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Immune-Epithelial Interactions and Tissue Remodeling in the Inflammatory Respiratory Nasal Tract [NanoString GeoMx spatial transcriptomics]

GSE235714 Homo sapiens (human) Spatial transcriptomics 40 samples Submitted 2025/11/13 Platform GPL21697
At a glance

Spatial transcriptomics · human · 40 samples

What it is
Spatial transcriptomicsGene activity measured with its position in a tissue section.
Organism
Homo sapiens (human)
Samples
40 samples: 20 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.
Paper
Multi-scaled transcriptomics of chronically inflamed nasal epithelium reveals immune-epithelial dynamics and tissue remodeling in nasal polyp formationImmunity · 2025
Summary (written by the submitters)
Chronic rhinosinusitis (CRS) is a common inflammatory disease of the nasal cavity and sinuses that affects millions of individuals worldwide. The complex pathophysiology of CRS remains poorly understood, with emerging evidence implicating diverse immune and epithelial cell types in the disease process. We employed NanoString GeoMx spatial transcriptomics in both intact tissues to investigate the cellular and molecular heterogeneity of CRS with and without nasal polyps.
Published in
Multi-scaled transcriptomics of chronically inflamed nasal epithelium reveals immune-epithelial dynamics and tissue remodeling in nasal polyp formation
Liao G, Nakayama T, Zhu B et al. · Immunity 2025 · PMID 40945518 · doi:10.1016/j.immuni.2025.08.009
This dataset
Open GSE235714 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 GSE235714_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: Spatial studies usually ship Space Ranger style folders (count matrix plus tissue images). Look for them among the supplementary files.

Also filed as BioProject PRJNA986942. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40945518) ↗
Study design
20 conditions, mostly in duplicate
CRSwNP_4, CD45+ ROI ×2 CRSwNP_5, CD45+ ROI ×2 CRSwNP_6, CD45+ ROI ×2 CRSwNP_7, CD45+ ROI ×2 CRSwNP_8, CD45+ ROI ×2 CRSwNP_9, CD45+ ROI ×2 CTRL_6, CD45+ ROI ×2 CTRL_7, CD45+ ROI ×2 +12 more

Supports a between-group comparison across 40 samples.

How we read this: 20 replicated groups read from 40 sample titles; they account for 40 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
Datasets on a similar topic

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