dbPepNeo2.0: A Database for Human Tumor Neoantigen Peptides From Mass Spectrometry and TCR Recognition

Manman Lu; Linfeng Xu; Xingxing Jian; Xiaoxiu Tan; Jingjing Zhao; Zhenhao Liu; Yu Zhang; Chunyu Liu; Lanming Chen; Yong Lin; Lu Xie

doi:10.3389/fimmu.2022.855976

dbPepNeo2.0: A Database for Human Tumor Neoantigen Peptides From Mass Spectrometry and TCR Recognition

Front Immunol. 2022 Apr 13:13:855976. doi: 10.3389/fimmu.2022.855976. eCollection 2022.

Authors

Manman Lu^{1

2}, Linfeng Xu^{2

3}, Xingxing Jian^{2

4}, Xiaoxiu Tan^{2

5}, Jingjing Zhao^{1

2}, Zhenhao Liu², Yu Zhang^{2

3}, Chunyu Liu^{1

2}, Lanming Chen¹, Yong Lin³, Lu Xie^{1

2

4}

Affiliations

¹ College of Food Science and Technology, Shanghai Ocean University, Shanghai, China.
² Shanghai-Ministry of Science and Technology (MOST) Key Laboratory of Health and Disease Genomics, Institute for Genome and Bioinformatics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China.
³ School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
⁴ Bioinformatics Center, National Clinical Research Centre for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, China.
⁵ Department of Bioinformatics and Biostatistics, Shanghai Jiao Tong University, Shanghai, China.

Abstract

Neoantigens are widely reported to induce T-cell response and lead to tumor regression, indicating a promising potential to immunotherapy. Previously, we constructed an open-access database, i.e., dbPepNeo, providing a systematic resource for human tumor neoantigens to storage and query. In order to expand data volume and application scope, we updated dbPepNeo to version 2.0 (http://www.biostatistics.online/dbPepNeo2). Here, we provide about 801 high-confidence (HC) neoantigens (increased by 170%) and 842,289 low-confidence (LC) HLA immunopeptidomes (increased by 107%). Notably, 55 class II HC neoantigens and 630 neoantigen-reactive T-cell receptor-β (TCRβ) sequences were firstly included. Besides, two new analytical tools are developed, DeepCNN-Ineo and BLASTdb. DeepCNN-Ineo predicts the immunogenicity of class I neoantigens, and BLASTdb performs local alignments to look for sequence similarities in dbPepNeo2.0. Meanwhile, the web features and interface have been greatly improved and enhanced.

Keywords: TCR; deep learning; experimental validation; mass spectrometry; neoantigen.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Antigens, Neoplasm*
Humans
Mass Spectrometry
Neoplasms*
Peptides
Receptors, Antigen, T-Cell, alpha-beta

Substances

Antigens, Neoplasm
Peptides
Receptors, Antigen, T-Cell, alpha-beta