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ITGAV in PBMCs is identified as a hub gene in oxidative stress-related immunosuppression and delayed burn wound healing and is reversed by MnCl2

GSE254221 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2025/01/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 10 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
10 samples
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.
Summary (written by the submitters)
Peripheral blood mononuclear cell (PBMC) RNA-seq datasets from burn patients with sepsis were acquired from the Gene Expression Omnibus (GEO), and OSRGs were retrieved from the GeneCards database. Weighted gene coexpression network analysis (WGCNA) was performed to validate the relationships between burns and immune cells. Machine learning and logistic regression were employed to select hub genes, which were used to construct predictive signatures.
Read the full summary ↓
High- and low-risk groups were defined by risk scores, and the expression of integrative hub genes was confirmed, with the results validated by real-time quantitative polymerase chain reaction (PCR) in PBMCs from 30 burn patients and burn models with different levels of severity. Integrin subunit alpha V (ITGAV) was confirmed as a hub gene, and its regulatory role was explored in vivo. Finally, the therapeutic role of MnCl2 was confirmed, and RNA-seq was performed to evaluate the associated signaling mechanisms.
This dataset
Open GSE254221 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 GSE254221_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 PRJNA1069028 and SRA study SRP486018. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Samples in this study

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