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Updated: May 31, 2025

A Nonviral Approach to Generate Transient Chimeric Antigen Receptor T Cells Using mRNA for Cancer Immunotherapy
Published on: February 21, 2025
Leveraging mRNA technology for antigen based immuno-oncology therapies
Charalampos S Floudas1, Siranush Sarkizova2, Michele Ceccarelli3
1Center for Immuno-Oncology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA charalampos.floudas@nih.gov.
Abstract:
The application of messenger RNA (mRNA) technology in antigen-based immuno-oncology therapies represents a significant advancement in cancer treatment. Cancer vaccines are an effective combinatorial partner to sensitize the host immune system to the tumor and boost the efficacy of immune therapies. Selecting suitable tumor antigens is the key step to devising effective vaccinations and amplifying the immune response. Tumor neoantigens are de novo epitopes derived from somatic mutations, avoiding T-cell central tolerance of self-epitopes and inducing immune responses to tumors. The identification and prioritization of patient-specific tumor neoantigens are based on advanced computational algorithms taking advantage of the profiling with next-generation sequencing considering factors involved in human leukocyte antigen (HLA)-peptide-T-cell receptor (TCR) complex formation, including peptide presentation, HLA-peptide affinity, and TCR recognition. This review discusses the development and clinical application of mRNA vaccines in oncology, with a particular focus on recent clinical trials and the computational workflows and methodologies for identifying both shared and individual antigens. While this review centers on therapeutic mRNA vaccines targeting existing tumors, it does not cover preventative vaccines. Preclinical experimental validations are crucial in cancer vaccine development, but we emphasize the computational approaches that facilitate neoantigen selection and design, highlighting their role in advancing mRNA vaccine development. The versatility and rapid development potential of mRNA make it an ideal platform for personalized neoantigen immunotherapy. We explore various strategies for antigen target identification, including tumor-associated and tumor-specific antigens and the computational tools used to predict epitopes capable of eliciting strong immune responses. We address key design considerations for enhancing the immunogenicity and stability of mRNA vaccines, as well as emerging trends and challenges in the field. This comprehensive overview highlights the therapeutic potential of mRNA-based cancer vaccines and underscores ongoing research efforts aimed at optimizing these therapies for improved clinical outcomes.
Insights
Messenger RNA (mRNA) cancer vaccines leverage tumor neoantigens for personalized immunotherapy. Computational methods are key for identifying and designing these neoantigens to boost anti-tumor immune responses effectively.
Area of Science:
- Oncology
- Immunology
- Biotechnology
Background:
- Messenger RNA (mRNA) technology offers a powerful platform for developing novel cancer therapies.
- Antigen-based immuno-oncology, particularly cancer vaccines, enhances immune system recognition and response to tumors.
- Tumor neoantigens, derived from somatic mutations, are crucial for eliciting specific anti-tumor immune responses by evading self-tolerance.
Purpose of the Study:
- To review the development and clinical applications of mRNA vaccines in oncology.
- To highlight the role of computational approaches in identifying and designing patient-specific neoantigens for cancer vaccines.
- To discuss strategies for antigen target identification and vaccine design for enhanced immunogenicity.
Main Methods:
- Utilizing next-generation sequencing and advanced computational algorithms for neoantigen identification and prioritization.
- Analyzing factors critical for human leukocyte antigen (HLA)-peptide-T-cell receptor (TCR) complex formation.
- Reviewing computational workflows for identifying shared and individual tumor antigens.
Main Results:
- mRNA vaccines represent a significant advancement in cancer treatment, acting as effective combinatorial partners for immune therapies.
- Computational neoantigen selection is pivotal for designing effective cancer vaccines and amplifying immune responses.
- The review emphasizes the critical role of computational methods in advancing mRNA vaccine development for personalized immunotherapy.
Conclusions:
- mRNA technology is a versatile and rapidly developable platform ideal for personalized neoantigen immunotherapy.
- Optimizing mRNA cancer vaccines involves strategic antigen selection, enhanced immunogenicity, and stability.
- Ongoing research focuses on refining these therapies to improve clinical outcomes in cancer treatment.
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