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Chemotherapy-induced CAR cell senescence disrupts bone homeostasis to induce bone loss

GSE289491 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2025/10/06 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 2 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
Mus musculus (mouse)
Samples
2 samples
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
Chemotherapy-induced adipo-lineage cell senescence drives bone lossNature communications · 2025
Summary (written by the submitters)
To identify which bone resident cells senesced in response to chemotherapy, we performed scRNA-Seq on bone marrow depleted of CD45+, CD71+, Ter119+, CD31+ cells. Our scRNA-Seq analysis identified seven clusters in both Veh- and Doxo-treated mice: CAR cells, three fibroblast populations, chondrocytes, endothelial cells, and osteoblasts that were identified based on cell specific markers.
Read the full summary ↓
Next, we assessed the expression of the senescence markers (p16 and p21), cell proliferation marker (Mki67) and SASP factors (IL6, Spp1, Cstb, Serpine1, Mmp3). As expected, we found a down regulation of Mki67 and upregulation of senescence markers and SASP factors in the Doxo-treated group compared to Veh. we also checked senescence markers across the clusters and found CAR cells undergo senescence and impact bone homeostasis.
Published in
Chemotherapy-induced adipo-lineage cell senescence drives bone loss
Raut GK, Malachowski T, Melam A et al. · Nature communications 2025 · PMID 41469373 · doi:10.1038/s41467-025-67793-3
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 GSE289491_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 PRJNA1222909 and SRA study SRP563510. Searching any of these in the dataset finder brings you back here.

Samples in this study

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