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The lower the better? Impact of radiation dose reduction on radiation-induced lung fibrosis molecular signature: approach towards preclinical model perfection

GSE205025 Mus musculus (mouse) RNA-seq (gene expression) 17 samples Submitted 2024/04/17 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 17 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
17 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.
Paper
Transcriptional Changes in Radiation-Induced Lung Injury: A Comparative Analysis of Two Radiation Doses for Preclinical ResearchInternational journal of molecular sciences · 2024
Summary (written by the submitters)
Radiation-induced pulmonary fibrosis (RIPF) is the most common bottleneck of radiation therapy (RT) that limits its tumor-killing effect. Up to date, there is no effective therapeutic agent for RIPF treatment due to absence of realistic preclinical models. Lungs of mice exposed to focal, highly localized dose of 75Gy-100Gy represents short time-taking (up to 6 weeks) modality for mimicking recent advanced RT, stereotactic body RT-associated lung fibrosis.
Read the full summary ↓
However, extensive fibrosis and possibility of animal lethality resulted from exposure to high dose raises a question regarding the appropriate dose threshold for limiting unnecessary responses and obtain clinically relevant results. We observed in preliminary trials that lung tissues of 65Gy-exposed mice are still able to develop inflammation and fibrosis at the same time cap. But the molecular changes associated with dose reduction is still unknown. To examine this, bulk RNA from 65Gy and 75Gy irradiated as well as normal lung tissues of mice were obtained, and analysed using computational approach to uncover the transcriptomal similarities and differences between the differentially irradiated samples. Differentially expressed genes (DEGs) were analysed and 2-week and 6-week intersected DEGs as well as 65 and 75Gy exclusive DEGs at 2-week and 6-week time points were detected using venn diagramme. Expression direction of intersected DEGs between 65Gy and 75Gy was checked and found to be consistent at both inflammation and fibrosis stages proven visually by MDS and heatmap graphs. All-times intersected DEGs are 488 and involved in inflammation, cytokine production, and cell proliferation; 2-week intersected DEGs are 221 and involved in cell cycle and DNA damage; 6-week intersected DEGs are 403 and involved in immunoglobin production, extracellular matrix (ECM) deposition, and ECM-receptor interactions. Interestingly, only 75Gy exclusive DEGs of 2 and 6 weeks presented inflammation and fibrosis-related biological process, respectively. These include anti-inflammatory process, cytokine production, EMT, vasculogenesis, and angiogenesis. These results suggested that 65Gy maybe a better dose for delivering less exaggerated, clinically relevant inflammation and fibrotic events, and thus, it can be utilised in establishing appropriate preclinical models for studying RIPF pathology and therapy.
Published in
Transcriptional Changes in Radiation-Induced Lung Injury: A Comparative Analysis of Two Radiation Doses for Preclinical Research
Farh ME, Kim HJ, Kim SY et al. · International journal of molecular sciences 2024 · PMID 38612576 · doi:10.3390/ijms25073766
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 GSE205025_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 PRJNA843100 and SRA study SRP377460. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 17 more — browse all 17 samples with per-sample file links →

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