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Single-cell and spatial transcriptomics analysis of tobacco-associated lung adenocarcinoma development, and in response to targeting inflammation alone or in combination with immune checkpoint blockade in precancerous phase [scRNA-seq]

GSE300288 Mus musculus (mouse) Spatial transcriptomics 31 samples Submitted 2025/10/11 Platform GPL24247
At a glance

Spatial transcriptomics · mouse · 31 samples

What it is
Spatial transcriptomicsGene activity measured with its position in a tissue section.
Organism
Mus musculus (mouse)
Samples
31 samples: 8 conditions, mostly with about 4 replicates eachGroups 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
Multimodal spatial-omics reveal co-evolution of alveolar progenitors and proinflammatory niches in progression of lung precursor lesionsCancer cell · 2026
Summary (written by the submitters)
Understanding cellular processes underlying early lung adenocarcinoma (LUAD) development is needed to devise intervention strategies. Here, we performed single-cell RNA sequencing (scRNA-seq) of mouse lungs from Gprc5a−/− mice during lung tumor development and also following therapeutic targeting of inflammation (IL-1 ) alone and in combination with immune checkpoint blockade in precancerous stages. We coupled scRNA-seq analysis with spatial transcriptomics of mouse lungs under different conditions.
Published in
Multimodal spatial-omics reveal co-evolution of alveolar progenitors and proinflammatory niches in progression of lung precursor lesions
Peng F, Sinjab A, Dai Y et al. · Cancer cell 2026 · PMID 41202811 · doi:10.1016/j.ccell.2025.10.004
This dataset
Open GSE300288 in finder → Find more mouse 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 GSE300288_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 PRJNA1280046 and SRA study SRP593376. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41202811) ↗
Study design
8 conditions, mostly with about 4 replicates each
Lungs of Gprc5a-/- mice exposed to Control Ig… ×4 Lungs of Gprc5a-/- mice exposed to anti-PD-1 … ×4 Lungs of Gprc5a-/- mice exposed to anti-IL-1𝛽… ×4 Lungs of Gprc5a-/- mice exposed to Control Ig… ×4 Lungs of Gprc5a-/- mice exposed to anti-IL-1𝛽… ×4 Lungs of Gprc5a-/- mice exposed to anti-PD-1 … ×4 Lungs of Gprc5a-/- mice exposed to anti-IL-1𝛽… ×4 Lungs of Gprc5a-/- mice exposed to anti-IL-1𝛽… ×3

Supports a between-group comparison across 31 samples.

How we read this: 8 replicated groups read from 31 sample titles; they account for 31 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
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