Original Article Protein-protein interaction (PPI) network and significant gene analysis of breast cancer

Weihua Ren, Yawei Li, Shuangting Wu, Hongbo Feng, Rui Li
2016 Int J Clin Exp Med   unpublished
The incidence of breast cancer is one of the highest female malignant tumors. While, the early diagnosis and treatment of breast cancer with microarray technology are requisite in breast cancer research. We aimed to identify new potential signaling pathways and key genes in breast cancer. The transcription profile of GSE54002 was downloaded from Gene Expression Omnibus (GEO) database, including 417 breast cancer and 16 healthy samples. The differentially expressed genes (DEGs) between cancer
more » ... healthy group were screened with non-paired t-test and analyzed by Cluster 3.0 software. We used the DAVID online tools to enrich the Gene Ontology function and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of significantly up-and down-regulated genes. After construction of interaction network of proteins encoded by DEGs, the topological properties of networks and function modules were analyzed with Cytoscape. A total of 789 DEGs were identified in breast cancer samples compared to normal tissue samples, including 257 up-regulated and 532 down-regulated genes. In GO terms, the up-regulated genes are mainly related with cell cycle and interaction of extracellular matrix; While in KEGG pathways , up-regulated genes were enriched in cell cycle pathway and ECM-receptor interaction pathway. In addition, the transcription factor FOS and its multiple downstream regulatory factors were highly expressed in cancer tissue. The discovery of the DEGs with high expression in enrichment analysis might help understand the mechanism of breast cancer. Moreover, the key factors we predicted in development of breast cancer could provide references for the diagnosis and treatment of this disease.