← BioTransfer GEO Dataset Finder
GEO series

Monocyte Subset Predicts Clinical Outcomes in Fibrotic Hypersensitivity Pneumonitis

GSE317902 Homo sapiens (human) Single-cell RNA-seq 33 samples Submitted 2026/04/01 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 33 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
33 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.
Summary (written by the submitters)
This study aimed to identify circulating immune cell populations associated with disease severity and progression in fibrotic hypersensitivity pneumonitis (fHP). Using single-cell RNA sequencing of peripheral blood mononuclear cells from 33 fHP patients (NCT02958917) and 36 sex-matched healthy controls (GSE196735, pools 1-3), we identified significant shifts in immune cell composition.
Read the full summary ↓
Compared to controls, fHP patients exhibited a marked increase in classical monocytes (CD14⁺), non-classical monocytes (CD16⁺), and myeloid-derived dendritic cells. Classical monocytes, in particular, were strongly correlated with baseline lung fibrosis severity—quantified by data-driven texture analysis of high-resolution computed tomography—and with reduced progression-free survival. Pathway analysis revealed that monocytes from patients with severe disease were enriched for inflammatory and metabolic processes, whereas those from patients with poor outcomes showed upregulation of interferon and NF-κB signaling. These findings highlight peripheral monocytes as promising prognostic biomarkers in fHP and suggest their role in driving fibrotic progression through dysregulated immune responses.
This dataset
Open GSE317902 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 GSE317902_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 PRJNA1415781. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
A cohort of 33 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run HPR001 … HPR042 and carry no group information.

Samples in this study
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.