Abstract
Personalized neoantigen cancer mRNA vaccines are promising candidates for precision medicine. However, the difficulty of identifying neoantigens heavily hinders their broad applicability. This study developed a universal strategy of anti-tumor mRNA vaccine by harnessing “off-the-shelf” immunity to known antigens. First, the model antigen ovalbumin (OVA) is used for mRNA vaccine design. In vitro test indicated that this mRNA vaccine reprogrammed tumor cells that can be recognized and killed by OVA-specific cytotoxic T lymphocytes (CTLs). In situ mRNA vaccine notably inhibited tumor growth across three subcutaneous solid tumor models in mice. Further single-cell sequencing analyses revealed that mRNA vaccination act to reshape the immunosuppressive tumor microenvironment (TME) toward more proinflammatory characteristics. Strikingly, this framework of mRNA-based strategy can be applied to two clinical pathogen antigens, hepatitis B surface antigen (HBsAg), and SARS-CoV-2 spike receptor-binding domain (SRBD). Interestingly, the mRNA-based strategy largely recapitulated the scenario of spontaneous cancer regression following pathogen infection or vaccination. Collectively, this study provides not only proof of concept for universal anti-tumor mRNA therapy, but also mechanistic insights in echoing the long-standing puzzle of spontaneous cancer regression.
Data Availability
The raw sequence data of bulk RNA-seq data generated in this study have been deposited in the Sequence Read Archive (SRA) database with accession numbers PRJNA1045070 and PRJNA1178826. The raw sequence data of single-cell RNA-seq data generated in this study have been deposited in the SRA database with accession numbers PRJNA1045076. All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.
Acknowledgements
This work was supported by research grants from the National Key Research and Development Program of China (2023YFC2604300; 2021YFE0114900), the Starry Night Science Fund at Shanghai Institute for Advanced Study of Zhejiang University (SN-ZJU-SIAS-009), the Department of Science and Technology of Zhejiang Province (2023C03063), and the Fundamental Research Funds for the Central Universities (No. K20220228). The authors thank members of the Jin laboratory for suggestions and discussion during the course of this work. The authors thank Professor A. L. for 4T1 cell line; The authors thank Professor J. W. for Hepa1-6 cell line; The authors Professor J. W. for preparation of lipid nanoparticles. The authors thank T. W. for suggestions for scRNA-seq analyses. The authors are grateful to LC Bio Technology CO., Ltd for assisting in sequencing and bioinformatics analysis.
Conflict of Interest
The authors declare no conflict of interest.
The authors declare no conflict of interest.
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