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Vascular-type heterogeneity is associated with differential gene expression profiles of endothelial cells under shear stress

GSE294621 Homo sapiens (human) RNA-seq (gene expression) 74 samples Submitted 2025/07/23 Platform GPL24676Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 74 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
74 samples: 8 conditions, mostly in triplicateGroups 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
Vascular-type heterogeneity is associated with differential gene expression profiles of endothelial cells under shear stressResearch and practice in thrombosis and haemostasis · 2025
Summary (written by the submitters)
Background: Endothelial cell (ECs) heterogeneity is an emerging area of research in EC biology. Veins, arteries, and microvascular endothelial cells, termed “vascular-type” heterogeneity in this report, have been shown to have heterogeneity in gene expression and function. In addition to this innate heterogeneity, we hypothesized that different vascular-type ECs would also demonstrate heterogeneity in their response to shear stress.
Read the full summary ↓
Objectives: We interrogated whether vascular-type ECs would demonstrate variations in transcriptional expression patterns under shear stress. Methods: Human umbilical vein endothelial cells (HUVECs), human pulmonary arterial endothelial cells (HPAECs), and human microvascular endothelial cells (HMVECs) were commercially purchased and subjected to shear stress conditions of 0, 1, 4, and 10 dynes/cm2 of laminar shear stress. After exposure to shear stress, cells were analyzed for cellular alignment and RNA was extracted and evaluated via bulk RNA-sequencing (RNA-seq). Results: All ECs demonstrated significant changes in alignment under shear stress. Shear stress significantly affected the transcriptomes of ECs resulting in differentially expressed genes and pathways; while several genes were differentially expressed across all three vascular-types (44.2%), most differentially expressed genes were limited to 1 or 2 of the vascular-types. Hemostatic and thrombotic genes were found to have differential expression patterns under conditions of shear stress, and VWF demonstrated a pattern of vascular-type heterogeneity in response to shear stress. Conclusions: Shear stress causes changes in cellular alignment and transcriptional patterns in ECs that is dependent upon underlying vascular-type. Therefore, endothelial vascular-type heterogeneity can regulate response to shear stress, especially in hemostatic and thrombotic gene expression.
Published in
Vascular-type heterogeneity is associated with differential gene expression profiles of endothelial cells under shear stress
Cox AA, Ng CJ · Research and practice in thrombosis and haemostasis 2025 · PMID 40678357 · doi:10.1016/j.rpth.2025.102894
This dataset
Open GSE294621 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 GSE294621_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 PRJNA1250946 and SRA study SRP578665. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40678357) ↗
Study design
8 conditions, mostly in triplicate
48hrs, Seeding density (cells/cm2): 60,000, D… ×32 48hrs, Seeding density (cells/cm2): 60,000, D… ×10 48hrs, Seeding density (cells/cm2): 60,000, D… ×10 48hrs, Seeding density (cells/cm2): 60,000, D… ×9 24hrs, Seeding density (cells/cm2): 100,000, … ×3 24hrs, Seeding density (cells/cm2): 100,000, … ×3 24hrs, Seeding density (cells/cm2): 60,000, D… ×3 24hrs, Seeding density (cells/cm2): 60,000, D… ×2 +2 more

Supports a between-group comparison across 72 samples.

How we read this: 8 replicated groups read from 74 sample titles; they account for 72 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

+ 34 more — browse all 74 samples with per-sample file links →

Datasets on a similar topic

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