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dbPepNeo: a manually curated database for human tumor neoantigen peptides

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 hav...

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Autores principales: Tan, Xiaoxiu, Li, Daixi, Huang, Pengjie, Jian, Xingxing, Wan, Huihui, Wang, Guangzhi, Li, Yuyu, Ouyang, Jian, Lin, Yong, Xie, Lu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043295/
https://www.ncbi.nlm.nih.gov/pubmed/32090262
http://dx.doi.org/10.1093/database/baaa004
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author Tan, Xiaoxiu
Li, Daixi
Huang, Pengjie
Jian, Xingxing
Wan, Huihui
Wang, Guangzhi
Li, Yuyu
Ouyang, Jian
Lin, Yong
Xie, Lu
author_facet Tan, Xiaoxiu
Li, Daixi
Huang, Pengjie
Jian, Xingxing
Wan, Huihui
Wang, Guangzhi
Li, Yuyu
Ouyang, Jian
Lin, Yong
Xie, Lu
author_sort Tan, Xiaoxiu
collection PubMed
description 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/.
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spelling pubmed-70432952020-03-02 dbPepNeo: a manually curated database for human tumor neoantigen peptides Tan, Xiaoxiu Li, Daixi Huang, Pengjie Jian, Xingxing Wan, Huihui Wang, Guangzhi Li, Yuyu Ouyang, Jian Lin, Yong Xie, Lu Database (Oxford) Original Article 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/. Oxford University Press 2020-02-22 /pmc/articles/PMC7043295/ /pubmed/32090262 http://dx.doi.org/10.1093/database/baaa004 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Tan, Xiaoxiu
Li, Daixi
Huang, Pengjie
Jian, Xingxing
Wan, Huihui
Wang, Guangzhi
Li, Yuyu
Ouyang, Jian
Lin, Yong
Xie, Lu
dbPepNeo: a manually curated database for human tumor neoantigen peptides
title dbPepNeo: a manually curated database for human tumor neoantigen peptides
title_full dbPepNeo: a manually curated database for human tumor neoantigen peptides
title_fullStr dbPepNeo: a manually curated database for human tumor neoantigen peptides
title_full_unstemmed dbPepNeo: a manually curated database for human tumor neoantigen peptides
title_short dbPepNeo: a manually curated database for human tumor neoantigen peptides
title_sort dbpepneo: a manually curated database for human tumor neoantigen peptides
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043295/
https://www.ncbi.nlm.nih.gov/pubmed/32090262
http://dx.doi.org/10.1093/database/baaa004
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