Objective To screen the lapatinib resistance-related hub genes of breast cancer by bioinformatics initially in order to lay the foundation for further study. Methods We screened and downloaded the gene expression profile data of GSE16179 and GSE38376 from the gene expression omnibus (GEO), and used the limma package of R software to identify the differential expressed genes (DEGs) in breast cancer cells. Then we used the DAVID online website for pathway and function enrichment. With the usage of STRING and Cytoscape, the protein-protein interaction network (PPI) was constructed, and the plug-in app MCODE in Cytoscape was applied to screen hub genes. Then we performed the function enrichment and co-expression analysis of hub genes by DAVID and GeneMANIA. Kaplan-Meier Plotter was used to conduct survival analysis of hub genes. Results A total of 206 kinds of DEGs were screened, and there were 126 kinds of up-regulated genes and 80 kinds of down-regulated genes. DAVID results showed that DEGs were mainly enriched in the biological processes of extracellular space and extracellular region, including extracellular matrix organization, oxygen binding, integrin binding, cell adhesion, positive regulation of angiogenesis, Hippo signaling pathway, transforming growth factor-β signaling pathway and so on. PPI network visualized 74 nodes, the top 10 kinds of hub genes with high connectivity in the gene expression network were screened by MCODE. The Kaplan-Meier Plotter analysis confirmed that 6 of the 10 kinds of hub genes, including peroxisome proliferator activated receptor gamma, transforming growth factor beta receptor 2, tissue inhibitor of metalloproteinase 1, transforming growth factor beta induced, serpin family E member 1, and thrombospondin 1, were correlated with the prognosis of breast cancer patients. Conclusion This 6 kinds of genes may play a significant role in lapatinib resistance of breast cancer.