TANTIGEN 2.0

TANTIGEN 2.0 catalogs tumor T cell antigens, epitopes, neoantigens, HLA ligands and validated TCR sequences to support analysis of antigen presentation and T cell recognition in cancer.


Key Features:

  • Database content: Contains 4,296 antigen variants derived from 403 unique tumor antigens.
  • T cell epitopes and HLA ligands: Includes more than 1,500 T cell epitopes and HLA ligands.
  • Neoantigens: Incorporates neoantigens defined as tumor-specific antigens arising from mutations that generate novel amino acid sequences within tumor proteins.
  • Validated TCR sequences: Integrates validated T-cell receptor (TCR) sequences specific to cognate T cell epitopes.
  • Expression data: Includes gene, mRNA, and protein expression data for tumor antigens across major human cancers sourced from the Human Pathology Atlas.
  • Integrated analytics: Provides tailored data analytics tools integrated with the dataset to support analysis workflows.

Scientific Applications:

  • Immunotherapy target identification: Identification of potential targets for cancer immunotherapy based on antigen and epitope data.
  • Immune evasion studies: Study of immune evasion mechanisms in tumors using antigen, neoantigen, and expression data.
  • Personalized vaccine development: Support for the development of personalized cancer vaccines by cataloging neoepitopes and cognate TCRs.
  • Antigen presentation and recognition analysis: Analysis of antigen presentation and T cell recognition using integrated epitope, HLA ligand, and TCR information.

Methodology:

Integration of antigen variants, T cell epitopes, HLA ligands, neoantigens and validated TCR sequences, incorporation of gene/mRNA/protein expression data from the Human Pathology Atlas, and integration of tailored data analytics tools.

Topics

Details

Tool Type:
web application
Added:
12/13/2021
Last Updated:
12/13/2021

Operations

Publications

Zhang G, Chitkushev L, Olsen LR, Keskin DB, Brusic V. TANTIGEN 2.0: a knowledge base of tumor T cell antigens and epitopes. BMC Bioinformatics. 2021;22(S8). doi:10.1186/s12859-021-03962-7. PMID:33849445. PMCID:PMC8045306.

PMID: 33849445
PMCID: PMC8045306
Funding: - National Cancer Institute: NCI-SPORE-2P50CA101942-11A1 - Division of Cancer Epidemiology and Genetics, National Cancer Institute: R21 CA216772-01A1