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KMT2D promotes castration-resistant prostate cancer progerssion by reactivating AR via FOXA1 [RNA-Seq]

GSE285692 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2025/02/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 16 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)
Topic
Prostate cancerThis series is part of our curated briefing on it.
Samples
16 samples: 8 conditions, mostly in duplicateGroups 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 GSE285692 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 GSE285692_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 PRJNA1205655 and SRA study SRP554884. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in duplicate
LNCaP_DHT_siNC ×2 LNCaP_DHT_siKMT2D ×2 LNCaP_CSS_siNC ×2 LNCaP_CSS_siKMT2D ×2 C4_DHT_siNC ×2 C4_DHT_siKMT2D ×2 C4_CSS_siNC ×2 C4_CSS_siKMT2D ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 16 sample titles; they account for 16 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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