Molecular mechanisms associated with breast cancer based on integrated gene expression profiling by bioinformatics analysis

Abstract

In this study, we aimed to gain more insights into the underlying molecular mechanisms responsible for breast cancer (BC) progression. Three gene expression profiles of human BC were integrated and used to screen the differentially expressed genes (DEGs) between healthy breast samples and BC samples. Protein–protein interaction (PPI) network of DEGs was constructed by mapping DEGs into the Search Tool for the Retrieval of Interacting Genes (STRING) database; then the subnetworks of PPI were constructed with plug-in, MCODE and DEGs in Subnetwork 1 were analysed based on Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway database (http://www.genome.jp/kegg/). In addition, co-expression network of DEGs was established using the Cytoscape. Totalally 931 DEGs were selected, including 340 up-regulated genes and 591 down-regulated genes. KEGG pathway analysis for DEGs in Subnetwork 1 showed that the pathogenesis of BC was associated with cell cycle, oocyte meiosis, progesterone-mediated oocyte maturation and p53 signalling pathways. Meanwhile, the most significant-related DEGs were found by co-expression network analysis of DEGs. In conclusion, CCNG1 might be involved in the progression of BC via inhibiting cell proliferation, and ADAMTS1 might play a crucial role in BC development through the regulation of angiogenesis.