Literature DB >> 28280852

TANTIGEN: a comprehensive database of tumor T cell antigens.

Lars Rønn Olsen1,2, Songsak Tongchusak1, Honghuang Lin1,3, Ellis L Reinherz1,4,5, Vladimir Brusic1,6,7, Guang Lan Zhang8,9.   

Abstract

Tumor T cell antigens are both diagnostically and therapeutically valuable molecules. A large number of new peptides are examined as potential tumor epitopes each year, yet there is no infrastructure for storing and accessing the results of these experiments. We have retroactively cataloged more than 1000 tumor peptides from 368 different proteins, and implemented a web-accessible infrastructure for storing and accessing these experimental results. All peptides in TANTIGEN are labeled as one of the four categories: (1) peptides measured in vitro to bind the HLA, but not reported to elicit either in vivo or in vitro T cell response, (2) peptides found to bind the HLA and to elicit an in vitro T cell response, (3) peptides shown to elicit in vivo tumor rejection, and (4) peptides processed and naturally presented as defined by physical detection. In addition to T cell response, we also annotate peptides that are naturally processed HLA binders, e.g., peptides eluted from HLA in mass spectrometry studies. TANTIGEN provides a rich data resource for tumor-associated epitope and neoepitope discovery studies and is freely available at http://cvc.dfci.harvard.edu/tantigen/ or http://projects.met-hilab.org/tadb (mirror).

Entities:  

Keywords:  Bioinformatics; Cancer vaccine; Immunotherapy; Neoepitopes; T cell epitope prediction; Tumor Antigens

Mesh:

Substances:

Year:  2017        PMID: 28280852     DOI: 10.1007/s00262-017-1978-y

Source DB:  PubMed          Journal:  Cancer Immunol Immunother        ISSN: 0340-7004            Impact factor:   6.968


  20 in total

Review 1.  Mapping the tumour human leukocyte antigen (HLA) ligandome by mass spectrometry.

Authors:  Lena Katharina Freudenmann; Ana Marcu; Stefan Stevanović
Journal:  Immunology       Date:  2018-05-08       Impact factor: 7.397

2.  Negative trade-off between neoantigen repertoire breadth and the specificity of HLA-I molecules shapes antitumor immunity.

Authors:  Máté Manczinger; Balázs Koncz; Gergő Mihály Balogh; Benjamin Tamás Papp; Leó Asztalos; Lajos Kemény; Balázs Papp; Csaba Pál
Journal:  Nat Cancer       Date:  2021-07-08

3.  iTTCA-MFF: identifying tumor T cell antigens based on multiple feature fusion.

Authors:  Hongliang Zou; Fan Yang; Zhijian Yin
Journal:  Immunogenetics       Date:  2022-03-05       Impact factor: 3.330

4.  BioReader: a text mining tool for performing classification of biomedical literature.

Authors:  Christian Simon; Kristian Davidsen; Christina Hansen; Emily Seymour; Mike Bogetofte Barnkob; Lars Rønn Olsen
Journal:  BMC Bioinformatics       Date:  2019-02-04       Impact factor: 3.169

Review 5.  Breast cancer vaccination comes to age: impacts of bioinformatics.

Authors:  Sepideh Parvizpour; Jafar Razmara; Yadollah Omidi
Journal:  Bioimpacts       Date:  2018-04-18

6.  Level of neo-epitope predecessor and mutation type determine T cell activation of MHC binding peptides.

Authors:  Hanan Besser; Sharon Yunger; Efrat Merhavi-Shoham; Cyrille J Cohen; Yoram Louzoun
Journal:  J Immunother Cancer       Date:  2019-05-22       Impact factor: 13.751

7.  Irradiation increases the immunogenicity of lung cancer cells and irradiation-based tumor cell vaccine elicits tumor-specific T cell responses in vivo.

Authors:  Lumeng Luo; Minghe Lv; Xibing Zhuang; Qi Zhang; Tiankui Qiao
Journal:  Onco Targets Ther       Date:  2019-05-16       Impact factor: 4.147

Review 8.  In silico prediction of cancer immunogens: current state of the art.

Authors:  Irini A Doytchinova; Darren R Flower
Journal:  BMC Immunol       Date:  2018-03-15       Impact factor: 3.615

9.  Network assessment of demethylation treatment in melanoma: Differential transcriptome-methylome and antigen profile signatures.

Authors:  Zhijie Jiang; Caterina Cinti; Monia Taranta; Elisabetta Mattioli; Elisa Schena; Sakshi Singh; Rimpi Khurana; Giovanna Lattanzi; Nicholas F Tsinoremas; Enrico Capobianco
Journal:  PLoS One       Date:  2018-11-28       Impact factor: 3.240

10.  Quantitative Prediction of the Landscape of T Cell Epitope Immunogenicity in Sequence Space.

Authors:  Masato Ogishi; Hiroshi Yotsuyanagi
Journal:  Front Immunol       Date:  2019-04-16       Impact factor: 7.561

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