Numerous neoepitope-based vaccination strategies are in testing for clinical use in the treatment of cancer. Rapid identification of immunostimulatory neoantigen targets hastens neoantigen vaccine development. Papers recently published in Nature Biotechnology describe two independent machine-learning-based algorithms that demonstrate improved identification of MHC class II-binding peptides. Herein, we outline the benefits of these algorithms and their implications for future immunotherapies.

中文翻译：

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改进的 MHC II 表位预测 - 迈向个性化医疗的一步。

许多基于新表位的疫苗接种策略正在测试用于治疗癌症的临床应用。免疫刺激性新抗原靶点的快速识别加速了新抗原疫苗的开发。最近发表在 Nature Biotechnology 上的论文描述了两种独立的基于机器学习的算法，它们证明了 MHC II 类结合肽的识别得到了改进。在这里，我们概述了这些算法的好处及其对未来免疫疗法的影响。