Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with poor survival, underscoring the need for robust molecular markers that can refine diagnosis and guide therapy. Objective: The goal of this study is to enhance diagnostic and treatment approaches for Pancreatic Ductal Adenocarcinoma (PDAC), a highly aggressive malignancy. We utilized RNA sequencing (RNA-Seq) data to identify differentially expressed genes (DEGs), examine gene networks, and uncover critical molecular links that are involved in the development and progression of PDAC. Methods: Four microarray datasets (GSE15471, GSE16515, GSE62165, and GSE62452) were obtained from the Gene Expression Omnibus (GEO). Data normalization and differential expression analysis were conducted using GEO2R, with a p-value cut-off of < 0.001 to identify DGEs. Functional annotation of these genes was carried out using DAVID Bioinformatics Resources, focusing on KEGG pathways and Gene Ontology (GO) terms. Gene interaction networks were constructed using STRING, and hub genes were identified with the cytoHubba plugin in Cytoscape. Results: A total of 614 up-regulated and 314 down-regulated genes were identified. The functional annotation of these genes revealed notable enrichment in several KEGG pathways and GO categories associated with molecular functions, biological processes, and cellular constituents. Key biological pathways implicated in PDAC were identified by the gene interaction networks derived from the DEGs. The top ten hub genes were identified. Conclusion: This comprehensive analysis of RNA-Seq data from multiple PDAC datasets successfully identified hub genes. These findings provide a molecular foundation for developing novel therapeutic strategies and improved diagnostic markers for the treatment of PDAC.
Nawab et al. (Sun,) studied this question.