Lv Jinli, Zhu Bo, Zhang Liang, Xie Qichao, Zhuo Wenlei
Institute of Cancer, Xinqiao Hospital, Third Military Medical University Chongqing 400037, China ; Department of General Surgery, The 153th Central Hospital of PLA Zhengzhou 450007, Henan, China.
Institute of Cancer, Xinqiao Hospital, Third Military Medical University Chongqing 400037, China.
Int J Clin Exp Med. 2015 Feb 15;8(2):2317-25. eCollection 2015.
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.
索拉非尼是一种新型口服多激酶抑制剂，可阻断多种关键致癌信号通路，具有生存获益，成为治疗肝细胞癌（HCC）患者的一线药物。然而，对索拉非尼获得性耐药导致获益有限。在本研究中，我们旨在通过生物信息学方法探索可能克服索拉非尼耐药的药物。从基因表达综合数据库（GEO）下载了HCC-3sp（获得性索拉非尼耐药）和HCC-3p（索拉非尼敏感）细胞系的基因表达谱。然后，使用dChip软件选择差异表达基因（DEGs）。此外，通过DAVID数据库进行基因本体（GO）和通路富集分析。最后，利用连通性图谱预测逆转索拉非尼耐药的潜在化学物质。结果，共鉴定出541个DEGs，它们与细胞外基质、细胞黏附和结合相关项目有关。KEGG通路分析表明有8条功能失调的通路被富集。最后，筛选出孕烯醇酮和洛莫司汀等几种小分子作为能够克服索拉非尼耐药的潜在治疗药物。这些数据确定了一些治疗索拉非尼耐药的潜在小分子药物，并为HCC的研究和治疗提供了一种新策略。
