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ACBP: a poor-prognosis biomarker in sepsis and a target for disease mitigation [Lung]

GSE313149 Mus musculus (mouse) RNA-seq (gene expression) 50 samples Submitted 2026/01/26 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 50 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
50 samples: 50 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
Acyl-CoA-binding protein (ACBP): a poor-prognosis biomarker in sepsis and a target for disease mitigationSignal transduction and targeted therapy · 2026
Summary (written by the submitters)
Sepsis remains a major clinical challenge, with high mortality and long-term disability despite current interventions. Here, we identify the tissue hormone acyl-CoA–binding protein (ACBP), also known as diazepam-binding inhibitor (DBI), as a biomarker and driver of poor outcome in sepsis. ACBP/DBI was elevated in the plasma of septic patients and associated with organ dysfunction and increased mortality.
Read the full summary ↓
In murine models of endotoxemia, Escherichia coli infection, and polymicrobial sepsis, genetic deletion or antibody-mediated neutralization of ACBP/DBI conferred robust protection by enhancing pathogen clearance, dampening cytokine storm, and preserving organ function. Notably, ACBP/DBI inhibition could be favorably combined with glucocorticoids, enhancing survival and reversing histopathological, transcriptional, or metabolic signatures of septic shock across heart, kidney, liver, lung, spleen, and plasma. These findings position ACBP/DBI as a mechanistic amplifier of sepsis pathophysiology and propose its neutralization, alone or in combination with corticosteroids, as a promising therapeutic strategy to interrupt the fatal trajectory of septic shock.
Published in
Acyl-CoA-binding protein (ACBP): a poor-prognosis biomarker in sepsis and a target for disease mitigation
Lambertucci F, Motiño O, Nogueira-Recalde U et al. · Signal transduction and targeted therapy 2026 · PMID 41927523 · doi:10.1038/s41392-026-02670-z
This dataset
Open GSE313149 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 GSE313149_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 PRJNA1378702 and SRA study SRP653971. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41927523) ↗
Study design
50 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 50 sample titles: 50 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

+ 10 more — browse all 50 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.