The DOI matches its Crossref record; 138 of the 138 references it cites were found in a registry or an index.
Nanomedicinal Strategies to Treat Multidrug-Resistant Tumors: Current Progress
Open accessAbstract
Multidrug resistance (MDR) is a major impediment to the success of cancer chemotherapy. P-glycoprotein is an important and the best-known membrane transporter involved in MDR. Several strategies have been used to address MDR, especially P-glycoprotein-mediated drug resistance in tumors. However, clinical success has been limited, largely due to issues regarding lack of efficacy and/or safety. Nanoparticles have shown the ability to target tumors based on their unique physical and biological properties. To date, nanoparticles have been investigated primarily to address P-glycoprotein and the observed improved anticancer efficacy suggests that nanomedicinal strategies provide a new opportunity to overcome MDR. This article focuses on nanotechnology-based formulations and current nanomedicine approaches to address MDR in tumors and discusses the proposed mechanisms of action.
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Cited by
Development of exosome-encapsulated paclitaxel to overcome MDR in cancer cells
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Challenges in Development of Nanoparticle-Based Therapeutics
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Nanomedicine therapeutic approaches to overcome cancer drug resistance
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“With repeated treatment, tumors often become resistant not only to the specific chemotherapeutic agent being employed, but cross-resistant to both similar and structurally unrelated classes of cytotoxic drugs [16-18].”
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Yergeri, M., Kapse-Mistry, S., Srivastava, R., & Govender, T. (2014) · Frontiers in Pharmacology · doi:10.3389/fphar.2014.00159 · Cited by 255
Metadata
- Authors
- Dong, X., & Mumper, R. J.
- Venue
- Nanomedicine
- Publisher
- Informa UK Limited
- Published
- 2010-06
- Volume
- 5
- Issue
- 4
- Pages
- 597-615
- ISSN
- 1743-5889 (ISSN-L)
- 1748-6963
- OpenAlex
- W2119203526
- Cited by
- 317
- References
- 138
- FWCI
- 7.84
- Type
- journal article
- Language
- en
- Open access
- green
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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.