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In silico designed mRNA vaccines targeting CA-125 neoantigen in breast and ovarian cancer
Lingeng Lu1, Wenxue Ma2, Caroline H Johnson3
1Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, CT 06510, USA; Yale Cancer Center, Yale University, New Haven, CT 06510, USA.
Abstract:
Somatic mutation-derived neoantigens are associated with patient survival in breast and ovarian cancer. These neoantigens are targets for cancer, as shown by the implementation of neoepitope peptides as cancer vaccines. The success of cost-effective multi-epitope mRNA vaccines against SARS-Cov-2 in the pandemic established a model for reverse vaccinology. In this study, we aimed to develop an in silico pipeline designing an mRNA vaccine of the CA-125 neoantigen against breast and ovarian cancer, respectively. Using immuno-bioinformatics tools, we predicted cytotoxic CD8+ T cell epitopes based on somatic mutation-driven neoantigens of CA-125 in breast or ovarian cancer, constructed a self-adjuvant mRNA vaccine with CD40L and MHC-I -targeting domain to enhance cross-presentation of neoepitopes by dendritic cells. With an in silico ImmSim algorithm, we estimated the immune responses post-immunization, showing IFN-γ and CD8+ T cell response. The strategy described in this study may be scaled up and implemented to design precision multi-epitope mRNA vaccines by targeting multiple neoantigens.
Insights
This study developed an in silico pipeline for designing a CA-125 neoantigen mRNA vaccine against breast and ovarian cancers. The vaccine design enhances T cell responses, offering a scalable strategy for precision cancer vaccines.
Area of Science:
- Oncology
- Immunology
- Bioinformatics
Background:
- Somatic mutation-derived neoantigens are crucial biomarkers for patient survival in breast and ovarian cancers.
- Neoantigens serve as targets for cancer vaccines, with neoepitope peptides demonstrating therapeutic potential.
- The success of mRNA vaccines against SARS-CoV-2 provides a model for reverse vaccinology.
Purpose of the Study:
- To develop an in silico pipeline for designing a CA-125 neoantigen-based mRNA vaccine against breast and ovarian cancers.
- To predict cytotoxic CD8+ T cell epitopes from CA-125 neoantigens using immuno-bioinformatics tools.
- To construct a self-adjuvant mRNA vaccine incorporating CD40L and MHC-I targeting domains.
Main Methods:
- Utilized immuno-bioinformatics tools to predict CD8+ T cell epitopes from CA-125 neoantigens in breast and ovarian cancers.
- Designed a self-adjuvant mRNA vaccine construct with CD40L and MHC-I targeting domains to enhance neoepitope cross-presentation by dendritic cells.
- Employed the in silico ImmSim algorithm to simulate and estimate immune responses, including IFN-γ and CD8+ T cell activation, post-immunization.
Main Results:
- Successfully predicted cytotoxic CD8+ T cell epitopes derived from CA-125 neoantigens.
- Designed a novel mRNA vaccine construct aimed at enhancing the cross-presentation of neoepitopes by dendritic cells.
- In silico simulations predicted a robust immune response, characterized by IFN-γ production and CD8+ T cell activation.
Conclusions:
- The developed in silico pipeline provides a framework for designing precision mRNA vaccines targeting neoantigens.
- The strategy is scalable and can be adapted to create multi-epitope mRNA vaccines targeting various neoantigens for personalized cancer therapy.
- This approach holds promise for advancing neoantigen-based cancer vaccine development in breast and ovarian cancers.
