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Upregulated cholesterol biosynthesis facilitates the survival of methylation-retaining AML cells following decitabine treatment [single_colony_TEM-Seq]

GSE256353 Homo sapiens (human) DNA methylation 1728 samples Submitted 2025/07/22 Platform GPL15520Platform GPL24676Platform GPL18573
At a glance

DNA methylation · human · 1728 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
1728 samples: 1728 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.
Paper
Hypomethylating agents induce epigenetic and transcriptional heterogeneity with implications for acute myeloid leukemia cell self-renewalLeukemia · 2025
Summary (written by the submitters)
DNA hypomethylating agents (HMAs) are used to treat acute myeloid leukaemia (AML) and myelodysplasia patients who are unsuitable for intensive chemotherapy, but low response rates and therapy-resistant relapse remain significant challenges. To optimise HMA efficacy, we must understand how resistance and relapse arise from cells that survive treatment.
Read the full summary ↓
Here we combine single-cell multi-omic analysis with parallel colony-forming assays to link HMA-induced molecular heterogeneity with functional consequences in AML cells. HMAs, azacytidine cytidine (azacytidine ) and decitabine (decitabine ), induced global epigenetic heterogeneity associated with upregulation of inflammatory responses and cell death pathways in a subset of hypomethylated cells. Some AML cells maintained high DNA methylation during treatment, and these methylation-retaining cells had increased self-renewal capacity following decitabine , but not azacytidine . Molecular profiling of individual colonies revealed upregulated cholesterol biosynthesis as an adaptation to HMA treatment, and inhibition by rosuvastatin enhanced decitabine effects in vitro and in vivo. Thus, HMA-induced heterogeneity has important implications for AML cell growth and statins are a candidate co-treatment strategy to delay or prevent HMA-resistant relapse.
Published in
Hypomethylating agents induce epigenetic and transcriptional heterogeneity with implications for acute myeloid leukemia cell self-renewal
Bond DR, Burnard SM, Uddipto K et al. · Leukemia 2025 · PMID 40676205 · doi:10.1038/s41375-025-02693-5
This dataset
Open GSE256353 in finder → Find more human 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 GSE256353_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 PRJNA1079256 and SRA study SRP491019. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40676205) ↗
Study design
1728 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 the first 400 of 1728 sample titles: 400 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

+ 1688 more — browse all 1728 samples with per-sample file links →

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.