Database of Collected Peptides for Neoantigen

Welcome to dbPepNeo

A Manually Curated Database for Human Tumor Neoantigen Peptides
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  • Xiaoxiu Tan, Daixi Li*, Pengjie Huang, Xingxing Jian, Huihui Wan, Guangzhi Wang, Yuyu Li, Jian Ouyang, Yong Lin*, Lu Xie*. dbPepNeo: a manually curated database for human tumor neoantigen peptides. Database, 2020, 2020.


Neoantigens can function as actual antigens to facilitate tumor rejection, which play a crucial role in cancer immunology and immunotherapy. Emerging evidence revealed that neoantigens can be used to develop personalized, cancer-specific vaccines. To date, large numbers of immunogenomic peptides have been computationally predicted to be potential neoantigens. However experimental validation remains the gold standard for potential clinical application. Experimentally validated neoantigens are rare and mostly appear scattered among scientific papers and various databases. Here we constructed dbPepNeo, a specific database for human leukocyte antigen class I (HLA-I) binding neoantigen peptides based on mass spectrometry (MS) validation or immunoassay in human tumors. According to the verification methods of these neoantigens, the collection of peptides was classified as 295 high confidence, 247 medium confidence and 407,794 low confidence neoantigens respectively. Three applications of dbPepNeo are shown. In addition, two in-house tools are incorporated into dbPepNeo: ProGeo-neo which is a proteogenomics neoantigen prediction pipeline taking use of mass spectrometry data, INeo-Epp which is a machine learning algorithm for prediction of neoepitope immunogenicity based on the features of neoantigen peptides. In summary, this work resulted in a platform to promote the screening and confirmation of potential neoantigens in cancer immunotherapy.Database URL: www.biostatistics.online/dbPepNeo/ .

Powered by Xiaoxiu Tan, Pengjie Huang, Lu Xie@2019 沪ICP:18037576

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