| URL: | https://pgx.zju.edu.cn/tsnadb/ |
| Full name: | Tumor-Specific NeoAntigen database |
| Description: | TSNAdb v2.0 combines the predcited results of DeepHLApan, MHCflurry and NetMHCpan v4.0 for the identification of higher confidence neoantigens derived from SNV, INDEL and Fusion, respectively. |
| Year founded: | 2018 |
| Last update: | 2022 |
| Version: | v2.0 |
| Accessibility: |
Accessible
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| Country/Region: | China |
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| Database category: | |
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| University/Institution: | Zhejiang University |
| Address: | College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China. |
| City: | Hangzhou |
| Province/State: | Zhejiang |
| Country/Region: | China |
| Contact name (PI/Team): | Zhan Zhou |
| Contact email (PI/Helpdesk): | zhanzhou@zju.edu.cn |
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TSNAdb v2.0: The Updated Version of Tumor-specific Neoantigen Database. [PMID: 36209954]
In recent years, neoantigens have been recognized as ideal targets for tumor immunotherapy. With the development of neoantigen-based tumor immunotherapy, comprehensive neoantigen databases are urgently needed to meet the growing demand for clinical studies. We have built the tumor-specific neoantigen database (TSNAdb) previously, which has attracted much attention. In this study, we provide TSNAdb v2.0, an updated version of the TSNAdb. TSNAdb v2.0 offers several new features, including (1) adopting more stringent criteria for neoantigen identification, (2) providing predicted neoantigens derived from three types of somatic mutations, and (3) collecting experimentally validated neoantigens and dividing them according to the experimental level. TSNAdb v2.0 is freely available at https://pgx.zju.edu.cn/tsnadb/. |
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TSNAdb: A Database for Tumor-specific Neoantigens from Immunogenomics Data Analysis. [PMID: 30223042]
Tumor-specific neoantigens have attracted much attention since they can be used as biomarkers to predict therapeutic effects of immune checkpoint blockade therapy and as potential targets for cancer immunotherapy. In this study, we developed a comprehensive tumor-specific neoantigen database (TSNAdb v1.0), based on pan-cancer immunogenomic analyses of somatic mutation data and human leukocyte antigen (HLA) allele information for 16 tumor types with 7748 tumor samples from The Cancer Genome Atlas (TCGA) and The Cancer Immunome Atlas (TCIA). We predicted binding affinities between mutant/wild-type peptides and HLA class I molecules by NetMHCpan v2.8/v4.0, and presented detailed information of 3,707,562/1,146,961 potential neoantigens generated by somatic mutations of all tumor samples. Moreover, we employed recurrent mutations in combination with highly frequent HLA alleles to predict potential shared neoantigens across tumor patients, which would facilitate the discovery of putative targets for neoantigen-based cancer immunotherapy. TSNAdb is freely available at http://biopharm.zju.edu.cn/tsnadb. |