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Predicting cancer risk through studying mutations in blood

last modified Apr 20, 2020 04:02 PM

Cancer is evolution at the cellular level. As we age, we acquire mutations in the cells that make up our tissues. Whilst the vast majority of these mutations are harmless, some of them can increase the risk of developing cancer. 

In research recently published in Science Jamie Blundell's Group (Department of Oncology) explored which specific mutations in blood enable cells to expand most rapidly, and might confer the highest risk of cancer. The Group developed a method to estimate the growth rates of mutations that expand in healthy tissues, without needing to use longitudinal data.

photo of Jamie BlundellJamie Blundell said: “Blood provides an ideal model system for understanding the earliest stages in cancer development. The scale and resolution of the genomic data in blood is unparalleled, and, combined with quantitative methods borrowed from evolutionary biology has enabled us to identify the variants most likely to pose a high risk of a future blood cancer developing.”

The research team applied evolutionary theory to mutation size estimates in blood sequencing data collected from around 50,000 individuals to quantify the growth potential (or ‘fitness effect’) of specific mutations at single nucleotide resolution. This enabled them to build a league table of the ‘fittest’ and therefore potentially most pathogenic mutations in blood. 

The researchers were also able to quantify the distribution of fitness effects within genes and therefore what proportion of mutations within a gene are potentially high risk.

Caroline Watson

Lead author, Caroline Watson commented: "Knowing whether specific mutations are high-risk or clinically insignificant will be key in the future of personalised cancer risk stratification. Our framework provides a rational basis for quantifying the growth potential of mutations and, in combination with studies that can track these mutations and their outcomes over time, will be an important step towards this goal.”

Caroline has also created a video abstract which can be viewed on YouTube.