The DOI matches its Crossref record; 142 of the 142 references it cites were found in a registry or an index.
Nanocarrier-based drug combination therapy for glioblastoma
Open accessAbstract
The current achievements in treating glioblastoma (GBM) patients are not sufficient because many challenges exist, such as tumor heterogeneity, the blood brain barrier, glioma stem cells, drug efflux pumps and DNA damage repair mechanisms. Drug combination therapies have shown increasing benefits against those challenges. With the help of nanocarriers, enhancement of the efficacy and safety could be gained using synergistic combinations of different therapeutic agents. In this review, we will discuss the major issues for GBM treatment, the rationales of drug combinations with or without nanocarriers and the principle of enhanced permeability and retention effect involved in nanomedicine-based tumor targeting and promising nanodiagnostics or -therapeutics. We will also summarize the recent progress and discuss the clinical perspectives of nanocarrier-based combination therapies. The goal of this article was to provide better understanding and key considerations to develop new nanomedicine combinations and nanotheranostics options to fight against GBM.
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Cites
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Liu, S., Liu, J., Li, H., Mao, K., Wang, H., Meng, X., Wang, J., Wu, C., Chen, H., Wang, X., et al. (2022) · Biomaterials · doi:10.1016/j.biomaterials.2022.121645 · Cited by 122
Metadata
- Authors
- Zhao, M., van Straten, D., Broekman, M. L. D., Préat, V., & Schiffelers, R. M.
- Venue
- Theranostics
- Publisher
- Ivyspring International Publisher
- Published
- 2020
- Volume
- 10
- Issue
- 3
- Pages
- 1355-1372
- ISSN
- 1838-7640 (ISSN-L)
- OpenAlex
- W2997516063
- Cited by
- 373
- References
- 142
- FWCI
- 11.38
- Type
- journal article
- Language
- en
- Open access
- gold
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- Zhao, M., van Straten, D., Broekman, M. L. D., Préat, V., & Schiffelers, R. M. (2020). Nanocarrier-based drug combination therapy for glioblastoma. Theranostics. https://doi.org/10.7150/thno.38147
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.