Genetic Interaction-Based Biomarkers Identification for Drug Resistance and Sensitivity in Cancer Cells

Yue Han; Chengyu Wang; Qi Dong; Tingting Chen; Fan Yang; Yaoyao Liu; Bo Chen; Zhangxiang Zhao; Lishuang Qi; Wenyuan Zhao; Haihai Liang; Zheng Guo; Yunyan Gu

doi:10.1016/j.omtn.2019.07.003

Genetic Interaction-Based Biomarkers Identification for Drug Resistance and Sensitivity in Cancer Cells

Mol Ther Nucleic Acids. 2019 Sep 6:17:688-700. doi: 10.1016/j.omtn.2019.07.003. Epub 2019 Jul 17.

Authors

Yue Han¹, Chengyu Wang¹, Qi Dong¹, Tingting Chen¹, Fan Yang¹, Yaoyao Liu¹, Bo Chen¹, Zhangxiang Zhao¹, Lishuang Qi¹, Wenyuan Zhao¹, Haihai Liang², Zheng Guo³, Yunyan Gu⁴

Affiliations

¹ Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China.
² Department of Pharmacology, College of Pharmacy, Harbin Medical University, Harbin, China.
³ Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China; Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou, China; Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China. Electronic address: guoz@ems.hrbmu.edu.cn.
⁴ Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China. Electronic address: guyunyan@ems.hrbmu.edu.cn.

Abstract

Cancer cells generally harbor hundreds of alterations in the cancer genomes and act as crucial factors in the development and progression of cancer. Gene alterations in the cancer genome form genetic interactions, which affect the response of patients to drugs. We developed an algorithm that mines copy number alteration and whole-exome mutation profiles from The Cancer Genome Atlas (TCGA), as well as functional screen data generated to identify potential genetic interactions for specific cancer types. As a result, 4,529 synthetic viability (SV) interactions and 10,637 synthetic lethality (SL) interactions were detected. The pharmacogenomic datasets revealed that SV interactions induced drug resistance in cancer cells and that SL interactions mediated drug sensitivity in cancer cells. Deletions of HDAC1 and DVL1, both of which participate in the Notch signaling pathway, had an SV effect in cancer cells, and deletion of DVL1 induced resistance to HDAC1 inhibitors in cancer cells. In addition, patients with low expression of both HDAC1 and DVL1 had poor prognosis. Finally, by integrating current reported genetic interactions from other studies, the Cancer Genetic Interaction database (CGIdb) (http://www.medsysbio.org/CGIdb) was constructed, providing a convenient retrieval for genetic interactions in cancer.

Keywords: biomarker; drug resistance; drug sensitivity; synthetic lethality; synthetic viability.