GEO series

Macrophages expressing Macrophage Receptor with Collagen Structure Attenuate Liver Fibrosis Through a Tissue Restoration Phenotype [macrophage_liverFibrosis_scRNA-seq]

GSE291710 Mus musculus (mouse) Single-cell RNA-seq 10 samples Submitted 2025/05/30 Platform GPL17021Platform GPL34328

At a glance

Single-cell RNA-seq · mouse · 10 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 10 samples: 10 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: Macrophages expressing macrophage receptor with collagen structure attenuate liver fibrosis through a tissue restoration phenotypeJCI insight · 2026

Summary (written by the submitters)

Liver macrophages are central in maintaining hepatic homeostasis and mediating immune responses during liver injury, including fibrosis. Macrophages may have proinflammatory or anti-inflammatory properties, but which properties influence fibrosis remains unclear. To explore the role of macrophages in liver fibrosis, we performed single-cell RNA sequencing in a mouse model of liver injury and found that macrophage diversity was increased.

Read the full summary ↓

A subset of macrophages expressing high levels of Marco gene was the most significantly upregulated after injury but was spatially segregated to non-fibrotic areas. The macrophage receptor with collagenous structure (MARCO) protein is a scavenger receptor expressed by specific subsets of macrophages, and its role in liver fibrosis is unclear. In vitro induction of Marco in bone marrow-derived macrophages decreased proinflammatory gene expression, increased anti-inflammatory and antifibrotic gene expression, and enhanced phagocytosis, indicating a restorative phenotype. Adoptive transfer of MARCO-positive macrophages in a mouse model of liver fibrosis reduced the expression of extracellular matrix (ECM)-associated genes in hepatic stellate cells (HSCs) and reduced collagen deposition, which did not occur with the transfer of MARCO-negative macrophages. Therefore, MARCO-positive macrophages have a tissue restorative role in the liver and attenuate fibrogenesis through interaction with HSCs, thereby providing a novel therapeutic pathway for liver fibrosis.

Published in

Macrophages expressing macrophage receptor with collagen structure attenuate liver fibrosis through a tissue restoration phenotype

Jerez S, Cooper SA, Yaqoob U et al. · JCI insight 2026 · PMID 41869728 · doi:10.1172/jci.insight.193172

This dataset

Open GSE291710 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 GSE291710_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 PRJNA1234715 and SRA study SRP569721. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41869728) ↗

Study design

10 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 10 sample titles: 10 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

GSM8840605 scRNAseq CCl4, liver cells
GSM8840606 scRNAseq Healthy, liver cells
GSM9530776 Intrahepatic leukocytes, OO-1, scRNAseq
GSM9530777 Intrahepatic leukocytes, OO-2, scRNAseq
GSM9530778 Intrahepatic leukocytes, OO-3, scRNAseq
GSM9530779 Intrahepatic leukocytes, OO-4, scRNAseq
GSM9530780 Intrahepatic leukocytes, CCl4-1, scRNAseq
GSM9530781 Intrahepatic leukocytes, CCl4-2, scRNAseq
GSM9530782 Intrahepatic leukocytes, CCl4-3, scRNAseq
GSM9530783 Intrahepatic leukocytes, CCl4-4, scRNAseq

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