GEO series

Multiomics immune profiling of a patient-relevant orthotopic lung cancer model using SEPARATE-Seq.

GSE304864 Mus musculus (mouse) Single-cell RNA-seq 11 samples Submitted 2026/03/06 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 11 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Mus musculus (mouse)
Samples: 11 samples: 11 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: Multiomics immune profiling of a patient-relevant orthotopic lung cancer model using SEPARATE-SeqNature communications · 2026

Summary (written by the submitters)

Relevant pre-clinical models are essential for driving progress in cancer therapy research. Here, we developed a pre-clinical study framework using an injectable orthotopic lung adenocarcinoma (LUAD) model (ORTHO) that replicates key features of human LUAD patients and is dissectible into tumoural and non-tumoural adjacent tissue, in analogy with patient samples.

Read the full summary ↓

We also present SEPARATE-Seq, a technique enabling the partitioning of vascular and intratissue immune cells along with scRNA-Seq. By applying both SEPARATE-Seq and spatial transcriptomics to our dissectible ORTHO model, we confirmed that our model replicates key immune features of human LUAD patients. Similarly to these patients, we observed NK-cell dysfunction and neutrophil dichotomy, and uncovered that these are driven by their vascular/intratissue or tumour/adjacent location, highlighting the need for these spatial distinctions. Additionally, we reveal that several immune populations are restricted to specialised, local niches within the tumour, including a ring of lipid-associated TAMs lining the tumour edge and hubs of interferon-stimulated cells. Overall, our resource, available through an interactive tool, provides a comprehensive multiomics immune characterisation of a reproducible pre-clinical LUAD mouse model.

Published in

Multiomics immune profiling of a patient-relevant orthotopic lung cancer model using SEPARATE-Seq

Bardet PMR, Allonsius L, Hadadi E et al. · Nature communications 2026 · PMID 42026061 · doi:10.1038/s41467-026-72247-5

This dataset

Open GSE304864 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 GSE304864_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1303097 and SRA study SRP607353. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42026061) ↗

Study design

11 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 7 samples read as cases, 4 as controls.

How we read this: Read from 11 sample titles: 11 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

GSM9158785 Subcutaneous LLC-Thy1.1 P2 mouse tumors, cDNA
GSM9158786 Subcutaneous LLC-Thy1.1 P2 mouse tumors, ADT
GSM9158787 Orthotopic LLC-Thy1.1 P2 mouse LUAD tumors (ORTHO-T), cDNA
GSM9158788 Orthotopic LLC-Thy1.1 P2 mouse LUAD tumors (ORTHO-T), ADT
GSM9158789 Orthotopic LLC-Thy1.1 P2 mouse LUAD adjacent lung tissue (ORTHO-A), cDNA
GSM9158790 Orthotopic LLC-Thy1.1 P2 mouse LUAD adjacent lung tissue (ORTHO-A), ADT
GSM9158791 Orthotopic HBSS-inoculated (mock) mouse lung tissue (ORTHO-M), cDNA
GSM9158792 Orthotopic HBSS-inoculated (mock) mouse lung tissue (ORTHO-M), ADT
GSM9158793 LLC-Thy1.1 P0 and P2 cancer cell lines, cDNA
GSM9158794 LLC-Thy1.1 P0 and P2 cancer cell lines, CMO
GSM9158801 LLC-Thy1.1 P0 and P2 cancer cell lines, HTO

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