Sleeping beauty plays a significant role in identifying cancer genes


Researchers at the University of Minnesota Cancer Center and the National Cancer Institute ( NCI ), have discovered a new method that could accelerate the way cancer-causing genes are found and could lead to a more accurate identification of the genes.

The gene identification method was developed in genetically modified mice and utilized a piece of jumping DNA, called Sleeping Beauty.

Jumping genes, or transposons, insert themselves into or between genes and can activate or inactivate a gene's normal function.
Related transposons are natural to the genetic makeup of humans, animals and fish, but, through millions of years of evolution, most transposons became inactive dead-ends.

In 1997, in another study, University of Minnesota researchers took defunct, non-functioning jumping genes from fish and made the genes jump again.
This research had reactivated the jumping genes from millions of years of evolutionary sleep; hence the name Sleeping Beauty.

In the two current research studies, specially designed Sleeping Beauty transposons were introduced into mouse DNA and made to jump around in the nucleus of mouse cells.
Eventually the transposons jumped into cancer-causing genes and caused a tumor to form.
By isolating and studying the genes from tumors that contained Sleeping Beauty, researchers were able to efficiently find genes linked to cancer by seeing whether Sleeping Beauty turned them on or off -- in effect, uncovering the fingerprint of each tumor's cancer genes.

The University of Minnesota Cancer Center research team, led by David Largaespada, focused on cancer gene discovery in solid tumors using transposon-based techniques.

"Current cancer gene identification methods, such as microarrays, give correlations typically of thousands of genes, and it's hard to know from the correlations which genes relate to cancer and which do not," said Largaespada. "By comparison, the jumping gene has inserted itself into cancer genes in the tumors we studied and thereby allows us to focus on smaller numbers of genes -- genes that we know are important to the genesis of tumors. The result is a quicker, more efficient and accurate identification of cancer-causing genes."

Although our discovery was made in laboratory mice," said Nancy Jenkins at the NCI , "we believe that the technology used will reveal new insights into human cancer and could be translated for clinical use. Hopefully, this discovery will speed up the development of new drugs and improve already-in-use drugs that target specific genes for treatment of various types of cancer, including lymphomas.

The outcome of the new Sleeping Beauty method could be a major leap forward in understanding cancer's weak points and thus lead to better treatments."

According to Largaespada, "About 300 human cancer-related genes have thus far been reported in the scientific literature. Most of those identified are involved in cancers of the blood system. So, there are likely to be many more cancer genes that still need to be identified."

Additionally, he noted that the Sleeping Beauty technology is capable of providing important information about the genes that current methods do not -- such as the specific combinations of mutant genes that can work together to cause cancer. "With this information, we will understand the development of tumors at the genetic level in much finer detail," he said. "This is important because no single kind of cancer is going to be cured by one drug; it is going to take a combination of drugs to attack the pathways that are required for cancer to start and continue growing."

The next step for Largaespada, Jenkins, Copeland and their colleagues will be to generate and analyze a large number of other tumors induced in mice using the Sleeping Beauty jumping gene. Largaespada and his team will focus on identifying genes causing prostate, lung and colorectal cancer; Jenkins and her team will study genes for tumors in the brain, melanoma, breast, leukemia and lymphoma.

Source: National Cancer Institute, 2005


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