Predicting HLA CD4 Immunogenicity in Human Populations.
Predicting HLA CD4 Immunogenicity in Human Populations.
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DOI：
10.3389/fimmu.2018.01369
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发表时间：
2018
影响因子：
7.3
通讯作者：
Sette A
中科院分区：
文献类型：
--
作者：
Dhanda SK;Karosiene E;Edwards L;Grifoni A;Paul S;Andreatta M;Weiskopf D;Sidney J;Nielsen M;Peters B;Sette A
无论是从对 T 细胞反应机制的基本了解还是在实际应用方面来说，T 细胞免疫原性的预测都是一个颇受关注的话题。 HLA 结合亲和力通常用于预测 T 细胞表位，因为 HLA 结合亲和力是人类 T 细胞免疫原性的关键必要条件。然而，由于 HLA 分子的高度变异性、HLA 以外的潜在其他因素以及经常缺乏 HLA 分型数据，人群的免疫原性变得复杂。为了克服这些问题，我们探索了一种替代方法来识别能够区分免疫原性肽和未识别肽的共同特征。来自同行评审的已发表论文的显性表位组与来自相同实验/供体的负肽结合使用，以训练神经网络并生成“免疫原性评分”。我们还将免疫原性评分的性能与之前描述的基于群体水平的 HLA II 类结合的免疫原性预测方法进行了比较。免疫原性评分在一系列源自已发表文献的独立数据集上进行了验证，这些数据集代表了 57 项独立研究，其中通过测试跨越不同抗原的重叠肽来评估人群的免疫原性。总体而言，这些测试数据集对应了 2,000 多种肽，并在 1,600 多名不同的人类捐赠者中进行了测试。 7 等位基因方法预测和免疫原性评分与相似的性能相关 [ROC 曲线下面积 (AUC) 值的平均值分别为 0.703 和 0.702]，而组合方法的平均 AUC 为 0.725。与免疫原性评分相比，平均 AUC 值的增加是显着的 (p = 0.0135)，并且与 7 等位基因方法相比，观察到显着性的强烈趋势 (p = 0.0938)。现在可以使用免疫表位数据库网站 () 上的 CD4 T 细胞免疫原性预测工具免费获得新的免疫原性评分方法。新的免疫原性评分从蛋白质序列开始预测群体水平的 CD4 T 细胞免疫原性，无需 HLA 分型。其功效已在不同抗原来源、种族和不同表位鉴定技术的背景下得到验证。
Prediction of T cell immunogenicity is a topic of considerable interest, both in terms of basic understanding of the mechanisms of T cells responses and in terms of practical applications. HLA binding affinity is often used to predict T cell epitopes, since HLA binding affinity is a key requisite for human T cell immunogenicity. However, immunogenicity at the population it is complicated by the high level of variability of HLA molecules, potential other factors beyond HLA as well as the frequent lack of HLA typing data. To overcome those issues, we explored an alternative approach to identify the common characteristics able to distinguish immunogenic peptides from non-recognized peptides. Sets of dominant epitopes derived from peer-reviewed published papers were used in conjunction with negative peptides from the same experiments/donors to train neural networks and generate an “immunogenicity score.” We also compared the performance of the immunogenicity score with previously described method for immunogenicity prediction based on HLA class II binding at the population level. The immunogenicity score was validated on a series of independent datasets derived from the published literature, representing 57 independent studies where immunogenicity in human populations was assessed by testing overlapping peptides spanning different antigens. Overall, these testing datasets corresponded to over 2,000 peptides and tested in over 1,600 different human donors. The 7-allele method prediction and the immunogenicity score were associated with similar performance [average area under the ROC curve (AUC) values of 0.703 and 0.702, respectively] while the combined methods reached an average AUC of 0.725. This increase in average AUC value is significant compared with the immunogenicity score (p = 0.0135) and a strong trend toward significance is observed when compared to the 7-allele method (p = 0.0938). The new immunogenicity score method is now freely available using CD4 T cell immunogenicity prediction tool on the Immune Epitope Database website (). The new immunogenicity score predicts CD4 T cell immunogenicity at the population level starting from protein sequences and with no need for HLA typing. Its efficacy has been validated in the context of different antigen sources, ethnicities, and disparate techniques for epitope identification.
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DOI：
10.4049/jimmunol.1103556
发表时间：
2012-05-15
期刊：
Journal of immunology (Baltimore, Md. : 1950)
影响因子：
--
作者：
Arlehamn CS;Sidney J;Henderson R;Greenbaum JA;James EA;Moutaftsi M;Coler R;McKinney DM;Park D;Taplitz R;Kwok WW;Grey H;Peters B;Sette A
通讯作者：
Sette A
MHC I类的性质提出了增强免疫原性的肽。
影响因子：
4.3
作者：
Calis JJ;Maybeno M;Greenbaum JA;Weiskopf D;De Silva AD;Sette A;Keşmir C;Peters B
通讯作者：
Peters B
影响因子：
2.8
作者：
Etto, Tamara;de Boer, Carmela;Rolland, Jennifer M.
通讯作者：
Rolland, Jennifer M.
DOI：
10.1073/pnas.85.4.1199
发表时间：
1988-02-01
影响因子：
11.1
作者：
GOOD, MF;POMBO, D;MILLER, LH
通讯作者：
MILLER, LH
影响因子：
6.7
作者：
Lindestam Arlehamn CS;McKinney DM;Carpenter C;Paul S;Rozot V;Makgotlho E;Gregg Y;van Rooyen M;Ernst JD;Hatherill M;Hanekom WA;Peters B;Scriba TJ;Sette A
通讯作者：
Sette A