Lipid nanoparticle-mediated lymph node-targeting delivery of mRNA cancer vaccine elicits robust CD8+ T cell response.
Proc Natl Acad Sci U S A
; 119(34): e2207841119, 2022 08 23.
Article
in English
| MEDLINE | ID: covidwho-1991768
ABSTRACT
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 (TRP2180-188)-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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Cancer Vaccines
/
Nanoparticles
/
MRNA Vaccines
/
Neoplasms
Type of study:
Prognostic study
Topics:
Vaccines
Limits:
Animals
Language:
English
Journal:
Proc Natl Acad Sci U S A
Year:
2022
Document Type:
Article
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