Spotlight on Research
CGAP Is a Gateway to New Exploration and Discovery
NCI's Cancer Genome Anatomy Project (CGAP) was established in 1997 to determine the gene expression profiles of normal, precancer, and cancer cells and to provide public access to this information for all cancer researchers.
The project is now providing:
- A wealth of human and mouse genomic data
- Informatics tools to query and analyze the data
- Information on methods
- Access to biologic materials developed through the project
With public data and analysis tools, researchers can now find "in silico" answers to biological questions in a fraction of the time it used to take in the lab.
Researchers have started mining the CGAP databases and are:
- Discovering new, potentially cancer-causing genes
- Identifying candidates for molecular targeting research
- Helping to build microarrays for cancer cell signature research
For example:
- Because cancer is such a complex disease, finding the many cancer-causing genes involved and understanding their role is crucial to developing new treatments to combat the disease. Cancer researchers at Duke University Medical Center, in collaboration with CGAP, examined the expression of more than 24,000 genes in the oxygen-deprived (hypoxic) cells of glioblastoma multiforme, a form of brain cancer. They identified ten genes believed to play a significant role in allowing this tumor to thrive under hypoxic conditions. Scientists are working to find the function of these genes with the long-term goal of developing targeted inhibitors that may be used in formulations against the cancer.
- Until recently, diffuse large B-cell lymphoma (DLBCL) had been traditionally classified as a single cancer, but patients suffering from this disease show diverse responses to chemotherapy. Only 40% of patients respond well to treatment, while the remainder succumb quickly to the disease. Using CGAP data, NCI and NCI-supported scientists developed a microarray called a lymphochip that contained 18,000 genes, which included those preferentially expressed in lymphoid cells as well as in cancer and the immune system. The expression analysis showed that DLBCL can be categorized into two distinct classes that broadly correlate with the clinical outcomes.
These results have already begun to contribute to our goal to improve detection, diagnosis and treatment of cancer. Since these discoveries come from early application of CGAP resources, CGAP's impact on the future of cancer research and clinical advances promises to be substantial.
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