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Cup-like nuclei is a hallmark of IGH:DUX4 acute lymphoblastic leukemia and reveals cytoplasmic mitochondria accumulation

GSE288566 Homo sapiens (human) RNA-seq (gene expression) 57 samples Submitted 2026/02/02 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 57 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
Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
57 samples: 22 × DUX4_patient vs 21 × non DUX4 hyperdiploidy, control vs 14 × non DUX4 ETV6-RUNX1, controlGroups 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
Cup-Like Nuclei Is a Hallmark of DUX4/ERG Acute Lymphoblastic Leukemia and Reveals Cytoplasmic Mitochondria AccumulationPediatric blood & cancer · 2026
Summary (written by the submitters)
Cup-like nuclei are a distinctive morphological feature observed in certain cases of acute lymphoblastic leukemia (ALL). We provide evidence that they characterize DUX4-rearranged ALL independently of IKZF1 deletion, and reveal marked mitochondrial accumulation in this ALL subset. We provide here the RNAseq data from DUX4 rearranged ALL and non-DUX4 rearranged ALL which revealed DUX4-rearranged distinct transcriptional mitochondrial signature.
Published in
Cup-Like Nuclei Is a Hallmark of DUX4/ERG Acute Lymphoblastic Leukemia and Reveals Cytoplasmic Mitochondria Accumulation
Arfeuille C, Roux H, Fenneteau O et al. · Pediatric blood & cancer 2026 · PMID 42520297 · doi:10.1002/1545-5017.70422
This dataset
Open GSE288566 in finder → Find more human RNA-seq datasets → Acute lymphoblastic leukemia 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 GSE288566_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 PRJNA1218448 and SRA study SRP561114. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42520297) ↗
Study design
22 × DUX4_patient vs 21 × non DUX4 hyperdiploidy, control vs 14 × non DUX4 ETV6-RUNX1, control

Supports a case/control comparison: 22 samples read as cases, 35 as controls.

How we read this: 3 replicated groups read from 57 sample titles; they account for 57 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

+ 17 more — browse all 57 samples with per-sample file links →

More Acute lymphoblastic leukemia 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.