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Pre-clinical proof-of-concept of anti-fibrotic activity of caveolin-1 scaffolding domain peptide LTI-03 in ex vivo precision cut lung slices from patients with Idiopathic Pulmonary Fibrosis

GSE305464 Homo sapiens (human) RNA-seq (gene expression) 94 samples Submitted 2025/08/21 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 94 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
94 samples: 35 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.
Summary (written by the submitters)
Human lung tissues from idiopathic pulmonary fibrosis (IPF) patients undergoing lung transplantation and non-IPF donors were obtained via the European IPF Registry (euIPFreg) sites Vienna and Giessen and delivered via the European IPF Biobank or the UGMLC Biobank, a member of the DZL platform biobanking. The study protocol was approved by the Ethics Committee of the Justus-Liebig University School of Medicine (No.
Read the full summary ↓
111/08: European IPF Registry and 58/15: UGMLC Giessen Biobank), and informed consent was obtained in written form from each subject (a comprehensive list of patient data and applied assays is provided in Table 2). Lung biopsy cores were obtained exclusively from 8 patients undergoing lung transplant for treatment of IPF and processed for PCLS culture as previously described18. All patients were male, an average of 61.5 years of age (std dev 6.56 years), and had a clinical diagnosis of IPF alone, or IPF with secondary pulmonary hypertension (PH). Usual interstitial pneumonia (UIP) was the main pathological finding on all explant tissue.
This dataset
Open GSE305464 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 GSE305464_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 PRJNA1306023 and SRA study SRP609011. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
35 conditions, mostly in duplicate
#999_UT_d2 ×4 #975_N_d2 ×3 #975_LTI3_d5 ×3 Gi-51_N_d2 ×3 Gi-51_UT_d2 ×3 Gi-51_LTI05_d5 ×3 Gi-51_LTI3_d5 ×3 Gi-51_LTI10_d5 ×3 +34 more

Supports a between-group comparison across 87 samples.

How we read this: 35 replicated groups read from 94 sample titles; they account for 87 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

+ 54 more — browse all 94 samples with per-sample file links →

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.