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在免疫治疗中进行肿瘤新抗原的计算机识别。

Toward in silico Identification of Tumor Neoantigens in Immunotherapy.

机构信息

Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200072, China.

Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200072, China; Department of Ophthalmology, Ninghai First Hospital, Ninghai, Zhejiang, 315600, China.

出版信息

Trends Mol Med. 2019 Nov;25(11):980-992. doi: 10.1016/j.molmed.2019.08.001. Epub 2019 Sep 4.

Abstract

Cancer immunotherapy includes cancer vaccination, adoptive T cell transfer (ACT) with chimeric antigen receptor (CAR) T cells, and administration of tumor-infiltrating lymphocytes and immune-checkpoint blockade such as anti-CTLA4/anti-PD1 inhibitors that can directly or indirectly target tumor neoantigens and elicit a T cell response. Accurate, rapid, and cost-effective identification of neoantigens, however, is critical for successful immunotherapy. Here, we review computational issues for neoantigen identification by summarizing the various sources of neoantigens and their identification from high-throughput sequencing data. Several opinions are presented to inspire further discussions toward improving neoantigen identification. Continuing efforts are required to improve the sensitivity and specificity of bona fide neoantigens, taking advantage of the development of high-throughput sequencing techniques for effective and personalized cancer immunotherapy.

摘要

癌症免疫疗法包括癌症疫苗接种、嵌合抗原受体 (CAR) T 细胞的过继性 T 细胞转移 (ACT),以及肿瘤浸润淋巴细胞的输注和免疫检查点阻断,如抗 CTLA4/抗 PD1 抑制剂,这些方法可以直接或间接靶向肿瘤新生抗原并引发 T 细胞反应。然而,准确、快速和具有成本效益的新抗原识别对于成功的免疫治疗至关重要。在这里,我们通过总结新抗原的各种来源及其从高通量测序数据中的鉴定,综述了用于新抗原鉴定的计算问题。提出了一些观点,以激发进一步的讨论,以提高新抗原的识别。需要继续努力提高真实新抗原的灵敏度和特异性,利用高通量测序技术的发展,为有效的个性化癌症免疫治疗提供帮助。

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