Detection and screening of small molecule agents for overcoming Sorafenib resistance of hepatocellular carcinoma: a bioinformatics study.

Sorafenib, a novel orally-available multikinase inhibitor blocking several crucial oncogenic signaling pathways, presented survival benefits and became the first-line drug for treatment of patients with Hepatocellular carcinoma (HCC). However, the acquired resistance to Sorafenib resulted in limited benefits. In this study, we aimed to explore possible agents that might overcome Sorafenib resistance by bioinformatics methods. The gene expression profiles of HCC-3sp (acquired Sorafenib-resistance) and HCC-3p (Sorafenib-sensitive) cell line were downloaded from Gene Expression Omnibus (GEO) database. Then, the differentially expressed genes (DEGs) were selected using dChip software. Furthermore, Gene Ontology (GO) and pathway enrichment analyses were performed by DAVID database. Finally, the Connectivity Map was utilized to predict potential chemicals for reversing Sorafenib resistance. Consequently, a total of 541 DEGs were identified, which were associated with cell extracellular matrix, cell adhesion and binding-related items. KEGG pathway analysis indicated that 8 dysfunctional pathways were enriched. Finally, several small molecules, such as pregnenolone and lomustine, were screened out as potential therapeutic agents capable of overcoming Sorafenib resistance. The data identified some potential small molecule drugs for treatment of Sorafenib resistance and offered a novel strategy for investigation and treatments of HCC.