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Emergence of a mixed CAF population by FAP-CD3 T cell engager limits therapeutic efficacy

GSE330430 Mus musculus (mouse) Single-cell RNA-seq 19 samples Submitted 2026/05/13 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 19 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
19 samples: 5 × TH2, Ctrl TcE, tumo vs 5 × TH2, FAP TcE, tumo vs 5 × TC4, Ctrl TcE, tumo vs 4 × TC4, FAP TcE, tumoGroups 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.
Summary (written by the submitters)
Background: Fibroblast activating protein (FAP) expressing fibroblasts are an attractive target for cancer therapeutic depletion and while preclinical depletion shows success, previous modalities have unsuccessful clinical impact. Here, we wanted to comprehensively understand the tumor microenvironmental changes after FAP+ fibroblast depletion and unravel potential reasons for resistance and vulnerabilities that exist using a FAP targeted T cell engager.
Read the full summary ↓
To unveil the complex changes that occur in the tumor microenvironment after FAP+ fibroblast depletion, we generated comprehensive single cell RNA-sequencing analysis of FAP+ CAFs depletion within the TME to understand the key population and genetic modulations in all cell subtypes.Methods: A CD3 T cell engager directed against FAP (FAP TcE) was utilized to deplete FAP+ fibroblasts in a preclinical murine model of pancreatic cancer. To understand complex population dynamics upon FAP TcE, we performed single cell RNA-sequencing of treated vs. untreated tumors to unveil population and genetic changes. Results: Administration of FAP TcE resulted in tumor growth control in vivo that was not dependent on T cell priming and egress via draining lymph nodes. After FAP TcE, T cell exhaustion was prevalent with increased T cell exhaustive state (Tex) and the emergence of a T cell progenitor exhausted state (Tpex), yet addition of anti-PD1 failed to enhance tumor efficacy. Within fibroblast populations, FAP TcE depleted FAP+ cancer associated fibroblasts (CAFs); however, depletion is compensated by an emergence of a “mixed CAF” population, potentially limiting the efficacy of FAP TcE. Conclusion: This study highlights the complex and plastic fibroblast changes occurring with stroma targeted therapies that may limit therapeutic efficacy.
This dataset
Open GSE330430 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 GSE330430_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 PRJNA1463824 and SRA study SRP698770. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 × TH2, Ctrl TcE, tumo vs 5 × TH2, FAP TcE, tumo vs 5 × TC4, Ctrl TcE, tumo vs 4 × TC4, FAP TcE, tumo

Supports a between-group comparison across 19 samples.

How we read this: 4 replicated groups read from 19 sample titles; they account for 19 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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