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Distinct Molecular Responses of Human Intestinal Organoids to Proton and Photon Radiation

GSE297090 Homo sapiens (human) RNA-seq (gene expression) 40 samples Submitted 2025/10/28 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 40 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
40 samples: 40 samples, each with a distinct title — no replicated groupsGroups 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
Distinct molecular responses of human intestinal organoids to proton and photon radiationAmerican journal of physiology. Gastrointestinal and liver physiology · 2025
Summary (written by the submitters)
Radiation exposure causes damage to tissues with high numbers of rapidly dividing cells such as the intestine. Mouse models have been widely used to understand the effects of radiation injury, repair following exposure, and to develop and test potential therapies for radiation-induced damage. However, although the mouse intestine shares physiological and molecular similarities with human intestine, translation and validation of findings in mouse radiation models to the human intestine have been limited by the lack of models.
Read the full summary ↓
The development of ex vivo human intestinal organoids provides a new model in which the effects of radiation on the human intestinal epithelium can be examined and compared to in vivo animal models. Using human small intestinal jejunal organoids, multi-omic profiles were analyzed using bioinformatic pipelines to explore the response to a dose of proton and photon radiation exposure which may be encountered during a radiotherapy treatment or over time in high background radiation environments. Transcriptional signatures following radiation exposure were indicative of reprogramming of cells to a more primitive state that has been associated with regeneration and repair. Integrative analyses of transcriptomic and metabolomic datasets revealed enrichment of amino acid synthesis and metabolism pathways. Human intestinal organoids can complement and validate findings from traditional animal models and are emerging as a powerful tool to study responses to radiation exposure.
Published in
Distinct molecular responses of human intestinal organoids to proton and photon radiation
Poplaski V, Patel TD, Nguyen-Phuc H et al. · American journal of physiology. Gastrointestinal and liver physiology 2025 · PMID 41165566 · doi:10.1152/ajpgi.00186.2025
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 GSE297090_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 PRJNA1262498 and SRA study SRP584993. Searching any of these in the dataset finder brings you back here.

Study design
40 samples, each with a distinct title — no replicated groups

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

How we read this: Read from 40 sample titles: 40 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
Datasets on a similar topic

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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.