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NIH Research Matters

October 13, 2006

Connecting Small Molecules, Genes and Disease

Chemists have been creating millions of small molecules in the hope that they might affect the body and make good medications. A major challenge for modern medicine is to understand how all these potential drugs interact with our genes to affect disease. Now, a team of researchers has created a systematic approach to uncovering the complex functional connections among diseases, genes and drugs.

Picture of the Affymetrix GeneChip.

The researchers used the Affymetrix GeneChip® microarray to look at the activity of thousands of genes at once. Image courtesy of Affymetrix.

The human genome project has revealed that people have between 30,000 and 40,000 genes. Researchers around the world are now working to figure out what they do and how they interact. Understanding how small molecules might interact with all these genes is a daunting task. A team of researchers led by Todd R. Golub at the Broad Institute of Massachusetts Institute of Technology and Harvard University set out to create a "Connectivity Map" revealing these complex connections. Their work was supported in part by grants from NIH’s National Cancer Institute, the Howard Hughes Medical Institute and the Paul G. Allen Family Foundation.

The researchers reasoned that, to get the quantity and quality of information they needed, they had to develop a system that uses a small number of cells at low cost that could quickly generate information with a lot of complexity. They turned to a breast cancer cell line that’s been extensively studied and is used as a reference cell line in laboratories throughout the world. They also tested three other cell lines for comparison.

They decided to measure levels of messenger RNAs — the transient copies of genes that cells create to work from when genes are turned on, or “expressed”. The expression of thousands of genes can be monitored at once using microarray technology to measure messenger RNA levels. Microarrays, or gene chips, are made by robotic arms that can drop hundreds or thousands of spots of genetic material onto a small slide or chip. A machine can then quickly read the chip to see which genes are expressed. Gene chips are already widely used to look at specific biological pathways and to diagnose subtypes of diseases that can’t be distinguished under the microscope, such as some types of cancer.

For their pilot study, the researchers tested a range of 164 small molecules in the cells, including drugs approved by the U.S. Food and Drug Administration and some compounds commonly used in laboratories. They looked at the cells’ gene expression six hours after adding the compounds, and also profiled some cells at 12 hours for comparison. Using computer software, they then compared the gene expression patterns.

In the September 29 issue of Science, the researchers show that their method could be used to recognize seemingly unrelated drugs with common mechanisms of action, to discover unknown mechanisms of actions and to identify potential new therapeutics. The expression patterns were often similar across the diverse cell types, but not always. For example, cells without lack estrogen receptors don’t respond to an estrogen compound.

The initial Connectivity Map results are encouraging, but the authors caution that this is only a first step. The methods still need refinement, and more rigorous statistical methods will be needed as the database grows. In the meantime, the researchers have created a Web-based tool for other researchers to perform their own Connectivity Map analyses.

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Editor: Harrison Wein, Ph.D.
Assistant Editors: Vicki Contie, Carol Torgan, Ph.D.

NIH Research Matters is a weekly update of NIH research highlights from the Office of Communications and Public Liaison, Office of the Director, National Institutes of Health.

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This page last reviewed on December 4, 2012

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