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FTO degrader inhibits acute myeloid leukemia by impairing ribosome biogenesis and translation

GSE282823 Homo sapiens (human) DNA methylation 22 samples Submitted 2025/07/08 Platform GPL34281
At a glance

DNA methylation · human · 22 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Topic
Acute myeloid leukemiaThis series is part of our curated briefing on it.
Samples
22 samples: 8 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
FTO degrader impairs ribosome biogenesis and protein translation in acute myeloid leukemiaScience advances · 2025
Summary (written by the submitters)
The fat mass and obesity-associated protein (FTO), an RNA m6A eraser, has been identified as a critical oncogenic factor in acute myeloid leukemia (AML). We presented the development of an FTO degrader(FP54) that selectively degrades FTO in AML cells, demonstrating superior efficacy both in vitro and in vivo. Mechanistically, FTO degradation increases m6A modifications on ribosome biogenesis related mRNAs and thus promotes YTHDF2-mediated degradation. This process impairs ribosome biogenesis and translation process, ultimately inhibiting AML progression.
Published in
FTO degrader impairs ribosome biogenesis and protein translation in acute myeloid leukemia
Li W, Zhao Y, Wu D et al. · Science advances 2025 · PMID 40815637 · doi:10.1126/sciadv.adv7648
This dataset
Open GSE282823 in finder → Find more human RNA-seq datasets → Acute myeloid 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 GSE282823_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: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1190481 and SRA study SRP547511. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40815637) ↗
Study design
8 conditions, mostly in triplicate
MOLM13-RNAseq-DMSO-rp ×3 MOLM13-RNAseq-FP54-rp ×3 MOLM13-m6Aseq-DMSO-rp ×3 MOLM13-m6Aseq-FP54-rp ×3 NB4-RNAseq-DMSO-rp ×3 NB4-RNAseq-FP54-rp ×3 MOLM13-Polysome-seq-DMSO-rp ×2 MOLM13-Polysome-seq-FP54-rp ×2

Supports a between-group comparison across 22 samples.

How we read this: 8 replicated groups read from 22 sample titles; they account for 22 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
More Acute myeloid 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.