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The soluble factor milieu in IPF and in COPD exacerbations dysregulates epithelial differentiation

GSE245259 Mus musculus (mouse) RNA-seq (gene expression) 30 samples Submitted 2024/04/30 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 30 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
Mus musculus (mouse)
Samples
30 samples: 17 distinct titles, 1 of them repeatedGroups 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
The disruptive effects of COPD exacerbation-associated factors on epithelial repair responsesFrontiers in immunology · 2024
Summary (written by the submitters)
In idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD), epithelial abnormalities are present including bronchiolization and alveolar cell death and dysfunction. As epithelial progenitor cells are directed by their microenvironment, we hypothesized that changes in the microenvironment disrupt normal epithelial growth and differentiation.
Read the full summary ↓
We therefore mimicked the soluble factor microenvironment in IPF using an IPF cocktail (IPFc), composed of 9 factors which are increased in IPF lungs (CCL2, IL-1β, IL-4, IL-8, IL-13, IL-33, TGF-β, TNFα and TSLP) and in COPD exacerbations using an exacerbation cocktail (EC) composed of 4 factors that are increased during an exacerbation of COPD (TNFα, IL-1β, IL-6, IL-8). We asked whether the soluble factor milieu in IPF and COPD exacerbations affects epithelial growth and differentiation. Mouse lung organoids (primary EpCAM+ cells co-cultured with CCL206 fibroblasts) were used to study epithelial growth and differentiation. Organoids exposed to IPFc, EC or TGF-β (as a comparator) were resorted into EpCAM+ and CCL206 fractions, and subjected to RNA-sequencing.
Published in
The disruptive effects of COPD exacerbation-associated factors on epithelial repair responses
Kortekaas RK, Geillinger-Kästle KE, Fuentes-Mateos R et al. · Frontiers in immunology 2024 · PMID 38911863 · doi:10.3389/fimmu.2024.1346491
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 GSE245259_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: 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 PRJNA1027466 and SRA study SRP466033. Searching any of these in the dataset finder brings you back here.

Study design
17 distinct titles, 1 of them repeated
105096-001 ×14

How we read this: Read from 30 sample titles: 17 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
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