GEO series

Lung microenvironments and disease progression in fibrotic hypersensitivity pneumonitis

GSE184316 Homo sapiens (human) RNA-seq (gene expression) 100 samples Submitted 2022/01/01 Platform GPL17303

At a glance

RNA-seq (gene expression) · human · 100 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: 100 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)

Rationale: Fibrotic hypersensitivity pneumonitis (fHP) is an interstitial lung disease caused by sensitization to an inhaled allergen. Objectives: We aimed to identify the molecular determinants associated with progression of fibrosis. Methods: Nine fHP explant lungs and six unused donor lungs (as controls) were systematically sampled (4 samples/lung).

Read the full summary ↓

According to microCT measures, fHP cores were clustered into a mild, moderate and severe fibrosis group. Gene expression profiles were assessed using Weighted Gene Co-expression Network Analysis (WGCNA), xCell, gene ontology and structure enrichment analysis. Gene expression of the prevailing molecular traits was also compared with IPF. The explant lung findings were evaluated in separate clinical fHP cohorts using tissue, bronchoalveolar lavage samples and computed tomography scans. Results: We found six molecular traits that associated with differential lung involvement. In fHP, extracellular matrix and antigen presentation/sensitization transcriptomic signatures characterized lung zones with only mild structural and histological changes, whereas signatures involved in honeycombing and B-cells dominated the transcriptome in the most severely affected lung zones. With increasing disease severity, endothelial function was progressively lost and progressive disruption in normal cellular homeostatic processes emerged. All six were also found in IPF, with largely similar associations with disease microenvironments. The molecular traits correlated with in vivo disease behaviour in a separate clinical fHP cohort. Conclusion: We identified six molecular traits which characterise the morphological progression of fHP and associate with in vivo clinical behaviour. Comparing IPF with fHP, the transcriptome landscape was determined considerably by local disease extent, rather than by diagnosis alone.

This dataset

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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 GSE184316_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 PRJNA763978 and SRA study SRP337516. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 100 more — browse all 100 samples with per-sample file links →

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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.