همایش ملی بیوانفورماتیک ایران

صفحه اصلی / 4th international edition and 13th Iranian Conference on Bioinformatics

Validation of Prognostic Biomarkers in Pancreatic Cancer Through Multi-Dataset Analysis and Pathway Enrichment

نویسندگان :

Ana Roohani¹ Somayeh Reiisi²

1- دانشگاه آزاد اسلامی واحد پزشکی تهران 2- دانشگاه شهرکرد

کلمات کلیدی :

Pancreatic cancer،Hub genes،DEGs،Pathway enrichment analysis

چکیده :

Pancreatic cancer remains one of the lethal forms of gastrointestinal cancer, characterized by a low five-year survival rate and challenges in early detection. The disease is often diagnosed at an advanced stage due to the pancreas's anatomical position, making it crucial to understand its risk factors for effective prevention (Hu, J.X, 2021). This study aims to identify sets of prognostic biomarkers from pancreatic cancer genomic data by applying to multiple independent datasets to find sets of genes related to malignant stage of pancreatic cancer. The research will also involve pathway enrichment analysis to elucidate the biological significance of these biomarkers and their potential roles in tumor progression and therapeutic response. Data set GSE32688 with GPL570 was received from the Gene Expression Omnibus, and then the differentially expressed genes (DEGs) between pancreatic cancer and non-malignant pancreas samples were identified using the R package including GEOquery, limma, BiocGenerics, affy, and oligo. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to identify the biological function of DEGs by Enrichr (Ma'ayan Laboratory, 2024). String database was used to investigate protein-protein interactions (STRING, 2024). A protein-protein Interaction network was constructed to display key target genes by using CytoHubba plugin in Cytoscape software. For hub genes validation, Gene Expression Profiling Interactive Analysis (GEPIA) databases were used and survival curve plotted by Kaplan-Meier plotter (Gene Expression Profiling Interactive Analysis, 2024; Kaplan-Meier Plotter, 2024). In total 570 DEGs were selected, comprising of 444 upregulated (logFC<1, adj.p value <0.01) and 126 downregulated genes (logFC>-1, adj.p value <0.01). The KEGG pathways were significantly enriched including Adherens junctions, Tight junctions, Extra cellular matrix receptor interaction, and PI3K-Akt signaling pathway. Also, DEGs were enriched in biological processes associated with Establishment of skin barrier, Skin epidermis development, Cell-Matrix adhesion and Positive regulation of protein Serin-Threonine kinase activity. Molecular functions also were associated with Cadherin binding, Cadherin binding involved in cell-cell adhesion and Myosin Binding. The 10 hub genes include: CDH1, MYC, IL6, ERBB2, KRAS, MET, CCND1, MUC1, IL1B, and TJP1 with CDH1 ranking highest. Among these genes CDH1, KRAS, CCND1, MET and TJP1 were considered by survival analysis. All these hub genes were upregulated in tumor cells based on analysis with GEPIA. These findings contribute to understanding gene regulation in pancreatic cancer and identifying new therapeutic targets and biomarkers in associated.

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