dbPepNeo: a manually curated database for human tumor neoantigen peptides

Abstract 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 pep...

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Bibliographic Details
Published in:Database : the journal of biological databases and curation 2020, Vol.2020
Main Authors: Tan, Xiaoxiu, Li, Daixi, Huang, Pengjie, Jian, Xingxing, Wan, Huihui, Wang, Guangzhi, Li, Yuyu, Ouyang, Jian, Lin, Yong, Xie, Lu
Format: Article
Language:English
Subjects:
Antigen (tumor-associated)
Cancer
Cancer immunotherapy
Cancer vaccines
Genomics
Histocompatibility antigen HLA
Immune system
Immunotherapy
Lymphocytes T
Mass spectroscopy
Neoantigens
Original
Peptides
T cell receptors
Tumors
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Summary:Abstract 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. This can serve as a valuable resource to aid further screening for effective neoantigens, optimize a neoantigen prediction pipeline and study T-cell receptor (TCR) recognition. Three applications of dbPepNeo are shown. 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/.
ISSN:1758-0463
1758-0463
DOI:10.1093/database/baaa004