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HLA Ⅰ类信号肽多态性决定了 CD94/NKG2-HLA-E 介导的效应细胞反应调节的水平。

HLA class I signal peptide polymorphism determines the level of CD94/NKG2-HLA-E-mediated regulation of effector cell responses.

机构信息

Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA.

Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.

出版信息

Nat Immunol. 2023 Jul;24(7):1087-1097. doi: 10.1038/s41590-023-01523-z. Epub 2023 Jun 1.

Abstract

Human leukocyte antigen (HLA)-E binds epitopes derived from HLA-A, HLA-B, HLA-C and HLA-G signal peptides (SPs) and serves as a ligand for CD94/NKG2A and CD94/NKG2C receptors expressed on natural killer and T cell subsets. We show that among 16 common classical HLA class I SP variants, only 6 can be efficiently processed to generate epitopes that enable CD94/NKG2 engagement, which we term 'functional SPs'. The single functional HLA-B SP, known as HLA-B/-21M, induced high HLA-E expression, but conferred the lowest receptor recognition. Consequently, HLA-B/-21M SP competes with other SPs for providing epitope to HLA-E and reduces overall recognition of target cells by CD94/NKG2A, calling for reassessment of previous disease models involving HLA-B/-21M. Genetic population data indicate a positive correlation between frequencies of functional SPs in humans and corresponding cytomegalovirus mimics, suggesting a means for viral escape from host responses. The systematic, quantitative approach described herein will facilitate development of prediction algorithms for accurately measuring the impact of CD94/NKG2-HLA-E interactions in disease resistance/susceptibility.

摘要

人类白细胞抗原 (HLA)-E 结合来自 HLA-A、HLA-B、HLA-C 和 HLA-G 信号肽 (SP) 的表位,作为自然杀伤细胞和 T 细胞亚群上表达的 CD94/NKG2A 和 CD94/NKG2C 受体的配体。我们表明,在 16 种常见的经典 HLA Ⅰ类 SP 变体中,只有 6 种能够有效地被加工生成能够与 CD94/NKG2 结合的表位,我们称之为“功能性 SP”。唯一的功能性 HLA-B SP,称为 HLA-B/-21M,诱导高水平的 HLA-E 表达,但赋予最低的受体识别。因此,HLA-B/-21M SP 与其他 SP 竞争提供 HLA-E 的表位,并降低 CD94/NKG2A 对靶细胞的总体识别,这需要重新评估涉及 HLA-B/-21M 的先前疾病模型。遗传群体数据表明,人类功能性 SP 的频率与相应的巨细胞病毒模拟物之间存在正相关,这表明病毒逃避宿主反应的一种手段。本文描述的系统、定量方法将有助于开发预测算法,以准确测量 CD94/NKG2-HLA-E 相互作用在疾病易感性/抗性中的影响。

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