← BioTransfer GEO Dataset Finder
GEO series

Regulation of temozolomide resistance by m6A mRNA methylation in glioma cell lines

GSE306559 Homo sapiens (human) DNA methylation 24 samples Submitted 2026/06/01 Platform GPL34284
At a glance

DNA methylation · human · 24 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Topic
GlioblastomaThis series is part of our curated briefing on it.
Samples
24 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.
Summary (written by the submitters)
N6-methyladenosine (m6A) is a critical regulator of mRNA processing and function, playing roles in mRNA processing, translation, and decay. Changes in m6A status have been implicated in various cancers, including glioblastoma (GBM), where acquired chemoresistance to temozolomide (TMZ) remains a major clinical challenge. We developed cell culture models of acquired TMZ resistance in GBM and analyzed the regulation of resistance-associated genes and pathways by m6A.
Read the full summary ↓
We find that key resistance-associated genes and pathways are regulated by m6A methylation, including MGMT, the enzyme that repairs primary TMZ-induced DNA damage. Inhibition of METTL3 with STM2457 treatment destabilizes MGMT mRNA. Intriguingly, other TMZ resistance-associated genes are similarly regulated by m6A, suggesting that METTL3 inhibition may represent a promising therapeutic approach for overcoming TMZ resistance.
This dataset
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.

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 GSE306559_RAW.tar (it can run to tens of gigabytes).

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.

What the files usually look like: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1311120 and SRA study SRP612773. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in triplicate
U87 MG, DMSO, ×3 U87 MG, STM2457, ×3 U87-R, DMSO, ×3 U87-R, STM2457, ×3 LN229, DMSO, ×3 LN229, STM2457, ×3 LN229-R, DMSO, ×3 LN229-R, STM2457, ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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 Glioblastoma datasets

Search all human 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.