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scRNA-seq of MC38 syngeneic colorectal tumors after FAP-CAR mRNA-LNP therapy

GSE307699 Mus musculus (mouse) Single-cell RNA-seq 3 samples Submitted 2025/12/10 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 3 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
3 samples
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
Targeting fibroblast activation protein in solid tumors via LNP-mediated CAR-mRNA delivery promotes durable regression in murine modelsScientific reports · 2025
Summary (written by the submitters)
This study investigates the therapeutic potential of an mRNA–lipid nanoparticle (LNP)-based strategy delivering fibroblast activation protein (FAP)-specific chimeric antigen receptor (CAR) mRNA in colorectal cancer. Syngeneic colorectal mouse tumor models were treated with FAP-CAR mRNA-LNPs, and single-cell RNA sequencing (scRNA-seq) of tumor tissues was performed.
Read the full summary ↓
The analysis aimed to explore mechanisms of tumor relapse following treatment, with a particular focus on the MIF–CD74 signaling axis. The data revealed heterogeneous immune and stromal cell states, highlighting immunosuppressive pathways associated with relapse.
Published in
Targeting fibroblast activation protein in solid tumors via LNP-mediated CAR-mRNA delivery promotes durable regression in murine models
Meng S, Hara T, Sato T et al. · Scientific reports 2025 · PMID 41366016 · doi:10.1038/s41598-025-31128-5
This dataset
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.

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 GSE307699_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1322559 and SRA study SRP618933. Searching any of these in the dataset finder brings you back here.

Samples in this study

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