Abstract：Abstract: To explore the pathogenesis of pancreatic cancer and provide bioinformatics basis for the prevention and treatment of pancreatic cancer, the GEO2R online tool was used to analyze the differentially expressed genes (DEGs) between the tumor and normal tissues of pancreatic cancer patients in GSE16515. GO analysis and KEGG pathway enrichment analysis of DEGs were performed using DAVID database. The STRING database was used to construct a protein-protein interaction (PPI) network. The key genes (hub genes) were screened and function modules were analyzed using Cytoscape software. The hub genes were verified in the GEPIA database, and the expression levels of the target genes in pancreatic cancer tissues and cell lines were detected using CCLE database. The results showed that 376 DEGs screened from pancreatic cancer were mainly involved in cell cycle, p53 signaling pathway, protein digestion and absorption, ECM-receptor interaction, PI3K-Akt signaling pathway, and platelet activation signaling pathway. GEPIA database verification showed that 10 hub genes were highly expressed in pancreatic cancer tissues, and 8 hub genes were associated with poor prognosis of pancreatic cancer patients. The CCLE database showed that cyclin-dependent kinase 1 (CDK1) had a high expression level in pancreatic cancer tissues and cells. The above results indicated that CDK1 may be the most relevant to the occurrence and development of pancreatic cancer, providing a bioinformatics basis for further exploration of the pathogenesis of pancreatic cancer.
引用本文:
杨万霞, 潘云燕, 李 雪, 管沛文, 尤崇革. 胰腺癌中CDK1的表达与预后的生物信息学分析[J]. 生命科学研究, 2020, 24(1): 30-38.
YANG Wan-xia, PAN Yun-yan, LI Xue, GUAN Pei-wen, YOU Chong-ge. Bioinformatics Analysis of CDK1 Expression and Pancreatic Cancer Prognosis. Life Science Research, 2020, 24(1): 30-38.
2020, Vol. 24 
