Bioinformatics-Ｂased Analysis and Screening of
Differentially Expressed Genes in Pancreatic Cancer

Abstract

Abstract: Objective：To analyze the information of GEO database by bioinformatics， and explore the key genes and signal pathways of pancreatic cancer. Methods：The gene expression profile chip GSE107610 of pancreatic cancer was downloaded， and the differentially expressed genes were statistically analyzed by R software， so as to study the related biological processes， signal pathways and protein-protein interaction. The protein-protein interaction network diagram was constructed by Cytoscape software， the differences of samples were verified by hematoxylin and eosin staining， and the four core genes screened out were verified by real-time fluorescence quantitative polymerase chain reaction. Results：Among 71 differentially expressed genes， 17 were up-regulated and 54 were down-regulated. The functions of these genes were predominantly involved in protein hydrolysis， alcohol metabolism， exogenous metabolism， digestion， immune response regulation and other processes. The results of the GEO database analysis were consistent with the expression of key genes at the mRNA levels. Conclusion：Using bioinformatics technology， the differentially expressed genes related to the occurrence and development of pancreatic cancer have been successfully discovered. It has been verified that the expression levels of the above differentially expressed genes are consistent in human pancreatic cancer tissues. This study provides a new idea for determining early diagnostic markers and therapeutic targets of pancreatic cancer.

Key words: font-family:Times New Roman, ">pancreatic cancerfont-family:Times New Roman, ">, font-family:Times New Roman, "> bioinformaticsfont-family:Times New Roman, ">, font-family:Times New Roman, "> GEO databasefont-family:Times New Roman, ">, font-family:Times New Roman, "> differentially expressed genes

CLC Number:

Li Weiqian, Chen Yiming, Zhang Wenting, Su Yingzhen, Shuai Hongyan, Yu Xin.

Bioinformatics-Ｂased Analysis and Screening of Differentially Expressed Genes in Pancreatic Cancer [J]. Journal of Dali University, 2023, 8(2): 24-30.

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Bioinformatics-Ｂased Analysis and Screening of Differentially Expressed Genes in Pancreatic Cancer

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