‘Information theory’ recruited to help scientists find cancer genes — ScienceDaily

Scientists at Johns Hopkins Medicine and Johns Hopkins Kimmel Cancer Center use a well-known area of ​​mathematics primarily designed to study how digital and other forms of information are measured, stored and shared, saying they have a likely major genetic culprit discovered in the development of acute lymphoblastic leukemia (ALL).

ALL is the most common form of childhood leukemia, affecting an estimated 3,000 children and teens in the United States alone every year.

In particular, the Johns Hopkins team used “information theory,” which involved an analysis based on sequences of zeros and ones – the binary system of symbols common in computer languages ​​and codes – to identify variables or outcomes of a particular process. In the case of human cancer biology, the scientists focused on a chemical process in cells called DNA methylation, in which certain chemical groups attach to regions of genes that control the on / off switches of genes.

“This study shows how a mathematical language of cancer can help us understand how cells should behave and how changes in that behavior affect our health,” said Andrew Feinberg, MD, MPH, Bloomberg Distinguished Professor at Johns Hopkins University School of Medicine. . , Whiting School of Engineering and Bloomberg School of Public Health. As the founder of the field of cancer epigenetics, Feinberg discovered altered DNA methylation in cancer in the 1980s.

Feinberg and his team say that using information theory to find genes driving cancer can be applicable to a wide variety of cancers and other diseases.

Methylation is now recognized as a way to change DNA without changing a cell’s genetic code. When methylation fails in such epigenetic phenomena, certain genes are abnormally turned on or off, leading to uncontrolled cell growth or cancer.

“Most people are familiar with genetic changes in 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, with pauses and stops as we read,” Feinberg says. In search of a new and more efficient way to read and understand the epigenetic code altered by DNA methylation, he teamed up with John Goutsias, Ph.D., professor in the Department of Electrical and Computer Engineering at Johns Hopkins University and Michael Koldobskiy, MD, Ph.D., pediatric oncologist and assistant professor of oncology at Johns Hopkins Kimmel Cancer Center.

“We wanted to use this information to identify genes that stimulate cancer development, even though their genetic code is not mutated,” says Koldobskiy.

The results of the study’s findings, led by Feinberg, Koldobskiy and Goutsias, were published April 15 in Nature Biomedical Engineering.

Koldobskiy explains that methylation at a particular gene location is binary – methylation or no methylation – and a system of zeros and ones can represent these differences, just as they are used to represent computer codes and instructions.

For the study, the Johns Hopkins team analyzed DNA extracted from bone marrow samples from 31 children who had recently been diagnosed with ALL at Johns Hopkins Hospital and Texas Children’s Hospital. They sequenced the DNA to determine which genes, across the genome, were methylated and which were not.

Newly diagnosed leukemia patients have billions of leukemia cells in their bodies, Koldobskiy says.

By assigning zeros and ones to pieces of genetic code that were methylated or unmethylated and by using concepts of information theory and computer programs to recognize methylation patterns, the scientists were able to find regions of the genome that were consistently methylated in patients with leukemia and patients with leukemia . without cancer.

They also saw genomic regions in the leukemia cells that were more randomly methylated, compared to the normal genome, a signal to scientists that those spots may be specifically linked to leukemia cells compared to normal ones.

One gene, called UHRF1, stood out among other gene regions in leukemia cells that showed differences in DNA methylation compared to the normal genome.

“It was a great surprise to find this gene, as it has been suggested to be linked to prostate and other cancers but has never been identified as a cause of leukemia,” says Feinberg.

In normal cells, the protein products of the UHRF1 gene form a biochemical bridge between DNA methylation and DNA packaging, but scientists have not deciphered exactly how alteration of the gene contributes to cancer.

Experiments by the Johns Hopkins team show that lab-grown leukemia cells without UHRF1 gene activity cannot self-renew and perpetuate additional leukemia cells.

“Leukemia cells are meant to survive, and the best way to ensure survival is to vary the epigenetics in many genome regions so that no matter what the cancer is trying to kill, at least some will survive,” says Koldobskiy.

ALL is the most common childhood cancer, and Koldobskiy says decades of research into different treatments and the order of those treatments have helped clinicians to cure most of these leukemias, but recurrent disease remains a leading cause of cancer death in children.

“This new approach could lead to more rational ways to address the changes that cause these and probably many other cancers,” says Koldobskiy.

The Johns Hopkins team plans to use information theory to analyze methylation patterns in other cancers. They also plan to determine whether epigenetic changes in URFH1 are related to treatment resistance and disease progression in patients with childhood leukemia.

The new research was funded by the National Institutes of Health’s National Cancer Institute (R01CA65438), the National Institute of Diabetes and Digestive and Kidney Diseases (DP1 DK119129), the National Human Genome Research Institute (R01 HG006282), National Science Foundation (1656201) , St. Baldrick’s Foundation Fellowship, Unravel Pediatric Cancer, and the Damon Runyon Cancer Research Foundation.

In addition to Feinberg, Koldobskiy and Goutsias, contributors to the research include Garrett Jenkinson, Jordi Abante, Varenka Rodriguez DiBlasi, Weiqiang Zhou, Elisabet Pujadas, Adrian Idrizi, Rakel Tryggvadottir, Colin Callahan, Challice Bonifant, Patrick Brown and Hongkai Ji from Johns Hopkins. . and Karen R. Rabin of Baylor College of Medicine.

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