ArticleOncology letters2019
Identification of potential hub genes associated with the pathogenesis and prognosis of pancreatic duct adenocarcinoma using bioinformatics meta-analysis of multi-platform datasets.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Folate Intake and Risk of Pancreatic Cancer: A Systematic Review and Updated Meta-Analysis of Epidemiological Studies.Digestive diseases and sciences · 2021Pooled it
- The Janus Face of sFRP4 in Cancer: From Mechanistic Complexity to Therapeutic Potential.International journal of molecular sciences · 2026Review
- Inhibitor of DNA binding-1 is a key regulator of cancer cell vasculogenic mimicry.Molecular oncology · 2025Article
- Finding spatially variable ligand-receptor interactions with functional support from downstream genes.Nature communications · 2025Article
- Distance-depending transcriptome changes of pancreatic stellate cells in paracrine pancreatic ductal adenocarcinoma co-culture models.Scientific reports · 2024Article
- Metastatic phenotype and immunosuppressive tumour microenvironment in pancreatic ductal adenocarcinoma: Key role of the urokinase plasminogen activator (PLAU).Frontiers in immunology · 2022Article
- Cancer Progression Gene Expression Profiling Identifies the Urokinase Plasminogen Activator Receptor as a Biomarker of Metastasis in Cutaneous Squamous Cell Carcinoma.Frontiers in oncology · 2022Article
- Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics.Cancer metastasis reviews · 2021Review
- Identification of novel candidate biomarkers for pancreatic adenocarcinoma based on TCGA cohort.Aging · 2021Article
- PLAU1 Facilitated Proliferation, Invasion, and MetastasisFrontiers in oncology · 2021Article
- From Genetic Alterations to Tumor Microenvironment: The Ariadne's String in Pancreatic Cancer.Cells · 2020Review
- Is There a Trojan Horse to Aggressive Pancreatic Cancer Biology? A Review of the Trypsin-PAR2 Axis to Proliferation, Early Invasion, and Metastasis.Journal of pancreatic cancer · 2020Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatic duct adenocarcinoma (PDAC) is a highly malignant type of cancer with a low five-year survival rate. Gene alterations are crucial to the molecular pathogenesis of PDAC. Therefore, the present study analyzed gene expression profiles to reveal genes involved in the tumorigenesis of PDAC. A total of eight gene expression profiles (GSE15471, GSE16515, GSE41368, GSE62165, GSE62452, GSE71729, GSE71989 and GSE91035) and a PDAC dataset were acquired from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) database, respectively. Differentially expressed genes (DEGs) were screened using functional annotation, Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and protein-protein interaction (PPI) network construction. A Cox proportional hazards model was then constructed and used to analyze the data. A total of 136 DEGs (67 up- and 69 downregulated genes) were identified between PDAC tissues and normal tissues. The 'extracellular matrix-related' genes were the most enriched in the GO term analysis. 'Pancreatic secretion', 'phosphoinositide-3-kinase-protein kinase B/Akt (PI3K-Akt) signaling pathway', 'protein digestion and absorption' and 'ECM-receptor interaction' were the most enriched categories in KEGG pathway analysis. Following PPI network construction, the 10 most significant genes [albumin, epidermal growth factor, matrix metalloproteinase (MMP) 9, epidermal growth factor receptor, fibronectin 1, MMP1, plasminogen activator inhibitor-1, tissue inhibitor of metalloproteinase 1, plasminogen activator urokinase (PLAU) and PLAU receptor) exhibiting a high degree of connectivity, were identified as the hub genes likely to be associated with the pathogenesis of PDAC. In addition, a prognostic predictive system for PDAC, composed of five genes (laminin subunit γ 2, laminin subunit β 3, serpin family B member 5, amphiregulin and secreted frizzled related protein 4), was constructed. This was validated in the GSE62452 dataset (using 66 PDAC samples with outcome data) and TCGA PDAC dataset (using 146 PDAC samples with outcome data). In conclusion, the present study revealed potential hub genes involved in PDAC progression, providing directive significance for individualized clinical decision-making and molecular-targeting therapy in patients with PDAC.
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