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Cellular heterogeneity during mouse pancreatic ductal adenocarcinoma progression at single-cell resolution
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Abstract
Pancreatic ductal adenocarcinoma (PDA) is a major cause of cancer-related death, with limited therapeutic options available. This highlights the need for improved understanding of the biology of PDA progression, a highly complex and dynamic process, featuring changes in cancer cells and stromal cells. A comprehensive characterization of PDA cancer cell and stromal cell heterogeneity during disease progression is lacking. In this study, we aimed to profile cell populations and understand their phenotypic changes during PDA progression. To that end, we used single-cell RNA–sequencing technology to agnostically profile cell heterogeneity during different stages of PDA progression in genetically engineered mouse models. Our data indicate that an epithelial-mesenchymal transition of cancer cells accompanies tumor progression in addition to distinct populations of macrophages with increasing inflammatory features. We also noted the existence of 3 distinct molecular subtypes of fibroblasts in the normal mouse pancreas, which ultimately gave rise to 2 distinct populations of fibroblasts in advanced PDA, supporting recent reports on intratumor fibroblast heterogeneity. Our data also suggest that cancer cells and fibroblasts may be dynamically regulated by epigenetic mechanisms. This study systematically describes the landscape of cellular heterogeneity during the progression of PDA and has the potential to act as a resource in the development of therapeutic strategies against specific cell populations of the disease.
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“The data gained through this approach suggests neoadjuvant treated patients would potentially respond better to adjuvant immunotherapy.”
From Pancreatic cancer: Advances and challenges (2023) · cites this paper as [268]
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“Illustrating this, a 36 marker CyTOF characterization of peripheral blood from PDAC patients revealed neoadjuvant FOLFIRINOX promotes an increase in effector T cells and concurrent decrease in suppressive immune populations268.”
From Pancreatic cancer: Advances and challenges (2023) · cites this paper as [268]
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Metadata
- Authors
- Hosein, A. N., Huang, H., Wang, Z., Parmar, K., Du, W., Huang, J., Maitra, A., Olson, E., Verma, U., & Brekken, R. A.
- Affiliations
- The University of Texas MD Anderson Cancer Center (US)
- The University of Texas Southwestern Medical Center (US)
- Corresponding author
- Brekken, Rolf A.
- ORCID
- Venue
- JCI Insight
- Published
- 2019-08-22
- Volume
- 4
- Issue
- 16
- ISSN
- 2379-3708 (ISSN-L)
- PMC
- PMC6777805
- OpenAlex
- W2964097765
- Cited by
- 302
- References
- 58
- Citations by year
- 2026: 22 · 2025: 29 · 2024: 41 · 2023: 64 · 2022: 61 · 2021: 41 · 2020: 39 · 2019: 4
- FWCI
- 15.22
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- JCI Insight (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Texas Southwestern Medical Center (See comments)
- Topics
- Health Sciences › Medicine › Oncology › Pancreatic and Hepatic Oncology Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- pancreatic ductal adenocarcinoma, tumor progression, cellular heterogeneity, epithelial-mesenchymal transition, tumor-associated macrophages, tumor-infiltrating fibroblasts, fibroblast heterogeneity, tumor microenvironment, epigenetic regulation, genetically engineered mouse models, tumor heterogeneity, stromal heterogeneity
- MeSH terms
- Animals, Disease Models, Animal, Fibroblasts, Mice, Inbred C57BL, Mutation, Pancreatic Neoplasms, Gene Expression Regulation, Neoplastic, Sequence Analysis, Genetic Heterogeneity, Genetic Predisposition to Disease, Carcinoma, Pancreatic Ductal, Mice, Epigenomics, Single-Cell Analysis, Transcriptome
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