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Transcriptomic Profiling of CD66b+ Neutrophils from Healthy Controls and Cardiac Surgery Patients with Vasoplegic and Septic Shock Syndromes Across Multiple Timepoints

GSE302306 Homo sapiens (human) RNA-seq (gene expression) 68 samples Submitted 2026/05/14 Platform GPL21290
At a glance

RNA-seq (gene expression) · human · 68 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
68 samples: 68 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
Neutrophil Transcriptomic Changes in Severe Sterile Vasoplegic Syndrome Resemble a Distinct Molecular Subtype of Septic ShockShock (Augusta, Ga.) · 2026
Summary (written by the submitters)
Background: The systemic response to inflammation involves massive reorganization of gene expression which contributes to protection from infection but can also precipitate septic shock and organ failure. Understanding the early molecular events of systemic inflammation in sepsis is complicated by variance in both host-pathogen interactions and responses over time.
Read the full summary ↓
Vasoplegic syndrome after cardiac surgery resembles septic shock but lacks pathogen-related variables and proceeds over a defined, reproducible time course. Analysis of a single leukocyte cell type further enhances signal-to-noise. We hypothesized that human neutrophil transcriptomic changes in sterile vasoplegic syndrome would resemble neutrophil transcriptomic changes in one or more molecular subtypes of septic shock. Results: We enrolled seven patients with vasoplegic syndrome after cardiac surgery, eight cardiac surgical controls, and 12 patients with septic shock. In principal component analysis, isolated neutrophil transcriptomes from surgical patients clustered together by timepoint and demonstrated core dynamic gene expression changes in response to cardiac surgery that were independent of outcome. Additionally, among vasoplegic syndrome patients, two marked and consistent neutrophil transcriptomic phenotypes were observed and associated with distinct clinical phenotypes. A subset of dynamic expression changes in severe vasoplegic syndrome which were not seen in surgical controls instead resembled expression in patients with septic shock characterized by increased MMP8 mRNA. Similar results were obtained for plasma cytokine levels. Conclusions: Dynamic gene expression in neutrophils from patients with severe vasoplegic syndrome includes both expression changes in response to surgery, and development of a phenotype resembling septic shock with elevated MMP8 expression. Molecular events in severe vasoplegic syndrome may provide insights into the early mechanisms driving both septic and sterile inflammatory shock. Keywords: Sepsis, Surgical Trauma, Traumatic Injury
Published in
Neutrophil Transcriptomic Changes in Severe Sterile Vasoplegic Syndrome Resemble a Distinct Molecular Subtype of Septic Shock
Siletz AE, Kelly-Scumpia KM, Scumpia PO et al. · Shock (Augusta, Ga.) 2026 · PMID 41879344 · doi:10.1097/SHK.0000000000002827
This dataset
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.

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 GSE302306_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1289838. Searching any of these in the dataset finder brings you back here.

Study design
68 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 68 sample titles: 68 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

+ 28 more — browse all 68 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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