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Autocrine TGFβ2 enforces a transcriptionally hybrid cell state in Ewing sarcoma

GSE299137 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2025/12/22 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 48 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)
Topic
Ewing sarcomaThis series is part of our curated briefing on it.
Samples
48 samples: 16 conditions, mostly in triplicateGroups 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
Autocrine TGFβ2 enforces a transcriptionally hybrid cell state in Ewing sarcomaScience advances · 2026
Summary (written by the submitters)
Sub-populations of cancer-associated fibroblast (CAF)-like tumor cells deposit extracellular matrix (ECM) proteins that support Ewing sarcoma (EwS) progression and metastasis. We previously showed a hallmark of CAF-like EwS cells is their hybrid transcriptional state wherein the driver fusion oncogene, EWS::FLI1, maintains activation of proliferative programs but loses capacity to repress mesenchymal genes.
Read the full summary ↓
Here, we studied primary patient tumors and cell line models to identify molecular drivers of this hybrid state. Our data reveal that hybrid EwS cells are induced and maintained by a TGFβ signaling positive feedback loop. Hybrid cells de-repress TGFBR2 and upregulate expression and secretion of TGFβ2 to sustain pathway activation and ECM deposition. While TGFβ ligands can potently induce growth arrest in cells of epithelial origin, we show that TGFβ1 and TGFβ2 have no impact on EwS proliferation but instead promote cell invasion. Thus, stroma and tumor-derived TGFβ ligands induce and maintain hybrid EwS cells to promote metastatic phenotypes.
Published in
Autocrine TGFβ2 enforces a transcriptionally hybrid cell state in Ewing sarcoma
Wrenn ED, Harris JC, Apfelbaum AA et al. · Science advances 2026 · PMID 41564188 · doi:10.1126/sciadv.ady0550
This dataset
Open GSE299137 in finder → Find more human RNA-seq datasets → Ewing sarcoma 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 GSE299137_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 PRJNA1272641 and SRA study SRP590238. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41564188) ↗
Study design
16 conditions, mostly in triplicate
TC71_veh ×3 TC71_TGFB1 ×3 TC71_TGFB2 ×3 TC71_Vacto 1uM ×3 A673_veh ×3 A673_TGFB1 ×3 A673_TGFB2 ×3 A673_Vacto 1uM ×3 +8 more

Supports a between-group comparison across 48 samples.

How we read this: 16 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 samples with per-sample file links →

More Ewing sarcoma datasets

Search all human RNA-seq datasets in GEO →

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