26 April 2021

Scientists in the USA have used a field of mathematics - information theory - to find a gene which is a potential driver of the development of acute lymphoblastic leukaemia (ALL).

Scientists at Johns Hopkins Medicine and Johns Hopkins Kimmel Cancer Center, Baltimore, Maryland, applied information theory to identify differences in DNA methylation in the UHRF1 gene when compared with the normal genome.

The study was led by Prof Andrew Feinberg, Bloomberg Distinguished Professor at the Johns Hopkins University School of Medicine, Whiting School of Engineering and Bloomberg School of Public Health. He said the study showed how a mathematical language of cancer can help understand how cells are supposed to behave and how alterations in that behaviour affect our health. Prof Feinberg added that using information theory to find cancer driver genes may be applicable to other cancers and diseases.

Prof Feinberg worked with Prof John Goutsias, from the Department of Electrical and Computer Engineering at Johns Hopkins University, and Dr Michael Koldobskiy, paediatric oncologist and assistant professor of oncology at Johns Hopkins Kimmel Cancer Center. The team set out to look for a more efficient way to read and understand the epigenetic code altered by DNA methylation in ALL.

They analysed DNA extracted from bone marrow samples of 31 children who were newly diagnosed with ALL at The Johns Hopkins Hospital and Texas Children’s Hospital. The DNA was sequenced 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 recognise patterns of methylation, the scientists found regions of the genome that were consistently methylated in patients with leukaemia and those without cancer.

They also saw genome regions in the leukaemia cells that were more randomly methylated, compared with the normal genome, which suggested those spots might be specifically linked to leukaemia cells compared with normal ones.

The UHRF1 gene stood out among other gene regions in leukaemia cells that had differences in DNA methylation compared with the normal genome.

“It was a big surprise to find this gene, as its link to prostate and other cancers has been suggested but never identified as a driver of leukaemia,” said Prof Feinberg.

Experiments by the Johns Hopkins team show that laboratory-grown leukaemia cells lacking activity of the UHRF1 gene cannot self-renew and perpetuate additional leukaemia cells.

The team will use information theory to analyse methylation patterns in other cancers. They hope to determine if epigenetic alterations in URFH1 are linked to treatment resistance and disease progression in patients with childhood leukaemia.


Koldobskiy MA, Jenkinson G, Abante J, Rodriguez DiBlasi VA, Zhou W, Pujadas E, Idrizi A, Tryggvadottir R, Callahan C, Bonifant CL, Rabin KR, Brown PA, Ji H, Goutsias J, Feinberg AP. (2021) “Converging genetic and epigenetic drivers of paediatric acute lymphoblastic leukaemia identified by an information-theoretic analysis.” Nature Biomedical Engineering, doi: 10.1038/s41551-021-00703-2


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