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METTL3-dependent m6A RNA Modifications Orchestrate the HNF1B-associated Redox and the Metabolic Vulnerability in Cancer [RNA-seq]

GSE286384 Homo sapiens (human) RNA-seq (gene expression) 40 samples Submitted 2026/01/01 Platform GPL18573Platform GPL19057
At a glance

RNA-seq (gene expression) · human · 40 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
40 samples: 40 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
Systemic control of HNF1B-driven redox homeostasis by N6-adenosine methylationNucleic acids research · 2026
Summary (written by the submitters)
Internal RNA modifications, such as N6-methyladenosine (m6A), are widespread in mammalian cells but their importance in cancer metabolism remains poorly understood. Here, we demonstrate that the m6A methyltransferase complex, composed of METTL3 and METTL14, is a critical regulator of the metabolic dependencies in human cancers. Inhibiting METTL3-mediated m6A modifications, both genetically and chemically, significantly impairs the antioxidant capacity of pancreatic cancer cells, sensitizing them to the oxidative stress.
Read the full summary ↓
We found that m6A modifications at the 3'-untranslated regions (3'-UTRs) of the HNF1B mRNA enhances its stability and expression levels. Furthermore, the loss of HNF1B triggers oxidative stress-induced cell death across multiple cancer types, recapitulating the metabolic dysfunction caused by m6A depletion and revealing HNF1B as a key mediator of the glutathione metabolic program. By establishing a link between m6A modifications and cellular antioxidant responses via HNF1B, our findings suggest that METTL3 is a metabolic vulnerability in cancer and highlight its potential as a therapeutic target for m6A-directed therapies in cancer.
Published in
Systemic control of HNF1B-driven redox homeostasis by N6-adenosine methylation
Park M, Kim HR, Park JH et al. · Nucleic acids research 2026 · PMID 41495907 · doi:10.1093/nar/gkaf1504
This dataset
Open GSE286384 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 GSE286384_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 PRJNA1209036 and SRA study SRP556516. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41495907) ↗
Study design
40 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 40 sample titles: 40 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
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.