ArticleScientific reports2025
Integrative multi-omics analysis reveals the role of toll-like receptor signaling in pancreatic cancer.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Multiomics Analysis of Nucleotide Metabolism Highlights the Important Role of Adenylate Kinase 4 in Pancreatic Cancer.Human mutation · 2026Article
- Single-Cell Analysis Delineates Glutathione Metabolism-Related Gene Signatures in the Glioblastoma Microenvironment and Identifies GSTA4 as a Regulator of Malignant Behaviors.International journal of genomics · 2026Article
- Determining a Stability Prognostic Panel for 636 Patients With Melanoma Using a Machine Learning Computational Framework.Experimental dermatology · 2025Article
- Thymidine kinase 1 related to Prolif-like T cells promoted GBM through regulation of cell cycle and EMT signals: a comprehensive research based on multi-omics analysis and experimental validation.Frontiers in immunology · 2025Article
- Single-cell transcriptomics identifies anFrontiers in molecular biosciences · 2025Article
- Single-cell atlas of endothelial cells in atherosclerosis: identifying C1 CXCL12+ ECs as key proliferative drivers for immunological precision therapeutics in atherosclerosis.Frontiers in immunology · 2025Article
- Integrative single-cell RNA sequencing and bulk RNA sequencing reveals the characteristics of glutathione metabolism and protective role of GSTA4 gene in pancreatic cancer.Frontiers in immunology · 2025Article
- The role of ATF3 in precision medicine of brain arteriovenous malformation: based on endothelial cell proliferation.Frontiers in immunology · 2025Article
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5 authors.
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Abstract
As one of the most destructive and invasive cancers, pancreatic cancer exhibits complex tumor heterogeneity, which has been a major challenge for clinicians in terms of patient treatment and prognosis. The toll-like receptor (TLR) pathway is closely related to the immune microenvironment within various cancer tissues. To explore the development pattern of pancreatic cancer and find an ideal biomarker, our research has explored the mechanism of the TLR pathway in pancreatic cancer. We collected single-cell expression data from 57,024 cells and transcriptomic data from 945 pancreatic cancer patients, and conducted a series of analyses at both the single-cell and transcriptomic levels. By calculating the TLR pathway score, we clustered pancreatic cancer patients and conducted a series of analyses including metabolic pathways, immune microenvironment, drug sensitivity and so on. In the process of building prognostic models, we screened 33 core genes related to the prognosis of pancreatic cancer, and combined a series of machine learning algorithms to build the prognosis model of pancreatic cancer. We used single cell sequencing to clarify the complex intrinsic relationship between TLR pathway and pancreatic cancer. The strongest TLR signals were observed in macrophages and endothelial cells. With the occurrence of pancreatic cancer, the TLR signal of various cell types gradually increased, but with the increase of the malignant degree of ductal epithelial cells, the TLR signal gradually weakened. Cluster analysis showed that patients with the most active TLR pathway had severe dysregulation of immune microenvironment and the worst prognosis. Finally, we combined a series of machine learning algorithms to build a pancreatic cancer prognosis model that includes four genes (NT5E, TGFBI, ANLN, and FAM83A). The model showed strong performance in predicting the survival state of pancreatic cancer samples. We explored the important role of TLR pathway in pancreatic cancer and established and validated a new prognosis model for pancreatic cancer based on TLR-related genes.
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