A Systematic Review of Neoantigen Identification and Clinical Translation in Cancer Immunotherapy (2015–2025)
DOI:
https://doi.org/10.56919/usci.2544.006Keywords:
Cancer Immunotherapy, Neoantigens, Immunopeptidomics, Bioinformatics, histocompatibility complexAbstract
Tumour neoantigens, which are products of tumour-specific mutations, are ideal targets for cancer immunotherapy because they are highly specific and have the potential to elicit a robust T-cell response. Nevertheless, clinical translation of neoantigen-based therapy is not uniform, and systematic analysis of the discovery, validation, and implementation plans is required. A systematic literature search was conducted across PubMed, Scopus, Web of Science, Google Scholar, and Embase in July, 2025, to identify articles on neoantigen discovery and clinical use. In accordance with the PRISMA, 20 studies were included. Among the 20 original papers, 65% (13/20) were based on computational prediction, and only 35% (7/20) contained experimental validation, such as mass spectrometry-based immunopeptidomics or cell-based T-cell assays. Some studies used clinical translation, most of which used personalised vaccines and T-cell therapies, and, in some cases, immune checkpoint inhibitors. A high level of technological heterogeneity and inconsistent accuracy in neoantigen prioritisation were identified as critical limitations to clinical reliability. Neoantigen-based immunotherapy (immunotherapy) presents a high potential, but it is limited by the inaccuracy of predictions and low levels of validation. To enhance the chances of a successful translation, we suggest incorporating immunopeptidomics regularly, implementing AI-based models, expanding the global HLA sample, accelerating the manufacturing process, and standardising validation pipelines.
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