Scientists link gene behavior with disease and drugs
Connectivity Map opens doors to early prediction of effective or detrimental drug candidates.
BOSTON—As described in Science and Cancer Cell, researchers have developed a system that correlates gene expression with human diseases and small molecules. In the process, the Connectivity Map (cmap) has opened doors to early prediction of effective or detrimental drug candidates.
"The Connectivity Map works much like a Google search to discover connections among drugs and diseases," said Dr. Todd Golub, director of the cancer program at the Broad Institute, in announcing the project. "These connections are notoriously difficult to find in part because drugs and diseases are characterized in completely different scientific languages."
The researchers monitored changes in gene expression of human cells treated with 164 small-molecule compounds—so-called perturbagens—that reflected a range of activities and included FDA-approved drugs and nondrug bioactive molecules. They then compared these profiles with gene expression signatures from various human disease states.
What makes this effort distinct from other efforts to tie gene expression with disease is how the researchers worked with the data.
"Rather that trying to correlate disease/drug-induced states with gene expression, the basic idea of cmap is to use gene expression data to connect disease states with the actions of small molecules," says Dr. Justin Lamb, a Broad researcher. "In other words, we use gene expression changes as a transitory feature, and often don't even look at the lists of genes that underlie the connections."
The theory ran that if a given disease increased expression in 10 genes and decreased activity of 15 genes, the best drug candidate would be the compound that decreased and increased expression in the same 10 and 15 genes, respectively.
While the researchers acknowledge their repertoire of cells, compounds or dosing regimens were not comprehensive, they were still able to identify compounds with high cmap scores for their ability to either mimic or suppress a handful of diseases. For example, a compound that had a high score against Alzheimer's disease had been shown elsewhere to reverse fibril formation in vitro.
"There are circumstances where using the correct cellular context and small molecule concentration, for example, are absolutely critical to finding strong connectivity," Lamb says. "But what is remarkable, I think, is that the approach does not seem unduly sensitive to these parameters. We find many connections largely independent of cell type, for example."
According to Lamb, the team is quite open to outside assistance in their efforts to expand cmap, whether it comes from other academic groups or government agencies. Likewise, he says they would be delighted by any interest from pharmaceutical or biotechnology companies. As an incentive to all—and as a general belief—the group is making cmap publicly available through a web site hosted by the Broad.