HLA-binding properties of tumor neoepitopes in humans.
HLA-binding properties of tumor neoepitopes in humans.
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DOI：
10.1158/2326-6066.cir-13-0227
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发表时间：
2014-06
影响因子：
10.1
通讯作者：
Wu CJ
中科院分区：
文献类型：
--
作者：
Fritsch EF;Rajasagi M;Ott PA;Brusic V;Hacohen N;Wu CJ
癌症基因组测序使得能够快速鉴定患者肿瘤内编码序列突变的完整库，并促进其作为个性化免疫原的使用。虽然有多种技术可用于帮助选择肿瘤疫苗中包含的突变定义的表位，但肽结合患者MHC的能力是肽呈递的关键途径。随着MHC I类结合的预测算法的准确性的进步，基于预测亲和力选择表位提供了一种快速且无偏见的表位优先化方法。我们在本文中展示了预测算法对大量真正的T细胞定义的突变的人肿瘤抗原的回顾性应用，所述抗原诱导免疫应答，其中大部分与肿瘤消退或长期疾病稳定性相关。结果支持这种方法用于表位选择的应用，并揭示了这些天然存在的表位的信息特征，以帮助在肿瘤疫苗中使用的表位优先化。
Cancer genome sequencing has enabled the rapid identification of the complete repertoire of coding sequence mutations within a patient’s tumor and facilitated their use as personalized immunogens. While a variety of techniques are available to assist in the selection of mutation-defined epitopes to be included within the tumor vaccine, the ability of the peptide to bind patient MHC is a key gateway to peptide presentation. With advances in the accuracy of predictive algorithms for MHC class I binding, choosing epitopes on the basis of predicted affinity provides a rapid and unbiased approach to epitope prioritization. We show herein the retrospective application of a prediction algorithm to a large set of bona fide T-cell defined mutated human tumor antigens that induced immune responses most of which were associated with tumor regression or long-term disease stability. The results support the application of this approach for epitope selection and reveal informative features of these naturally occurring epitopes to aid in epitope prioritization for use in tumor vaccines.