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TGF-beta promotes human T follicular helper cell stemness properties at the expense of effector function

GSE320556 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/04/15 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 12 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
12 samples: 3 × naïve-derived TFH_control vs 3 × naïve-derived TFH_TGF-beta vs 3 × memory TFH_control vs 3 × memory TFH_TGF-betaGroups 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
TGF-beta promotes human T follicular helper cell stemness properties at the expense of effector functionFrontiers in immunology · 2026
Summary (written by the submitters)
Follicular helper T (TFH) cells are essential for germinal center reactions and the maintenance of long-lived humoral immunity. Transforming growth factor-β (TGF-β) is a multifunctional cytokine implicated in immune regulation, T-cell differentiation, and the maintenance of cellular stemness. Prior studies have shown that TGF-β promotes stemness across a wide range of cell types and facilitates the differentiation of naïve CD4⁺ T cells into various T helper cell subsets.
Read the full summary ↓
However, its precise effects on TFH effector function and stem-like properties remain poorly understood. Here, the dual regulatory roles of TGF-β1 in modulating TFH effector functions and stem-like properties were investigated. We found that TGF-β1 treatment in vitro promoted human naïve CD4+ T cells differentiation into CXCR3⁺ TFH, but significantly attenuated their effector molecule expression and TFH-mediated memory B-cell differentiation and antibody production, whereas it enhanced the expression of stemness-associated molecules in TFH cells both differentiated in vitro from naïve CD4+ T cells and isolated from blood. Notably, TGF-β1 promoted proliferation and reduced apoptosis of naïve-derived TFH cells in vitro, but suppressed proliferation and increased early apoptosis in blood-derived mature TFH cells. Collectively, these findings indicate that TGF-β1 tunes the balance between TFH effector function and stem-like properties, and show differential regulations of the early phase of TFH differentiation and mature TFH cells, which may have implications for TFH-driven immune pathology and disease.
Published in
TGF-beta promotes human T follicular helper cell stemness properties at the expense of effector function
Yang Y, Wu C, Yang W et al. · Frontiers in immunology 2026 · PMID 41958642 · doi:10.3389/fimmu.2026.1732275
This dataset
Open GSE320556 in finder → Find more human RNA-seq datasets →
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 GSE320556_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1428819 and SRA study SRP679575. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41958642) ↗
Study design
3 × naïve-derived TFH_control vs 3 × naïve-derived TFH_TGF-beta vs 3 × memory TFH_control vs 3 × memory TFH_TGF-beta

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
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