Lapatinib, a novel oral dual tyrosine kinase inhibitor blocking HER1 and HER2 pathways, has presented beneficial effects on breast cancer with positive HER2. However, its efficacy is largely limited by the occurrence of acquired drug resistance. In this study, we aimed to explore the underlying molecular mechanisms of Lapatinib resistance using bioinformatics strategies. The gene expression profile of SKBR3-R (acquired Lapatinib-resistant) and SKBR3 (Lapatinib-sensitive) cell line was downloaded from gene expression omnibus database. Then, the differentially expressed genes (DEGs) were selected using dChip software. Furthermore, gene ontology (GO) and pathway enrichment analyses were carried out by using DAVID database. Finally, the protein-protein interaction network was constructed, and the hub genes in the network were analyzed by using STRING database. A total of 300 DEGs, such as HSPA5, MAP1LC3A and RASSF2, were screened out. GO functional enrichment analysis showed that the genes were associated with cell membrane component-related, stimulus-related and binding-related items. KEGG pathway analysis indicated that three dysfunctional pathways, including PPAR signaling pathway, cytokine-cytokine receptor interaction and pathways in cancer, were enriched. Protein-protein interaction network construction revealed that some hub genes, such as PPARG, TGFBI, TGFBR2, TIMP1, CTGF, UBA52 and JUN, might have an association with Lapatinib resistance. The present study offered new insights into the molecular mechanisms of Lapatinib resistance and identified a series of important hub genes that have the potential to be the targets for treatment of Lapatinib-resistant breast cancer.
Keywords: Breast cancer; Differentially expressed genes; Dysfunctional pathway; Function enrichment analysis; Lapatinib resistance.