Jove
Visualize
Contact Us
  1. Home
  3. Computational Identification Of Migrating T Cells In Spatial Transcriptomics Data.
  1. Home
  3. Computational Identification Of Migrating T Cells In Spatial Transcriptomics Data.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Identification of the gene cluster for the dithiolopyrrolone antibiotic holomycin in Streptomyces clavuligerus.

Proceedings of the National Academy of Sciences of the United States of America·2010
Same author

Safety evaluation of tea (Camellia sinensis (L.) O. Kuntze) flower extract: assessment of mutagenicity, and acute and subchronic toxicity in rats.

Journal of ethnopharmacology·2010
Same author

Influences of soil properties and leaching on nickel toxicity to barley root elongation.

Ecotoxicology and environmental safety·2010
Same author

Effects of CO2 insufflation on cerebrum during endoscopic thyroidectomy in a porcine model.

Surgical endoscopy·2010
Same author

Plants' use of different nitrogen forms in response to crude oil contamination.

Environmental pollution (Barking, Essex : 1987)·2010
Same author

Overexpression of p35 in Min6 pancreatic beta cells induces a stressed neuron-like apoptosis.

Journal of the neurological sciences·2010
Same journal

AFF3 maintains metabolic quiescence in naïve CD8 T cells and prevents premature immune aging.

JCI insight·2026
Same journal

Microbiotas from extremely preterm infants with growth faltering impair postnatal growth and metabolism in mice.

JCI insight·2026
Same journal

The Investigation of Human Cerebrospinal Fluid Exosome in Spinal Cord Injury.

JCI insight·2026
Same journal

Macrophage-fibroblast signaling networks identified by single-cell RNA sequencing in juvenile systemic sclerosis.

JCI insight·2026
Same journal

The protein tyrosine phosphatase CD45 promotes PMN transepithelial migration, antimicrobial function and colonic mucosal repair.

JCI insight·2026
Same journal

Programmed cycle-induced endometrial perturbations do not independently influence angiogenic imbalance or hypertensive disorders in pregnancy.

JCI insight·2026
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Real-Time In Vitro Migration Assay for Primary Murine CD8+ T Cells
06:42

Real-Time In Vitro Migration Assay for Primary Murine CD8+ T Cells

Published on: May 24, 2024

Computational identification of migrating T cells in spatial transcriptomics data.

Lin Zhong1,2, Bo Li3,4, Zhikai Chi5

  • 1Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.

JCI Insight
|May 8, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Researchers developed ReMiTT, a computational method to track T cell migration in tumors. This tool reveals how T cells move through the tumor microenvironment (TME) and identifies key factors influencing their antitumor immunity.

Keywords:
CancerCell migration/adhesionImmunologyOncologyT cells

More Related Videos

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
10:22

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

Related Experiment Videos

Real-Time In Vitro Migration Assay for Primary Murine CD8+ T Cells
06:42

Real-Time In Vitro Migration Assay for Primary Murine CD8+ T Cells

Published on: May 24, 2024

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
10:22

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

Area of Science:

  • Immunology
  • Computational Biology
  • Oncology

Background:

  • T cells are crucial for antitumor immunity, but tumor progression often hinders their infiltration and function.
  • Tumor microenvironments (TME) can be immunosuppressive, impeding T cell migration and leading to T cell exhaustion.
  • Understanding T cell migration in vivo is vital for insights into tumor immune escape.

Purpose of the Study:

  • To develop a computational method for tracking T cell migration patterns within human tumors using spatial transcriptomics data.
  • To identify migration trails and associated molecular mechanisms within the TME.
  • To characterize the phenotype of T cells along these identified migration routes.

Main Methods:

  • Development of ReMiTT, a novel computational method.
  • Application of ReMiTT to spatial transcriptomics data from multiple human tumor samples.
  • Analysis of gene expression trends, pathway enrichment, and T cell phenotypes along identified migration trails.

Main Results:

  • ReMiTT successfully identified potential T cell migration trails in tumor tissues.
  • Chemokines promoting T cell trafficking showed increasing trends along these trails.
  • Enriched pathways included cytoskeleton rearrangement, leukocyte chemotaxis, cell adhesion, and extracellular matrix remodeling.
  • Migrating T cells identified along these trails were characterized as highly proliferative.

Conclusions:

  • The ReMiTT method provides a novel approach to study T cell migration and interactions within the TME.
  • Findings offer insights into the molecular landscape of T cell migration routes.
  • This research contributes to understanding tumor-immune dynamics and potential therapeutic strategies targeting T cell trafficking.