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The single-cell transcriptome defines an effector Vd1 gd T cell-dependent anti-tumor immunity in human gastrointestinal stromal tumor (GIST) [10X]

GSE301351 Homo sapiens (human) Single-cell RNA-seq 6 samples Submitted 2026/08/07 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 6 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Topic
Gastrointestinal stromal tumourThis series is part of our curated briefing on it.
Samples
6 samples: 4 × Sorted gamma-delta T cells, PBMC HG vs 2 × Sorted gamma-delta T cells, tumor HGGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Effector Vδ1 γδ T cells mediate anti-tumor immunity and are reprogrammed by imatinib in human gastrointestinal stromal tumorResearch square · 2026
Summary (written by the submitters)
Gamma-delta (gd) T cells bridge innate and adaptive immunity and have the ability to recognize diverse tumor-associated antigens. However, the function of gd T cells in human gastrointestinal stromal tumor (GIST), the most common type of human sarcoma, is unknown. Here, we combined single-cell RNA-seq (scRNA-seq), immunophenotyping, and next-generation T-cell receptor (TCR) sequencing of sorted human circulating and intratumoral gd T cells to query their impact on tumor immunity in GIST.
Read the full summary ↓
We identified major subtypes of Vd1 and Vd2 cells, which were more differentiated in tumors. The effector Vd1 subset exhibited higher expression of cytotoxicity-related transcription and exhaustion molecules, and highly expressed the key transcription factors TBX21 and EOMES. Tyrosine kinase inhibitor (TKI) treatment induced the tumor-enriched Vd1 cells to undergo profound phenotype differentiation, alternative clonal expansion, and TCR diversity. Upon antigen exposure, the Vd1 subset maintained enhanced cytotoxicity properties through an innate-effector phenotype and adaptive-like activation. In a genetically engineered murine GIST model, combination therapy of imatinib with a checkpoint inhibitor increased the adaptive immune response of gd T cell subsets in GIST. Collectively, our findings highlight the importance of Vd1-dependent anti-tumor immunity and open the possibility of specific targeting of gd T subsets based on V gene usage for immunotherapy of GIST.
Published in
Effector Vδ1 γδ T cells mediate anti-tumor immunity and are reprogrammed by imatinib in human gastrointestinal stromal tumor
Zeng S, Sussman JH, Morris M et al. · Research square 2026 · PMID 42282009 · doi:10.21203/rs.3.rs-9557741/v1
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE301351_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1284849 and SRA study SRP596508. Searching any of these in the dataset finder brings you back here.

Study design
4 × Sorted gamma-delta T cells, PBMC HG vs 2 × Sorted gamma-delta T cells, tumor HG

Supports a between-group comparison across 6 samples.

How we read this: 2 replicated groups read from 6 sample titles; they account for 6 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
More Gastrointestinal stromal tumour datasets

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.