A Gene Co-Expression Network-Based Drug Repositioning Approach Identifies Candidates for Treatment of Hepatocellular Carcinoma

Cancers

Jens Nielsen¹  Hasan Turkez²  Sajda Ashraf³  Koeun Shong⁴  Adil Mardinoglu⁴  Woonghee Kim⁴  Xiangyu Li⁴  Cheng Zhang⁴  Mengnan Shi⁴  Saeed Shoaie⁴  Mathias Uhlen⁴  Meng Yuan⁴ 

[1] Department of Biology and Biological Engineering, Chalmers University of Technology, SE-41296 Gothenburg, Sweden;Department of Medical Biology, Faculty of Medicine, Atatürk University, Erzurum 25240, Turkey;Heka Lab, Camlik Mah. Hearty, Sk. No:4 Heka Human Plaza Umraniye, Istanbul 34774, Turkey;Science for Life Laboratory, KTH—Royal Institute of Technology, SE-17165 Stockholm, Sweden;

关键词: systems biology;    co-expression network;    survival analysis;    drug repositioning;    hepatocellular carcinoma (HCC);   

DOI  :  10.3390/cancers14061573

来源: DOAJ

【 摘 要 】

Hepatocellular carcinoma (HCC) is a malignant liver cancer that continues to increase deaths worldwide owing to limited therapies and treatments. Computational drug repurposing is a promising strategy to discover potential indications of existing drugs. In this study, we present a systematic drug repositioning method based on comprehensive integration of molecular signatures in liver cancer tissue and cell lines. First, we identify robust prognostic genes and two gene co-expression modules enriched in unfavorable prognostic genes based on two independent HCC cohorts, which showed great consistency in functional and network topology. Then, we screen 10 genes as potential target genes for HCC on the bias of network topology analysis in these two modules. Further, we perform a drug repositioning method by integrating the shRNA and drug perturbation of liver cancer cell lines and identifying potential drugs for every target gene. Finally, we evaluate the effects of the candidate drugs through an in vitro model and observe that two identified drugs inhibited the protein levels of their corresponding target genes and cell migration, also showing great binding affinity in protein docking analysis. Our study demonstrates the usefulness and efficiency of network-based drug repositioning approach to discover potential drugs for cancer treatment and precision medicine approach.

【 授权许可】

Unknown