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Fabp4 is Essential for the Maintenance of Leukemia Stem Cells while Sparing Hematopoietic Stem Cells [bulkRNA-seq]

GSE289635 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/02/19 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 18 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.
Summary (written by the submitters)
Fatty acid-binding protein 4 (FABP4) plays a crucial role in the uptake, transport, and metabolic regulation of fatty acids. Previous research has found that the abnormal expression of FABP4 is associated with certain cancers, and it may become a new target for tumor therapy. We discovered that a haploinsufficient or absent dosage of Fabp4 does not affect the function of hematopoietic stem cells in mice, but significantly impacts the maintenance of leukemia stem cells (LSC).
Read the full summary ↓
Our findings indicate that while Fabp4 does not influence the initiation of acute myeloid leukemia (AML) transformed by MLL-AF9 (MA9) in mice, it markedly promotes the progression of AML. A haploinsufficient or absent dosage of Fabp4 significantly extends the survival time of MA9 mice. Our research reveals the key role and mechanism of Fabp4 in MA9-LSC, suggesting that Fabp4 is a potential target for selectively eliminating MLL-rearranged leukemia.
This dataset
Open GSE289635 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 GSE289635_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 PRJNA1223865 and SRA study SRP563985. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 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 18 sample titles: 18 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
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.