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Cell type-specific apoptosis resistance in juvenile myelomonocytic leukemia

GSE277667 Mus musculus (mouse) RNA-seq (gene expression) 21 samples Submitted 2025/03/19 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 21 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
21 samples: 9 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.
Paper
Oncogenic and microenvironmental signals drive cell type specific apoptosis resistance in juvenile myelomonocytic leukemiaCell death & disease · 2025
Summary (written by the submitters)
Juvenile myelomonocytic leukemia (JMML) is caused by constitutively activated RAS signaling. Activation of the RAS pathway in the JMML mouse model (MxCre;Ptpn11D61Y) affects apoptosis signaling by regulating BCL-2 family members through oncogenic and microenvironemtal signals, in a cell type-dependent manner. Apoptosis resistance mediated by overexpression of anti-apoptotic and downregulation of pro-apoptotic BCL-2 family members was observed in monocytes and granulocytes.
Published in
Oncogenic and microenvironmental signals drive cell type specific apoptosis resistance in juvenile myelomonocytic leukemia
Koleci N, Wu Y, Wehner NA et al. · Cell death & disease 2025 · PMID 40057493 · doi:10.1038/s41419-025-07479-2
This dataset
Open GSE277667 in finder → Find more mouse 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 GSE277667_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1163322 and SRA study SRP533850. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40057493) ↗
Study design
9 conditions, mostly in duplicate
S3 leukemic MxCre;Ptpn11D61Y/+ - BM - LSK ×3 S3 leukemic MxCre;Ptpn11D61Y/+ - BM - CD11b+ ×3 S3 leukemic MxCre;Ptpn11D61Y/+ - Spleen - CD1… ×3 Control MxCre - BM - LSK ×2 Control MxCre - BM - CD11b+ ×2 Control MxCre - Spleen - CD11b+ ×2 Control Ptpn11D61Y/+ - BM - LSK ×2 Control Ptpn11D61Y/+ - BM - CD11b+ ×2 +1 more

Supports a between-group comparison across 21 samples.

How we read this: 9 replicated groups read from 21 sample titles; they account for 21 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
Datasets on a similar topic

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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.