← BioTransfer GEO Dataset Finder
GEO series

Cytotoxicity caused by 5-methylcytosine depletion on chromatin-associated RNA by 5-azacytosine in leukemia [RNA-seq]

GSE297591 Homo sapiens (human) RNA-seq (gene expression) 96 samples Submitted 2025/06/05 Platform GPL34281Platform GPL34328
At a glance

RNA-seq (gene expression) · human · 96 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)
Samples
96 samples: 32 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.
Summary (written by the submitters)
5-azacytidine (5-azaC) is a DNA hypomethylating agent clinically used to improve outcomes in myeloid malignancies. However, 5-azaC treatment causes gene dysregulation inconsistent with DNA hypomethylation changes. Some patients benefited from 5-azaC treatment did not display notable DNA demethylation. These observations suggest alternative mechanisms of action by 5-azaC.
Read the full summary ↓
As a ribonuleoside analogue, 5-azaC is more readily incorporated into nascent RNA. Here, we demonstrate that RNA 5-methycytosine (m5C) depletion by 5-azaC treatment, particularly at early time points, is sufficient to induce leukemia cell death. In contrast to its DNA demethylation function, the RNA-dependent process by 5-azaC causes transcriptional repression, disrupting genes involved in cell cycle regulation and DNA repair. Mechanistically, 5-azaC impairs two specific m5C-mediated transcriptional regulatory pathways. First, depletion of m5C in chromatin-associated RNA (caRNA) disrupts the MBD6-mediated H2AK119ub removal. In parallel, this also impairs SRSF2 recruitment and the downstream H3K27ac deposition by p300. Indeed, loss of the caRNA methyltransferase NSUN2 caused prolonged cell cycle, defective DNA repair, and shifted hematopoietic lineage commitment toward erythropoiesis, mirroring the effects of 5-azaC treatment. Furthermore, we performed leukemia cell line screen and identifies that TET2 and IKZF1 depletion can sensitize 5-azaC treatment, consistent with the observed RNA-dependent cytotoxicity of 5-azaC in leukemia cells. In summary, our findings highlight the transcription regulation by 5-azaC through depleting caRNA m5C, providing insights into the mechanism of action for 5-azaC, the prediction of its efficacy, and future directions for therapy developments based on 5-azaC.
This dataset
Open GSE297591 in finder → Find more 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 GSE297591_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 PRJNA1265233 and SRA study SRP586374. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
32 conditions, mostly in triplicate
MOLM13, RNA, Ctrl, ×3 MOLM13, RNA, 5azaC, ×3 SKM1, RNA, Ctrl, ×3 SKM1, RNA, 5azaC, ×3 LK, RNA, Ctrl, ×3 LK, RNA, 5azaC, ×3 MOLM13, tetshNSUN2, RNA, Ctrl, ×3 MOLM13, tetshNSUN2, RNA, Dox, ×3 +24 more

Supports a between-group comparison across 96 samples.

How we read this: 32 replicated groups read from 96 sample titles; they account for 96 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

+ 56 more — browse all 96 samples with per-sample file links →

Datasets on a similar topic

Search all RNA-seq datasets in GEO →

Share this dataset

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.