← BioTransfer GEO Dataset Finder
GEO series

Macrophage Cluster of Differentiation 163 promotes post-infarction cardiac repair and preserves left ventricular function via osteopontin

GSE306718 Mus musculus (mouse) Single-cell RNA-seq 37 samples Submitted 2026/04/18 Platform GPL34290Platform GPL28330
At a glance

Single-cell RNA-seq · mouse · 37 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
37 samples: 37 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
Macrophage Cluster of Differentiation 163 promotes post-infarction cardiac repair and preserves left ventricular function via osteopontinClinical and translational medicine · 2026
Summary (written by the submitters)
Background: Cardiac macrophages have been implicated in myocardial repair following myocardial infarction (MI), yet their therapeutic potential in ischemic cardiomyopathy (ICM) remains limited by an incomplete understanding of their molecular regulation. CD163 is highly expressed in these macrophages, yet its functional role in regulating post-MI cardiac repair remains unknown.
Read the full summary ↓
Methods: A cross-sectional clinical study was conducted to assess the association between circulating soluble CD163 concentration and heart failure due to ICM. To investigate the functional contribution of CD163 in ICM, Wild-type (WT) and Cd163/ mice were subjected to permanent ligation of the left anterior descending coronary artery. Single-cell RNA sequencing was employed to analyze transcriptional changes in cardiac immune cells. Recombinant osteopontin (OPN) and CD163 were administered to assess their therapeutic effect in Cd163/ mice. Results: Circulating soluble CD163 levels were markedly elevated in patients with ICM-induced heart failure compared with individuals without heart failure (median difference 34.5 ng/mL, IQR 13.6–54.6 ng/mL, P = 0.002) and showed a positive correlation with the extent of systolic dysfunction and left ventricular dilation. Cd163/ mice displayed aggravated left ventricular systolic dysfunction, reduced ejection fraction and fractional shortening, impaired myocardial strain, and reduced relative wall thickness post-MI. Recombinant CD163 protein could reverse systolic dysfunction and left ventricular dilation in Cd163/ mice after MI. CD163 was predominantly expressed in CCR2⁻ resident cardiac macrophages, and CD163 deficiency altered transcriptional programs of macrophages without affecting their polarization status, with enrichment in cytokine signaling and extracellular matrix-related pathways. Spp1 (OPN) expression was significantly downregulated in Cd163/ hearts under both sham and MI conditions. Administration of recombinant OPN improved systolic function, reduced ventricular dilation, decreased fibrotic scar size, and restored the elastin-to-collagen ratio in Cd163/ mice. Conclusions: In cardiac macrophages, CD163 contributes to post-myocardial infarction repair by upregulating OPN expression, which in turn helps maintain systolic function.
Published in
Macrophage Cluster of Differentiation 163 promotes post-infarction cardiac repair and preserves left ventricular function via osteopontin
Chen J, Chen L, Huang W et al. · Clinical and translational medicine 2026 · PMID 42026811 · doi:10.1002/ctm2.70662
This dataset
Open GSE306718 in finder → Find more mouse 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 GSE306718_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 PRJNA1311962 and SRA study SRP613901. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42026811) ↗
Study design
37 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 37 sample titles: 37 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
Datasets on a similar topic

Search all mouse 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.