A team of scientists at Johns Hopkins used “information theory” to uncover key cancer genes. One such culprit is in the development of acute lymphoblastic leukemia (ALL). By using information theory, researchers used a field of mathematics designed to study how digital and other forms of information are stored, shared, and measured.
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"This study demonstrates how a mathematical language of cancer can help us understand how cells are supposed to behave and how alterations in that behavior affect our health," says Andrew Feinberg, M.D., M.P.H., Bloomberg Distinguished Professor at the Johns Hopkins University School of Medicine, Whiting School of Engineering and Bloomberg School of Public Health.
Through the application of the binary system of symbols, scientists studied DNA methylation—a chemical process in which gene expression is turned on or off. Gene expression involves the production of certain proteins that have direct implications in cancer biology. With methylation, it was recognized as one way DNA can change without changing the genetic material of the cell.
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"Most people are familiar with genetic changes to DNA, namely mutations that change the DNA sequence. Those mutations are like the words that make up a sentence, and methylation is like punctuation in a sentence, providing pauses and stops as we read," says Feinberg.
DNA methylation is at the heart of epigenetics which is linked to cancer. Therefore, researchers found an efficient way to understand the epigenetic code by seeking methylation spots at a particular gene location. This location is binary like a system of zeros that can be interrupted as computer codes and instructions.
"We wanted to use this information to identify genes that drive the development of cancer even though their genetic code isn't mutated," says Koldobskiy.
Findings were reported in Nature Biomedical Engineering.
In the study, analysis was performed on DNA extractions from bone marrow samples of newly diagnosed with ALL. The genes were sequenced to determine which genes, across the entire genome, were methylated and or unmethylated. The analysis led to one gene—UHRF1—which was interesting because it stood out from other gene regions in leukemic cells because of differences in DNA methylation compared with the normal genome.
"Leukemia cells aim to survive, and the best way to ensure survival is to vary the epigenetics in many genome regions so that no matter what tries to kill the cancer, at least some will survive," says Koldobskiy. "This new approach can lead to more rational ways of targeting the alterations that drive this and likely many other forms of cancer.”
Source: Science Daily