← BioTransfer GEO Dataset Finder
GEO series

mRNA/sRNA Co-Sequencing Reveals Multiple New Targeted Therapy Candidates in Rhabdomyosarcoma

GSE279954 Homo sapiens (human) RNA-seq (gene expression) 26 samples Submitted 2025/04/28 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 26 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
Soft tissue sarcomaThis series is part of our curated briefing on it.
Samples
26 samples: 4 × ARMS sample vs 4 × ERMS sample vs 3 × SCRMS sample vs 2 × Control 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.
Summary (written by the submitters)
There have been few studies investigating the transcriptional-driver landscape of rhabdomyosarcoma (RMS). In this study, we performed genome-wide mRNA and sRNA co-sequencing from the same RMS and wildtype tissues to identify differentially expressed and differentially regulated genes involved in the molecular pathology of RMS. One key finding is the upregulation of RUNX2 transcription factor, which is normally under the negative control of HDAC4 transcriptional silencer, but this is lost in these tissues.
Read the full summary ↓
Similar to bone sarcomas, we propose that HDAC4 itself was under the negative regulated of miR-140, i.e., upregulation of miR-140 silences HDAC4, allowing for the expression of RUNX2. The data showed that most miRNAs known to target HDAC4 (e.g. miR-1, miR-206) including miR-140 were downregulated, with the exception of miR-155. There might be the possibility that miR-140/HDAC4/RUNX2 signalling pathway is specific to bone sarcoma but here, the miR-155/HDAC4/RUNX2 signalling pathway is specific to muscle sarcomas. Further studies are required to test this hypothesis.
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 GSE279954_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: 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 PRJNA1175612 and SRA study SRP539879. Searching any of these in the dataset finder brings you back here.

Study design
4 × ARMS sample vs 4 × ERMS sample vs 3 × SCRMS sample vs 2 × Control sample

Supports a between-group comparison across 13 samples.

How we read this: 4 replicated groups read from 26 sample titles; they account for 13 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 Soft tissue sarcoma datasets

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.