The DOI matches its Crossref record; 112 of the 112 references it cites were found in a registry or an index.
Combination therapy based on nano codelivery for overcoming cancer drug resistance
Open accessAbstract
Multidrug resistance (MDR) has long been a major obstacle in the treatment of malignant tumors. Combination therapy provides a viable and promising strategy to overcome MDR. This article discusses the advantages of nano-based combination therapy and proposes a 3R delivery principle (right place, right time, and right dose) as a reference for development of cancer nanomedicine containing drug combinations. The article also reviews the strategies of nano-based codelivery, with emphasis on the techniques designed to overcome chemoresistance, enhance drug targeting delivery, and reduce immunosuppression.
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“Additionally, to combat cancer’s multidrug resistance, smart nanoparticles transported synergistic drug combinations into cancer cells.335”
From Smart nanoparticles for cancer therapy (2023) · cites this paper as [335]
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Wang, H., Gao, Z. J., Liu, X., Agarwal, P., Zhao, S., Conroy, D. W., Ji, G., Yu, J., Jaroniec, C. P., Liu, Z., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-02915-8 · Cited by 331
Self-citationRetractedCancer immunoediting: from immunosurveillance to tumor escape
Dunn, G. P., Bruce, A. T., Ikeda, H., Old, L. J., & Schreiber, R. D. (2002) · Nature Immunology · doi:10.1038/ni1102-991 · Cited by 5,393
Analysis of nanoparticle delivery to tumours
Wilhelm, S., Tavares, A. J., Dai, Q., Ohta, S., Audet, J., Dvorak, H. F., & Chan, W. C. W. (2016) · Nature Reviews Materials · doi:10.1038/natrevmats.2016.14 · Cited by 5,218
Chou, T.-C. (2006) · Pharmacological Reviews · doi:10.1124/pr.58.3.10 · Cited by 5,163
Cancer drug resistance: an evolving paradigm
Holohan, C., Van Schaeybroeck, S., Longley, D. B., & Johnston, P. G. (2013) · Nature Reviews Cancer · doi:10.1038/nrc3599 · Cited by 4,681
Approaches to treat immune hot, altered and cold tumours with combination immunotherapies
Galon, J., & Bruni, D. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-018-0007-y · Cited by 3,520
The Tumor Microenvironment Innately Modulates Cancer Progression
Hinshaw, D. C., & Shevde, L. A. (2019) · Cancer Research · doi:10.1158/0008-5472.can-18-3962 · Cited by 3,270
Drug resistance in cancer: An overview
Housman, G., Byler, S., Heerboth, S., Lapinska, K., Longacre, M., Snyder, N., & Sarkar, S. (2014) · Cancers · doi:10.3390/cancers6031769 · Cited by 2,463
Drug Resistance and the Solid Tumor Microenvironment
Tredan, O., Galmarini, C. M., Patel, K., & Tannock, I. F. (2007) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djm135 · Cited by 2,116
Metabolic reprogramming in macrophages and dendritic cells in innate immunity
Kelly, B., & O'Neill, L. A. (2015) · Cell Research · doi:10.1038/cr.2015.68 · Cited by 1,876
Research works printed but not linked: 1
- Sharma, 2017, Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy, Cell, 168, 707
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Smart nanoparticles for cancer therapy
Sun, L., Liu, H., Ye, Y., Lei, Y., Islam, R., Tan, S., Tong, R., Miao, Y.-B., & Cai, L. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01642-x · Cited by 1,073
Advances in drug delivery systems, challenges and future directions
Ezike, T. C., Okpala, U. S., Onoja, U. L., Nwike, C. P., Ezeako, E. C., Okpara, O. J., Okoroafor, C. C., Eze, S. C., Kalu, O. L., Odoh, E. C., et al. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e17488 · Cited by 1,040
Multifunctional nanoparticle-mediated combining therapy for human diseases
Li, X., Peng, X., Zoulikha, M., Boafo, G. F., Magar, K. T., Ju, Y., & He, W. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01668-1 · Cited by 573
Lactate and lactylation in cancer
Chen, J., Huang, Z., Chen, Y., Tian, H., Chai, P., Shen, Y., Yao, Y., Xu, S., Ge, S., & Jia, R. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-02082-x · Cited by 545
Liposomes for Tumor Targeted Therapy: A Review
Wang, S., Chen, Y., Guo, J., & Huang, Q. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24032643 · Cited by 340
Metadata
- Authors
- Wang, H., & Huang, Y.
- Affiliations
- Chinese Academy of Sciences (CN)
- Corresponding author
- Huang, Yongzhuo
- Venue
- Medicine in Drug Discovery
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 6
- Pages
- 100024
- ISSN
- 2590-0986 (ISSN-L)
- OpenAlex
- W3014110015
- Cited by
- 115
- References
- 112
- Citations by year
- 2026: 6 · 2025: 23 · 2024: 23 · 2023: 24 · 2022: 24 · 2021: 13 · 2020: 2
- FWCI
- 4.10
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Medicine in Drug Discovery (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China
- Topics
- Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
- Health Sciences › Medicine › Oncology › Drug Transport and Resistance Mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Keywords
- multidrug resistance, combination therapy, cancer nanomedicine, chemoresistance, immunosuppression
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