Evidence map›Paper›PMID 41607803›Full record

ArticleFrontiers in immunology2025

A ligand-centered framework for γδ T cell activation in colorectal cancer revealed by single-cell and transformer-based perturbation.

Ran Ran, Douglas K Brubaker

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. IntegratingFrontiers in immunology · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ran RanCenter for Global Health and Diseases, Department of Pathology, Case Western Reserve University, Cleveland, OH, United States.
Douglas K BrubakerCenter for Global Health and Diseases, Department of Pathology, Case Western Reserve University, Cleveland, OH, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the activation mechanisms of γδ T cells in colorectal cancer (CRC) is critical for harnessing their therapeutic potential. Here, using an atlas of human CRC-infiltrating γδ T cells that we built by integrating multiple single-cell RNA-seq datasets, we developed a γδ T cell-refined ligand inference pipeline by combining differential gene expression, gene regulatory network prediction, ligand inference, and in silico perturbation analysis. This approach identified ligands, including IL-15 and TNFSF9 (4-1BBL), as candidates promoting γδ T cell effector function and highlighted NCR2 and KLRC3 (NKG2E), whose in silico overexpression was associated with γδ T cell activation. Ligand enrichment analyses further indicated that monocytes and dendritic cells are key contributors to γδ T cell activation in the tumor microenvironment. Our results also highlighted transcription factors IKZF1, FOSL2, and FOXO1 in the less activated γδ T cells and IRF1, KLF2, and BHLHE40 in the effector γδ T cells that plausibly regulated the differential activation state. Together, our results offer a systems-level view of the signaling and transcriptional programs governing γδ T cell phenotypes in CRC and provide a foundation for γδ T cell-based immunotherapies with enhanced antitumor functions.

Indexed as

Colorectal NeoplasmsIntraepithelial LymphocytesLymphocyte ActivationLymphocytes, Tumor-InfiltratingReceptors, Antigen, T-Cell, gamma-deltaGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansLigandsSingle-Cell AnalysisTumor MicroenvironmentLigandsReceptors, Antigen, T-Cell, gamma-deltacancer colorectaldeep learn inggamma delta (γδ) T cellsligandperturbation predictiontransformer

Identifiers

PMID41607803
PMCPMC12835328

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.