Cytosine (C) is one of the four bases that make up DNA, and it can be modified with a methyl-group that works like a small tag. These tags are an important way for the cell to annotate the genome and remember their identity. However, it has been known since at least the 1980s that these so-called “epigenetic” marks also increase the risk of mutations.
This phenomenon is thought to occur due to methyl-C sometimes reacting with water to form thymine (T). Several years ago, it was uncovered that these methyl-C to T mutations were unusually frequent in cancers that lost the ability to proofread the newly-copied DNA that is produced when the cell divides. Based on this observation, researchers at Ludwig Oxford decided to test if there could be another explanation for why methyl-C adjacent to a guanine (G) is often mutated.
Using a new sequencing technology built specifically for this project, the researchers found that methyl-C to T mutations can also be caused by “copy-errors”, where the cellular machine that copies DNA every time the cell divides accidentally reads methyl-C as T.
Until now, it has not been understood why only some cancer types show the same amount of C to T mutations, or why they become increasingly more common in metastases, i.e. when cancer spreads from where it first formed to another part of the body. The results from the study provide an explanation: methyl-C to T mutations accumulate more when cells divide, which happens more often in some types of tissues than others. This also means that methyl-C to T mutations can be used to date the age of cells, which could be useful to understand how fast different cancers grow before acquiring resistance to different treatments.
Additionally, the methods developed for this study will be beneficial when trying understand the importance of copy-errors in cancer in general, such as knowing which mutations are naturally caused by the cell itself when measuring how some environmental causes increase the risk of cancer.
Professor Benjamin Schuster-Böckler, Associate Professor at Ludwig Oxford said, ‘This work is an example of how analysis of existing data can generate important new hypotheses. However, none of this work would have been possible without deep knowledge of methylation biology and the ability to design and implement an assay to test the hypotheses. Only through close collaboration between data analysts and experimental biologists was it possible to crack this puzzle.’
Read the full paper here in Nature Genetics: https://www.nature.com/articles/s41588-024-01945-x