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Condensate-promoting ENL mutation induces tumorigenesis via chromatin remodeling [ChIP-seq and CUT&Tag]

GSE239468 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 46 samples Submitted 2024/04/14 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 46 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
Mus musculus (mouse)
Samples
46 samples: 46 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.
Paper
Condensate-Promoting ENL Mutation Drives Tumorigenesis In Vivo Through Dynamic Regulation of Histone Modifications and Gene ExpressionCancer discovery · 2024
Summary (written by the submitters)
Gain-of-function mutations in the chromatin ‘reader’ ENL, identified in AML and Wilms tumor, have been shown to induce aberrant formation of transcriptional condensates in cellular systems. However, the precise role of these mutations and their condensate forming property in tumorigenesis remains unclear. By creating a conditional knock-in mouse model for the most prevalent ENL mutation, we establish ENL mutant as a bona fide oncogenic driver of acute myeloid leukemia in vivo.
Read the full summary ↓
Heterozygous expression of ENL mutant perturbs the normal hematopoietic hierarchy and results in the aberrant expansion of myeloid progenitors with increased self-renewal property. Furthermore, the ENL mutant remodels histone modifications to alter differentiation processes and drive oncogenic gene expression during hematopoietic development. Importantly, targeted point mutagenesis to disrupt the condensate formation property completely abolishes ENL mutant’s oncogenic function in hematopoietic stem and progenitor cells (HSPCs). Lastly, short-term treatment with a small molecule inhibitor that blocks the acetyl-binding activity of ENL mutant reverts its impact on chromatin and significantly delays leukemia development in mice. Our studies reveal the crucial biological function of mutation-induced transcriptional condensates in chromatin regulation and cancer in vivo and provide proof-of-concept for targeting of pathogenic condensates as a promising therapy for certain cancers.
Published in
Condensate-Promoting ENL Mutation Drives Tumorigenesis In Vivo Through Dynamic Regulation of Histone Modifications and Gene Expression
Liu Y, Li Q, Song L et al. · Cancer discovery 2024 · PMID 38655899 · doi:10.1158/2159-8290.CD-23-0876
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 GSE239468_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA999348 and SRA study SRP451847. Searching any of these in the dataset finder brings you back here.

Study design
46 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 46 sample titles: 46 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

+ 6 more — browse all 46 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.