表型
生物
抗原
CD8型
病毒
细胞毒性T细胞
质量细胞仪
免疫系统
单细胞分析
病毒学
人类白细胞抗原
细胞
T细胞
免疫学
基因
遗传学
体外
作者
Florian Schmidt,Hannah Fields,Yovita Ida Purwanti,Ana Milojkovic,Saad Y. Salim,Kan Wu,Yannick Simoni,Antonella Vitiello,Daniel T. MacLeod,Alessandra Nardin,Evan W. Newell,Katja Fink,Andreas Wilm,Michael G. Fehlings
出处
期刊:Cell Reports
[Elsevier]
日期:2023-10-01
卷期号:42 (10): 113250-113250
被引量:3
标识
DOI:10.1016/j.celrep.2023.113250
摘要
Following viral infection, the human immune system generates CD8+ T cell responses to virus antigens that differ in specificity, abundance, and phenotype. A characterization of virus-specific T cell responses allows one to assess infection history and to understand its contribution to protective immunity. Here, we perform in-depth profiling of CD8+ T cells binding to CMV-, EBV-, influenza-, and SARS-CoV-2-derived antigens in peripheral blood samples from 114 healthy donors and 55 cancer patients using high-dimensional mass cytometry and single-cell RNA sequencing. We analyze over 500 antigen-specific T cell responses across six different HLA alleles and observed unique phenotypes of T cells specific for antigens from different virus categories. Using machine learning, we extract phenotypic signatures of antigen-specific T cells, predict virus specificity for bulk CD8+ T cells, and validate these predictions, suggesting that machine learning can be used to accurately predict antigen specificity from T cell phenotypes.
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