Frontiers in Immunology (Apr 2022)

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

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

DOI
https://doi.org/10.3389/fimmu.2022.855976
Journal volume & issue
Vol. 13

Abstract

Read online

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.

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