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Modeling arrhythmogenic cardiomyopathy fattyfibro pathology through the use of PKP2-deficient human iPSC-derived epicardial cells

GSE301005 Homo sapiens (human) RNA-seq (gene expression) 17 samples Submitted 2025/09/05 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 17 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
17 samples: 17 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
Modelling arrhythmogenic cardiomyopathy fattyfibro pathology with PKP2-deficient epicardial cells derived from human iPSCsCommunications biology · 2025
Summary (written by the submitters)
Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiac disease characterized by progressive fatty-fibro replacement of the ventricular myocardium leading to arrhythmias and an increased risk of sudden cardiac death. To date, the cell types and signaling mechanisms involved in fatty-fibro infiltration of the myocardium have yet to be fully resolved.
Read the full summary ↓
However, given that fatty-fibro replacement is initiated within the subepicardial layer, epicardial cells are predicted to contribute to the development of this pathology. To investigate the epicardial contributions to the development of ACM, we generated human induced pluripotent stem cell (hiPSC) lines from ACM patients harboring either a PKP2 1849C>T or a PKP2 2013delC mutation alongside CRISPR/Cas9 gene-edited isogenic control lines and a PKP2 knockout line. Epicardial cells derived from patient and knockout conditions displayed enhanced epithelial-to-mesenchymal transition characteristics, dysregulated Wnt and interferon signaling, increased lipid accumulation, and an enhanced fibrotic phenotype when converted to epicardial-derived fibroblasts. Transcriptomic analysis revealed upregulation of insulin growth factor 2 (IGF2) in ACM hiPSC-EPCs as well as in human ACM heart tissue. Subsequent treatment with exogenous IGF2 enhanced expression of the adipogenic transcription factors CEBPA and PPARG in hiPSC-EPCs, suggesting insulin growth factor signaling contributes to ACM fatty-fibro remodeling.
Published in
Modelling arrhythmogenic cardiomyopathy fattyfibro pathology with PKP2-deficient epicardial cells derived from human iPSCs
Falana SL, Kazmouz SG, Iwanski JB et al. · Communications biology 2025 · PMID 41145823 · doi:10.1038/s42003-025-08921-z
This dataset
Open GSE301005 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 GSE301005_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 PRJNA1283061 and SRA study SRP595556. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41145823) ↗
Study design
17 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 17 sample titles: 17 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

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