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Computational identification of migrating T cells in spatial transcriptomics data
Lin Zhong, Bo Li, Zhikai Chi, Siyuan Zhang, Qiwei Li, Guanghua Xiao
Lin Zhong, Bo Li, Zhikai Chi, Siyuan Zhang, Qiwei Li, Guanghua Xiao
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Research Article Immunology Oncology

Computational identification of migrating T cells in spatial transcriptomics data

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Abstract

T cells are the central players in antitumor immunity, and effective tumor killing depends on their ability to infiltrate into the tumor microenvironment (TME) while maintaining normal cytotoxicity. However, late-stage tumors develop immunosuppressive mechanisms that impede T cell movement and induce exhaustion. Investigating T cell migration in human tumors in vivo could provide insights into tumor immune escape, although it remains a challenging task. In this study, we developed ReMiTT, a computational method that leverages spatial transcriptomics data to track T cell migration patterns within tumor tissue. Applying ReMiTT to multiple tumor samples, we identified potential migration trails. On these trails, chemokines that promote T cell trafficking displayed an increasing trend. Additionally, we identified key genes and pathways enriched on these migration trails, including those involved in cytoskeleton rearrangement, leukocyte chemotaxis, cell adhesion, leukocyte migration, and extracellular matrix remodeling. Furthermore, we characterized the phenotypes of T cells along these trails, showing that the migrating T cells are highly proliferative. Our findings introduce an approach for studying T cell migration and interactions within the TME, offering valuable insights into tumor-immune dynamics.

Authors

Lin Zhong, Bo Li, Zhikai Chi, Siyuan Zhang, Qiwei Li, Guanghua Xiao

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Figure 6

Phenotypic investigation of T cells on the migration trails.

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Phenotypic investigation of T cells on the migration trails.
(A) t-SNE p...
(A) t-SNE plot for the 11,236 T cells from deep single-cell RNA-seq data of 14 patients with non–small cell lung cancer, with the nearest-neighboring clusters color-labeled. (B) Bubble plot showing the enrichment of overexpressed genes on T cell migration trails in each of the T cell clusters in A. The large bubble sizes and red colors indicate higher ranks of mean expression of each of the upregulated genes on migration trails among all the 13 clusters of T cells. Clusters (y axis) were ordered by their median ranks of the genes. (C) Volcano plots of gene fold change and adjusted P values for cluster 9 compared with other clusters. Statistical significance was evaluated using the Wilcoxon’s rank-sum test with FDR corrected using the Benjamini-Hochberg procedure. (D) Volcano plots of gene fold change and adjusted P values for cluster 3 compared with other clusters. Statistical significance was evaluated using the Wilcoxon’s rank-sum test with FDR corrected using the Benjamini-Hochberg procedure.

Copyright © 2026 American Society for Clinical Investigation
ISSN 2379-3708

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