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Cohesin mutations suppress HLA class II gene expression to promote immune evasion during the progression to acute leukemia in children with Down syndrome [CUT&Run]

GSE314930 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 72 samples Submitted 2026/07/20 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 72 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)
Samples
72 samples: 72 samples, each with a distinct title — no replicated groupsGroups 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)
Children with Down syndrome have a 150-fold increased risk of developing the myeloid leukemia of Down syndrome (ML-DS). ML-DS is preceded by transient abnormal myelopoiesis (TAM), which spontaneously resolves in most cases but progresses to AML with additional mutations most commonly in the cohesin complex or signaling genes. However, the mechanisms by which these alterations promote leukemia are unknown.
Read the full summary ↓
Here, we leveraged isogenic cell lines and patient data to investigate the role of cohesin mutations in leukemia progression. Multi-omic analyses revealed that haploinsufficiency of the cohesin complex suppresses the occupancy of CIITA at HLA class II loci, leading to a reduction in HLA Class II gene expression. Surface levels of HLA-DR are lower in ML-DS relative to TAM and these decreased levels are associated with an increased risk of TAM progression. Of note, a decrease in HLA-Class II gene expression is also a feature of non-DS AML with reduced expression of cohesin family members. These data suggest that unlike TAM, ML-DS blasts may evade the immune system by reduced HLA class II expression, providing a new model for leukemia progression in DS.
This dataset
Open GSE314930 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE314930_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 PRJNA1393136 and SRA study SRP657757. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
72 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 72 sample titles: 72 distinct titles with little repetition. 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

+ 32 more — browse all 72 samples with per-sample file links →

Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

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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.