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Mitochondrial Dysfunction Fuels Drug Resistance in Adult T-cell Acute Lymphoblastic Leukemia

GSE280250 Homo sapiens (human) RNA-seq (gene expression) 79 samples Submitted 2025/05/29 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 79 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
Homo sapiens (human)
Topic
Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
79 samples: 51 distinct titles, 7 of them repeatedGroups 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
Mitochondrial dysfunction fuels drug resistance in adult T-cell acute lymphoblastic leukemiaJournal of translational medicine · 2025
Summary (written by the submitters)
Following our previous work indicating that a decreased mitochondrial activity is an important feature of tumour aggressiveness in adult T-ALL, we assembled the largest known tumour bank, consisting of 133 samples, to uncover the underlying mechanism. Transcriptomic analysis of these tumours showed that down-regulation of mitochondrial activity plays a central role in mediating the activation of ABCB1, a gene associated with multidrug resistance.
Read the full summary ↓
Furthermore, our research identified de novo lipid synthesis and lipid accumulation as key mechanisms facilitating ABCB1 activation in T-ALL. Lipid accumulation, together with down-regulation of β-oxidation, promote the activation of lipogenic transcription factors, LXRs, which are the strong drivers of ABCB1 gene activation. This knowledge not only allows us to better understand the biology of aggressive T-ALL, but also to shed light on the mechanisms underlying tumour resistance to induction chemotherapy. We propose that in patients with tumours exhibiting low mitochondrial activity, the inhibition of de novo lipogenesis and restriction of dietary fats, such as caprylic acid, could mitigate the treatment resistance.
Published in
Mitochondrial dysfunction fuels drug resistance in adult T-cell acute lymphoblastic leukemia
Guo S, Bourova-Flin E, Rousseaux S et al. · Journal of translational medicine 2025 · PMID 40369632 · doi:10.1186/s12967-025-06423-4
This dataset
Open GSE280250 in finder → Find more human RNA-seq datasets → Acute lymphoblastic leukemia landscape →
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 GSE280250_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 PRJNA1177446 and SRA study SRP540664. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40369632) ↗
Study design
51 distinct titles, 7 of them repeated
RJ-A ×23 LJR-2012011 ×2 LJR-210428 ×2 LJR-210906 ×2 LJR-210917 ×2 LJR-210922 ×2 LJR-220107 ×2

How we read this: Read from 79 sample titles: 51 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

+ 39 more — browse all 79 samples with per-sample file links →

More Acute lymphoblastic leukemia datasets

Search all human RNA-seq datasets in GEO →

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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.