of etoposide in combinatory anti-angiogenic chemotherapy.
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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) | 0.001 | 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 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".