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Small molecule-directed differentiation of submerged-cultured human nasal airway epithelia for respiratory disease modelling [bulkRNA-seq]

GSE318346 Homo sapiens (human) RNA-seq (gene expression) 27 samples Submitted 2026/02/05 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 27 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
27 samples: 27 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
Small molecule-directed differentiation of submerged-cultured human nasal airway epithelia for respiratory disease modelingCell reports. Medicine · 2026
Summary (written by the submitters)
Submerged cultures of undifferentiated or transformed epithelial cells are widely used in respiratory research due to their ease of use and scalability. However, these systems fail to capture the cellular diversity of the human airway epithelium. Here, we describe a submerged differentiation model using cryopreserved human nasal epithelial cells obtained via minimally invasive brushings.
Read the full summary ↓
By targeting Notch and BMP signaling with small-molecule inhibitors, we differentiate these cells into complex epithelial cultures containing basal, secretory, and ciliated cell types on standard plastic cultureware. This method supports scalable culturing of both 2D epithelial monolayers and 3D organoids, and is applied to disease modeling in primary ciliary dyskinesia, cystic fibrosis, and respiratory syncytial virus infection. The resulting system enables scalable assessment of disease-relevant epithelial functions in respiratory research
Published in
Small molecule-directed differentiation of submerged-cultured human nasal airway epithelia for respiratory disease modeling
Dreyer HHM, Ithakisiou GN, Spelier S et al. · Cell reports. Medicine 2026 · PMID 41875894 · doi:10.1016/j.xcrm.2026.102692
This dataset
Open GSE318346 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 GSE318346_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 PRJNA1418616. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41875894) ↗
Study design
27 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 27 sample titles: 27 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

Search all human RNA-seq datasets in GEO →

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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.