Research Papers:

dbCPG: A web resource for cancer predisposition genes

Ran Wei, Yao Yao, Wu Yang, Chun-Hou Zheng, Min Zhao and Junfeng Xia _

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Oncotarget. 2016; 7:37803-37811. https://doi.org/10.18632/oncotarget.9334

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Ran Wei1, Yao Yao1, Wu Yang2, Chun-Hou Zheng2,3, Min Zhao4, Junfeng Xia1,3

1Institute of Health Sciences, School of Computer Science and Technology, Anhui University, Hefei, Anhui, 230601, China

2College of Electrical Engineering and Automation, Anhui University, Hefei, Anhui, 230601, China

3Co-Innovation Center for Information Support and Assurance Technology, Anhui University, Hefei, Anhui, 230601, China

4School of Engineering, Faculty of Science, Health, Education and Engineering, University of Sunshine Coast, Maroochydore DC, Queensland, 4558, Australia

Correspondence to:

Junfeng Xia, email: [email protected]

Keywords: cancer predisposition gene, database, functional annotation, gene prioritization, network module

Received: November 08, 2015     Accepted: April 28, 2016     Published: May 12, 2016


Cancer predisposition genes (CPGs) are genes in which inherited mutations confer highly or moderately increased risks of developing cancer. Identification of these genes and understanding the biological mechanisms that underlie them is crucial for the prevention, early diagnosis, and optimized management of cancer. Over the past decades, great efforts have been made to identify CPGs through multiple strategies. However, information on these CPGs and their molecular functions is scattered. To address this issue and provide a comprehensive resource for researchers, we developed the Cancer Predisposition Gene Database (dbCPG, Database URL: http://bioinfo.ahu.edu.cn:8080/dbCPG/index.jsp), the first literature-based gene resource for exploring human CPGs. It contains 827 human (724 protein-coding, 23 non-coding, and 80 unknown type genes), 637 rats, and 658 mouse CPGs. Furthermore, data mining was performed to gain insights into the understanding of the CPGs data, including functional annotation, gene prioritization, network analysis of prioritized genes and overlap analysis across multiple cancer types. A user-friendly web interface with multiple browse, search, and upload functions was also developed to facilitate access to the latest information on CPGs. Taken together, the dbCPG database provides a comprehensive data resource for further studies of cancer predisposition genes.

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