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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.<\/jats:p>\n                  <jats:p>We developed a computational tool to locate moving T cells in solid tumors and identified key genes involved in this process.<\/jats:p>","DOI":"10.1172\/jci.insight.192718","type":"journal-article","created":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T18:00:48Z","timestamp":1778176848000},"source":"Crossref","is-referenced-by-count":1,"title":["Computational identification of migrating T cells in spatial transcriptomics data"],"prefix":"10.1172","volume":"11","author":[{"given":"Lin","family":"Zhong","sequence":"first","affiliation":[{"name":"Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA."},{"name":"Department of Statistics and Data Science, Southern Methodist University, Dallas, Texas, 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