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KMT2D promotes castration-resistant prostate cancer progerssion by reactivating AR via FOXA1 [ChIP-seq, Cut & Tag]

GSE285790 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 48 samples Submitted 2025/02/01 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 48 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
48 samples: 48 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)
Histone methyltransferase KMT2D is epigenetic modifier mediates histone H3 lysine 4 methylation (H3K4me) with distinct roles across different cancer types. We previous found that KMT2D promotes growth and metastasis in Androgen receptor (AR)-negative prostate cancer (PCa). However, the functions of KMT2D and the relationship with AR in AR-positive prostate cancer remain unclear.
Read the full summary ↓
Here, we showed that inhibition of KMT2D reduced AR-positive PCa cell survival and the sensitivity to dihydrotestosterone, a ligand for AR. RNA-Seq analysis revealed that KMT2D suppression significantly attenuated AR signaling pathway. Through multiple-omics analysis, we revealed that KMT2D recruits pioneering transcription factor Forkhead box A1 (FOXA1) to AR-specific enhancer sites, induces open chromatin conformations, and facilitates AR binding at enhancers to activate downstream gene expression, ultimately leading to AR reactivation. KMT2D knockout by CRISPR/Cas9 reduced CRPC tumor growth and AR signaling pathway activation in vivo. KMT2D-FOXA1-AR axis also mediates ketone metabolic reprogramming by regulating the expression of the key enzyme HMGCS2 to promote PCa progression. Finally, targeting UTX, a member of complex of proteins associated with SET1 (COMPASS) in which KMT2D involved, suppressed PCa cell survival and tumor growth by impairing H3K4me1 modification via KMT2D. These findings demonstrate the oncogenic role of KMT2D in PCa, suggesting that blocking COMPASS to inhibition KMT2D’s function may be a promising strategy to treat PCa.
This dataset
Open GSE285790 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 GSE285790_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 PRJNA1206094 and SRA study SRP555109. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
48 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 48 sample titles: 48 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

+ 8 more — browse all 48 samples with per-sample file links →

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.