Cell Talk

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by Neil Caudle

One reason for this optimism is that the human-genome projects have cranked out an enormous index of genetic information, including many molecules that may be involved in signaling. Another is that new technologies are helping researchers mine meaning from this mountain of genetic information. For example, Chuck Perou, who recently came to Carolina from Stanford, helped pioneer a technique for rapidly measuring changes in the expression of genes, enabling researchers to "profile" cancers and their genetic origins.

But along with the opportunities, these advances have revealed enormous complications. Over the next decade, Carolina will invest at least $245 million in public and private funds to support studies in genomics. These will include work in bioinformatics, the intense computations required to make sense of the mountains of data from the human-genome projects and other sources.

"If you walk around the cancer center and look at the diagrams people are drawing on their boards, you’ll see that these signaling networks are in fact multiple networks, and they interact with each other," Earp says. "So bioinformatics, or computational biology, is really trying to understand how these signaling mechanisms integrate in the cell."

Channing Der, a professor of pharmacology who works with Earp at the cancer center, says that even if we understand a signaling mechanism in one cell type, it may not be the same in another. Der is a leading expert in the Ras oncoprotein, which regulates cell growth. Because human tumors frequently contain mutated Ras proteins, Der and others believe that the proteins are involved in cancer.

"The Ras oncoprotein we study is important in lung cancer, colon cancer, and pancreatic cancer," Der says, "but how it contributes to the development of cancers in each of those organs may not be the same."

Der’s lab, working closely with Adrienne Cox of radiation oncology, isolates specific molecules that show promise for cancer treatment, then works with drug companies to test the compounds on cultured cells and laboratory mice. Because these tests cannot reliably predict results in humans, the testing itself adds another level of complexity.

"When we decide a target is important and we make inhibitors against that target, they may work fantastically in cell-culture models or even in mouse models," Der says. "But whether they will work in humans is a big question mark."

Despite the complications, Der is convinced that the next generation of cancer treatments will arise from cell-signaling studies. "All you have to do is look at cancer survival rates for the last two decades and see that they haven’t improved dramatically," Der says. "That’s because our conventional approaches, while useful, have simply exhausted themselves with regard to making a breakthrough, and so understanding signal transduction is the great hope. This just has to be how we’ll make inroads into solving the complexities of human disease."

Next: Picking the Right Pocket

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