Identification of therapeutic targets for breast cancer using biological informatics methods

The present study aimed to investigate the modular mechanisms underlying breast cancer and identify potential targets for breast cancer treatment. The differentially expressed genes (DEGs) between breast cancer and normal cells were assessed using microarray data obtained from the Gene Expression Omnibus database. Gene ontology (GO) and pathway enrichment analyses were performed in order to investigate the functions of these DEGs. Subsequently, the protein-protein interaction (PPI) network was constructed using the Cytoscape software. The identified subnetworks were further analyzed using the Molecular Complex Detection plugin. In total, 571 genes (241 upregulated and 330 downregulated genes) were found to be differentially expressed between breast cancer and normal cells. The GO terms significantly enriched by DEGs included cell adhesion, immune response and extracellular region, while the most significant pathways included focal adhesion and complement and coagulation cascade pathways. The PPI network was established with 273 nodes and 718 edges, while fibronectin 1 (FN1, degrees score, 39), interleukin 6 (IL6; degree score, 96) and c-Fos protein (degree score, 32) were identified as the hub proteins in subnetwork 2. These dysregulated genes were found to be involved in the development of breast cancer. The FN1, IL6 and FOS genes may therefore be potential targets in the treatment of breast cancer.