Digestive Oncology Unit, KULeuven, Leuven, Belgium.
de Duve Institute, Université catholique de Louvain, Brussels, Belgium.
Methods Cell Biol. 2024;183:265-302. doi: 10.1016/bs.mcb.2023.06.005. Epub 2023 Sep 19.
Neoantigens have emerged as promising targets for cutting-edge immunotherapies, such as cancer vaccines and adoptive cell therapy. These neoantigens are unique to tumors and arise exclusively from somatic mutations or non-genomic aberrations in tumor proteins. They encompass a wide range of alterations, including genomic mutations, post-transcriptomic variants, and viral oncoproteins. With the advancements in technology, the identification of immunogenic neoantigens has seen rapid progress, raising new opportunities for enhancing their clinical significance. Prediction of neoantigens necessitates the acquisition of high-quality samples and sequencing data, followed by mutation calling. Subsequently, the pipeline involves integrating various tools that can predict the expression, processing, binding, and recognition potential of neoantigens. However, the continuous improvement of computational tools is constrained by the availability of datasets which contain validated immunogenic neoantigens. This review article aims to provide a comprehensive summary of the current knowledge as well as limitations in neoantigen prediction and validation. Additionally, it delves into the origin and biological role of neoantigens, offering a deeper understanding of their significance in the field of cancer immunotherapy. This article thus seeks to contribute to the ongoing efforts to harness neoantigens as powerful weapons in the fight against cancer.
新兴抗原已成为癌症疫苗和过继细胞疗法等先进免疫疗法的有前途的靶点。这些新抗原是肿瘤特有的，仅源自肿瘤蛋白中的体细胞突变或非基因组异常。它们包含广泛的改变，包括基因组突变、转录后变体和病毒癌蛋白。随着技术的进步，免疫原性新抗原的鉴定取得了快速进展，为增强其临床意义带来了新的机会。新抗原的预测需要获取高质量的样本和测序数据，然后进行突变调用。随后，该流程涉及整合各种工具，这些工具可以预测新抗原的表达、加工、结合和识别潜力。然而，计算工具的不断改进受到包含已验证免疫原性新抗原的数据集的可用性的限制。这篇综述文章旨在全面总结新抗原预测和验证方面的现有知识和局限性。此外，它还深入探讨了新抗原的起源和生物学作用，加深了对它们在癌症免疫治疗领域重要性的理解。因此，本文旨在为利用新抗原作为对抗癌症的强大武器的持续努力做出贡献。
