Carnegie Mellon University

Cancer Research

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International Team Finds Clues on How Disease Develops

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A team of American, Israeli and German scientists led by Carnegie Mellon researcher Ziv Bar-Joseph recently found important clues on how cancers develop. Using computational biology techniques, the team identified more than 100 genes involved in human cell division that have an abnormal pattern of activation in cancer cells. The genes are potential targets for drug therapy.

Unlike many cancer studies, which seek to identify "missing" genes that might cause cancer, this new research shows that genes can contribute to cancer in less obvious ways.

"What we see is that there are many genes that are present and yet still involved in cancer because they are not activated, or expressed, in the way they normally are," said co-lead author Itamar Simon, a molecular biologist at Hebrew University Medical School in Israel.

Rather than cycling on and off, as normally occurs when cell replication and development proceeds, these genes are expressed in a steady state or not at all. The findings were reported Jan. 7 in the Proceedings of the National Academy of Science's online "Early Edition."

The genes found to be abnormally regulated in cancer cells include a few that already have been linked to cancer. Most have not, including at least three genes responsible for repairing genetic mutations that occur as DNA is duplicated in the cell.

The failure of the DNA repair genes to cycle in cancer cells raises the possibility that some mutations associated with cancer may not cause cancer.

"Some of the mutations may be caused by the non-cycling genes, rather than the other way around," said Bar-Joseph, an assistant professor of computer science and machine learning in the School of Computer Science and a member of Carnegie Mellon's Ray and Stephanie Lane Center for Computational Biology.

Determining if genetic mutations are a side effect of certain cancers rather than a cause will require further investigation, as will identifying which of the 118 genes that do not cycle in cancer cells are most significant.

In addition to Bar-Joseph and Simon, the team included Yong Lu of Carnegie Mellon's Computer Science Department; Zahava Siegfried and Michael Brandeis of Hebrew University; Benedikt Brors and Roland Eils of the German Cancer Research Center in Heidelberg; and Brian D. Dynlacht of the New York University School of Medicine.

The Ray and Stephanie Lane Center for Computational Biology was recently established at Carnegie Mellon with a focus on bringing machine learning methods to bear on complex biological problems, especially cancer diagnosis and treatment.

Related Links: Read Press Release  |  Lane Center  |  Mellon College of Science