← BioTransfer GEO Dataset Finder
GEO series

TRIM33 loss reduces Androgen Receptor transcriptional output and H2BK120 ubiquitination [RNA-seq]

GSE284520 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2025/06/10 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 36 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)
Samples
36 samples: 12 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
TRIM33 loss reduces androgen receptor transcriptional output and H2BK120 ubiquitinationCommunications biology · 2025
Summary (written by the submitters)
The Androgen Receptor (AR) is a ligand-dependent transcription factor that drives prostate cancer development and progression. Although, a detailed effect on AR biology has been described for a number of interacting proteins, many AR coregulators remain to be characterized in relation to their distinct impact on AR function. Here, we describe TRIM33 as a conserved AR-interactor across multiple prostate cancer cell lines.
Read the full summary ↓
We observed that TRIM33 and AR share overall chromatin interaction profiles, in which TRIM33 is involved in downstream responsive transcriptomic output. In contrast to prior reports, we show that TRIM33 does not impact AR protein stability, but instead propose a model in which TRIM33 facilitates maximal AR activity by interfering with H2BK120 ubiquitination levels.
Published in
TRIM33 loss reduces androgen receptor transcriptional output and H2BK120 ubiquitination
Eickhoff N, Janetzko J, Padrão N et al. · Communications biology 2025 · PMID 40646276 · doi:10.1038/s42003-025-08449-2
This dataset
Open GSE284520 in finder → Find more human RNA-seq datasets →
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 GSE284520_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 PRJNA1199467 and SRA study SRP552156. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40646276) ↗
Study design
12 conditions, mostly in triplicate
LNCaP_NT3_DMSO_RNA-seq ×3 LNCaP_NT3_6hR1881_RNA-seq ×3 LNCaP_sgT33-5_DMSO_RNA-seq ×3 LNCaP_sgT33-5_6hR1881_RNA-seq ×3 LNCaP_sgT33-5_MC_C2_DMSO_RNA-seq ×3 LNCaP_sgT33-5_MC_C2_6hR1881_RNA-seq ×3 LNCaP_sgT33-5_MC_F2_DMSO_RNA-seq ×3 LNCaP_sgT33-5_MC_F2_6hR1881_RNA-seq ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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
Datasets on a similar topic

Search all human RNA-seq 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.