Li Wendong, Sun Ting, Li Muyang, He Yufei, Li Lin, Wang Lu, Wang Haoyu, Li Jing, Wen Hao, Liu Yong, Chen Yifan, Fan Yubo, Xin Beibei, Zhang Jing
Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Centre for Biomedical Engineering, School of Engineering Medicine, School of Biological Science and Medical Engineering, Beihang University, No.37 Xueyuan Road, Haidian District, Beijing 100083, P. R. China.
Department of Plant Genetics and Breeding, State Key Laboratory of Plant Physiology and Biochemistry & National Maize Improvement Center, China Agricultural University, No.17 Qinghua East Road, Haidian District, Beijing 100193, P. R. China.
Database (Oxford). 2022 Feb 12;2022. doi: 10.1093/database/baac004.
Neoantigens are mutation-containing immunogenic peptides from tumor cells. Neoantigen intrinsic features are neoantigens' sequence-associated features characterized by different amino acid descriptors and physical-chemical properties, which have a crucial function in prioritization of neoantigens with immunogenic potentials and predicting patients with better survival. Different intrinsic features might have functions to varying degrees in evaluating neoantigens' potentials of immunogenicity. Identification and comparison of intrinsic features among neoantigens are particularly important for developing neoantigen-based personalized immunotherapy. However, there is still no public repository to host the intrinsic features of neoantigens. Therefore, we developed GNIFdb, a glioma neoantigen intrinsic feature database specifically designed for hosting, exploring and visualizing neoantigen and intrinsic features. The database provides a comprehensive repository of computationally predicted Human leukocyte antigen class I (HLA-I) restricted neoantigens and their intrinsic features; a systematic annotation of neoantigens including sequence, neoantigen-associated mutation, gene expression, glioma prognosis, HLA-I subtype and binding affinity between neoantigens and HLA-I; and a genome browser to visualize them in an interactive manner. It represents a valuable resource for the neoantigen research community and is publicly available at http://www.oncoimmunobank.cn/index.php.
新抗原是来自肿瘤细胞的含突变免疫原性肽段。新抗原内在特征是新抗原的序列相关特征，由不同的氨基酸描述符和物理化学性质所表征，这些特征在具有免疫原性潜力的新抗原的优先级排序以及预测生存期较长的患者方面具有关键作用。不同的内在特征在评估新抗原的免疫原性潜力方面可能具有不同程度的作用。新抗原之间内在特征的识别和比较对于开发基于新抗原的个性化免疫疗法尤为重要。然而，目前仍没有公共数据库来存储新抗原的内在特征。因此，我们开发了GNIFdb，这是一个专门设计用于存储、探索和可视化新抗原及其内在特征的胶质瘤新抗原内在特征数据库。该数据库提供了一个全面的存储库，包含通过计算预测的人类白细胞抗原I类（HLA-I）限制性新抗原及其内在特征；对新抗原进行系统注释，包括序列、新抗原相关突变、基因表达、胶质瘤预后、HLA-I亚型以及新抗原与HLA-I之间的结合亲和力；以及一个基因组浏览器，以交互方式对它们进行可视化。它为新抗原研究群体提供了宝贵资源，可通过http://www.oncoimmunobank.cn/index.php公开获取。
