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dbPepNeo:一个人类肿瘤新生抗原肽的人工 curated 数据库。

dbPepNeo: a manually curated database for human tumor neoantigen peptides.

机构信息

School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, No. 516, Jungong Road, Yangpu District, Shanghai 200093, China.

Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, No. 1278, Keyuan Road, Pudong New District, Shanghai 201203, China.

出版信息

Database (Oxford). 2020 Jan 1;2020. doi: 10.1093/database/baaa004.

Abstract

Neoantigens can function as actual antigens to facilitate tumor rejection, which play a crucial role in cancer immunology and immunotherapy. Emerging evidence revealed that neoantigens can be used to develop personalized, cancer-specific vaccines. To date, large numbers of immunogenomic peptides have been computationally predicted to be potential neoantigens. However, experimental validation remains the gold standard for potential clinical application. Experimentally validated neoantigens are rare and mostly appear scattered among scientific papers and various databases. Here, we constructed dbPepNeo, a specific database for human leukocyte antigen class I (HLA-I) binding neoantigen peptides based on mass spectrometry (MS) validation or immunoassay in human tumors. According to the verification methods of these neoantigens, the collection of peptides was classified as 295 high confidence, 247 medium confidence and 407 794 low confidence neoantigens, respectively. This can serve as a valuable resource to aid further screening for effective neoantigens, optimize a neoantigen prediction pipeline and study T-cell receptor (TCR) recognition. Three applications of dbPepNeo are shown. In summary, this work resulted in a platform to promote the screening and confirmation of potential neoantigens in cancer immunotherapy. Database URL: www.biostatistics.online/dbPepNeo/.

摘要

新抗原可以作为实际抗原促进肿瘤排斥,在癌症免疫和免疫治疗中起着至关重要的作用。新出现的证据表明,新抗原可用于开发个性化的、针对癌症的疫苗。迄今为止,已经通过计算预测了大量的免疫基因组肽,它们被认为是潜在的新抗原。然而,实验验证仍然是潜在临床应用的金标准。经实验验证的新抗原很少,而且大多散见于科学论文和各种数据库中。在这里,我们构建了 dbPepNeo,这是一个基于质谱 (MS) 验证或人类肿瘤免疫测定的人类白细胞抗原 I 类 (HLA-I) 结合新抗原肽的特定数据库。根据这些新抗原的验证方法,肽的收集分别被分类为 295 个高可信度、247 个中可信度和 407794 个低可信度的新抗原。这可以作为一个有价值的资源,以帮助进一步筛选有效的新抗原,优化新抗原预测管道和研究 T 细胞受体 (TCR) 识别。展示了 dbPepNeo 的三个应用。总之,这项工作为癌症免疫治疗中潜在新抗原的筛选和确认提供了一个平台。数据库网址:www.biostatistics.online/dbPepNeo/。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281a/7043295/9c2ef3b42863/baaa004f1.jpg

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