来自杂志 Nature Reviews Drug Discovery 的文献。
当前共找到 2 篇文献分享。
1.
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(2023-02-28 23:14):
#paper DOI：10.1038/s41573-021-00387-y. Identification of neoantigens for individualized therapeutic cancer vaccines.目前肿瘤疫苗、CART等通过应用人体自身适应性免疫系统来治疗的方式非常火热，其中有关肿瘤新新抗原识别尤其重要，在20的特斯拉联盟比赛中可以看到，大部分预测出的新抗原，其产生真正免疫原性的数量是很少的，不足30%，继续优化新抗原识别算法非常必要，如果要学习新抗原的识别算法，就必须了解肿瘤新抗原在免疫系统中的作用机制。在这篇综述中，作者比较全面的阐述了T细胞识别新抗原的基本机制，并结合体细胞突变和癌症免疫治疗的新抗原预测的现有方法逻辑之间的关系。并且作者也提出一种新抗原的分类方法，这个分类方法更多考虑了临床关注点，可以了解一下。
Abstract:
Somatic mutations in cancer cells can generate tumour-specific neoepitopes, which are recognized by autologous T cells in the host. As neoepitopes are not subject to central immune tolerance and are …
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Somatic mutations in cancer cells can generate tumour-specific neoepitopes, which are recognized by autologous T cells in the host. As neoepitopes are not subject to central immune tolerance and are not expressed in healthy tissues, they are attractive targets for therapeutic cancer vaccines. Because the vast majority of cancer mutations are unique to the individual patient, harnessing the full potential of this rich source of targets requires individualized treatment approaches. Many computational algorithms and machine-learning tools have been developed to identify mutations in sequence data, to prioritize those that are more likely to be recognized by T cells and to design tailored vaccines for every patient. In this Review, we fill the gaps between the understanding of basic mechanisms of T cell recognition of neoantigens and the computational approaches for discovery of somatic mutations and neoantigen prediction for cancer immunotherapy. We present a new classification of neoantigens, distinguishing between guarding, restrained and ignored neoantigens, based on how they confer proficient antitumour immunity in a given clinical context. Such context-based differentiation will contribute to a framework that connects neoantigen biology to the clinical setting and medical peculiarities of cancer, and will enable future neoantigen-based therapies to provide greater clinical benefit.
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2.
na na na
(2023-01-31 22:49):
#paper,dentification of neoantigens for individualized therapeutic cancer vaccines. Nat Rev Drug Discov. https://www.nature.com/articles/s41573-021-00387-y. PMID: 35105974; PMCID: PMC7612664.
近几年肿瘤疫苗是一个非常热门的领域，我们知道肿瘤细胞的体细胞突变可以产生肿瘤特异性的肿瘤表位，被宿主体内的自体T细胞识别，从而产生相应的杀伤；而肿瘤的异质性和个体化程度高，因此个体化治疗性癌症疫苗肿瘤抗原的鉴定就显得十分重要。目前已经开发了许多计算算法和机器学习工具，以识别序列数据中的突变，并优先筛选可能被T细胞识别的突变，为下游每个患者的个体化疫苗设计提供靶点。本篇综述结合T细胞识别肿瘤抗原的基本机制和发现体细胞突变和癌症免疫治疗预测肿瘤抗原的计算方法，比较完整的提供了新抗原算法开发目前成果和待解决问题。是一篇比较好的学习指南，推荐一下
Abstract:
Somatic mutations in cancer cells can generate tumour-specific neoepitopes, which are recognized by autologous T cells in the host. As neoepitopes are not subject to central immune tolerance and are …
>>>
Somatic mutations in cancer cells can generate tumour-specific neoepitopes, which are recognized by autologous T cells in the host. As neoepitopes are not subject to central immune tolerance and are not expressed in healthy tissues, they are attractive targets for therapeutic cancer vaccines. Because the vast majority of cancer mutations are unique to the individual patient, harnessing the full potential of this rich source of targets requires individualized treatment approaches. Many computational algorithms and machine-learning tools have been developed to identify mutations in sequence data, to prioritize those that are more likely to be recognized by T cells and to design tailored vaccines for every patient. In this Review, we fill the gaps between the understanding of basic mechanisms of T cell recognition of neoantigens and the computational approaches for discovery of somatic mutations and neoantigen prediction for cancer immunotherapy. We present a new classification of neoantigens, distinguishing between guarding, restrained and ignored neoantigens, based on how they confer proficient antitumour immunity in a given clinical context. Such context-based differentiation will contribute to a framework that connects neoantigen biology to the clinical setting and medical peculiarities of cancer, and will enable future neoantigen-based therapies to provide greater clinical benefit.
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