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Single cell profiling of bone metastasis ecosystems from multiple cancer types reveals convergent and divergent mechanisms of bone colonization

GSE266330 Homo sapiens (human) Single-cell RNA-seq 63 samples Submitted 2025/05/27 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 63 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
63 samples: 16 conditions, mostly in duplicateGroups 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
Single-cell profiling of bone metastasis ecosystems from multiple cancer types reveals convergent and divergent mechanisms of bone colonizationCell genomics · 2025
Summary (written by the submitters)
Bone represents congenial soil for metastatic seeds and is frequently affected by metastasis of multiple cancer types. The histological and molecular characteristics of bone metastases (BMs) are diverse but poorly understood. Herein, we performed single-cell RNA-seq on 34 BMs from 6 cancer types and identified 3 ecosystem archetypes characterized by enrichment of macrophages/osteoclasts (Mφ-OC), regulatory/exhausted T cells (Treg-Tex), and monocytes (Mono), respectively.
Read the full summary ↓
Breast cancer BMs are mostly the Mφ-OC archetype driven by the osteolytic vicious cycle, whereas kidney cancers BMs mainly belong to the Treg-Tex archetype that lacks osteoclasts. Lung cancers BMs evenly distributed across all archetypes. Further analyses revealed parallel mechanisms of immunosuppression and bone remodeling. Elevated estrogen signaling distinguishes macrophages in the Mφ-OC subtype, which was investigated in a companion study. Together, we elucidated that divergent mechanisms toward bone colonization and that BMs of different origins can adopt the same mechanism through convergent evolution or adaptation.
Published in
Single-cell profiling of bone metastasis ecosystems from multiple cancer types reveals convergent and divergent mechanisms of bone colonization
Liu F, Ding Y, Xu Z et al. · Cell genomics 2025 · PMID 40412393 · doi:10.1016/j.xgen.2025.100888
This dataset
Open GSE266330 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 GSE266330_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 PRJNA1106749 and SRA study SRP505107. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40412393) ↗
Study design
16 conditions, mostly in duplicate
BC_08 ×2 CC_01 ×2 ctrl_01 ×2 ctrl_02 ×2 ctrl_03 ×2 ctrl_04 ×2 ctrl_05 ×2 CC_02 ×2 +39 more

Supports a between-group comparison across 32 samples.

How we read this: 16 replicated groups read from 63 sample titles; they account for 32 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

+ 23 more — browse all 63 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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