GEO series

A single cell transcriptional profile of benign prostatic hyperplasia

GSE290213 Homo sapiens (human) Single-cell RNA-seq 27 samples Submitted 2026/02/25 Platform GPL11154

At a glance

Single-cell RNA-seq · human · 27 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 27 samples: 27 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: A single cell transcriptional profile of benign prostatic hyperplasiaScientific reports · 2026

Summary (written by the submitters)

Benign prostatic hyperplasia (BPH) is characterized by excessive cell proliferation and inflammation and affects most aging men. The development of new therapies for BPH requires a deeper understanding of the underlying pathophysiology and cellular components of BPH. Single-cell RNA-sequencing was performed on prostate tissue from 15 patients undergoing holmium laser enucleation of the prostate for treatment of BPH.

Read the full summary ↓

Clustering and differential expression analysis on aligned single cell RNA-seq data was performed to annotate all cell types. 16,234 cells were analyzed and specific stromal, epithelial, and immune subgroups were found to be strongly associated with inflammation. A rare luminal subgroup was identified and pseudotime analysis indicated this luminal subgroup might give rise to other luminal cells. Using a gene set derived from epithelial stem cells, we found that this luminal subgroup had a significantly higher stem cell signature score than all other epithelial subgroups, suggesting this subgroup is a luminal precursor state. Ligand-receptor interactions between stromal, epithelial, and immune cells were explored with CellPhoneDB. Significant interactions involving MIF, a pro-inflammatory cytokine that promotes epithelial cell growth and inflammatory response in the prostate, were identified between the progenitor-like luminal subgroup and both fibroblasts and macrophages. Our single-cell profiling of BPH provides a roadmap for investigating inflammation-linked cell subgroups and highlights a progenitor-like luminal subgroup interacting with other cell groups via MIF that may contribute to the inflammation and cell proliferation phenotype associated with BPH.

Published in

A single cell transcriptional profile of benign prostatic hyperplasia

Unno R, Akutagawa J, Song H et al. · Scientific reports 2026 · PMID 41832222 · doi:10.1038/s41598-025-02417-w

This dataset

Open GSE290213 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 GSE290213_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: 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 PRJNA1226580 and SRA study SRP565512. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41832222) ↗

Study design

27 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 27 sample titles: 27 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

GSM8808499 HoLEP4 [PA_HoLEP4_A_S13]
GSM8808500 HoLEP4 [PA_HoLEP4_B_S14]
GSM8808501 HoLEP9 [RU_HoLEP9_A_S4]
GSM8808502 HoLEP9 [RU_HoLEP9_B_S5]
GSM8808503 HoLEP10 [RU_HoLEP10_A_S6]
GSM8808504 HoLEP10 [RU_HoLEP10_B_S7]
GSM8808505 HoLEP11 [RU_HoLEP11_AB_S8]
GSM8808506 HoLEP14 [RU_HoLEP14_B_S11]
GSM8808507 HoLEP16 [HoLEP_16A_S99]
GSM8808508 HoLEP16 [HoLEP_16B_S75]
GSM8808509 HoLEP17 [HoLEP_17A_S97]
GSM8808510 HoLEP17 [HoLEP_17B_S76]
GSM8808511 HoLEP18 [HoLEP_18A_18B_S78]
GSM8808512 HoLEP20 [HoLEP_20A_S80]
GSM8808513 HoLEP20 [HoLEP_20B_S81]
GSM8808514 HoLEP21 [HoLEP_21A_S82]
GSM8808515 HoLEP21 [HoLEP_21B_S83]
GSM8808516 HoLEP23 [HoLEP_23A_S84]
GSM8808517 HoLEP23 [HoLEP_23B_S85]
GSM8808518 HoLEP26 [HoLEP_26A_S86]
GSM8808519 HoLEP26 [HoLEP_26B_S87]
GSM8808520 HoLEP28 [HoLEP_28A_S88]
GSM8808521 HoLEP28 [HoLEP_28B_S89]
GSM8808522 HoLEP29 [HoLEP_29_A_S90]
GSM8808523 HoLEP29 [HoLEP_29B_S91]
GSM8808524 HoLEP30 [HoLEP_30A_S100]
GSM8808525 HoLEP30 [HoLEP_30B_S77]

Datasets on a similar topic

GSE295879 Immune cell single-cell RNA sequencing analyses link an age-associated T cell subset to symptomatic benign prostatic hyperplasia 17 samples shares hyperplasia, prostatic, benign
GSE330752 Single-cell RNA-seq analysis of benign prostatic hyperplasia prostate specimens stratified by prostate weight 6 samples shares hyperplasia, prostatic, benign
GSE272950 tRNA m1A modification promotes benign prostatic hyperplasia through translational regulation of the TGF-β pathway [RNA-seq] 6 samples shares hyperplasia, prostatic, benign
GSE269205 Infiltrating lipid-rich macrophage subpopulations identified as a regulator of increasing prostate size in human benign prostatic hyperplasia 12 samples shares hyperplasia, prostatic, benign
GSE119195 Expression data from benign prostatic hyperplasia samples and normal controls 8 samples shares hyperplasia, prostatic, benign
GSE168292 Androgen Deprivation Alters the Transcriptome of Endothelial Cells More Dramatically in Human Prostate Cancer Tissue than in Benign Prostate Tissue 127 samples shares benign
GSE307655 Single cell RNA sequencing of patient-derived origanoids of prostate cancer reveals specific markers for prostatic ductal adenocarcinoma 5 samples shares prostatic
GSE262946 Change in prostate tissue gene expression following finasteride or doxazosin administration in the Medical Therapy for Prostatic Symptoms (MTOPS) Study 216 samples shares prostatic

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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.