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A Ligandable PNT-Domain Establishes ERG as a Directly Targetable Oncogenic Driver in Prostate Cancer

GSE331048 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2026/05/15 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 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.
Summary (written by the submitters)
The TMPRSS2:ERG gene fusion, present in approximately 50% of prostate cancers in patients of European ancestry, drives oncogenesis through aberrant overexpression of the ERG transcription factor. Despite its role as a truncal oncogenic driver, ERG has long been considered undruggable due to the absence of enzymatic activity and an apparent lack of ligandable pockets.
Read the full summary ↓
Here, we demonstrate continued dependency on ERG in metastatic prostate cancer and identify a druggable pocket within its structured N-terminal Pointed (PNT) domain. Using an inducible shRNA system in TMPRSS2:ERG-positive VCaP cells, we show that ERG depletion causes profound growth inhibition in vitro and in vivo. To therapeutically exploit this vulnerability, we conducted a domain-focused differential scanning fluorimetry screen targeting the ERG PNT domain, followed by structure–activity relationship optimization. This approach yielded PBITE-1 (PNT-Binding Inhibitor of the Transcription factor ERG), a lead small molecule that selectively binds the ERG PNT domain in biochemical assays. NMR chemical-shift perturbation mapping and molecular docking revealed that PBITE-1 engages a discrete, solvent-exposed surface comprising two α-helices and an adjacent flexible loop, thereby defining a coherent ligand-binding pocket within the PNT domain. In cellular models, PBITE-1 directly engaged ERG, selectively inhibited proliferation and invasion, and induced apoptosis in ERG-driven prostate and hematologic malignancies. PBITE-1 also potently suppressed growth of ERG-positive prostate organoids derived from genetically engineered mouse models, as well as patient-derived human prostate cancer organoids. Furthermore, PBITE-1 treatment significantly induced tumor cell apoptosis in vivo in VCaP xenograft models. These findings establish the ERG PNT domain as ligandable and provide the first preclinical evidence that ERG is directly targetable by small molecules, enabling future development of ERG-directed inhibitors and targeted protein degraders.
This dataset
Open GSE331048 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 GSE331048_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 PRJNA1466606 and SRA study SRP700758. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
VCaP.shERG.DMSO ×3 VCaP.shERG.Dox.1ug.mL ×3 VCaP.DMSO ×3 VCaP.4hr.PBITE.1.50uM ×3 VCaP.8hr.PBITE.1.50uM ×3 VCaP.12hr.PBITE.1.50uM ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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