NEPdb: A Database of T-Cell Experimentally-Validated Neoantigens and Pan-Cancer Predicted Neoepitopes for Cancer Immunotherapy

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 <i>in silico</i> 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) <i>via</i> 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/.