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Crosstalk between EZH2 and m6A RNA methylation promotes prostate cancer progression through modulating an m6A autoregulation pathway

GSE296858 Homo sapiens (human) DNA methylation 30 samples Submitted 2025/10/05 Platform GPL34284Platform GPL24106
At a glance

DNA methylation · human · 30 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Topic
Prostate cancerThis series is part of our curated briefing on it.
Samples
30 samples: 11 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.
Paper
EZH2 crosstalk with RNA methylation promotes prostate cancer progression through modulation of m6A autoregulation pathwayThe Journal of clinical investigation · 2026
Summary (written by the submitters)
N6-methyladenosine (m6A), the most predominant RNA modification in humans, participates in various fundamental and pathological bioprocesses. Dynamic manipulation of m6A deposition in the transcriptome is critical for cancer progression, while how this regulation is achieved remains understudied. Here, we report that in prostate cancer (PCa), Polycomb group (PcG) protein Enhancer of Zeste Homolog 2 (EZH2) exerts an additional function in m6A regulation via its enzymatic activity.
Read the full summary ↓
Mechanistically, EZH2 methylates and stabilizes FOXA1 proteins from degradation, which in turn facilitates the transcription of m6A reader YTHDF1. Through activating a m6A autoregulation pathway, YTHDF1 enhances the translation of METTL14 and WTAP, two critical components of the m6A methyltransferase complex (MTC), and thereby upregulates the global m6A level in PCa cells. We further demonstrate that inhibiting the catalytic activity of EZH2 suppresses the translation process globally through targeting the YTHDF1-m6A axis. By disrupting both the expression and interaction of key m6A MTC subunits, combinational treatment of EZH2 degrader MS8815 and m6A inhibitor STM2457 mitigates PCa tumor growth synergistically. Together, our study decodes a previously hidden interrelationship between EZH2 and RNA modification, which may be leveraged to advance the EZH2-targeting curative strategies in cancer.
Published in
EZH2 crosstalk with RNA methylation promotes prostate cancer progression through modulation of m6A autoregulation pathway
Yi Y, Fry J, Yum C et al. · The Journal of clinical investigation 2026 · PMID 41252201 · doi:10.1172/JCI195840
This dataset
Open GSE296858 in finder → Find more human RNA-seq 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 GSE296858_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 PRJNA1261828 and SRA study SRP584602. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41252201) ↗
Study design
11 conditions, mostly in triplicate
C4-2, siCTRL, ×3 C4-2, siYTHDF1, ×3 C4-2, DMSO, ×3 C4-2, EPZ6438, ×3 C4-2, siCTRL, RiboLace, ×3 C4-2, siYTHDF1, RiboLace, ×3 C4-2, DMSO, RiboLace, ×3 C4-2, EPZ6438, RiboLace, ×3 +3 more

Supports a between-group comparison across 30 samples.

How we read this: 11 replicated groups read from 30 sample titles; they account for 30 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 Prostate cancer datasets

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