Sep 2026· International Journal of Molecular Sciences· Vol 27· 0 citations· 40 references
Medicine
TL;DR
By integrating molecular vaccine design with tumor evolution, immune-contexture remodeling, and checkpoint sensitivity, this review identifies determinants that may distinguish successful immune priming from durable therapeutic efficacy and outlines priorities for biomarker-guided patient selection and future combination strategies.
Abstract
Personalized mRNA neoantigen vaccines represent an emerging form of precision cancer immunotherapy designed to generate de novo T-cell responses against patient-specific tumor mutations. Their therapeutic activity, however, depends not only on neoantigen selection and vaccine-induced immune priming but also on whether these responses can remain functional within an immunosuppressive tumor microenvironment. Immune checkpoint blockade provides a mechanistically complementary strategy by relieving inhibitory signaling that constrains vaccine-expanded tumor-reactive lymphocytes. This review examines this therapeutic interface across three interconnected levels: molecular neoantigen selection and mRNA vaccine design, vaccine-driven remodeling of antitumor T-cell immunity, and clinical integration with PD-1/PD-L1 blockade. Particular emphasis is placed on how neoantigen clonality, antigen presentation, tumor heterogeneity, and immune escape influence the translation of vaccine immunogenicity into clinical benefit. Current evidence is evaluated across melanoma, non-small cell lung cancer, and pancreatic ductal adenocarcinoma, including randomized and ongoing trials of intismeran autogene, an individualized synthetic mRNA therapy encoding patient-specific neoantigens, and autogene cevumeran, an individualized uridine mRNA-lipoplex neoantigen vaccine. By integrating molecular vaccine design with tumor evolution, immune-contexture remodeling, and checkpoint sensitivity, this review identifies determinants that may distinguish successful immune priming from durable therapeutic efficacy and outlines priorities for biomarker-guided patient selection and future combination strategies.
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