The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Lipid nanoparticle-mediated lymph node–targeting delivery of mRNA cancer vaccine elicits robust CD8 + T cell response
Open accessAbstract
The targeted delivery of messenger RNA (mRNA) to desired organs remains a great challenge for in vivo applications of mRNA technology. For mRNA vaccines, the targeted delivery to the lymph node (LN) is predicted to reduce side effects and increase the immune response. In this study, we explored an endogenously LN-targeting lipid nanoparticle (LNP) without the modification of any active targeting ligands for developing an mRNA cancer vaccine. The LNP named 113-O12B showed increased and specific expression in the LN compared with LNP formulated with ALC-0315, a synthetic lipid used in the COVID-19 vaccine Comirnaty. The targeted delivery of mRNA to the LN increased the CD8 + T cell response to the encoded full-length ovalbumin (OVA) model antigen. As a result, the protective and therapeutic effect of the OVA-encoding mRNA vaccine on the OVA-antigen–bearing B16F10 melanoma model was also improved. Moreover, 113-O12B encapsulated with TRP-2 peptide (TRP2 180–188 )–encoding mRNA also exhibited excellent tumor inhibition, with the complete response of 40% in the regular B16F10 tumor model when combined with anti–programmed death-1 (PD-1) therapy, revealing broad application of 113-O12B from protein to peptide antigens. All the treated mice showed long-term immune memory, hindering the occurrence of tumor metastatic nodules in the lung in the rechallenging experiments that followed. The enhanced antitumor efficacy of the LN-targeting LNP system shows great potential as a universal platform for the next generation of mRNA vaccines.
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Cited by
mRNA-based cancer therapeutics
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Lipid Nanoparticle (LNP) Enables mRNA Delivery for Cancer Therapy
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Targeting cancer with mRNA–lipid nanoparticles: key considerations and future prospects
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Circular RNA vaccine in disease prevention and treatment
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Metadata
- Authors
- Chen, J., Ye, Z., Huang, C., Qiu, M., Song, D., Li, Y., & Xu, Q.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2022-08-15
- Volume
- 119
- Issue
- 34
- Pages
- e2207841119-e2207841119
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W4291804571
- Cited by
- 422
- References
- 32
- FWCI
- 23.82
- Type
- journal article
- Language
- en
- Open access
- hybrid
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