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Dissecting CAF subtypes in Pancreatic Cancer

https://doi.org/10.71540/eq7d-nd59
Within the stroma of pancreatic ductal adenocarcinoma (PDAC), mesenchymal cells differentiate into cancer-associated fibroblast (CAF) subtypes that differentially mediate disease progression. Defining the regulatory mechanism and diversity of CAF subtypes could identify potential therapeutic strategies to harness the tumor suppressive activities of CAFs. To address this, we utilized single-cell RNA sequencing to profile fibroblast activation protein-alpha (FAP) expressing mesenchymal cells in human PDAC. The mesenchymal subpopulations in PDAC reflected mesenchymal cell heterogeneity found in the normal developing pancreas. In addition to characterizing inflammatory CAF (iCAF) and myofibroblastic CAF (myCAF) subpopulations in detail, the analysis uncovered a previously undescribed interferon-response CAF (ifCAF) subtype. Tumor-derived signals induced specific CAF subtypes from pancreatic stellate cells (PSCs) in an organoid-based co-culture model, and time-course experiments revealed regulatory mechanisms that govern subtype formation. STING agonists promoted an ifCAF phenotype in vivo and in vitro. Importantly, induction of an ifCAF phenotype suppressed tumor cell invasiveness and induced an anti-tumor phenotype in tumor-associated neutrophils. Together, this study resolves FAP+ stromal cell heterogeneity in PDAC and identifies an ifCAF subtype that can be induced to suppress pro-tumorigenic features of PDAC (Cumming et al., 2025). This dataset contains the following data and metadata files: 1. Six pairs of fastq files that contain the actual sequencing data. The total size is 230 GB. Each pair represents a paired-end single-cell RNA sequencing from an individual patient sample. The fastq files are text files with genomic sequence and sequence quality metrics. They are stored as compressed gzip-ed files. 2. A metadata file with sample information. The variables included are: Sample name, sequencing library ID, sequencing depth, sequencing index, number of cells, barcode set, patient pseudo ID (P1-P5), pathologic diagnosis, gender, age, surgical procedure, pathological classification, tumour location, histological status (desmoplasia). This is an Excel file (xlsx). 3. A metadata file with sample information according to the Federated European Genome-Phenome Archive Sweden (FEGA-sweden) template format. This is an Excel file (xlsx). 4. Twelve processed data tables with raw read (UMI) count; Six files for quality filtered cells, and six files with all cells. Each table corresponds to a separate sample. This corresponds to gene expression levels after mapping to the reference genome. The data is stored in MEX format, i.e. three tab-delimited text files in sparse matrix format. The files are compressed with gzip. 5. Two cell annotation tables for the single-cell data. The tables describe read count, gene count, cluster number, and cell type annotation for 30786/26733 single cells from the 6 samples described in the sample information metadata file. The tables are submitted as tab-delimited text files. 6. Two binary files written in R programming language containing an object readable by the Seurat package. The files contain processed data in the form of read count (i.e. gene expression levels) and also as transformed (normalized and scaled) data and analysis results. The files are in RDS format and can be loaded in R. For more information about the data files, please read the documentation files that accompany this data description. If you would like to submit a request to access data of this dataset, please read the document Readme_before_submission_of_an_access_request.
Download documentation (5 files / 43.74 KiB)

Documentation files

  • ega-metadata_template.xlsx
    26.87 KiB
  • Manifest_version_02.txt
    3.51 KiB
  • Readme_before_submission_of_an_access_request.md
    3.03 KiB
  • Readme_before_submission_of_an_access_request.txt
    2.99 KiB
  • Readme_version_02.md
    7.34 KiB

Citation and access

Data access level:

Creator/Principal investigator(s):

Research principal:

Principal's reference number:

  • 2019-00399

Data contains personal data:

Yes

Type of personal data:

Genomic sequence data, gender, clinical diagnosis, age

Code key exists:

Yes

Sensitive personal data:

Yes

Citation:

Language:

Method and outcome

Time period(s) investigated:

Data format/data structure:

Species and taxons:

Data collection Experiment

Mode of collection:

Experiment

Description of the mode of collection:

cDNA and libraries were prepared across 6 samples derived from 5 human PDAC tumors. according to the manufacturers’ instructions (Chromium Single Cell 3’ v3.1 protocol). cDNA libraries were sequenced on an Illumina NovaSeq 6000 S2-100 v1.5 flow cell at the Science for Life Laboratory National Genomic Infrastructure.

Time period(s) for data collection:

2020-09-17 - 2021-02-03

Data collector:

Source of the data:

  • Biological samples

Temporal resolution:

6 month

Sample

Name:

Pancreatic ductal adenocarcinoma (PDAC) tissue from surgical resection

Description of sample:

Human PDAC tumor samples were resected at Umeå University Hospital. The study was conducted according to declaration of the Helsinki and was approved by the ethical review board at Umeå University (09–175M) and the Swedish ethical review authority (2019–00399). All subjects taking part in the study provided written informed consent. Samples were included when confirmed as PDAC through assessment by a pathologist. 6 tumor samples from 5 patients were profiled.

Instrument

Name:

10x Chromium cartridge (10x Genomics, 1000127)

Description of the instrument:

The 10x Genomics Single Cell Gene Expression solution provides users with 3’ transcriptome gene expression analysis at single-cell resolution. This enables molecular and cellular characterization of individual cells. This high-throughput single-cell sequencing solution is highly suitable for larger projects that require data for a few thousand cells per sample.

Name:

NovaSeq™6000SequencingSystem

Description of the instrument:

Improvements to the NovaSeq 6000 Reagent Kits include an enhanced reagent chemistry to streamline the workflow and accommodate more complex indexing strategies, an extended reagent shelf life of six months to provide project planning flexibility, and radio-frequency identification (RFID) to ensure reagent traceability and compatibility.

Geographic coverage

Geographic location:

Geographic description:

Northern Sweden

Administrative information

Responsible department/unit:

Department of Diagnostics and Intervention

Ethics Review:

Swedish Ethical Review Authority - 2019-00399

Project title: Tumor stroma as drug target in pancreatic cancer

Funding

Funding agency:

Award number:

PT2015-6432

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

  • Cancer Research Foundation in Northern Sweden

Award number:

LP18-2202, LP20-2257, and LP 21-2298, LP- 22-2332, LP-23-2347, and LP 24-2377

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

Award number:

2017-01531_VR

Award title:

Targeting Tumor-stromal Interactions in Pancreatic Cancer

Funding information:

Pancreatic cancer is resistant to all available adjuvant therapies, indicating that novel strategies to tackle the disease are needed. The pancreatic tumor is characterized by a pronounced tumor stroma that surrounds the cancer cells, containing extracellular matrix and cancer-associated fibroblasts that provide the cancer cells with important signals that regulate cancer cell growth and survival, and contribute to therapy resistance. The overall goal of this project is to get a deeper understanding in the stromal heterogeneity, and to reveal and explore potential drugable targets hidden within the stroma. First, we will decipher the composition of the extracellular matrix by applying mass spectrometry-based methods, then resolving the phenotypic diversity found in cancer- associated fibroblasts embedded within the tumor by utilizing fluorescent in situ RNA sequencing techniques. Next, we aim to determine which stromal elements that are important in regulating cancer cell growth, survival, immune escape, and drug resistance by using genetically engineered mouse models of pancreatic cancer and organoid based co-culture systems. Finally, we will develop and test drugs that target the most pro-tumorigenic stromal interactions with the aim to discover and explore novel therapeutic strategies. The project is initiated and spans over a time period of  5 years and will be conducted at a newly established research group at Wallenberg centre for molecular medicine at Umeå University.

Funding agency:

  • Sjöberg Foundation

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

Award number:

RV-978812 and RV-930167, VLL-643451, and VLL-832001

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

Award number:

890521 and SLS-786661, SLS-691681, SLS-591551

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

Award number:

KAW 2015.0114

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

Award number:

MMW 2020.0189

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

Award number:

CAN 2017/332

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

Award number:

2022-00855_VR

Award title:

Targeting Tumor-stromal Interactions in Pancreatic Cancer

Funding information:

Pancreatic cancer is a disease resistant to available therapies, hence novel strategies to tackle the disease are urgently needed. The pancreatic tumor is characterized by a dense tumor stroma consisting of a diverse extracellular matrix (ECM) and different subtypes of cancer-associated fibroblasts (CAFs) that provide cancer cells with signals that regulate cancer cell growth and survival, and contribute to immune evasion. The purpose of this project is to get a deeper understanding of the pathophysiological role of the stroma. This will obtained by studies on the functional heterogeneity of the different stromal components, with the aim to reveal potential druggable targets found in the stroma, and to identify stroma-derived diagnostic and prognostic biomarkers for the disease. We will first resolve the functional diversity in subtypes of CAFs and prominent ECM proteins, and then determine which of these stromal components that are important for tumorogenesis and tumor progression. Finally, we will develop drug candidates that inhibit pro-tumorigenic, and/or induce anti-tumorigenic, stromal interactions. This will be achieved by applying single cell transcriptomics methods on patient tissue and tissue from mouse models of pancreatic cancer, and by performing high throughput compound screens in organoid/CAF based co-cultures. The ultimate goal of the project is to bring new diagnostic, prognostic and therapeutic strategies for pancreatic cancer into the clinic.

Funding agency:

Award number:

CAN 2017/827

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

Award number:

20 1339 PjF

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

Award number:

23 2707 Pj

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Funding agency:

  • The Kempe Foundations

Award number:

JCK-1301, SMK-1765

Award title:

Targeting Tumor-Stromal Interactions in Pancreatic Cancer

Topic and keywords

Standard för svensk indelning av forskningsämnen 2025:

INSPIRE topic categories:

Keywords:

Relations

Requires:

Seurat: Tools for Single Cell Genomics (R package)Opens in a new tab

Metadata

Versions

Version:

2

DOI:

https://doi.org/10.71540/eq7d-nd59Opens in a new tab

  • Metadata added:

    Version 2 contains the new documentation files "Readme_before_submission_of_an_access_request.md" and "Readme_before_submission_of_an_access_request.txt".

Published:

Version:

1

DOI:

https://doi.org/10.5878/0ehq-1434Opens in a new tab

Published:

doris
umu
Published: