Identification of driver copy number alterations in diverse cancer types and application in drug repositioning

Wenbin Zhou; Zhangxiang Zhao; Ruiping Wang; Yue Han; Chengyu Wang; Fan Yang; Ya Han; Haihai Liang; Lishuang Qi; Chenguang Wang; Zheng Guo; Yunyan Gu

doi:10.1002/1878-0261.12112

Identification of driver copy number alterations in diverse cancer types and application in drug repositioning

Mol Oncol. 2017 Oct;11(10):1459-1474. doi: 10.1002/1878-0261.12112. Epub 2017 Aug 3.

Authors

Wenbin Zhou¹, Zhangxiang Zhao^{1

2}, Ruiping Wang¹, Yue Han¹, Chengyu Wang^{1

2}, Fan Yang^{1

2}, Ya Han^{1

2}, Haihai Liang³, Lishuang Qi¹, Chenguang Wang¹, Zheng Guo^{1

4

5}, Yunyan Gu^{1

2}

Affiliations

¹ Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, China.
² Training Center for Student Innovation and Entrepreneurship Education, Harbin Medical University, China.
³ Department of Pharmacology, Harbin Medical University, China.
⁴ Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
⁵ Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China.

Abstract

Results from numerous studies suggest an important role for somatic copy number alterations (SCNAs) in cancer progression. Our work aimed to identify the drivers (oncogenes or tumor suppressor genes) that reside in recurrently aberrant genomic regions, including a large number of genes or non-coding genes, which remain a challenge for decoding the SCNAs involved in carcinogenesis. Here, we propose a new approach to comprehensively identify drivers, using 8740 cancer samples involving 18 cancer types from The Cancer Genome Atlas (TCGA). On average, 84 drivers were revealed for each cancer type, including protein-coding genes, long non-coding RNAs (lncRNA) and microRNAs (miRNAs). We demonstrated that the drivers showed significant attributes of cancer genes, and significantly overlapped with known cancer genes, including MYC, CCND1 and ERBB2 in breast cancer, and the lncRNA PVT1 in multiple cancer types. Pan-cancer analyses of drivers revealed specificity and commonality across cancer types, and the non-coding drivers showed a higher cancer-type specificity than that of coding drivers. Some cancer types from different tissue origins were found to converge to a high similarity because of the significant overlap of drivers, such as head and neck squamous cell carcinoma (HNSC) and lung squamous cell carcinoma (LUSC). The lncRNA SOX2-OT, a common driver of HNSC and LUSC, showed significant expression correlation with the oncogene SOX2. In addition, because some drivers are common in multiple cancer types and have been targeted by known drugs, we found that some drugs could be successfully repositioned, as validated by the datasets of drug response assays in cell lines. Our work reported a new method to comprehensively identify drivers in SCNAs across diverse cancer types, providing a feasible strategy for cancer drug repositioning as well as novel findings regarding cancer-associated non-coding RNA discovery.

Keywords: copy number alterations; driver; drug repositioning; lncRNAs.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

DNA Copy Number Variations*
Drug Repositioning* / methods
Gene Expression Regulation, Neoplastic*
Genomics / methods
Humans
MicroRNAs / genetics
Neoplasms / drug therapy
Neoplasms / genetics*
Oncogenes
RNA, Long Noncoding / genetics

Substances

MicroRNAs
RNA, Long Noncoding