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Single-cell multi-omics reveals the TNF-α activation threshold for Classical Monocytes by studying healthy donors and rheumatoid arthritis patients

GSE289019 Homo sapiens (human) Single-cell RNA-seq 2 samples Submitted 2025/04/01 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 2 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
2 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.
Paper
Single-cell multi-omics reveals the TNF-α activation threshold for Classical Monocytes by studying healthy donors and rheumatoid arthritis patientsFrontiers in immunology · 2025
Summary (written by the submitters)
Tumor Necrosis Factor Alpha is a known pro-inflammatory cytokine that plays a key role in the pathogenesis of rheumatoid arthritis. Anti-cytokine therapies targeting Tumor Necrosis Factor Alpha have greatly succeeded in treating rheumatoid arthritis in many patients. Despite these developments, many of the mechanisms of Tumor Necrosis Factor Alpha action have yet to be uncovered.
Read the full summary ↓
In this study, we incubated PBMCs from healthy donors and rheumatoid arthritis patients with Tumor Necrosis Factor Alpha and then performed their single-cell multi-omics analysis via BD Rhapsody. We have observed that Classical Monocytes have responded to the Tumor Necrosis Factor Alpha stimulation the most and that there was an activational threshold for such response that was dependent on the TNFR2 protein expression level. The profiling of TNFR2 protein expression level on immune cell populations can be a good predictive factor for the assessment of their activation by Tumor Necrosis Factor Alpha.
Published in
Single-cell multi-omics reveals the TNF-α activation threshold for Classical Monocytes by studying healthy donors and rheumatoid arthritis patients
Perik-Zavodskii R, Perik-Zavodskaia O, Alrhmoun S et al. · Frontiers in immunology 2025 · PMID 40453083 · doi:10.3389/fimmu.2025.1572823
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 GSE289019_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1220642 and SRA study SRP562214. Searching any of these in the dataset finder brings you back here.

Samples in this study

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