Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies without effective screening strategy during the early stage. Therefore, a novel screening panel was identified based on potential biomarkers associated with PDAC using the gene expression profile. The dataset GSE15471, which was downloaded from the Gene Expression Omnibus (GEO) database, included matching pairs of normal and tumor tissue samples from the resected pancreas of 39 pancreatic cancer patients. We used the online tool GEO2R to screen and pick out the differentially expressed genes (DEGs). Then we performed functional and pathway enrichment and constructed a DEG-associated protein-protein interaction (PPI) network by searching interacting genes in STRING. By using the visualization software Cytoscape, we sorted the modules in the PPI network and hub genes of DEGs through the MCODE and CytoHubba plugins. In total, 326 DEGs, including 306 upregulated genes and 20 downregulated genes, were targeted in PDAC. Kyoto Encyclopedia of Gene and Genome (KEGG) pathway and gene ontology (GO), based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID), revealed that the DEGs are mainly involved in ‘PI3K-Akt signaling pathway,’ ‘Focal adhesion,’ and ‘ECM-receptor interaction.’ In addition, top 50 core genes were identified from the PPI network by CytoHubba. Gene Expression Profiling Interactive Analysis (GEPIA) survival analysis showed that high expressions of KRT7, KRT19, SEMA3C, ITGA2, MYOF, and ANXA1 may predict poor survival outcome in PDAC. Finally, Oncomine confirmed that the high expressions of these genes were strongly related to cancer grade. These hub genes and regulators straightened out the molecular pathways and recurrence mechanisms in PDAC and could be used as targets for PDAC’s diagnosis, treatment, and prognostic prediction.