Quan Shen, Miao Yu, Jiang-Kun Jia, Wen-Xi Li, Yu-Wei Tian, Huan-Zhou Xue
Department of Hepatobiliary Pancreatic Surgery, Henan Provincial People’s Hospital, Zhengzhou, Henan, China (mainland)
Med Sci Monit 2018; 24: MOL2368-2376
Available online: 2018-04-19
We aimed to identify pivotal genes and pathways involved in pancreatic ductal adenocarcinoma (PDAC), and explore possible molecular markers for the early diagnosis of the disease.
MATERIAL AND METHODS: The array data of GSE74629, including 34 PDAC samples and 16 healthy samples, was downloaded from GEO (Gene Expression Omnibus) database. Then, the DEGs (differentially expressed genes) in PDAC samples were compared with healthy samples using limma (linear models for microarray). Gene functional interaction networks were analyzed with Cytoscape and ReactomeFIViz. PPI networks were constructed with Cytoscape software. In addition, PPI (protein-protein interaction) network clustering modules were analyzed with ClusterONE, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses for modules were performed.
RESULTS: A total of 630 upregulated and 1,002 downregulated DEGs were identified in PDAC samples compared with healthy samples. Some ribosomal protein genes with higher average correlation in module 0 were enriched in the ribosome pathway. NUP107 (nucleoporin 107 kDa) and NUP160 (nucleoporin 160 kDa) were enriched in module 3. HNRNPU (heterogeneous nuclear ribonucleoprotein U) with higher average correlation in module 8 was enriched in the spliceosome pathway. The ribosome pathway and the spliceosome pathway were significantly enriched in cluster 1 and cluster 2, respectively.
CONCLUSIONS: Ribosomal protein genes Nup170, Nup160, and HNRNPU, and the ribosome pathway as well as the spliceosome pathway may play important roles in PDAC progression. In addition, ribosomal protein genes Nup170, Nup160, and HNRNPU may be used as possible molecular markers for the early diagnosis of the disease.
Keywords: Carcinoma, Pancreatic Ductal, Chemistry, Bioinorganic, Community Networks