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Targeting signaling rewiring and resistant subpopulations in Philadelphia Chromosome-like Acute Lymphoblastic Leukemia [Bulk ATAC-seq]

GSE263710 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 39 samples Submitted 2025/01/09 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 39 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 lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
39 samples
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
Targeting senescent stemlike subpopulations in Philadelphia chromosome-like acute lymphoblastic leukemiaBlood · 2025
Summary (written by the submitters)
Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) is a common high-risk leukemia subtype defined by a kinase-activated gene expression pattern and chemoresistance, with low overall survival rates in both children and adults. Clinical responses of patients with Ph-like ALL to tyrosine kinase inhibitor (TKI)-based therapies are incomplete, suggesting partial oncogene addiction and highlighting the need to elucidate alternative biologic dependencies to cure patients.
Read the full summary ↓
Herein, we report integrated bulk and single-cell multiomics studies of Ph-like ALL cells treated in vitro and in vivo with targeted agents to comprehensively define signaling adaptations and resistant subpopulations. Characterizing residual/resistant human ALL cells harvested from murine spleens revealed transcriptional regulatory network changes and kinase signaling adaptations. We identified key transcription factors including c-MYC and AP1 that mediate transcriptional rewiring associated with therapeutic escape, and demonstrate a specific MYC dependency in Ph-like ALL cells. We found a sub-population of leukemia blasts that have high senescence-associated stem cell-like features that is effectively eradicated only with combined STAT and BCL-2 inhibition. This is clinically significant since both conventional chemotherapy and ruxolitinib are ineffective against senescent stem-like blasts, which may mediate therapeutic tolerance and repopulate relapse. Our findings demonstrate that systems level discovery of key oncogenic dependencies and escape pathways can be exploited for co-targeting or sequential treatment to optimally eradicate blasts and cure this high-risk leukemia subtype.
Published in
Targeting senescent stemlike subpopulations in Philadelphia chromosome-like acute lymphoblastic leukemia
Ding YY, Sussman JH, Madden K et al. · Blood 2025 · PMID 39774844 · doi:10.1182/blood.2024026482
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 GSE263710_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 PRJNA1098763 and SRA study SRP500838. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 39 more — browse all 39 samples with per-sample file links →

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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.