Pancreatic cancer is a malignant neoplasm originating from transformed cells arising in tissues forming the pancreas. A major challenge in current cancer research is biological interpretation of complexity of cancer somatic mutation profiles. It has been suggested that several molecular alterations may play important roles in pancreatic carcinogenesis. In this study, by using the GSE28735 affymetrix microarray data accessible from Gene Expression Omnibus (GEO) database, we identified differentially expressed genes (DEGs) between paired pancreatic cancer tissues and adjacent nontumor tissues, followed the protein-protein interaction of the DEGs. Our study identified thousands of DEGs involved in regulation of cell cycle and apoptosis in progression of pancreatic cancer. Sp1 was predicted to be the major regulator by transcription factors analysis. From the protein-protein interaction networks, we found that Tk1 might play an important role in the progression of pancreatic cancer. Finally, we predicted candidate agents, including tomatidine and nialamide, which may be used as drugs to treat pancreatic cancer. In conclusion, our data provide a comprehensive bioinformatics analysis of genes and pathways which may be involved in the progression of pancreatic cancer.