Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States.
Department of Immunology, St Jude Children's Research Hospital, Memphis, United States.
Elife. 2021 Nov 30;10:e68605. doi: 10.7554/eLife.68605.
T-cell receptors (TCRs) encode clinically valuable information that reflects prior antigen exposure and potential future response. However, despite advances in deep repertoire sequencing, enormous TCR diversity complicates the use of TCR clonotypes as clinical biomarkers. We propose a new framework that leverages experimentally inferred antigen-associated TCRs to form meta-clonotypes - groups of biochemically similar TCRs - that can be used to robustly quantify functionally similar TCRs in bulk repertoires across individuals. We apply the framework to TCR data from COVID-19 patients, generating 1831 public TCR meta-clonotypes from the SARS-CoV-2 antigen-associated TCRs that have strong evidence of restriction to patients with a specific human leukocyte antigen (HLA) genotype. Applied to independent cohorts, meta-clonotypes targeting these specific epitopes were more frequently detected in bulk repertoires compared to exact amino acid matches, and 59.7% (1093/1831) were more abundant among COVID-19 patients that expressed the putative restricting HLA allele (false discovery rate [FDR]<0.01), demonstrating the potential utility of meta-clonotypes as antigen-specific features for biomarker development. To enable further applications, we developed an open-source software package, that implements this framework and facilitates flexible workflows for distance-based TCR repertoire analysis.
T 细胞受体 (TCRs) 编码具有临床价值的信息,反映了先前的抗原暴露和潜在的未来反应。然而,尽管在深度库测序方面取得了进展,但巨大的 TCR 多样性使得 TCR 克隆型难以作为临床生物标志物使用。我们提出了一个新的框架,该框架利用实验推断的与抗原相关的 TCR 形成元克隆型 - 一组具有相似生化特性的 TCR - 可用于在个体的大量库中稳健地定量功能相似的 TCR。我们将该框架应用于来自 COVID-19 患者的 TCR 数据,从 SARS-CoV-2 抗原相关的 TCR 中生成 1831 个公共 TCR 元克隆型,这些 TCR 具有强烈的证据表明受到特定人类白细胞抗原 (HLA) 基因型患者的限制。在独立队列中的应用表明,与精确的氨基酸匹配相比,针对这些特定表位的元克隆型在大量库中更频繁地被检测到,并且在表达假定限制 HLA 等位基因的 COVID-19 患者中,59.7%(1093/1831)更为丰富(错误发现率 [FDR]<0.01),表明元克隆型作为抗原特异性特征用于生物标志物开发的潜力。为了实现进一步的应用,我们开发了一个开源软件包 ,该软件包实现了这个框架,并为基于距离的 TCR 库分析提供了灵活的工作流程。