GEO series

A stem cell model identifies two alternative cell fates in CBFA2T3::GLIS2-driven acute megakaryoblastic leukemia initiation (Multiome scRNA-seq/scATAC-seq)

GSE278751 Homo sapiens (human) Single-cell RNA-seq 14 samples Submitted 2025/08/15 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 14 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 14 samples: 14 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: A stem cell differentiation model reveals two alternative fates in CBFA2T3::GLIS2-driven acute megakaryoblastic leukemia initiationCommunications biology · 2025

Summary (written by the submitters)

CBFA2T3::GLIS2 (CG) is an oncogenic fusion protein found in high-risk pediatric acute megakaryoblastic leukemia (AMKL). To gain insight into its leukemogenic mechanism, we developed a disease model based on genetically modified human induced pluripotent stem cells. We found that CG expression disrupts myeloid differentiation in this model via two alternate paths: either by delaying differentiation of aberrant megakaryocytes (aMK) or by locking aberrant megakaryocyte progenitors (aMKP) in a proliferative state akin to AMKL tumor cells.

Read the full summary ↓

We characterized the gene-regulatory networks characterizing both cell states by single-cell and epigenome analysis, and observed that CG sustains aMKPs along with cooperators GATA2 and ERG, while repressing differentiation factors like CEBPA, LYL1, and NFE2. In contrast, aMKs maintained many differentiation factors and did not up-regulate regulators of self-renewal. In future, our findings may contribute to improved diagnostic and therapeutic procedures aimed at interconverting cell states in CG-positive patients.

Published in

A stem cell differentiation model reveals two alternative fates in CBFA2T3::GLIS2-driven acute megakaryoblastic leukemia initiation

Shoeb MR, Schinnerl D, Shaw LE et al. · Communications biology 2025 · PMID 40866546 · doi:10.1038/s42003-025-08730-4

This dataset

Open GSE278751 in finder → Find more human RNA-seq 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 GSE278751_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1168570 and SRA study SRP536465. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40866546) ↗

Study design

14 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 14 sample titles: 14 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

GSM8554306 WT_UNTREATED_D13_REP1 + WT_DTAG13_D13_REP1 GEX
GSM8554307 WT_UNTREATED_D13_REP1 + WT_DTAG13_D13_REP1 ATAC
GSM8554308 WT_UNTREATED_D25_REP1 + WT_DTAG13_D25_REP1 GEX
GSM8554309 WT_UNTREATED_D25_REP1 + WT_DTAG13_D25_REP1 ATAC
GSM8554310 CG_UNTREATED_D13_REP1 + CG_UNTREATED_D13_REP2 + CG_UNTREATED_D13_REP3 GEX
GSM8554311 CG_UNTREATED_D13_REP1 + CG_UNTREATED_D13_REP2 + CG_UNTREATED_D13_REP3 ATAC
GSM8554312 CG_DTAG13_D13_REP1 + CG_DTAG13_D13_REP2 + CG_DTAG13_D13_REP3 GEX
GSM8554313 CG_DTAG13_D13_REP1 + CG_DTAG13_D13_REP2 + CG_DTAG13_D13_REP3 ATAC
GSM8554314 CG_UNTREATED_D25_REP1 + CG_UNTREATED_D25_REP2 + CG_UNTREATED_D25_REP3 GEX
GSM8554315 CG_UNTREATED_D25_REP1 + CG_UNTREATED_D25_REP2 + CG_UNTREATED_D25_REP3 ATAC
GSM8554316 CG_UNTREATED_LONGTERM_REP1 + CG_UNTREATED_LONGTERM_REP2 + CG_UNTREATED_LONGTERM_REP3 GEX
GSM8554317 CG_UNTREATED_LONGTERM_REP1 + CG_UNTREATED_LONGTERM_REP2 + CG_UNTREATED_LONGTERM_REP3 ATAC
GSM8554318 CG_DTAG13_D25_REP1 + CG_DTAG13_D25_REP2 + CG_DTAG13_D25_REP3 GEX
GSM8554319 CG_DTAG13_D25_REP1 + CG_DTAG13_D25_REP2 + CG_DTAG13_D25_REP3 ATAC

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GSE277485 A stem cell model identifies two alternative cell fates in CBFA2T3::GLIS2-driven acute megakaryoblastic leukemia initiation (scRNA-seq) 14 samples shares cbfa2t3, megakaryoblastic, glis2-driven, alternative, identifies, initiation, scrna-seq
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