GEO series

RNA next-generation sequencing of cardiac fibroblasts isolated from young and old mice 7 days post-MI

GSE279927 Mus musculus (mouse) RNA-seq (gene expression) 25 samples Submitted 2025/10/21 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 25 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: 25 samples: 6 conditions, mostly with about 5 replicates eachGroups 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: From cancer to heart fibrosis - GLIPR1 highlights a subset of myofibroblasts responsive to mesenchymal stem cell therapy after myocardial infarctionBiomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2025

Summary (written by the submitters)

Despite recent advances in pre-clinical research on cardiac remodeling following myocardial infarction (MI), the precise molecular pathways remain poorly understood, and effective therapies for heart failure are still delayed in development. The use of young animal models fails to mirror the clinical scenario of aged human patients, as aging is associated to less well-defined cellular identities that can alter the overall picture of cardiac repair.

Read the full summary ↓

Here, we explore the active role of cardiac fibroblasts in post-MI ventricular remodeling, aiming to identify fibroblast-specific pathways through the lens of aging that enhance translational relevance. Cardiac fibroblasts were isolated from mice with MI through 5 day-culture of total interstitial population of cardiac cells under fibroblast-favoring conditions. The expression profiling of these cells was conducted as the initial approach to depict fibroblasts-specific changes that are common to young and old animals. For a translational perspective of the study, a group of young animals that endured MSC therapy after MI surgery was also included, to help identify the molecular changes that are amenable for therapeutic modulation. This analysis revealed GLIPR1 as being activated in cardiac fibroblasts within the infarct zone during the maturation phase post-MI, thus suggesting a role in the fibrotic process. Further investigations indicated that the inflammatory environment post-MI induced the upregulation of GLIPR1 in the myofibroblast subpopulation of infarcted cardiac fibroblasts, which promoted matrix reorganization by increase in TIMP3 expression. Our study shows a key role of GLIPR1 in modulating the matrix remodeling during cardiac repair post-MI. The data presented here provide a fundamental cellular and molecular knowledge that paves the way for further exploration of GLIPR1 as a potential therapeutic target to reduce cardiac fibrosis.

Published in

From cancer to heart fibrosis - GLIPR1 highlights a subset of myofibroblasts responsive to mesenchymal stem cell therapy after myocardial infarction

Marinescu-Colan CI, Nastase-Rusu EG, Neculachi CA et al. · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 2025 · PMID 40306172 · doi:10.1016/j.biopha.2025.118087

This dataset

Open GSE279927 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 GSE279927_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 PRJNA1175563 and SRA study SRP539824. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40306172) ↗

Study design

6 conditions, mostly with about 5 replicates each

cFb_Young ×5 cFb_Young_sham-MI ×5 cFb_Young_MI ×5 cFb_Young_MI+MSC ×5 cFb_Old_MI ×3 cFb_Old_sham-MI ×2

Supports a between-group comparison across 25 samples.

How we read this: 6 replicated groups read from 25 sample titles; they account for 25 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

GSM8583503 cFb_Young_rep1 cFb_Young
GSM8583504 cFb_Young_rep2 cFb_Young
GSM8583505 cFb_Young_rep3 cFb_Young
GSM8583506 cFb_Young_rep4 cFb_Young
GSM8583507 cFb_Young_rep5 cFb_Young
GSM8583508 cFb_Young_sham-MI_rep1 cFb_Young_sham-MI
GSM8583509 cFb_Young_sham-MI_rep2 cFb_Young_sham-MI
GSM8583510 cFb_Young_sham-MI_rep3 cFb_Young_sham-MI
GSM8583511 cFb_Young_sham-MI_rep4 cFb_Young_sham-MI
GSM8583512 cFb_Young_sham-MI_rep5 cFb_Young_sham-MI
GSM8583513 cFb_Young_MI_rep1 cFb_Young_MI
GSM8583514 cFb_Young_MI_rep2 cFb_Young_MI
GSM8583515 cFb_Young_MI_rep3 cFb_Young_MI
GSM8583516 cFb_Young_MI_rep4 cFb_Young_MI
GSM8583517 cFb_Young_MI_rep5 cFb_Young_MI
GSM8583518 cFb_Young_MI+MSC_rep1 cFb_Young_MI+MSC
GSM8583519 cFb_Young_MI+MSC_rep2 cFb_Young_MI+MSC
GSM8583520 cFb_Young_MI+MSC_rep3 cFb_Young_MI+MSC
GSM8583521 cFb_Young_MI+MSC_rep4 cFb_Young_MI+MSC
GSM8583522 cFb_Young_MI+MSC_rep5 cFb_Young_MI+MSC
GSM8583523 cFb_Old_sham-MI_rep1 cFb_Old_sham-MI
GSM8583524 cFb_Old_sham-MI_rep2 cFb_Old_sham-MI
GSM8583525 cFb_Old_MI_rep1 cFb_Old_MI
GSM8583526 cFb_Old_MI_rep2 cFb_Old_MI
GSM8583527 cFb_Old_MI_rep3 cFb_Old_MI

Datasets on a similar topic

GSE319401 Exercise Mitigates Cardiac Dysfunction Post-MI in Ovariectomized Mice via miR-21/Sox7-Mediated Suppression of Cardiac Fibroblast Activation 24 samples shares cardiac, post-mi
GSE261643 Hippo deficient cardiac fibroblasts promote atrial remodeling 24 samples shares fibroblasts, cardiac
GSE267256 Bulk RNA-seq analysis reveals the crucial role of Collagen triplex helix repeat containing-1 (Cthrc1) cardiac fibroblasts for ventricular remodeling after myocardial infarction 17 samples shares fibroblasts, cardiac
GSE261783 Identification of epigenetic regulators of fibrotic transformation in cardiac fibroblasts through bulk and single-cell CRISPR screens [scRNA-seq] 10 samples shares fibroblasts, cardiac
GSE261740 Identification of epigenetic regulators of fibrotic transformation in cardiac fibroblasts through bulk and single-cell CRISPR screens (ATAC-Seq) 35 samples shares fibroblasts, cardiac
GSE22292 Gene expression in mouse neonatal cardiomyocytes, cardiac fibroblasts, reprogramming failed GFP- cells, and GFP+ iCMs 18 samples shares fibroblasts, cardiac
GSE229916 Pericytes and perivascular fibroblasts contribute to central nervous system fibrosis in a region dependent manner 832 samples shares fibroblasts
GSE309251 Western diet-induced MASH in PWK/PhJ mice identifies disruptions in amino acid and sphingolipid metabolism contributing to cardiac dysfunction 347 samples shares cardiac

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.