GEO series

Transcriptional network analysis of PTEN protein-deficient prostate tumors reveals robust stromal reprogramming and signs of senescent paracrine communication

GSE288484 Homo sapiens (human) RNA-seq (gene expression) 197 samples Submitted 2025/11/05 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 197 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: 197 samples: 197 × Localized PCa patientGroups 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: Transcriptional network analysis of PTEN-protein-deficient prostate tumors reveals robust stromal reprogramming and signs of senescent paracrine communicationMolecular oncology · 2026

Summary (written by the submitters)

Among the extensive genomic alterations in prostate cancer, PTEN deletion stands out as one of the most consistently observed events. PTEN loss in prostate tumors is primarily associated with cancer cell proliferation and survival through the activation of the PI3K-AKT-mTOR signaling pathway. However, the use as a robust biomarker in clinical practice is hampered by its complex epigenetic, transcriptional, and post-translational regulation.

Read the full summary ↓

In situ protein assessment by immunohistochemistry (IHC) captures PTEN protein status, but it does not report on associated tumor microenvironment remodeling. Here, we undertook an approach that combined PTEN immunoreactivity analysis with high-throughput transcriptional analysis to gain insights into the downstream functional effects of PTEN protein loss in primary tumors. Our extensive bioinformatic analyses highlighted stromal remodeling as a prominent cancer cell-extrinsic process associated with PTEN loss. By extending our transcriptomic computational strategy to Pten-loss driven murine prostate cancer, we validated the causal role of Pten in the stromal reaction observed in clinical specimens. Mechanistically, we provide experimental evidence for the activation of a paracrine program that encompasses enhanced TGF-β signaling and that is compatible with the secretome of PTEN-deficient senescent cancer cells. Finally, our findings enable the sub-stratification of tumors with PTEN loss based on their senescence-associated stroma remodeling program to distinguish indolent from aggressive cases. Our study provides relevant biological context to the cellular and molecular alterations unleashed upon PTEN protein loss in prostate cancer.

Published in

Transcriptional network analysis of PTEN-protein-deficient prostate tumors reveals robust stromal reprogramming and signs of senescent paracrine communication

Rondon-Lorefice I, Lopez JI, Ugalde-Olano A et al. · Molecular oncology 2026 · PMID 41247227 · doi:10.1002/1878-0261.70164

This dataset

Open GSE288484 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 GSE288484_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 PRJNA1217849 and SRA study SRP560924. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41247227) ↗

Study design

197 × Localized PCa patient

Supports a between-group comparison across 197 samples.

How we read this: 1 replicated groups read from 197 sample titles; they account for 197 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

GSM8768687 Localized PCa patient 1 Localized PCa patient
GSM8768688 Localized PCa patient 2 Localized PCa patient
GSM8768689 Localized PCa patient 3 Localized PCa patient
GSM8768690 Localized PCa patient 4 Localized PCa patient
GSM8768691 Localized PCa patient 5 Localized PCa patient
GSM8768692 Localized PCa patient 6 Localized PCa patient
GSM8768693 Localized PCa patient 7 Localized PCa patient
GSM8768694 Localized PCa patient 8 Localized PCa patient
GSM8768695 Localized PCa patient 9 Localized PCa patient
GSM8768696 Localized PCa patient 10 Localized PCa patient
GSM8768697 Localized PCa patient 11 Localized PCa patient
GSM8768698 Localized PCa patient 12 Localized PCa patient
GSM8768699 Localized PCa patient 13 Localized PCa patient
GSM8768700 Localized PCa patient 14 Localized PCa patient
GSM8768701 Localized PCa patient 15 Localized PCa patient
GSM8768702 Localized PCa patient 16 Localized PCa patient
GSM8768703 Localized PCa patient 17 Localized PCa patient
GSM8768704 Localized PCa patient 18 Localized PCa patient
GSM8768705 Localized PCa patient 19 Localized PCa patient
GSM8768706 Localized PCa patient 20 Localized PCa patient
GSM8768707 Localized PCa patient 21 Localized PCa patient
GSM8768708 Localized PCa patient 22 Localized PCa patient
GSM8768709 Localized PCa patient 23 Localized PCa patient
GSM8768710 Localized PCa patient 24 Localized PCa patient
GSM8768711 Localized PCa patient 25 Localized PCa patient
GSM8768712 Localized PCa patient 26 Localized PCa patient
GSM8768713 Localized PCa patient 27 Localized PCa patient
GSM8768714 Localized PCa patient 28 Localized PCa patient
GSM8768715 Localized PCa patient 29 Localized PCa patient
GSM8768716 Localized PCa patient 30 Localized PCa patient
GSM8768717 Localized PCa patient 31 Localized PCa patient
GSM8768718 Localized PCa patient 32 Localized PCa patient
GSM8768719 Localized PCa patient 33 Localized PCa patient
GSM8768720 Localized PCa patient 34 Localized PCa patient
GSM8768721 Localized PCa patient 35 Localized PCa patient
GSM8768722 Localized PCa patient 36 Localized PCa patient
GSM8768723 Localized PCa patient 37 Localized PCa patient
GSM8768724 Localized PCa patient 38 Localized PCa patient
GSM8768725 Localized PCa patient 39 Localized PCa patient
GSM8768726 Localized PCa patient 40 Localized PCa patient

+ 157 more — browse all 197 samples with per-sample file links →

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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.