Abstract 2764: Impaired tumor growth and extended animal survival with Abraxane treatment in neuroblastoma xenograft models.
Bibliographic record
Abstract
Abstract Background: Abraxane (ABI-007), a novel, solvent free, protein-stabilized formulation of paclitaxel, was developed to reduce the toxicity of solvent-based paclitaxel and improve drug efficacy. It has recently been approved by FDA for metastatic breast cancer and the first-line treatment of locally advanced or metastatic non-small cell lung cancer. In this study, we investigated the anti-tumor effect of Abraxane on neuroblastoma (NB) both in vitro and in vivo. We also compared drug distribution between Abraxane and DMSO-based paclitaxel in NB xenografts. Methods: A panel of eight NB cell lines were exposed to increased concentrations (10−3 -103 ng/ml) of Abraxane in vitro for 72 hours. Cell viability was evaluated with Alamar Blue assay. Anti-tumor effect of Abraxane was further assessed in vivo with NB xenograft models with 4 different intravenous dosages, 2, 5, 10mg/kg daily and 50mg/kg weekly. Animal survival was also evaluated in metastatic NB models. To uncover the regulators of anti-tumor effects of Abraxane and potential biomarkers for predicting drug response, SPARC and PTEN expression was assessed by Western Blot. In addition, plasma and intratumoral paclitaxel concentrations were measure by liquid chromatography-mass spectrometry. Ratio of intratumoral and plasma concentration was compared between Abraxane and DMSO-based paclitaxel treatment groups. Results: Among all NB cell lines tested, CHLA-20 showed the highest EC50 (36nM), while LAN-5 and SK-N-BE(2) had the lowest EC50 (<1pM). In vivo, Abraxane demonstrated antitumor activity in a well-defined dose-dependent manner in SK-N-BE(2) xenograft model. Especially, at 50mg/kg dosage, average tumor volume on day 15 of Abraxane treatment reduced to 29% of the original tumor volume. With CHLA-20 xenograft model, tumor growth inhibition was achieved only at a higher dosage, 50mg/kg, which is consistent with less drug response of CHLA-20 cell line in vitro. In SK-N-BE(2) metastatic tumor model, Abraxane treatment significantly extended animal survival compared to control animals (p<0.01). Median survival time for Abraxane treated animals was 59 days compared to 32 days for control animals. Furthermore, we demonstrated that Abraxane treatment had 5.4-fold higher ratio of intratumoral/ plasma concentration compared to paclitaxel treatment, which indicates improved intratumor accumulation of Abraxane. From molecular aspect, we observed variable expression levels of SPARC and PTEN in eight NB cell lines tested. However, we found no significant correlation between SPARC/PTEN expression and anti-tumor effects of Abraxane in NB cells in vitro. Conclusions: Abraxane impairs NB tumor growth and improves animal survival in NB xenograft models. Therapeutic improvement of Abraxane may be related to enhanced drug intratumor delivery. Further studies are required to define the roles of SPARC and PTEN in Abraxane drug response. Citation Format: Libo Zhang, Sushil Kumar, Michael Leadley, Evelyn Elias, Sylvain Baruchel. Impaired tumor growth and extended animal survival with Abraxane treatment in neuroblastoma xenograft models. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2764. doi:10.1158/1538-7445.AM2013-2764
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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) | 0.000 | 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) | 0.003 | 0.001 |
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".