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Genetic 'roadmap' charts links between drugs and human disease

A research team led by scientists at the Broad Institute of MIT and Harvard announced today the development of a new kind of genetic "roadmap" that can connect human diseases with potential drugs to treat them, as well as predict how new drugs work in human cells. Called the "Connectivity Map," the new tool and its uses are described in the September 29 issue of Science and in separate publications in the September 28 immediate early edition of Cancer Cell. The three papers show the map's ability to accurately predict the molecular actions of novel therapeutic compounds and to suggest ways that existing drugs can be newly applied to treat diseases such as cancer. Based on the results, the papers propose a public project to expand this initial human Connectivity Map -- in the spirit of the Human Genome Project -- to accelerate the search for new drugs to treat disease.

"The Connectivity Map works much like a Google search to discover connections among drugs and diseases," said senior author Todd Golub, the director of the Broad Institute's Cancer program, an investigator at the Dana-Farber Cancer Institute, an associate professor of pediatrics at Harvard Medical School, and an investigator at the Howard Hughes Medical Institute. "These connections are notoriously difficult to find in part because drugs and diseases are characterized in completely different scientific languages."

A key challenge in biomedicine is to connect each human disease with drugs that effectively treat it and to understand the molecular basis for such drugs' effects. To solve this problem systematically, the scientists described the effects of drugs and diseases in the common language of "genomic signatures," meaning the full complement of genes that the drugs turn on and off.

To create a first-generation Connectivity Map, the scientists measured the genomic signatures of more than 160 drugs and other biologically active compounds. They next developed a computer progr
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Source:Broad Institute of MIT and Harvard


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