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Phosphorylated DEK sustains leukemia stem cells by enabling PBX3-driven transcriptional reprogramming [CUT&Tag 2]

GSE329274 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2026/04/28 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 12 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
Acute myeloid leukemiaThis series is part of our curated briefing on it.
Samples
12 samples: 6 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.
Summary (written by the submitters)
Leukemia stem cells (LSCs) drive acute myeloid leukemia (AML) initiation, relapse, and chemoresistance, yet the core post-translational events governing LSC formation and maintenance remain elusive. Here, through phosphoproteomic profiling of normal hematopoietic stem and progenitor cells (HSPCs) versus LSC-enriched population, we identify DEK phosphorylation as a critical modification during leukemogenesis.
Read the full summary ↓
Functional studies in MLL-AF9- and HOXA9/MEIS1-driven AML mouse models, as well as patient-derived xenografts (PDXs), demonstrate that DEK deficiency impairs LSC maintenance and AML development. Moreover, DEK deletion enhances LSC chemosensitivity to the standard-of-care combination of azacitidine and venetoclax (Aza/Ven), whereas DEK overexpression confers robust chemoresistance. Mechanistically, DEK recruits the transcription factor GABPA to drive overexpression of transcriptional cofactor PBX3, a key oncogenic driver in AML, thereby sustaining a leukemogenic transcriptional program. This DEK-GABPA interaction strictly depends on DEK phosphorylation at Ser301/303/306/307 (the 4S site), which stabilizes the conformation of the DEK-GABPA complex. We demonstrate CK2 as the upstream kinase that directly phosphorylates DEK-4S site. Importantly, inhibition of DEK phosphorylation through 4S site mutations or treatment with a clinical-stage CK2 inhibitor CX-4945 selectively depletes LSCs while sparing normal HSPCs. Furthermore, combining CX-4945 with venetoclax promotes LSC apoptosis and suppresses the PBX3-mediated leukemogenic transcriptional program, exhibiting synergistic anti-AML effects both in vitro and in vivo. Collectively, our findings uncover a previously unrecognized phosphorylation event (DEK-4S phosphorylation) that sustains LSCs and establish the CK2-DEK axis as a promising LSC-specific therapeutic strategy in AML.
This dataset
Open GSE329274 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Acute myeloid 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 GSE329274_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 PRJNA1458255 and SRA study SRP695374. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in duplicate
DEK_CUT-Tag_MOLM13_shControl ×2 DEK_CUT-Tag_MOLM13_shDEK ×2 DEK_CUT-Tag_MOLM13_4S-A ×2 GABPA_CUT-Tag_MOLM13_shControl ×2 GABPA_CUT-Tag_MOLM13_shDEK ×2 GABPA_CUT-Tag_MOLM13_4S-A ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 12 sample titles; they account for 12 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
More Acute myeloid leukemia datasets

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

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