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Single cell RNA sequencing of Ewing sarcoma tumors demonstrate transcriptional heterogeneity and clonal evolution

GSE277083 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2025/01/15 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 15 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
Ewing sarcomaThis series is part of our curated briefing on it.
Samples
15 samples: 8 × Blood sample from vs 7 × Primary tumor sampleGroups 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
Single-Cell RNA Sequencing of Ewing Sarcoma Tumors Demonstrates Transcriptional Heterogeneity and Clonal EvolutionClinical cancer research : an official journal of the American Association for Cancer Research · 2025
Summary (written by the submitters)
Ewing sarcoma (ES) is the second most common bone cancer in children, accounting for 2% of pediatric cancer diagnoses. Patients who present with metastatic disease at the time of diagnosis have a dismal prognosis, compared to the >70% 5-year survival of those with localized disease. Here, we utilized single-cell RNA sequencing (scRNA-seq) to characterize the transcriptional landscape of primary ES tumors and surrounding tumor microenvironment (TME).
Read the full summary ↓
Copy-number analysis identified subclonal evolution within patients even prior to treatment. Primary tumor samples demonstrate a heterogenous transcriptional landscape with several conserved gene expression programs composed of gene related to proliferation and EWS targets. We also were able to identify the composition of the tumor microenvironment and molecularly dissect the transcriptional profile of circulating tumor cells (CTCs) in peripheral blood at the time of diagnosis.
Published in
Single-Cell RNA Sequencing of Ewing Sarcoma Tumors Demonstrates Transcriptional Heterogeneity and Clonal Evolution
Goodspeed A, Bodlak A, Duffy AB et al. · Clinical cancer research : an official journal of the American Association for Cancer Research 2025 · PMID 40029262 · doi:10.1158/1078-0432.CCR-24-2040
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 GSE277083_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 PRJNA1160347. Searching any of these in the dataset finder brings you back here.

Study design
8 × Blood sample from vs 7 × Primary tumor sample

Supports a between-group comparison across 15 samples.

How we read this: 2 replicated groups read from 15 sample titles; they account for 15 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 Ewing sarcoma 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.