| Autor: |
Manman Lu, Linfeng Xu, Xingxing Jian, Xiaoxiu Tan, Jingjing Zhao, Zhenhao Liu, Yu Zhang, Chunyu Liu, Lanming Chen, Yong Lin, Lu Xie |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Frontiers in Immunology, Vol 13 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1664-3224 |
| DOI: |
10.3389/fimmu.2022.855976 |
| Popis: |
Neoantigens are widely reported to induce T-cell response and lead to tumor regression, indicating a promising potential to immunotherapy. Previously, we constructed an open-access database, i.e., dbPepNeo, providing a systematic resource for human tumor neoantigens to storage and query. In order to expand data volume and application scope, we updated dbPepNeo to version 2.0 (http://www.biostatistics.online/dbPepNeo2). Here, we provide about 801 high-confidence (HC) neoantigens (increased by 170%) and 842,289 low-confidence (LC) HLA immunopeptidomes (increased by 107%). Notably, 55 class II HC neoantigens and 630 neoantigen-reactive T-cell receptor-β (TCRβ) sequences were firstly included. Besides, two new analytical tools are developed, DeepCNN-Ineo and BLASTdb. DeepCNN-Ineo predicts the immunogenicity of class I neoantigens, and BLASTdb performs local alignments to look for sequence similarities in dbPepNeo2.0. Meanwhile, the web features and interface have been greatly improved and enhanced. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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