Neoantigens have emerged as central targets in the development of individualized cancer vaccines, as they are recognized by the immune system as foreign and can elicit potent anti-tumor responses. Advances in computational algorithms and machine learning have improved the accuracy of neoantigen prediction, and clinical trials have reported promising results of vaccines incorporating validated neoantigens into peptide, RNA, or dendritic cell platforms. Despite this progress, the identification of immunologically effective neoantigens remains a complex multi-step process. Current attention is directed not only to conventional missense and indel mutations but also to non-coding RNA-derived neoantigens. A critical challenge is the establishment of reliable systems to verify whether candidate neoantigens can activate cytotoxic T lymphocytes. Moreover, neoantigen expression and immune responses are influenced by tumor-intrinsic and therapeutic factors. High programmed death-ligand 1 expression is known to suppress immune recognition, while ARID1A mutations, associated with tumor progression, can enhance neoantigen expression during chemoresistance, suggesting that drug resistance may be accompanied by new immunogenicity. This work provides an overview of current methodologies for neoantigen identification, advances in prediction and validation strategies, and the dynamic interplay between tumor-intrinsic and immune-related factors that regulate neoantigen expression. We also highlight recent clinical insights as well as novel analytical approaches and discuss challenges and future directions in this rapidly evolving field, emphasizing the potential of neoantigen-based therapies to transform cancer immunotherapy.
Okada et al. (Mon,) studied this question.