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Researchers develop promising new gene network analysis method

Compared with a long-used linear model, a correlation-based statistical method is a more reliable way to map complex gene interactions and pinpoint genes that may be potential cancer treatment targets, according to new Brown University research.

The research is important because it describes a promising new tool for tracing human gene connections, a task critical for understanding and treating cancer and other diseases. Results appeared this week in the online edition of the Proceedings of the National Academy of Sciences.

"Genes influence one another in many intricate ways," said Leon Cooper, professor of physics and neuroscience and director of the Institute for Brain and Neural Systems at Brown. "What we need is a map, or network, of these links. What we've identified in this project is a more effective method for making this map."

The research team ?which included scientists from the fields of biology, physics, statistics and computer science at Brown, Università di Bologna in Italy and Tel Aviv University in Israel ?set out to answer a question. When a deadly "oncoprotein" is switched on, what chain reaction of gene activity does it set off?

The protein, c-Myc, causes cells to multiply. If the protein is produced unchecked, it can cause breast, colon and other types of cancer. C-Myc contributes to more than 70,000 deaths in the United States each year.

Once the c-Myc switch is thrown, thousands of other genes start pumping out proteins or switching on other genes, which activates still more genes. One way to study this web of connections would be to set off the chain reaction and study it over time. To make that happen, Brown researchers came up with a clever experiment.

John Sedivy, a long-time c-Myc researcher and the director of Brown's Center for Genomics and Proteomics, developed rat cells that lacked the c-Myc gene. These cells were further modified to make a form of the c-Myc protein, which could be switched
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Source:Brown University


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