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Inflammatory transcriptomic signatures in a human cellular NMOSD model reveal upregulation of NF-κB and IL6 pathways

GSE291954 Homo sapiens (human) RNA-seq (gene expression) 60 samples Submitted 2025/10/01 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 60 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
60 samples: 60 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
Inflammatory transcriptomic signatures in a human cellular NMOSD model reveal upregulation of NF-κB and IL6 pathwaysScientific reports · 2025
Summary (written by the submitters)
Neuromyelitis optica spectrum disorder (NMOSD) is a rare neurological autoimmune disease caused autoantibodies targeting the astrocytic water channel aquaporin-4 (AQP4). Binding to AQP4 initiates the activation of innate immune components, especially the complement system. Both in-vivo and in-vitro models have been developed to study the molecular pathophysiology of NMOSD.
Read the full summary ↓
The aim of our study was to characterize the molecular response of four human cell lines (AQP4-ECFP expressing U-87MG glioblastoma cells, U-87MG expressing only ECFP, HEK293 cells expressing AQP4-EmGFP and human primary astrocytes) to a treatment with AQP4 antibody E5415A and human complement. Complement-dependent cytotoxicity was induced by this treatment in AQP4-expressing cells by the classical complement pathway. Transcriptomic profiles of the in-vitro U-87MG-AQP4-ECFP model and an in-vivo rat model shared a proinflammatory shift towards NF-κB and interleukin-6 pathways. These findings were confirmed on the mRNA and protein levels and treatment with serum samples from AQP4 antibody seropositive NMOSD patients resulted in a similar response. Additionally, NF-κB upregulation was shown by immunohistochemistry in medulla oblongata lesions of NMOSD patients. In conclusion, interleukin-6 and NF-κB pathways play a key role in inflammation caused by the activation of the classical complement pathway in a human cellular model of NMOSD using U-87MG-AQP4-ECFP cells. Brandl, S., Yu, Q., Hagenbuchner, J. et al. Inflammatory transcriptomic signatures in a human cellular NMOSD model reveal upregulation of NF-κB and IL6 pathways. Sci Rep 15, 43346 (2025). https://doi.org/10.1038/s41598-025-27335-9
Published in
Inflammatory transcriptomic signatures in a human cellular NMOSD model reveal upregulation of NF-κB and IL6 pathways
Brandl S, Yu Q, Hagenbuchner J et al. · Scientific reports 2025 · PMID 41361218 · doi:10.1038/s41598-025-27335-9
This dataset
Open GSE291954 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 GSE291954_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 PRJNA1236246 and SRA study SRP570592. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41361218) ↗
Study design
60 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 60 sample titles: 60 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

+ 20 more — browse all 60 samples with per-sample file links →

Datasets on a similar topic

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