T细胞受体
生物
流式细胞术
T细胞
转录组
克隆(Java方法)
细胞
计算生物学
头颈部鳞状细胞癌
单细胞分析
细胞生物学
癌症研究
表型
癌细胞
电池类型
核糖核酸
头颈部癌
分子生物学
祖细胞
头颈部
基因表达谱
染色质
质量细胞仪
作者
Kelli A. McCord,Emerald Kan,Sean Hyslop,Amanda Y. Xia,Colby J. Hofferek,James S. Lewis,Andreas Wieland,David J. Hernandez,Vlad C. Sandulache,William Henry Hudson
出处
期刊:Science immunology
[American Association for the Advancement of Science]
日期:2026-04-10
卷期号:11 (118): eaec3133-eaec3133
被引量:2
标识
DOI:10.1126/sciimmunol.aec3133
摘要
Current spatial T cell receptor (TCR) profiling approaches lack the resolution needed to link clonal identity, transcriptional state, and spatial positioning of individual T cells in the tumor microenvironment. Here, we introduce a spatial TCR profiling strategy that resolves individual T cell clones together with their transcriptional states at single-cell resolution and applied the method to human head and neck squamous cell carcinoma. Presumed tumor-specific T cells were broadly dispersed throughout the tumor microenvironment, and cells of the same clone occupied distinct transcriptional states in different locations: Immune-rich regions contained more plastic or progenitor cells, whereas tumor-dense regions were enriched for exhausted states. Patients exhibited notably different spatial architectures of antitumor T cell responses, revealing variation that was not captured by high-resolution, spatially agnostic methods such as spectral flow cytometry and single-cell RNA sequencing. These results provide a blueprint for dissecting antigen-specific T cell states in human tumors and reveal how T cell states are spatially coordinated with local cues across the tumor microenvironment.
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