Current methods of epitope identification for cancer vaccine design

被引：25
作者：
Cherryholmes, Gregory A. [1 ]
Stanton, Sasha E. [1 ]
Disis, Mary L. [1 ]
机构：
[1] Univ Washington, Ctr Translat Med Womens Hlth, Tumor Vaccine Grp, Seattle, WA 98109 USA
来源：
VACCINE | 2015年 / 33卷 / 51期
关键词：
Vaccine; Epitope detection; Sequence-based prediction; Structure-based prediction; Self-protein; Peptide; In silico prediction; T-CELL RESPONSES; CLASS-II; MHC-BINDING; PREDICTING PEPTIDES; IMMUNOTHERAPY; LIMITATIONS; REPERTOIRE; HER-2/NEU; AFFINITY; TARGETS;
D O I：
10.1016/j.vaccine.2015.06.116
中图分类号：
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号：
100102 ;
摘要：
The importance of the immune system in tumor development and progression has been emerging in many cancers. Previous cancer vaccines have not shown long-term clinical benefit possibly because were not designed to avoid eliciting regulatory T-cell responses that inhibit the anti-tumor immune response. This review will examine different methods of identifying epitopes derived from tumor associated antigens suitable for immunization and the steps used to design and validate peptide epitopes to improve efficacy of anti-tumor peptide-based vaccines. Focusing on in silico prediction algorithms, we survey the advantages and disadvantages of current cancer vaccine prediction tools. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：7408 / 7414
页数：7
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