The high connectivity of network confirms that the proteins and metabolites play a significant role in the same pathways and interact with each other. The proteins with highest connectivity are EGFR (18), STAT3 and CTNNB1 (17), CDH1, ERBB3, and TP53 (14), PDGFRA (13), the group of four plateletderived growth factors (PDGFA, PDGFB, PDGFC and PDGFD) and VEGFC (average connectivity 10.4) have a close relationship with each other and have a large impact on the disorder (Figure ). In FMC, these genes play a role in tumor growth, invasion, and metastasis. ERBB2 (also known as HER2) is a receptor tyrosine kinase that is often overexpressed in breast cancer and has been implicated in the development of FMC as well. PDGFA, PDGFB, PDGFC and PDGFD are ligands for the platelet-derived growth factor receptors (PDGFRA and PDGFRB), which are involved in cell proliferation, migration, and survival. EGFR (epidermal growth factor receptor) and ERBB3 (also known as HER3) are also receptor tyrosine kinases that have been implicated in the development of cancer. FLT4 (also known as VEGFR3) is a receptor for vascular endothelial growth factor (VEGF) C and D, which are involved in lymphangiogenesis (the formation of new lymphatic vessels). FIGF (also known as VEGFD) is a member of the VEGF family that has been implicated in tumor growth and lymphangiogenesis. CDH1 (cadherin 1) plays an essential role in epithelial cell adherence. The CDH1 mutation puts females at risk for a certain form of breast cancer called lobular breast cancer. Together ERBB2 and CDH1 mutations show a significantly worse prognosis to patients compared to their counterparts without such a mutation. In feline mammary cancer, these genes may be dysregulated, leading to abnormal activation of signaling pathways that promote tumor growth and metastasis. Using enrichment analysis, additional five proteins were elucidated by STRINGdb-CBL, GRB2, NOTCH1, PDGFRB, and TEK (Figure ). Network presented in Figure shows high-evidence associations of the proteins coded by selected genes. The additional proteins are also highly associated with the presented network (Figure ). The average connection association with added proteins increased from 7.40 to 10.46. Such an increase demonstrates that the added genes play a significant role in the organization of significantly connected protein network involved in cancer development. This fact points to these proteins as preferable targets for drug design.