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A single-cell RNA-seq dataset of synovial fluid from rheumatoid arthritis treated with TNF-α/JAK inhibitor

GSE296117 Homo sapiens (human) Single-cell RNA-seq 18 samples Submitted 2025/05/06 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 18 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: 18 samples: 9 conditions, mostly in duplicateGroups 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: A single-cell RNA-seq dataset of synovial fluid from rheumatoid arthritis treated with TNF-α/JAK inhibitorScientific data · 2025

Summary (written by the submitters)

Although multiple single-cell RNA sequencing (scRNA-seq) based studies have explored rheumatoid arthritis (RA), most have focused on synovial tissue, limiting the ability to perform paired pre- and post-treatment comparisons and to elucidate dynamic changes. Moreover, the single-cell impact of TNF-α and JAK inhibitors on RA remains poorly understood, hindering effects toward precision medicine for RA.

Read the full summary ↓

Here, we present a comprehensive scRNA-seq analysis of synovial fluid samples of RA patients treated with tofacitinib or adalimumab, both pre- and post-treatment. Following stringent quality control, we analyzed 106,506 high-quality cells, providing an in-depth characterization of cell composition, molecular signaling pathways, and functional properties. This rich dataset offers a valuable resource to address diverse research questions, from uncovering the mechanisms of action of TNF-α and JAK inhibitors, to identifying novel therapeutic targets for RA, and advancing our understanding of the pathogenesis of inflammatory diseases.

Published in

A single-cell RNA-seq dataset of synovial fluid from rheumatoid arthritis treated with TNF-α/JAK inhibitor

He C, Ren Z, Xia X et al. · Scientific data 2025 · PMID 40494845 · doi:10.1038/s41597-025-05339-4

This dataset

Open GSE296117 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 GSE296117_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: 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 PRJNA1257822. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40494845) ↗

Study design

9 conditions, mostly in duplicate

RA_1 ×2 RA_2 ×2 RA_3 ×2 RA_4 ×2 RA_5 ×2 RA_6 ×2 RA_9 ×2 RA_10 ×2 +1 more

Supports a between-group comparison across 18 samples.

How we read this: 9 replicated groups read from 18 sample titles; they account for 18 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

GSM8965453 RA_1_1 RA_1
GSM8965454 RA_1_2 RA_1
GSM8965455 RA_2_1 RA_2
GSM8965456 RA_2_2 RA_2
GSM8965457 RA_3_1 RA_3
GSM8965458 RA_3_2 RA_3
GSM8965459 RA_4_1 RA_4
GSM8965460 RA_4_2 RA_4
GSM8965461 RA_5_1 RA_5
GSM8965462 RA_5_2 RA_5
GSM8965463 RA_6_1 RA_6
GSM8965464 RA_6_2 RA_6
GSM8965465 RA_9_1 RA_9
GSM8965466 RA_9_2 RA_9
GSM8965467 RA_10_1 RA_10
GSM8965468 RA_10_2 RA_10
GSM8965469 RA_11_1 RA_11
GSM8965470 RA_11_2 RA_11

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