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3D Chromatin Remodeling in B-cell Development and B-cell Acute Lymphoblastic Leukemia [Hi-C]

GSE243298 Homo sapiens (human) Other 35 samples Submitted 2026/03/03 Platform GPL24676
At a glance

human · 35 samples

Organism
Homo sapiens (human)
Topic
Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
35 samples: 35 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.
Summary (written by the submitters)
The identification of molecular subgroups of B-cell progenitor acute lymphocytic leukemia (B-ALL) have proven to be a powerful tool in understanding the derivation of ALL while also providing essential prognostic information. Several studies have also shown changes in epigenetic landscape including differences across B-ALL subtypes. However, the state of the 3D genome across subtypes and how they compare to healthy B-cell progenitors remains unexplored.
Read the full summary ↓
Here we use Hi-C and RNA-seq to profile early B-cell progenitors from healthy donors and a number of B-ALL samples harboring the most frequent and prognostic structural variations, including KMT2A::AFF1 and BCR::ABL. We show that B-ALLs undergo subtype-specific changes in 3D genome organization that indicate the differentiation stage of the disease. Additional analysis shows B-ALLs acquire aberrant chromatin configurations and expression of oncogenic drivers compared to normal progenitors. We also find that the TF ERG is aberrantly activated in ETV6::RUNX1 B-ALL, and it aids in the establishment of a differentiation block. Overall, the findings from our study show the impact of altered chromatin folding on the leukemogenic state of B-ALL.
This dataset
Open GSE243298 in finder → Find more human datasets → Acute lymphoblastic leukemia landscape →
Download · which file do I need?

Direct links to NCBI, 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.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE243298_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

Also filed as BioProject PRJNA1017620. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
35 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 35 sample titles: 35 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
More Acute lymphoblastic leukemia datasets

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