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Updated: Sep 16, 2025

A Nonviral Approach to Generate Transient Chimeric Antigen Receptor T Cells Using mRNA for Cancer Immunotherapy
Published on: February 21, 2025
Immunogenicity of neoantigens: From CAR-T cell to various vaccines
Fatemeh Davodabadi1, Javad Arabpour2, Pouya Goleij3
1Department of Medical Nanotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Abstract:
The recent decade has experienced phenomenal progress in recruiting cutting-edge, high-throughput genomics in cancer research, providing unprecedented insights into neoplasia-contributor mutations. Genomic data analyses enable multiplex assessments for precision medicine. For instance, the path for predicting neoantigen targets for cancer vaccines has been paved by whole-exome and RNA sequencing in combination with bioinformatics algorithms. The application of personalized vaccines, which are highly specific to individuals' tumors and aimed to provoke de novo T-cell reactions against neoantigens, is a promising approach to cancer immunotherapy. In this regard, protein-altering modifications in cancerous cells are being deciphered in light of the predicted preferential binding of the mutated peptides by the patient's immune system constituents. Herein, we first scrutinize the immunogenicity caused by neoplasm-associated antigens and then the ways of identifying and predicting cancer neoantigens. This overview also addresses developed and ongoing neoantigen-based personalized vaccines and targeted drug delivery approaches using these cancerous antigens, as well as considerations for clinical research of this novel, individualized approach to immunotherapy.
Insights
High-throughput genomics advances cancer research by identifying mutations for personalized vaccines. This approach predicts neoantigens, stimulating T-cell responses for novel cancer immunotherapies.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- High-throughput genomics has revolutionized cancer research, revealing key mutations driving neoplasia.
- Genomic data analysis facilitates precision medicine through multiplex assessments.
Purpose of the Study:
- To review the immunogenicity of neoplasm-associated antigens.
- To explore methods for identifying and predicting cancer neoantigens.
- To discuss neoantigen-based personalized vaccines and targeted drug delivery.
Main Methods:
- Whole-exome sequencing and RNA sequencing.
- Bioinformatics algorithms for neoantigen prediction.
- Analysis of protein-altering modifications in cancer cells.
Main Results:
- Genomic insights enable the prediction of neoantigen targets for cancer vaccines.
- Personalized vaccines aim to elicit T-cell reactions against specific neoantigens.
- Deciphering protein modifications aids in predicting immune system binding.
Conclusions:
- Neoantigen-based personalized vaccines represent a promising avenue for cancer immunotherapy.
- Targeted drug delivery strategies can leverage cancer-specific antigens.
- Clinical research considerations are crucial for this individualized treatment approach.
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