Identifying Differentially Expressed Genes and Screening Small Molecule Drugs for Lapatinib-resistance of Breast Cancer by a Bioinformatics Strategy

Background: Lapatinib, a dual tyrosine kinase inhibitor that interrupts the epidermal growth factor receptor(EGFR) and HER2/neu pathways, has been indicated to have significant efficacy in treating HER2-positivebreast cancer. However, acquired drug resistance has become a very serious clinical problem that hampers theuse of this agent. In this study, we aimed to screen small molecule drugs that might reverse lapatinib-resistanceof breast cancer by exploring differentially expressed genes (DEGs) via a bioinformatics method. Materials and
Methods: We downloaded the gene expression profile of BT474-J4 (acquired lapatinib-resistant) and BT474(lapatinib-sensitive) cell lines from the Gene Expression Omnibus (GEO) database and selected differentiallyexpressed genes (DEGs) using dChip software. Then, gene ontology and pathway enrichment analyses wereperformed with the DAVID database. Finally, a connectivity map was utilized for predicting potential chemicalsthat reverse lapatinib-resistance.
Results: A total of 1, 657 DEGs were obtained. These DEGs were enrichedin 10 pathways, including cell cycling, regulation of actin cytoskeleton and focal adhesion associate examples.In addition, several small molecules were screened as the potential therapeutic agents capable of overcominglapatinib-resistance.
Conclusions: The results of our analysis provided a novel strategy for investigating themechanism of lapatinib-resistance and identifying potential small molecule drugs for breast cancer treatment.