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Updated: May 14, 2026
A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
Published on: April 18, 2025
Expression profiles analysis of pancreatic cancer
1Department of Gastrointestinal Surgery, Shanghai Changzheng Hospital affiliated to the Second Military Medical University, Shanghai, China.
Background:
[Corrected] Pancreatic cancer is the fourth most common cause of cancer-related deaths across the globe and has a poor prognosis.
Aim:
To investigate the characteristics of genomic expression profiles of pancreatic cancer and screen differentially expressed genes.
Materials And Methods:
Using GSE16515 dataset downloaded from GEO (Gene Expression Omnibus) database, we first screened the differentially expressed genes (DEGs) in pancreatic cancer by packages in R language. The key functions of DEGs were investigated by GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis. The potential functionally important SNP (Single Nucleotide Polymorphism) was selected from the dbSNP database.
Results:
A total of 1270 DEGs were identified. Most of them were predicted to be involved in pancreatic cancer development by sequence variant. Six genes (CDC42, STAT1, RALA, BCL2L1, TGFA, and EGF) were enriched in the known pancreatic cancer pathway. All these six genes had SNP, usually mutation at A/G and C/T point.
Conclusions:
Our results provide some underlying biomarkers for early diagnosis of pancreatic cancer.
