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NEPdb: A Database of T-Cell Experimentally-Validated Neoantigens and Pan-Cancer Predicted Neoepitopes for Cancer
Jiaqi Xia1, Peng Bai1, Weiliang Fan1
1State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Wuhan University, Wuhan, China.
Abstract:
T-cell recognition of somatic mutation-derived cancer neoepitopes can lead to tumor regression. Due to the difficulty to identify effective neoepitopes, constructing a database for sharing experimentally validated cancer neoantigens will be beneficial to precise cancer immunotherapy. Meanwhile, the routine neoepitope prediction in silico is important but laborious for clinical use. Here we present NEPdb, a database that contains more than 17,000 validated human immunogenic neoantigens and ineffective neoepitopes within human leukocyte antigens (HLAs) via curating published literature with our semi-automatic pipeline. Furthermore, NEPdb also provides pan-cancer level predicted HLA-I neoepitopes derived from 16,745 shared cancer somatic mutations, using state-of-the-art predictors. With a well-designed search engine and visualization modes, this database would enhance the efficiency of neoantigen-based cancer studies and treatments. NEPdb is freely available at http://nep.whu.edu.cn/.
Insights
NEPdb is a new database featuring over 17,000 validated cancer neoantigens and predicted neoepitopes. This resource aids in advancing cancer immunotherapy and neoantigen research.
Area of Science:
- Immunology
- Oncology
- Bioinformatics
Background:
- T-cell recognition of cancer neoepitopes can induce tumor regression, highlighting their therapeutic potential.
- Identifying effective neoepitopes for cancer immunotherapy is challenging and crucial for precise treatment strategies.
Purpose of the Study:
- To develop and present NEPdb, a comprehensive database of validated human immunogenic neoantigens and ineffective neoepitopes.
- To provide a resource for in silico prediction of neoepitopes across various cancer types.
Main Methods:
- Curated published literature using a semi-automatic pipeline to identify over 17,000 validated neoantigens and neoepitopes.
- Utilized state-of-the-art predictors to generate pan-cancer HLA-I neoepitopes from 16,745 shared somatic mutations.
Main Results:
- NEPdb houses >17,000 experimentally validated human immunogenic neoantigens and ineffective neoepitopes.
- The database includes predicted HLA-I neoepitopes from a large cohort of cancer somatic mutations, offering broad applicability.
Conclusions:
- NEPdb enhances the efficiency of neoantigen-based cancer studies and treatments.
- The database serves as a valuable, freely accessible resource for the cancer immunotherapy research community.
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