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Screening and validating the core biomarkers in patients with pancreatic ductal adenocarcinoma

Department of Oncology, The Second Affiliated Hospital of Jiaxing University, Jiaxing 314000, China

Special Issues: Advanced Big Data Analysis for Precision Medicine

Pancreatic ductal adenocarcinoma (PAAD) is one of the most common malignant tumors in digestive system. To find the new therapeutic targets and explore potential mechanisms underlying PAAD, the bioinformatics has been performed in our study. The PAAD gene expression profile GSE28735 was chosen to analyze the differentially expressed genes (DEGs) between PAAD carcinoma tissues and normal adjacent tissues from 45 patients with PAAD. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, a protein-protein interaction (PPI) network was also constructed to help us screen the top 20 hub genes in this profile and demonstrated the underlying interactions among them. The Gene Expression Profiling Interactive Analysis (GEPIA) was further performed in order to valid the mRNA levels of top5 up-regulated and top5 down-regualted DEGs, apart from exploring their association with survival rate as well as tumor stage. Finally, Q-PCR was further employed to valid the top5 up-regulated and top5 down-regulated genes in patients with PAAD. In our study, there were a total of 444 DEGs captured (271 up-regulated genes and 173 down-regulated genes). Among these DEGs, the top5 up-regulated genes were CEACAM5, SLC6A14, LAMC2, GALNT5 and TSPAN1 while the top5 down-regulated genes were GP2, CTRC, IAPP, PNLIPRP2 and PNLIPRP1. GO analysis disclosed that the DEGs were predominantly enriched in cell adhesion, lipid metabolism, integrin binding, proteolysis and calcium ion binding. KEGG analysis disclosed that the enriched pathway included pancreatic secretion, protein digestion and absorption, fat digestion and absorption, ECM-receptor interaction, focal adhesion and PI3K-Akt signaling pathway. Survival analysis unveiled that the high expression levels of SLC6A14, GALNT5 and TSPAN1 may correlate with the poor prognosis while high expression levels of IAPP may contribute to a better prognosis in patients with PAAD. Additionally, the levels of CEACAM5, SLC6A14, LAMC2 and GALNT5 were also associated with tumor stage. Furthermore, according to the connectivity degree of these DEGs, we selected the top20 hub genes, namely ALB, FN1, EGF, MMP9, COL1A1, COL3A1, FBN1, CXCL12, POSTIN, BGN, VCAN, THBS2, KRT19, MET, MMP14, COL5A2, GCG, MUC1, MMP1 and CPB1, which were expected to be promising therapeutic targets in PAAD. Collectively, our bioinformatics analysis showed that DEGs and hub genes may be defined as new biomarkers for diagnosis and for guiding the therapeutic strategies of PAAD.
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Keywords pancreatic ductal adenocarcinoma; biomarkers; hub genes; bioinformatics analysis

Citation: Yan Li, Yuzhang Zhu, Guiping Dai, Dongjuan Wu, Zhenzhen Gao, Lei Zhang, Yaohua Fan. Screening and validating the core biomarkers in patients with pancreatic ductal adenocarcinoma. Mathematical Biosciences and Engineering, 2020, 17(1): 910-927. doi: 10.3934/mbe.2020048


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