Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

CCGD

General information

URL: http://ccgd-starrlab.oit.umn.edu
Full name: Candidate Cancer Gene Database
Description: The Candidate Cancer Gene Database (CCGD) was developed to disseminate the results of transposon-based forward genetic screens in mice that identify candidate cancer genes.
Year founded: 2015
Last update: 2018-11-28
Version: v1.0
Accessibility:
Accessible
Country/Region: United States

Classification & Tag

Data type:
DNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: University of Minnesota
Address: University of Minnesota, MMC 395 420 Delaware St SE Minneapolis,MN 55455,USA
City: Minneapolis
Province/State: MN
Country/Region: United States
Contact name (PI/Team): Timothy K. Starr
Contact email (PI/Helpdesk): star0044@umn.edu

Publications

25190456
The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice. [PMID: 25190456]
Abbott KL, Nyre ET, Abrahante J, Ho YY, Isaksson Vogel R, Starr TK.

Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleic Acids Res. 2015:43(Database issue) | 87 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
1635/6895 (76.302%)
Health and medicine:
402/1738 (76.928%)
1635
Total Rank
83
Citations
8.3
z-index

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Record metadata

Created on: 2015-06-20
Curated by:
[2018-11-27]
Mengwei Li [2016-03-31]
Mengwei Li [2016-03-29]
Zhang Zhang [2015-12-31]
Mengwei Li [2015-12-01]
Mengwei Li [2015-06-27]