Network Pharmacology Approach: Analysing Pathways in Breast Cancer

Breast cancer is the most commonly occurring cancer in women. However, the efficacy and utility of the available drug therapies are limited. The objective of the present study was to determine the genes and molecular pathways associated with breast cancer by using computational tools. In this study, we used text mining and GeneCodis to mine genes which were highly related to breast cancer. Protein‑protein interaction (PPI) analysis was performed by using STRING and Cytoscape. In this present study, about 166 entries were taken from uniport database of breast cancer. After deleting the duplicate genes only 7 genes were selected for the gene ontology analysis. GO analysis showed that there were 80 pathways related to the Biological Process (BP) and 10 KEGG pathways obtained. Using STRING database three key target proteins were obtained(BRCA1, BRCA2 and RBBP6 ).To visualize the interaction between the target proteins Cytoscape 3.7.1 software were used. The degree and betweenness were measured using centiscape app. In conclusion, investigating candidate medications that target the genes or pathways relevant to breast cancer using in silico text mining and pathway analysis technologies.