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Functional Screening and Transcriptomic Analysis Identify Novel Druggable Dependencies and Immunotherapy Targets in Desmoplastic Small Round Cell Tumor

GSE264741 Homo sapiens (human) RNA-seq (gene expression) 124 samples Submitted 2025/11/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 124 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
124 samples: 62 conditions, mostly in duplicateGroups 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.
Summary (written by the submitters)
Desmoplastic small round cell tumor (DSRCT) is a rare, primitive sarcoma most commonly found in the abdominal and pelvic cavities. DSRCT is characterized by a chromosomal translocation that leads to the formation of the EWSR1::WT1 fusion oncogene, which alters gene expression and drives oncogenesis. With the exception of this translocation, few other recurrent mutations have been identified making it challenging to develop targeted therapies.
Read the full summary ↓
Given this low rate of recurrent mutations, we hypothesize that examining the DSRCT transcriptome may be more successful in identifying novel therapies. However, only limited transcriptomic analysis has been performed on primary DSRCT samples, none with associated outcomes data. Here we report the results of our effort to better characterize DSRCT using RNA-seq on more than 50 tumor samples. We identify pathways and genes not only enriched in DSRCT but associated with poor DSRCT prognosis and which may have important therapeutic implications. We further identify novel immunotherapy targets expressed on the surface of DSRCT and which have a greater specificity for DSRCT than current targets under investigation.
This dataset
Open GSE264741 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 GSE264741_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 PRJNA1104112 and SRA study SRP503731. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
62 conditions, mostly in duplicate
MSK_4746 ×2 MSK_4753 ×2 MSK_4781 ×2 MSK_4801 ×2 MSK_4807B ×2 MSK_4807C ×2 MSK_4807D ×2 MSK_4832 ×2 +54 more

Supports a between-group comparison across 124 samples.

How we read this: 62 replicated groups read from 124 sample titles; they account for 124 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

+ 84 more — browse all 124 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.