Combined Antitumor Therapy with Metronomic Topotecan and Hypoxia-Activated Prodrug, Evofosfamide, in Neuroblastoma and Rhabdomyosarcoma Preclinical Models
Bibliographic record
Abstract
PURPOSE: Tumor cells residing in tumor hypoxic zones are a major cause of drug resistance and tumor relapse. In this study, we investigated the efficacy of evofosfamide, a hypoxia-activated prodrug, and its combination with topotecan in neuroblastoma and rhabdomyosarcoma preclinical models. EXPERIMENTAL DESIGN: Neuroblastoma and rhabdomyosarcoma cells were tested in vitro to assess the effect of evofosfamide on cell proliferation, both as a single agent and in combination with topotecan. In vivo antitumor activity was evaluated in different xenograft models. Animal survival was studied with the neuroblastoma metastatic tumor model. RESULTS: All tested cell lines showed response to evofosfamide under normoxic conditions, but when exposed to hypoxia overnight, a 2- to 65-fold decrease of IC50 was observed. Adding topotecan to the evofosfamide treatment significantly increased cytotoxicity in vitro In neuroblastoma xenograft models, single-agent evofosfamide treatment delayed tumor growth. Complete tumor regression was observed in the combined topotecan/evofosfamide treatment group after 2-week treatment. Combined treatment also improved survival in a neuroblastoma metastatic model, compared to single-agent treatments. In rhabdomyosarcoma xenograft models, combined treatment was more effective than single agents. We also showed that evofosfamide mostly targeted tumor cells within hypoxic regions while topotecan was more effective to tumor cells in normoxic regions. Combined treatment induced tumor cell apoptosis in both normoxic and hypoxic regions. CONCLUSIONS: Evofosfamide shows antitumor effects in neuroblastoma and rhabdomyosarcoma xenografts. Compared with single-agent, evofosfamide/topotecan, combined therapy improves tumor response, delays tumor relapse, and enhances animal survival in preclinical tumor models. Clin Cancer Res; 22(11); 2697-708. ©2015 AACR.
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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".