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PAX translocations remodel mitochondrial metabolism through altered leucine usage in rhabdomyosarcoma

GSE253895 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 58 samples Submitted 2025/04/03 Platform GPL24676Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 58 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Topic
Soft tissue sarcomaThis series is part of our curated briefing on it.
Samples
58 samples: 26 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.
Paper
PAX translocations remodel mitochondrial metabolism through altered leucine usage in rhabdomyosarcomaCell · 2025
Summary (written by the submitters)
Alveolar rhabdomyosarcoma (ARMS) patients harboring PAX3-FOXO1 and PAX7-FOXO1 fusion proteins exhibit a greater incidence of tumor relapse, metastasis, and poor survival outcome, thereby underscoring the urgent need to develop effective therapies to treat this subtype of childhood cancer. To uncover mechanisms that contribute to tumor initiation, we develop a muscle progenitor model and use epigenomic approaches to unravel genome rewiring events mediated by PAX3/7 fusion proteins.
Read the full summary ↓
Among the key targets of PAX3/7 fusion proteins, we identify a cohort of oncogenes, FGF receptors, tRNA-modifying enzymes, and genes essential for mitochondrial metabolism and protein translation, which we successfully targeted in preclinical trials. We identify leucine usage as a key factor driving the growth of aggressive PAX-fusion tumors, as limiting its bioavailability impaired oxidative phosphorylation and mitochondrial metabolism, delaying tumor progression and improving survival in vivo. Our data provide a compelling list of actionable targets and suggest promising new strategies to treat this tumor. This SuperSeries is composed of the SubSeries listed below.
Published in
PAX translocations remodel mitochondrial metabolism through altered leucine usage in rhabdomyosarcoma
Kalita B, Martinez-Cebrian G, McEvoy J et al. · Cell 2025 · PMID 40185100 · doi:10.1016/j.cell.2025.03.008
This dataset
Open GSE253895 in finder → Find more human RNA-seq datasets → Soft tissue 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 GSE253895_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1067626 and SRA study SRP485230. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40185100) ↗
Study design
26 conditions, mostly in duplicate
Control_RNAseq_mDOX ×3 P3F1_RNAseq_mDOX ×3 P7F1_RNAseq_mDOX ×3 Control_RNAseq_pDOX ×3 P3F1_RNAseq_pDOX ×3 P7F1_RNAseq_pDOX ×3 Control_H3K4me1 ×2 P3F1_H3K4me1 ×2 +18 more

Supports a between-group comparison across 58 samples.

How we read this: 26 replicated groups read from 58 sample titles; they account for 58 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

+ 18 more — browse all 58 samples with per-sample file links →

More Soft tissue sarcoma datasets

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