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Bulk RNA sequencing of prostate cancer (PCa) primary tumors and metastases: Epworth Clinical Cohort

GSE339157 Homo sapiens (human) Single-cell RNA-seq 48 samples Submitted 2026/07/31 Platform GPL21290
At a glance

Single-cell RNA-seq · human · 48 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Topic
Prostate cancerThis series is part of our curated briefing on it.
Samples
48 samples: 6 conditions, mostly with about 4 replicates eachGroups 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)
Prostate cancer (PCa) frequently metastasizes to bone, marking incurable disease. This progression is driven by an immunologically cold bone tumor microenvironment that fosters resistance to therapy. To define the mechanisms underlying this uniquely immunosuppressive niche, we applied spatial single cell analyses across primary tumors and metastatic sites.
Read the full summary ↓
Bone metastases showed marked suppression of tumor-intrinsic type I interferon (IFN-I) signaling and loss of antigen presentation, features that strongly predicted reduced bone metastasis-free survival. Tumor-intrinsic IFN-I expression correlated with memory T cell infiltration, whereas the bone myeloid compartment was enriched for protumor macrophages and showed reduced dendritic cell (DC) activation and antigen presentation. Digital spatial profiling of matched tumors revealed a broad loss of IFN-I-regulated immunostimulatory and checkpoint molecules. Notably, B7-H3, a putative negative regulator of IFN-I, was highly expressed in bone metastases and inversely associated with antigen presentation. These findings define bone-specific mechanisms of immune resistance and highlight therapeutic vulnerabilities that could inform precision strategies for PCa.
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 GSE339157_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1497887 and SRA study SRP719553. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly with about 4 replicates each
Primary PCa, patient with bone-metastatic dis… ×14 Primary PCa, patient with no bone metastasis,… ×11 PCa bone metastases, donor RC ×11 Primary PCa, patient with bone-metastatic dis… ×4 PCa lymph node metastases, donor RC ×4 Primary PCa, patient with no bone metastasis,… ×4

Supports a between-group comparison across 48 samples.

How we read this: 6 replicated groups read from 48 sample titles; they account for 48 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

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

More Prostate cancer datasets

Search all human RNA-seq 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.