Cancer Genetic Markers for Susceptibility (CGEMS)
As part of the National Cancer Institute’s Cancer Genetic Markers for Susceptibility (CGEMS) project, genome-wide association studies (GWAS) have been conducted to identify common gene variations that influence risks for a number of cancers.
By the end of 2009, more than 550,000 common genetic variants were analyzed through CGEMS, and caBIG® tools are helping to share the study findings. Specifically, these data were made available through the caBIG® Genome-Wide Association Scan software, and the results have been aggregated and made available using caIntegrator.
Researchers conduct GWAS to scan the genomes of thousands of individuals, looking for common genetic variations—known as single nucleotide polymorphisms (SNPs)—that may be associated with specific diseases. The application of genomic and genetic information gained from large-scale research initiatives has improved our understanding of diseases and opened doors to faster and more effective diagnostic and therapeutic agents.
The first public release of a whole genome association study of cancer was completed in 2006 by the CGEMS project. Thus far, the CGEMS project has analyzed more than 550,000 SNPs. Once the SNP data are validated for quality, they are made publicly available on the caGWAS-based CGEMS Data Portal, a Web-based application. The Data Portal provides easy access to pre-computed SNP results and allows researchers to quickly and easily search and download specific data sets or samples.
The first stage of the CGEMS studies uses genome-wide association scans to identify significant SNPs, or "markers," of prostate or breast cancer. The second stage will include epidemiologic studies to test the promising markers found in phase one studies, which will limit false positives and build stronger support for common variants. The phase one data from several complete studies are already available via the Data Portal.
Following initial association analyses such as those being conducted by CGEMS, the next step for investigators is to conduct molecular-functional studies to find out how associated genes contribute to the underlying biology of a given disease.
Select caBIG® applications simplify the process of accessing and sharing GWAS data. The caBIG® Genome-Wide Association Scan is a model GWAS management system that allows researchers to share, integrate, query, and analyze associations between genetic variations and diseases, finding these associations more quickly than any prior analytical approach. caIntegrator is a novel translational informatics platform that allows researchers and bioinformaticians to access and analyze clinical and experimental data across multiple clinical trials and studies.