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Glycoconjugate Nanoparticle-Based Systems in Cancer Immunotherapy: Novel Designs and Recent Updates
For many years, cell-surface glycans (in particular, Tumor-Associated Carbohydrate Antigens, TACAs) have been the target of both passive and active anticancer immunotherapeutic design. Recent advances in immunotherapy as a treatment for a variety of malignancies has revolutionized anti-tumor treatme...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9006936/ https://www.ncbi.nlm.nih.gov/pubmed/35432351 http://dx.doi.org/10.3389/fimmu.2022.852147 |
Sumario: | For many years, cell-surface glycans (in particular, Tumor-Associated Carbohydrate Antigens, TACAs) have been the target of both passive and active anticancer immunotherapeutic design. Recent advances in immunotherapy as a treatment for a variety of malignancies has revolutionized anti-tumor treatment regimens. Checkpoint inhibitors, Chimeric Antigen Receptor T-cells, Oncolytic virus therapy, monoclonal antibodies and vaccines have been developed and many approvals have led to remarkable outcomes in a subset of patients. However, many of these therapies are very selective for specific patient populations and hence the search for improved therapeutics and refinement of techniques for delivery are ongoing and fervent research areas. Most of these agents are directed at protein/peptide epitopes, but glycans–based targets are gaining in popularity, and a handful of approved immunotherapies owe their activity to oligosaccharide targets. In addition, nanotechnology and nanoparticle-derived systems can help improve the delivery of these agents to specific organs and cell types based on tumor-selective approaches. This review will first outline some of the historical beginnings of this research area and subsequently concentrate on the last 5 years of work. Based on the progress in therapeutic design, predictions can be made as to what the future holds for increasing the percentage of positive patient outcomes for optimized systems. |
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