Objective：Using network databases and bioinformatics technology platforms，analyze the data of Umbilical cord mesenchymal stem cells （UC-MSCs） in the treatment of breast cancer （BC），and predict the core target of UC-MSCs in the treatment of BC. Methods：Use the GEO database in NCBI （www.ncbi.com.cn） to search the original data set GSE64827 of UC-MSCs treatment of BC. Then use R software to standardize the data to obtain differential genes；use STRING database to perform protein-protein interaction function network analysis and topology analysis，use DAVID online tools and R software to carry out GO enrichment analysis and KEGG pathway analysis of related genes. Results：Using R software to screen out 11 differential genes，do network analysis and topological analysis of their protein-protein interactions （relevant genes with confidence greater than or equal to 0.7），suggesting the association degree of ALDOC，IGFBP3，DDIT4 and PFKFB4 is higher. GO analysis and annotation obtained 3 biological processes，namely fructose metabolism process，glycolysis process and hypoxia reaction process. The main genes involved are PFKFB4，ALDOC，DDIT4 and CA9. KEGG pathway analysis yielded a fructose and mannose metabolic pathway，involving genes ALDOC and PFKFB4. Conclusion：This study uses network databases and bioinformatics technology platforms to predict that the core targets of UC-MSCs for breast cancer treatment are ALDOC，PFKFB4 and DDIT4.