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T 细胞受体库分析及多样性和克隆性指标。

T-cell repertoire analysis and metrics of diversity and clonality.

机构信息

Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.

Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne (UNIL), Lausanne, Switzerland; Molecular Modelling Group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.

出版信息

Curr Opin Biotechnol. 2020 Oct;65:284-295. doi: 10.1016/j.copbio.2020.07.010. Epub 2020 Sep 2.

Abstract

The recent developments of high-throughput bulk and single-cell sequencing technologies accelerated the understanding of the complexity of immune repertoire dynamics combined to transcriptomics. Also, profiling of cellular repertoires in health or disease requires statistical metrics to capture clonal diversity characterized by clones frequency, repertoire richness and convergence. Here we present the common technologies of bulk and single-cell sequencing of T-cell receptors (TCRs), discuss current knowledge regarding computational tools clustering and predicting specificity of TCR repertoires based on shared structural motifs and review main indices for repertoire diversity and convergence analyses. These tools represent potential biomarkers to decipher the fitness of immune repertoires in diseased or treated patients but also the presages and promises of computational approaches to revolutionize personalized immunotherapy.

摘要

高通量批量和单细胞测序技术的最新发展加速了对免疫受体库动态与转录组学相结合的复杂性的理解。此外,在健康或疾病中对细胞受体库进行分析需要统计指标来捕获以克隆频率、受体库丰富度和收敛性为特征的克隆多样性。本文介绍了 T 细胞受体(TCR)批量和单细胞测序的常见技术,讨论了基于共享结构基序对 TCR 受体库的聚类和预测特异性的计算工具的现有知识,并回顾了受体库多样性和收敛性分析的主要指标。这些工具代表了破译患病或接受治疗患者免疫受体库适应性的潜在生物标志物,也是计算方法革新个性化免疫疗法的先兆和承诺。

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