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<p>Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies due to its late diagnosis, chemoresistance, and lack of effective targeted treatments. These challenges are compounded by its molecular heterogeneity and complex tumor microenvironment. A deeper understanding of the molecular mechanisms underlying PDAC is essential for identifying novel diagnostic biomarkers and therapeutic targets. A comprehensive bioinformatics analysis was conducted on five microarray datasets obtained from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs) between PDAC and normal tissues. The DEGs were subjected to functional enrichment and protein–protein interaction (PPI) network analysis to identify key hub genes based on betweenness centrality. Subsequently, the validated hub genes were analyzed using miRTarBase to identify differentially expressed miRNAs with experimentally confirmed interactions. Our analysis revealed that three upregulated hub genes including, MET, MMP9, and AGR2 are targeted by the differentially expressed miRNAs hsa-miR-199a-3p, hsa-miR-140-3p, and hsa-miR-342-3p, respectively. Our analysis revealed that three upregulated hub genes, MET, MMP9, and AGR2, are targeted by the differentially expressed miRNAs hsa-miR-199a-3p, hsa-miR-140-3p, and hsa-miR-342-3p, respectively. These results highlight potential regulatory axes in PDAC and provide a foundation for future functional studies aimed at therapeutic development.</p>

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A network-based approach to identify hub genes in pancreatic ductal adenocarcinoma: proposing miRNA-Mediated combination therapy

  • 期刊论文

  • 发表日期：

    2025年10月10日

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  • Akramdokht Amjad,
  • Nafiseh Maghsoodi

摘要

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies due to its late diagnosis, chemoresistance, and lack of effective targeted treatments. These challenges are compounded by its molecular heterogeneity and complex tumor microenvironment. A deeper understanding of the molecular mechanisms underlying PDAC is essential for identifying novel diagnostic biomarkers and therapeutic targets. A comprehensive bioinformatics analysis was conducted on five microarray datasets obtained from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs) between PDAC and normal tissues. The DEGs were subjected to functional enrichment and protein–protein interaction (PPI) network analysis to identify key hub genes based on betweenness centrality. Subsequently, the validated hub genes were analyzed using miRTarBase to identify differentially expressed miRNAs with experimentally confirmed interactions. Our analysis revealed that three upregulated hub genes including, MET, MMP9, and AGR2 are targeted by the differentially expressed miRNAs hsa-miR-199a-3p, hsa-miR-140-3p, and hsa-miR-342-3p, respectively. Our analysis revealed that three upregulated hub genes, MET, MMP9, and AGR2, are targeted by the differentially expressed miRNAs hsa-miR-199a-3p, hsa-miR-140-3p, and hsa-miR-342-3p, respectively. These results highlight potential regulatory axes in PDAC and provide a foundation for future functional studies aimed at therapeutic development.