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Palmitoylethanolamide (PEA) Regulates Cell Cycle Progression and Promotes an Anti-Inflammatory Transcriptomic Signature in C2C12 Skeletal Muscle Cells

GSE307376 Mus musculus (mouse) RNA-seq (gene expression) 13 samples Submitted 2026/02/25 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 13 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
13 samples: 6 × Control vs 6 × PEAGroups 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
Palmitoylethanolamide (PEA) regulates cell cycle progression and promotes an anti-inflammatory transcriptomic signature in C2C12 skeletal muscle cellsPhysiological reports · 2026
Summary (written by the submitters)
Palmitoylethanolamide (PEA) is an endogenous lipid mediator with recognized immunomodulatory actions, yet its effects in skeletal muscle remain poorly defined. We investigated whether PEA influences myogenesis and profiled the acute transcriptomic response of differentiated C2C12 myotubes. Dose-tolerability assays identified reduced metabolic activity and viability at 100 µM PEA, so 10 µM was used for subsequent experiments.
Read the full summary ↓
Across differentiation, PEA decreased myotube number (90.3 ± 10.6 vs 112.6 ± 10.1 in control) while increasing nuclear fusion index (37.8 ± 5.7% vs 30.7 ± 3.2%); myotube area was unchanged. In myoblasts, 24 h PEA exposure increased the proportion of cells in G0/G1 (48.2 ± 1.2% vs 42.3 ± 1.9%) with a concomitant reduction in S-phase (21.7 ± 1.2% vs 25.5 ± 1.2%), consistent with G1 arrest and reduced proliferative drive. RNA sequencing revealed a distinct transcriptional signature after 24 h PEA treatment, with 1,952 differentially expressed genes (1,028 upregulated; 924 downregulated, q < 0.05). Pathway-level changes encompassed cytokine–receptor interactions, chemokine, JAK–STAT, NF-κB, NOD-like and Toll-like receptor signalling. PEA downregulated NF-κB target/pro-inflammatory cytokine genes (Il1a, Il1b, Il12a, Il33, Tnfrsf19) while upregulating interferon-related and chemokine genes (e.g., Stat2, Oas1b, Gbp7, Cxcl14, Ccl5), indicating an anti-inflammatory/immune-priming profile. Notably, N-acylethanolamine acid amidase (Naaa), a lysosomal PEA hydrolase, was highly expressed and significantly induced, whereas fatty acid amide hydrolase (Faah) was low and unchanged, suggesting a muscle-specific bias toward NAAA-dependent PEA metabolism. Peroxisome proliferator-activated receptor-α (PPARα) was expressed at low levels and unaffected by PEA, indicating that the observed responses occur largely independent of canonical PPARα signalling. Together, these data show that PEA biases skeletal muscle toward a less proliferative but more fused and inflammation-resolving phenotype, accompanied by transcriptional reprogramming of immune pathways and preferential engagement of NAAA. While in vitro concentrations exceed reported plasma levels and mRNA changes may not fully predict protein/function, these findings provide the first comprehensive transcriptomic characterisation of PEA in myotubes and motivate in vivo studies to test whether PEA’s dual actions translate into benefits for muscle regeneration, adaptation, or anti-atrophy interventions.
Published in
Palmitoylethanolamide (PEA) regulates cell cycle progression and promotes an anti-inflammatory transcriptomic signature in C2C12 skeletal muscle cells
Cole PL, Gillham SH, Viggars MR et al. · Physiological reports 2026 · PMID 41693292 · doi:10.14814/phy2.70780
This dataset
Open GSE307376 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 GSE307376_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 PRJNA1320549 and SRA study SRP617741. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41693292) ↗
Study design
6 × Control vs 6 × PEA

Supports a between-group comparison across 12 samples.

How we read this: 2 replicated groups read from 13 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
Datasets on a similar topic

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