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Human Multi-Regional Gastric Assembloids Favour Epithelial Cell Differentiation and Functional Parietal Maturation [paediatric patients]

GSE280843 Homo sapiens (human) RNA-seq (gene expression) 54 samples Submitted 2025/04/23 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 54 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
54 samples: 27 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)
Patient-derived human organoids have the remarkable capacity to self-organise into more complex structures. However, to which extend the gastric organoids can recapitulate the human stomach functions remains unexplored. Here, we report how gastric region-specific organoids can self-assemble into complex multi-regional assembloids showing levels of differentiation unattainable with simpler models.
Read the full summary ↓
The assembloid shows preserved fundus, body and antrum regionality and gastric-specific crosstalk pathways arise. Remarkably, the increased complexity and cross communication between the different gastric regions, allows for the arise of the elusive parietal cell type, responsible for the production of gastric acid, the essential function for food digestion. We showed functional response to drugs targeting ATPase H+/K+ and further maturation of the assembloid when transplanted in vivo. This advanced in vitro model, using patient-derived tissue-specific progenitors, successfully recapitulates the structural and functional characteristics of the human stomach, offering a promising strategy for studying developmental processes, tissue interactions, and disease mechanisms that were previously challenging to attain.
This dataset
Open GSE280843 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 GSE280843_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 PRJNA1180903 and SRA study SRP542579. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
27 conditions, mostly in duplicate
pat. 2, organoid, antrum, ×2 pat. 2, organoid, body, ×2 pat. 2, organoid, fundus, ×2 pat. 2, MRA, antrum, ×2 pat. 2, MRA, body, ×2 pat. 2, MRA, fundus, ×2 pat. 3, organoid, antrum, ×2 pat. 3, organoid, body, ×2 +19 more

Supports a between-group comparison across 54 samples.

How we read this: 27 replicated groups read from 54 sample titles; they account for 54 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

+ 14 more — browse all 54 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.