| Literature DB >> 35150127 |
Wendong Li1, Ting Sun1, Muyang Li2, Yufei He1, Lin Li1, Lu Wang1, Haoyu Wang1, Jing Li1, Hao Wen1, Yong Liu1, Yifan Chen1, Yubo Fan1, Beibei Xin2, Jing Zhang1.
Abstract
ABSTRACT: 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. DATABASE URL: http://www.oncoimmunobank.cn/index.php.Entities:
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Year: 2022 PMID: 35150127 PMCID: PMC9216533 DOI: 10.1093/database/baac004
Source DB: PubMed Journal: Database (Oxford) ISSN: 1758-0463 Impact factor: 4.462