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Human peripheral and tissue Foxp3-high regulatory T cells in patients with hepatocellular carcinoma [CITE-seq]

GSE307831 Homo sapiens (human) Single-cell RNA-seq 33 samples Submitted 2025/09/16 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 33 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
Hepatocellular carcinomaThis series is part of our curated briefing on it.
Samples
33 samples: 33 samples, each with a distinct title — no replicated groupsGroups 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
Tumor-migrating peripheral Foxp3-high regulatory T cells drive poor prognosis in HCCHepatology (Baltimore, Md.) · 2026
Summary (written by the submitters)
CD4⁺ regulatory T cells (Tregs) are pivotal in hepatocellular carcinoma (HCC) progression, but systemic depletion risks autoimmunity. Using single-cell CITE-seq on tumor, non-tumor, and peripheral blood samples, we identified a peripheral Foxp3^high Treg subset that preferentially migrates to tumors via the CCR5–CCL5 axis, where they acquire a terminally differentiated, activated phenotype with elevated LAYN and TRM signatures, and further enhance Foxp3 expression and immunosuppressive activity in response to pro-inflammatory cytokines.
Read the full summary ↓
The proportion of Foxp3^high Tregs in peripheral blood strongly correlated with their tumor infiltration, and a >3.5% Foxp3^high Tregs/CD4⁺ T cells ratio predicted poor survival and early recurrence (AUROC >0.75). These findings establish peripheral Foxp3^high Tregs as both key mediators of immunosuppression and a promising non-invasive biomarker for HCC prognosis.
Published in
Tumor-migrating peripheral Foxp3-high regulatory T cells drive poor prognosis in HCC
Huang CH, Ku WT, Mahalingam J et al. · Hepatology (Baltimore, Md.) 2026 · PMID 40590861 · doi:10.1097/HEP.0000000000001428
This dataset
Open GSE307831 in finder → Find more human RNA-seq datasets → Hepatocellular carcinoma landscape →
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.

Series matrix ↓
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 GSE307831_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1327378 and SRA study SRP619260. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40590861) ↗
Study design
33 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 33 sample titles: 33 distinct titles with little repetition. 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 Hepatocellular carcinoma 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.