Tumor Dynamics in Response to Antiangiogenic Therapy with Oral Metronomic Topotecan and Pazopanib in Neuroblastoma Xenografts
Bibliographic record
Abstract
Metronomic chemotherapy, combined with targeted antiangiogenic drugs, has demonstrated significant anticancer efficacy in various studies. Though, tumors do acquire resistance. Here, we have investigated the effect of prolonged therapy with oral metronomic topotecan and pazopanib on tumor behavior in a neuroblastoma mouse xenograft model. SK-N-BE(2) xenograft-bearing mice were treated with either of the following regimens (daily, orally): vehicle (control), 150 mg/kg pazopanib, 1.0 mg/kg topotecan, and combination of topotecan and pazopanib. Planned durations of treatment for each regimen were 28, 56, and 80 days or until the end point, after which animals were sacrificed. We found that only combination-treated animals survived until 80 days. Combination halted tumor growth for up to 50 days, after which gradual growth was observed. Unlike single agents, all three durations of combination significantly lowered microvessel densities compared to the control. However, the tumors treated with the combination for 56 and 80 days had higher pericyte coverage compared to control and those treated for 28 days. The proliferative and mitotic indices of combination-treated tumors were higher after 28 days of treatment and comparable after 56 days and 80 days of treatment compared to control. Immunohistochemistry, Western blot, and real-time polymerase chain reaction revealed that combination treatment increased the hypoxia and angiogenic expression. Immunohistochemistry for Glut-1 and hexokinase II expression revealed a metabolic switch toward elevated glycolysis in the combination-treated tumors. We conclude that prolonged combination therapy with metronomic topotecan and pazopanib demonstrates sustained antiangiogenic activity but also incurs resistance potentially mediated by elevated glycolysis.
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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".