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Epicardial-derived cells secrete extracellular vesicles that modulate gene expression in the cardiac response to ischemia-reperfusion injury [BW mRNAseq]

GSE300518 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/06/03 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 12 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
Homo sapiens (human)
Samples
12 samples: 3 × Epicardial Biowire tissue, vs 3 × Biowire tissue without epicardium, vs 3 × Epicardial Biowire tissue with IRI, vs 3 × Epicardial Biowire tissue with IRI and epicardial EVs,Groups 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
Epicardial extracellular vesicles modulate gene expression following ischemia-reperfusion injury in heart-on-a-chipMaterials today. Bio · 2026
Summary (written by the submitters)
The epicardium is an essential regulator of cardiac development, homeostasis, and injury. While advanced 3D human cardiac tissue models now facilitate physiologically relevant exploration of epicardial–myocardial interactions, the composition and impacts of epicardial cell-secreted extracellular vesicles (EVs) in regulating cardiac physiology remain incompletely understood.
Read the full summary ↓
Here we harnessed an “Epicardial Biowire” platform integrating human epicardial cells with functional myocardium, applying transcriptomics to reveal enriched vesicle transport in engineered tissues containing epicardial cells. Profiling epicardial-EVs identified key miRNAs in their cargo and indicated considerable conservation of miRNA cargo through stimulated epithelial‐to‐mesenchymal transition. Supplementation of epicardial-EVs to engineered tissues undergoing simulated ischemia–reperfusion injury (IRI) influenced gene expression associated with reduction of extracellular matrix remodeling, fibroblast modulation, and suppression of cell-ECM interactions. Correlation of EV‐miRNAs with mRNA targets highlighted implications of miR‐30d‐5p, miR‐9‐5p, miR‐16‐5p, and the let‐7 family, supporting a potential role for epicardial-EVs and their miRNA cargo in moderating deleterious fibrotic activation and matrix remodelling during myocardial injury in vitro. Collectively, these findings expand our understanding of epicardial-EV composition and function, highlighting epicardial signalling as a promising avenue to direct cardiac repair and inspiring the design of future EV‐based therapeutics.
Published in
Epicardial extracellular vesicles modulate gene expression following ischemia-reperfusion injury in heart-on-a-chip
Wagner KT, Bannerman D, Wu Q et al. · Materials today. Bio 2026 · PMID 42220610 · doi:10.1016/j.mtbio.2026.103236
This dataset
Open GSE300518 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 GSE300518_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 PRJNA1281102 and SRA study SRP594048. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42220610) ↗
Study design
3 × Epicardial Biowire tissue, vs 3 × Biowire tissue without epicardium, vs 3 × Epicardial Biowire tissue with IRI, vs 3 × Epicardial Biowire tissue with IRI and epicardial EVs,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
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