ArticleScientific reports2025
Single-cell transcriptomics analysis reveals dynamic changes and prognostic signature in tumor microenvironment of PDAC.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Exploratory single-nucleus multiomics analysis of myeloid cell states associated with neoadjuvant chemotherapy response in pancreatic ductal adenocarcinoma.Clinical and translational medicine · 2026Article
- Myofibroblastic CAF and Malignant Ductal Cell Crosstalk Drives Epithelial-Mesenchymal Transition and Progression in Pancreatic Ductal Adenocarcinoma via THBS2-SDC/Integrin Axes.International journal of molecular sciences · 2026Article
- CREB-SEC61G feedback loop sustains enhanced autophagy and boosts proliferation in PDAC.Cell death & disease · 2026Article
- Heterocellular crosstalk and architecture of the pancreatic tumour microenvironment.Nature reviews. Cancer · 2026Review
- Pancreatic cancer immunotherapy biomarkers: from traditional markers to multimodal integration and dynamic monitoring.Frontiers in immunology · 2026Review
- Construction and validation of a lysine beta hydroxybutyrylation related molecular model for predicting biochemical recurrence of prostate cancer.Scientific reports · 2025Article
- Advancing Precision Medicine in PDAC: An Ethical Scoping Review and Call to Action for IHC Implementation.Cancers · 2025Review
- Radiotherapy and immune microenvironment crosstalk in pancreatic cancer: a comprehensive review of current insights and future directions.Frontiers in immunology · 2025Review
- Peri-tumoural lymphocyte neighbourhoods predict longer survival in pancreatic ductal adenocarcinoma.Frontiers in immunology · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignant tumor characterized by a complex tumor microenvironment (TME) with significant heterogeneity, posing immense challenges for devising effective therapeutic strategies. This study aims to elucidate the dynamic changes in the TME during PDAC progression and develop a prognostic model using single-cell RNA sequencing (scRNA-seq) data. We utilized a previously published comprehensive dataset comprising 31 samples (including 8 PDAC I, 9 PDAC II, 6 PDAC III, and 8 PDAC IV) to characterize the changes in TME composition with PDAC progression through advanced scRNA-seq analysis. We found that as cancer progresses, immune cells gradually become a predominant component in late-stage PDAC. We defined a novel Treg and exhausted T cell signature gene, TNFRSF4. Additionally, we identified a prognostic gene set (RPS10, MIF, MT-ATP6, CSTB, IFI30, NPC2, BTG1, CTSD, FCGR2A, SEC61G, IER3, HSPB1, HMOX1, and ZFP36L1) and differentiated high-risk from low-risk PDAC patients based on median risk score threshold. Based on these findings, we developed a novel prognostic model that identifies poorer prognosis in high-risk groups. Furthermore, our analysis revealed significant interactions between cells at different stages of PDAC and identified three promising therapeutic agents (XR-11576, Ixabepilone, and AMONAFIDE) based on correlated genes. Finally, molecular docking studies validated their potential by confirming stable binding with key protein targets. This study not only provides insights into the evolving TME of PDAC but also offers a new prognostic model and potential therapeutic strategies, contributing to improved management and treatment of this aggressive cancer.
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