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Vacunas contra el cáncer impulsadas por neoantígenos en oncología personalizada: progreso, obstáculos y perspectivas
N Prabhu1, V Rajinikanth1, Mathiyazhagan Narayanan2
1Department of Biotechnology, Research and Innovations, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, SIMATS, Thandalam, Chennai, 602 105, Tamil Nadu, India.
Abstract:
The development of neoantigen-based cancer vaccines has emerged as a groundbreaking approach in the field of personalized oncology. Neoantigens, originating from tumor-specific somatic mutations, possess considerable immunogenic potential and are absent in normal tissues, making them ideal candidates for eliciting targeted and enduring anti-tumor immune responses. Progress in next-generation sequencing, immunopeptidomics, and computational epitope prediction, has accelerated the identification and prioritization of patient-specific neoantigens, thereby facilitating the development of diverse vaccine platforms, including peptide, mRNA, DNA, and dendritic cell-based formulations. Initial clinical trials have demonstrated the safety, practicality, and immunogenicity of neoantigen vaccines in various cancers, producing promising therapeutic responses, particularly when combined with immune checkpoint inhibitors. Despite these advancements, substantial challenges-such as tumor heterogeneity, the accuracy of neoantigen prediction, immune evasion mechanisms, and manufacturing complexities-continue in impede widespread clinical application. This study provides a comprehensive analysis of neoantigen biology, advanced detection technologies, and delivery platforms, while meticulously assessing clinical outcomes, combinatorial strategies, and existing limitations. It also highlights new opportunities, such as the use of artificial intelligence and the mass production of vaccines. Neoantigen-based vaccines represent a significant breakthrough in cancer immunotherapy, offering highly individualized, tumor-targeted treatment strategies that could improve long-term patient survival.
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