Single-cell transcriptomic analysis reveals key cell types and pathogenic genes associated with metastasis in pancreatic adenocarcinoma

Pancreatic ductal adenocarcinoma (PAAD) metastasis is driven by complex tumor-microenvironment interactions. Here, we integrated single-cell and bulk transcriptomic analyses of 104,855 cells from 10 patients to delineate the cellular and molecular landscape of primary versus metastatic PAAD. We identified metastasis-associated epithelial (LMO7⁺, TOP2A⁺, PIGR⁺), fibroblast (IGKC⁺, RGS5⁺), and M2-like macrophage (APOE⁺, CD14⁺, FOLR2⁺, SPP1⁺) subpopulations, validated via bulk deconvolution. Functional analyses revealed upregulated Wnt signaling, epithelial-mesenchymal transition, and angiogenesis in metastatic epithelial and fibroblast compartments. Intercellular communication analysis highlighted SPP1-mediated macrophage-epithelial/fibroblast crosstalk involving key receptor-ligand pairs, contributing to immune suppression and metastatic niche formation. Integrating gene expression and cell proportions, we developed a prognostic model with high predictive accuracy (C-index > 0.85), stratifying patients into risk groups with distinct immune landscapes. Furthermore, PTK6 was identified as a driver of PAAD proliferation, migration, and invasion. Collectively, our study elucidates TME-driven mechanisms of PAAD metastasis, identifies prognostic and therapeutic targets, and provides a framework for precision intervention.

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Publication Details

Journal
Clinical and Experimental Medicine
Published
2025-11-29
DOI
https://doi.org/10.1007/s10238-025-01974-8
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Single-cell transcriptomic analysis reveals key cell types and pathogenic genes associated with metastasis in pancreatic adenocarcinoma

Shijun Shen, Zhiqiang Li, Xinwei Zhang, Hong Yang et al.
Clinical and Experimental Medicine
Single-cell and spatial transcriptomics
article

Single-cell transcriptomic analysis reveals key cell types and pathogenic genes associated with metastasis in pancreatic adenocarcinoma

Shijun Shen, Zhiqiang Li, Xinwei Zhang, Hong Yang, Gang Chen, Chengzhou Pa
article en

Abstract

Pancreatic ductal adenocarcinoma (PAAD) metastasis is driven by complex tumor-microenvironment interactions. Here, we integrated single-cell and bulk transcriptomic analyses of 104,855 cells from 10 patients to delineate the cellular and molecular landscape of primary versus metastatic PAAD. We identified metastasis-associated epithelial (LMO7⁺, TOP2A⁺, PIGR⁺), fibroblast (IGKC⁺, RGS5⁺), and M2-like macrophage (APOE⁺, CD14⁺, FOLR2⁺, SPP1⁺) subpopulations, validated via bulk deconvolution. Functional analyses revealed upregulated Wnt signaling, epithelial-mesenchymal transition, and angiogenesis in metastatic epithelial and fibroblast compartments. Intercellular communication analysis highlighted SPP1-mediated macrophage-epithelial/fibroblast crosstalk involving key receptor-ligand pairs, contributing to immune suppression and metastatic niche formation. Integrating gene expression and cell proportions, we developed a prognostic model with high predictive accuracy (C-index > 0.85), stratifying patients into risk groups with distinct immune landscapes. Furthermore, PTK6 was identified as a driver of PAAD proliferation, migration, and invasion. Collectively, our study elucidates TME-driven mechanisms of PAAD metastasis, identifies prognostic and therapeutic targets, and provides a framework for precision intervention.

Clinical and Experimental MedicineVol. 26(1)
Kunming Medical University (CN), The First Hospital of Kunming (CN), Living Independently Now Center (US), First Affiliated Hospital of Kunming Medical University (CN), Zhejiang Provincial People's Hospital (CN), Pingliang People's Hospital (CN)
Openalex Percentile: Top 66%
Single-cell and spatial transcriptomics
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Single-cell transcriptomic analysis reveals key cell types and pathogenic genes associated with metastasis in pancreatic adenocarcinoma — Shijun Shen, Zhiqiang Li, et al. · Clinical and Experimental Medicine (2025) | TGRS Research Map | TGRS