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Effect of depletion of BCAT1 on gene expression during NOTCH1-dependent leukemia development in the mouse

GSE267966 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2024/09/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 15 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
15 samples: 5 conditions, mostly in triplicateGroups 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
BCAT1 is a NOTCH1 target and sustains the oncogenic function of NOTCH1Haematologica · 2025
Summary (written by the submitters)
High levels of branched-chain amino acid (BCAA) transaminase 1 (Bcat1) have been associated with adverse prognosis and drug resistance in several cancer types. However, the mechanistic role of Bcat1 in T-cell acute lymphoblastic leukemia (T-ALL) development is ill defined. Here, we used a mouse T-ALL model to show that Bcat1 is required for T-ALL development and maintenance.
Read the full summary ↓
Using a NOTCH1 gain-of-function retroviral model of T-ALL, mouse cells genetically deficient for Bcat1 showed defects in developing leukemia. Amongst the pathways upregulated in Bcat1 KO delta E-NOTCH1 cells we found “DNA repair”, “apoptosis”, and “p53 pathway”. We thus hypothesize that Bcat1 may be implicated in cell cycle progression or apoptosis of T-ALL cells.
Published in
BCAT1 is a NOTCH1 target and sustains the oncogenic function of NOTCH1
Tosello V, Di Martino L, Papathanassiu AE et al. · Haematologica 2025 · PMID 39234857 · doi:10.3324/haematol.2024.285552
This dataset
Open GSE267966 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 GSE267966_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 PRJNA1113955 and SRA study SRP508904. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39234857) ↗
Study design
5 conditions, mostly in triplicate
spleen leukemic T cells, WT0 control (PBS tre… ×3 spleen leukemic T cells, WT0 treated with BCA… ×3 spleen leukemic T cells, WT6, ×3 spleen leukemic T cells, BCAT1 KO 7, ×3 spleen leukemic T cells, BCAT1 KO 3, ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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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