← BioTransfer GEO Dataset Finder
GEO series

Extracellular vesicles from antler blastema progenitor cells reverse bone loss and improve aging-related phenotypes in mice and macaques

GSE289038 Mus musculus (mouse) RNA-seq (gene expression) 111 samples Submitted 2025/05/13 Platform GPL25947Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 111 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
Mus musculus (mouse)
Samples
111 samples: 87 distinct titles, 12 of them repeatedGroups 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
Extracellular vesicles from antler blastema progenitor cells reverse bone loss and mitigate aging-related phenotypes in mice and macaquesNature aging · 2025
Summary (written by the submitters)
Antler blastema progenitor cell (ABPC) is a novel type of skeletal mesenchymal stem cell with strong stemness and renewal ability. Here, we discovered that ABPC-derived extracellular vesicles (EVsABPCs) can strongly rejuvenate aging tissues in aged mice and rhesus macaques (Macaca mulattas). We identified a variety of rejuvenating molecules in EVsABPCs that differed from EVs of mouse bone marrow stromal stem cells (EVsBMSCs).
Read the full summary ↓
EVsABPCs exhibited a robust in vitro ability to rejuvenate senescence BMSCs of aged mice and shift their molecular signature into a youthful state. In vivo, EVsABPCs increased bone mineral density in the femur by 2.4-fold in mice, and 1.53-fold in rhesus macaques. Besides, intravenous EVsABPCs significantly outperformed mouse fetal-EVsBMSCs in improving physical performance, reducing systemic inflammation, and rejuvenating major tissues of elderly mice, with no observed immunological side effects. Furthermore, EVsABPCs showed similar rejuvenating effects in old rhesus macaques as in elderly mice. Particularly, EVsABPCs resulted in remarkable improvements in brain structure and behaviors of elderly rhesus macaques, providing the first batch of evidence of EVs’ beneficial effects on aging brains in primates. These findings suggest that the ABPC is a novel and practical source of EVs containing a wealth of systemic rejuvenating factors and has considerable translational value for anti-aging interventions, particularly the rejuvenation of aging bones.
Published in
Extracellular vesicles from antler blastema progenitor cells reverse bone loss and mitigate aging-related phenotypes in mice and macaques
Hao Y, Yu B, Qin M et al. · Nature aging 2025 · PMID 40660003 · doi:10.1038/s43587-025-00918-x
This dataset
Open GSE289038 in finder → Find more 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 GSE289038_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 PRJNA1220683 and SRA study SRP562243. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40660003) ↗
Study design
87 distinct titles, 12 of them repeated
Young ×3 ABPC_EVs ×3 FBMC_EVs ×3 ABMC_EVs ×3 Old ×3 ABMSC-EV ×3 ABPC-EV ×3 Vehicle ×3 +4 more

How we read this: Read from 111 sample titles: 87 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

+ 71 more — browse all 111 samples with per-sample file links →

Popular RNA-seq datasets

No close match found for this topic, so these are simply the most-viewed datasets of the same kind.

Search all 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.