Mathematical data uncovers possible gene that spurs childhood leukemia

April 21, 2021

Scientists at Johns Hopkins Medicine and Johns Hopkins Kimmel Cancer Center say they have uncovered a likely key genetic culprit in the development of acute lymphoblastic leukemia (ALL), the most common form of childhood leukemia, striking an estimated 3,000 children and teens each year in the United States, according to a news release from the university.

Specifically, the Johns Hopkins team used “information theory,” applying an analysis that relies on strings of zeros and ones – the binary system of symbols common to 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 areas of genes that guide genes’ on/off switches.

“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, MD, MPH, Bloomberg Distinguished Professor at the Johns Hopkins University School of Medicine, Whiting School of Engineering and Bloomberg School of Public Health. A founder of the field of cancer epigenetics, Feinberg discovered altered DNA methylation in cancer in the 1980s.

Methylation is now recognized as one way DNA can be altered without changing a cell’s genetic code. When methylation goes awry in such epigenetic phenomena, certain genes are abnormally turned on or off, triggering uncontrolled cell growth, or cancer.

“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.

Results of the study were published 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 of 31 children newly diagnosed with ALL at The Johns Hopkins Hospital and Texas Children’s Hospital. They sequenced the DNA to determine which genes, across the entire genome, were methylated and which were not.

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

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

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

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