← BioTransfer GEO Dataset Finder
GEO series

DBC1 promotes metastatic castration-resistant prostate cancer by enhancing the stability and activity of HSF1 [ChIP-seq]

GSE276302 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 37 samples Submitted 2025/09/02 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 37 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
37 samples: 37 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
HSF1-DBC1 axis drives prostate cancer progression by activating a metastatic transcriptional programExperimental & molecular medicine · 2025
Summary (written by the submitters)
Heat shock factor 1 (HSF1) is a key stress-protective transcription factor that is exploited by various cancers to promote cancer cell survival, therapy resistance, and metastasis. Metastatic castration-resistant prostate cancer (mCRPC) is the leading cause of cancer-related death in men worldwide, and mCRPC progression is associated with increased dependence on HSF1.
Read the full summary ↓
However, mechanisms underlying HSF1 stabilization and persistent activation in metastatic malignancies remain unclear. Here we show that the HSF1-driven transcriptional program and its genome occupancy in mCRPC cells are distinct from those of CRPC cells. HSF1 is highly activated and required for the metastatic potential of mCRPC cells. Moreover, we report DBC1 as a critical regulator of HSF1 stability and activity in mCRPC cells. DBC1 is required for genome-wide chromatin occupancy and target gene expression of HSF1. Mechanistically, DBC1 enhances DYRK2/PKA-mediated HSF1 phosphorylation at S320/S326 and inhibits CHIP-mediated HSF1 ubiquitination, thereby stabilizing and activating HSF1. Importantly, DBC1 loss suppresses growth and metastasis of mCRPC cells, and high DBC1 expression correlates with poor outcomes in patients with mCRPC. Our results highlight the critical role of DBC1 as a key HSF1 coregulator in mCRPC progression and provide insights into regulatory mechanisms of HSF1 stability and activity in advanced and metastatic cancers.
Published in
HSF1-DBC1 axis drives prostate cancer progression by activating a metastatic transcriptional program
Moon SJ, Kim HJ, Lim JE et al. · Experimental & molecular medicine 2025 · PMID 41028522 · doi:10.1038/s12276-025-01545-7
This dataset
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.

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 GSE276302_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1156585 and SRA study SRP530416. Searching any of these in the dataset finder brings you back here.

Study design
37 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 37 sample titles: 37 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 →

Share this dataset

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.