Journal of Shanghai Jiao Tong University (Medical Science) >

2021 , Vol. 41 >Issue 5: 571 - 578

DOI: https://doi.org/10.3969/j.issn.1674-8115.2021.05.003

Basic research

Identification of core genes in pancreatic cancer progression by bioinformatics analysis

  • Lu-di YANG ,
  • Gao-ming WANG ,
  • Ren-hao HU ,
  • Xiao-hua JIANG ,
  • Ran CUI
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  • 1.Ruijin College of Clinical Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
    2.Department of General Surgery, East Hospital Affiliated Tongji University, Shanghai 200120, China

Online published: 2021-05-27

Supported by

Research Project of Shanghai Municipal Health Commission(20204Y0302)

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Abstract

Objective

·To select pancreatic cancer progression-related core genes and key pathways.

Methods

·The dataset GSE28735 for pancreatic cancer was obtained by searching and screening in the Gene Expression Omnibus (GEO) database. Genes in 45 cases of cancer tissues and 45 cases of normal tissues adjacent to cancer were extracted by GEO2R and combined with RStudio to screen and visualize differentially expressed genes (DEGs). Genes with significant differential expression were analyzed by gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis through the gene utilization function annotation online tool DAVID. The protein-protein interaction (PPI) network was constructed by using the interactive gene retrieval tool, STRING and Cytoscape, to further screen core genes based on the node degree value. The relationship between the expression levels of core genes and overall survival (OS), disease-free survival (DFS) and tumor stage of 179 cases of patients was analyzed through the gene expression profile analysis database GEPIA.

Results

·A total of 131 DEGs were screened from the dataset GSE28735, including 115 up-regulated genes and 16 down-regulated genes. GO function enrichment analysis showed that DEGs were mainly enriched in cell adhesion, plasma membrane, and protein binding. KEGG pathway enrichment suggested that phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) was the main signaling pathway for DEG enrichment. Five core genes, fibronectin1 (FN1), mesenchymal to epithelial transition factor (MET), polyclonal antibody to laminin β3 (LAMB3), laminin subunit α3 (LAMA3), and integrin subunit α3 (ITGA3),were obtained through PPI network screening. The expression levels of MET, LAMA3, LAMB3 and ITGA3 were associated with OS of patients, and the expression levels of MET, LAMB3 and ITGA3 were associated with DFS. The prognosis of low gene expression group was significantly better than that of high gene expression group. There were significant differences in the expression levels of FN1, MET, LAMA3 and LAMB3 in the different stages of pancreatic cancer.

Conclusion

·The abnormal expression of FN1, MET, LAMB3, LAMA3 and ITGA3 is related to the changes of cell adhesion, plasma membrane component, protein binding function and PI3K/Akt pathway. The increased expression of MET and LAMB3 may predict poor prognosis of patients with pancreatic cancer.

Key words： pancreatic cancer; bioinformatics; differentially expressed gene; tumorigenesis

Cite this article

Lu-di YANG , Gao-ming WANG , Ren-hao HU , Xiao-hua JIANG , Ran CUI . Identification of core genes in pancreatic cancer progression by bioinformatics analysis[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2021 , 41(5) : 571 -578 . DOI: 10.3969/j.issn.1674-8115.2021.05.003

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