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A non-enzymatic role for METTL3 as an Androgen Receptor co-regulator promoting prostate cancer proliferation.

GSE335783 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 30 samples Submitted 2026/07/08 Platform GPL34284
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 30 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Topic
Prostate cancerThis series is part of our curated briefing on it.
Samples
30 samples: 30 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.
Summary (written by the submitters)
Metastatic prostate cancer (PCa) continues to be a major cause of death in males, despite advances in treatment. Most treatment focuses on targeting the Androgen Receptor (AR), the main oncogene responsible for driving most tumors, and despite these therapies targeting AR, majority of patients still succumb to AR-driven disease. Therefore, there is a critical need for understanding how AR functions to promote prostate cancer growth and identify alternative therapeutic targets in AR-driven PCa.
Read the full summary ↓
One avenue garnering attention is targeting epigenetic regulators that promote AR-activity, however, the importance of epitranscriptomic regulators is less understood. Here, we identify a new role for the key catalytic subunit of the RNA N6-methyladenosine (m6A) transferase complex, METTL3, as an AR-coregulator. METTL3 is overexpressed in prostate tumors compared to normal tissue, and METTL3 protein is elevated in AR-expressing cell lines. Depletion of METTL3 significantly reduces proliferation of cancer
This dataset
Open GSE335783 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Prostate cancer 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 GSE335783_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 peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1479436 and SRA study SRP710437. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
30 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 30 sample titles: 30 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
More Prostate cancer datasets

Search all human ChIP / ATAC / CUT&Tag 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.