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  3. Facilitating Anti-Cancer Combinatorial Drug Discovery by Targeting Epistatic Disease Genes

Facilitating Anti-Cancer Combinatorial Drug Discovery by Targeting Epistatic Disease Genes

  • Molecules. 2018 Mar 23;23(4):736. doi: 10.3390/molecules23040736.
Yuan Quan 1,  Meng-Yuan Liu 2,  Ye-Mao Liu 3,  Li-Da Zhu 4,  Yu-Shan Wu 5,  Zhi-Hui Luo 6,  Xiu-Zhen Zhang 7,  Shi-Zhong Xu 8,  Qing-Yong Yang 9,  Hong-Yu Zhang 10
Affiliations

Affiliations

  • 1 Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China. qyuan@webmail.hzau.edu.cn.
  • 2 Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China. liumengyuan2017@outlook.com.
  • 3 Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China. lym17@webmail.hzau.edu.cn.
  • 4 Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China. zhulinda@hotmail.com.
  • 5 School of Life Sciences, Shandong University of Technology; No. 12 Zhangzhou Road, Zibo 255049, China. wuyushanna@126.com.
  • 6 Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China. luozhihui@simm.ac.cn.
  • 7 School of Life Sciences, Shandong University of Technology; No. 12 Zhangzhou Road, Zibo 255049, China. sleevexz@sdut.edu.cn.
  • 8 Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA. shizhong.xu@ucr.edu.
  • 9 Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China. yqy@mail.hzau.edu.cn.
  • 10 Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China. zhy630@mail.hzau.edu.cn.
PMID: 29570606 DOI: 10.3390/molecules23040736
Abstract

Due to synergistic effects, combinatorial drugs are widely used for treating complex diseases. However, combining drugs and making them synergetic remains a challenge. Genetic disease genes are considered a promising source of drug targets with important implications for navigating the drug space. Most diseases are not caused by a single pathogenic factor, but by multiple disease genes, in particular, interacting disease genes. Thus, it is reasonable to consider that targeting epistatic disease genes may enhance the therapeutic effects of combinatorial drugs. In this study, synthetic lethality gene pairs of tumors, similar to epistatic disease genes, were first targeted by combinatorial drugs, resulting in the enrichment of the combinatorial drugs with Cancer treatment, which verified our hypothesis. Then, conventional epistasis detection software was used to identify epistatic disease genes from the genome wide association studies (GWAS) dataset. Furthermore, combinatorial drugs were predicted by targeting these epistatic disease genes, and five combinations were proven to have synergistic anti-cancer effects on MCF-7 cells through cell cytotoxicity assay. Combined with the three-dimensional (3D) genome-based method, the epistatic disease genes were filtered and were more closely related to disease. By targeting the filtered gene pairs, the efficiency of combinatorial drug discovery has been further improved.

Keywords

3D genome; GWAS; combinatorial drug; drug target; epistasis.

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