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Single-cell RNA-seq of patient-derived cancer-associated fibroblast in vitro cell line models from pancreatic ductal adenocarcinoma

GSE301398 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2025/11/01 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
16 samples: 4 × In vitro PDAC CAF cell line, untreated, dono vs 4 × In vitro PDAC CAF cell line, TGFb1-treated, dono vs 4 × In vitro PDAC CAF cell line, BxPC3-co-cultured, dono vs 4 × hTERT in vitro PDAC CAF cell line, BxPC3-co-cultured, donoGroups 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
In vitro models of cancer-associated fibroblast heterogeneity uncover subtype-specific effects of CRISPR perturbationsMolecular oncology · 2026
Summary (written by the submitters)
Cancer-associated fibroblasts (CAFs) are sought after as potential therapeutic targets due to their plethora of pro- and antitumorigenic functions. Recent findings attributed this functional heterogeneity to specializations in CAF subtypes. A precise targeting of specific subtypes would thus be required to design therapies that effectively modulate CAF phenotypes, but our knowledge of CAF heterogeneity in solid tumors, particularly pancreatic ductal adenocarcinoma (PDAC), is still lacking.
Read the full summary ↓
Here, we use single-cell transcriptomics to characterize CAF subtype heterogeneity in in vitro CAF cell lines isolated from PDAC patients and investigate subtype-resolution modulations arising from perturbing potential stromal genes. We demonstrate that co-culturing CAFs with tumor cells can produce primary cell line models that can reliably represent CAF phenotypes observed in tumors, with correlations to immuno-resistant and immuno-modulatory phenotypes. With trajectory analysis, we infer the continuum of state changes that underlie the interconvertibility of CAF subtypes. Finally, we use the immortalized CAF cell lines to perform single-cell CRISPR perturbations of candidate stromal targets, revealing not only the subtype-specific effects of the perturbations, but also the impact of model-type selection on the translatability of insights.
Published in
In vitro models of cancer-associated fibroblast heterogeneity uncover subtype-specific effects of CRISPR perturbations
Saputra E, Vellarikkal SK, Li L et al. · Molecular oncology 2026 · PMID 41146557 · doi:10.1002/1878-0261.70153
This dataset
Open GSE301398 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 GSE301398_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 PRJNA1284930 and SRA study SRP596593. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41146557) ↗
Study design
4 × In vitro PDAC CAF cell line, untreated, dono vs 4 × In vitro PDAC CAF cell line, TGFb1-treated, dono vs 4 × In vitro PDAC CAF cell line, BxPC3-co-cultured, dono vs 4 × hTERT in vitro PDAC CAF cell line, BxPC3-co-cultured, dono

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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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