Breast cancer (BC) is a serious risk to women's health and became the nation's top cause of death in women. To date, the potential to treat advanced cancer is constrained by a lack of understanding of the precise hub genes. The objective of this study would be to classify hub genes and identify novel biomarkers for designing therapeutic drugs as well as establish prognostically important DEG within upregulated and downregulated expression. There is a total of 433 genes breast cancer which retrieved from GEO database. A proteinprotein interaction (PPI) network was constructed for network analysis using Cytoscape. CytoHubba app in Cytoscape discovered the 6 hub genes. Moreover, GO and KEGG pathway analysis mainly involved cellular component, biological process, biological pathway and molecular function using DAVID database. MYLK, MYH11, PK5, ACTA2, TAGLN and CNN1 were recognized as the hub genes in the network based on MCC scoring method. A comprehensive perspective was provided by the bioinformatics analysis such as Cytoscape, GEO, DAVID to understand the mechanism underlying breast cancer development