GEO series

Gene expression profiles of cKit positive bone marrow cells from six genotype mice - WT, Idh1R132, Npm1c, Flt3ITD, Idh1R132+Npm1c, and Idh1R132+Flt3ITD

GSE215369 Mus musculus (mouse) RNA-seq (gene expression) 54 samples Submitted 2025/04/30 Platform GPL21103

At a glance

RNA-seq (gene expression) · mouse · 54 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: 54 samples: 12 conditions, mostly with about 5 replicates eachGroups 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: Mutant IDH1 cooperates with NPM1c or FLT3(ITD) to drive distinct myeloid diseases and molecular outcomesProceedings of the National Academy of Sciences of the United States of America · 2025

Summary (written by the submitters)

Here we show that the combination of Idh1R132 plus Npm1c mutations cooperatively induced overt AML in vivo, using genetically engineered mouse model. In contrast, the combination of Idh1R132 plus Flt3ITD led to myeloid proliferation disease, but not AML. The mice harboring both of Idh1R132 and Npm1c mutations got fatal (median survival, 254 days) due to AML, which demonstrated rapid lethality on recipient mice in secondary transplantation experiments.

Read the full summary ↓

We analyzed cKit-positive bone marrow cells from six genotype mice - WT, Idh1R132, Npm1c, Flt3ITD, Idh1R132+Npm1c, and Idh1R132+Flt3ITD. We isolated cKit positive BM cells from the mice of the two different ages (3 and 6 months old), and subjected to RNA-seq, bisulfite-seq, and ATAC-seq.

Published in

Mutant IDH1 cooperates with NPM1c or FLT3(ITD) to drive distinct myeloid diseases and molecular outcomes

Sakamoto T, Leca J, Zhang X et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 40377995 · doi:10.1073/pnas.2415779122

This dataset

Open GSE215369 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 GSE215369_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 PRJNA889926 and SRA study SRP402288. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40377995) ↗

Study design

12 conditions, mostly with about 5 replicates each

6mo WT RNA-Seq ×5 6mo IDH1 RNA-Seq ×5 6mo NPM1 RNA-Seq ×5 6mo IDH1NPM1 RNA-Seq ×5 6mo FLT3 RNA-Seq ×5 6mo IDH1FLT3 RNA-Seq ×5 3mo WT RNA-Seq ×4 3mo IDH1 RNA-Seq ×4 +4 more

Supports a between-group comparison across 54 samples.

How we read this: 12 replicated groups read from 54 sample titles; they account for 54 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

GSM6634514 3mo WT RNA-Seq Rep1 3mo WT RNA-Seq
GSM6634515 3mo WT RNA-Seq Rep2 3mo WT RNA-Seq
GSM6634516 3mo WT RNA-Seq Rep3 3mo WT RNA-Seq
GSM6634517 3mo WT RNA-Seq Rep4 3mo WT RNA-Seq
GSM6634518 3mo IDH1 RNA-Seq Rep1 3mo IDH1 RNA-Seq
GSM6634519 3mo IDH1 RNA-Seq Rep2 3mo IDH1 RNA-Seq
GSM6634520 3mo IDH1 RNA-Seq Rep3 3mo IDH1 RNA-Seq
GSM6634521 3mo IDH1 RNA-Seq Rep4 3mo IDH1 RNA-Seq
GSM6634522 3mo NPM1 RNA-Seq Rep1 3mo NPM1 RNA-Seq
GSM6634523 3mo NPM1 RNA-Seq Rep2 3mo NPM1 RNA-Seq
GSM6634524 3mo NPM1 RNA-Seq Rep3 3mo NPM1 RNA-Seq
GSM6634525 3mo NPM1 RNA-Seq Rep4 3mo NPM1 RNA-Seq
GSM6634526 3mo IDH1NPM1 RNA-Seq Rep1 3mo IDH1NPM1 RNA-Seq
GSM6634527 3mo IDH1NPM1 RNA-Seq Rep2 3mo IDH1NPM1 RNA-Seq
GSM6634528 3mo IDH1NPM1 RNA-Seq Rep3 3mo IDH1NPM1 RNA-Seq
GSM6634529 3mo IDH1NPM1 RNA-Seq Rep4 3mo IDH1NPM1 RNA-Seq
GSM6634530 3mo FLT3 RNA-Seq Rep1 3mo FLT3 RNA-Seq
GSM6634531 3mo FLT3 RNA-Seq Rep2 3mo FLT3 RNA-Seq
GSM6634532 3mo FLT3 RNA-Seq Rep3 3mo FLT3 RNA-Seq
GSM6634533 3mo FLT3 RNA-Seq Rep4 3mo FLT3 RNA-Seq
GSM6634534 3mo IDH1FLT3 RNA-Seq Rep1 3mo IDH1FLT3 RNA-Seq
GSM6634535 3mo IDH1FLT3 RNA-Seq Rep2 3mo IDH1FLT3 RNA-Seq
GSM6634536 3mo IDH1FLT3 RNA-Seq Rep3 3mo IDH1FLT3 RNA-Seq
GSM6634537 3mo IDH1FLT3 RNA-Seq Rep4 3mo IDH1FLT3 RNA-Seq
GSM6634538 6mo WT RNA-Seq Rep1 6mo WT RNA-Seq
GSM6634539 6mo WT RNA-Seq Rep2 6mo WT RNA-Seq
GSM6634540 6mo WT RNA-Seq Rep3 6mo WT RNA-Seq
GSM6634541 6mo WT RNA-Seq Rep4 6mo WT RNA-Seq
GSM6634542 6mo WT RNA-Seq Rep5 6mo WT RNA-Seq
GSM6634543 6mo IDH1 RNA-Seq Rep1 6mo IDH1 RNA-Seq
GSM6634544 6mo IDH1 RNA-Seq Rep2 6mo IDH1 RNA-Seq
GSM6634545 6mo IDH1 RNA-Seq Rep3 6mo IDH1 RNA-Seq
GSM6634546 6mo IDH1 RNA-Seq Rep4 6mo IDH1 RNA-Seq
GSM6634547 6mo IDH1 RNA-Seq Rep5 6mo IDH1 RNA-Seq
GSM6634548 6mo NPM1 RNA-Seq Rep1 6mo NPM1 RNA-Seq
GSM6634549 6mo NPM1 RNA-Seq Rep2 6mo NPM1 RNA-Seq
GSM6634550 6mo NPM1 RNA-Seq Rep3 6mo NPM1 RNA-Seq
GSM6634551 6mo NPM1 RNA-Seq Rep4 6mo NPM1 RNA-Seq
GSM6634552 6mo NPM1 RNA-Seq Rep5 6mo NPM1 RNA-Seq
GSM6634553 6mo IDH1NPM1 RNA-Seq Rep1 6mo IDH1NPM1 RNA-Seq

+ 14 more — browse all 54 samples with per-sample file links →

Datasets on a similar topic

GSE215368 DNA methylation profiles of cKit positive bone marrow cells from six genotype mice - WT, Idh1R132, Npm1c, Flt3ITD, Idh1R132+Npm1c, and Idh1R132+Flt3ITD 52 samples shares idh1r132, flt3itd, npm1c, profiles, positive, genotype, marrow, ckit
GSE215367 Chromation accessibility profiles of cKit positive bone marrow cells from six genotype mice - WT, Idh1R132, Npm1c, Flt3ITD, Idh1R132+Npm1c, and Idh1R132+Flt3ITD 47 samples shares idh1r132, flt3itd, npm1c, profiles, positive, genotype, marrow, ckit
GSE264700 RNA sequencing of NPM1cA/SMC+/- mouse myeloid sarcoma and whole bone marrow 16 samples shares npm1c, marrow
GSE312134 Gene expression profiles of GM-CSF cultured bone marrow cells treated with HCQ or cGAMP. 42 samples shares profiles, marrow
GSE288474 Gene expression profiles of genes extracted from the hearts of untreated FRDA mice (FA+FA), FRDA mice transplanted with total bone marrow (DP+FA), and WT mice transplanted with total bone marrow (DP+WT) 8 samples shares profiles, marrow
GSE215370 Mutant IDH1 cooperates with NPM1c or FLT3-ITD to drive distinct myeloid diseases and molecular outcomes 153 samples shares npm1c
GSE241165 Characterizing the gene expression profiles of 4T1 and 4T1.2 cells at different stages of bone metastsis using SMART-Seq2 technology 1248 samples shares profiles
GSE318348 Single cell LARRY state-fate analysis of Npm1cA/Flt3-ITD acute myeloid leukemia stem cells 20 samples shares npm1c

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