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S100A8/A9 Priming Alters Translational Related Proteins and Upregulates Pro‑Regenerative Factors in Mesenchymal Stromal Cells

GSE301531 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2026/06/09 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 18 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
S100A8/A9 Priming Alters Translational Related Proteins and Upregulates Pro-Regenerative Factors in Mesenchymal Stromal CellsThe Journal of investigative dermatology · 2026
Summary (written by the submitters)
Background: Non-healing wounds cause profound suffering of patients and a huge economic burden on society. Current research attempts to refine MSC-based therapies for this type of difficult-to-treat wounds. We earlier reported that injection of S100A8/A9 primed MSCs into the wound edge in mice accelerates wound healing compared to non-primed MSCs.
Read the full summary ↓
We here describe a protective response of differentially expressed isoforms of genes, proteins and their potential role in the reported beneficial effects of S100A8/A9 primed MSCs on tissue repair. Methods: Adipose‐derived MSCs were characterized for specific cell surface markers using flow cytometry and assessed for their ability to differentiate into different lineages. To further investigate the mechanisms underlying the beneficial effects of S100A8/A9 primed MSCs, we employed a multi‐omics strategy that combined transcriptome, secretome, and proteome analyses. Global translational activity and a potential metabolic shift were examined using fluorescent labeling alongside seahorse‐based metabolic assays. Additionally, in silico analysis was conducted to assess the presence of the DRACH motif in mRNAs encoding these proteins, thereby evaluating their potential for cap-independent, m6A‐mediated translation. Results: Enhanced protein translation was observed in MSCs primed with S100A8/A9. Priming significantly increased the levels of the cap-independent translation initiation factor EIF3I, while reducing the cap-dependent factor EIF4A1, suggesting a shift in the mode of translation. In addition, the secretome of S100A8/A9-primed MSCs exhibited upregulation of cystatin C, a tissue protective protease inhibitor, and angiopoietin-1, an inducer of angiogenesis. Furthermore, various collagens, which serve as MSC niche-protecting proteins, were expressed at higher levels in the S100A8/A9 primed MSCs. Notably, the mRNAs corresponding to these factors contained DRACH motifs. Conclusion: We uncovered a protective response in S100A8/A9 primed MSCs that alters translation processes and increases the secretion of protective proteins, whose functions warrant further exploration. In the long term, S100A8/A9 priming holds promise for developing more effective MSC‐based therapies to enhance wound healing.
Published in
S100A8/A9 Priming Alters Translational Related Proteins and Upregulates Pro-Regenerative Factors in Mesenchymal Stromal Cells
Wang Y, Koroma AK, Singh K et al. · The Journal of investigative dermatology 2026 · PMID 42309386 · doi:10.1016/j.jid.2026.06.1271
This dataset
Open GSE301531 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 GSE301531_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 PRJNA1285393 and SRA study SRP597864. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42309386) ↗
Study design
18 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 18 sample titles: 18 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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