DNA Research with comments from Professor Gareth Evans

Professor Gareth Evans, professor of clinical genetics at Genesis Breast Cancer Prevention, comments on the Institute of Cancer Research’s report into genetic codes and breast cancer.

The research, which was published in the Journal of the National Cancer Institute (JNCI) this week, shows that a woman’s risk of developing breast cancer could be predicted, even if they have no family history of the disease.

Professor Gareth Evans said: “The recent findings published in JNCI are of great importance to future attempts to accurately assess risk in al women in the general population.

While risk models incorporating standard risk factors like family history and age of childbirth are useful, they don’t help us when trying to predict the risk in women with no family history of breast cancer.

On the other hand, more commonly-used genetic tests, such as those carried out on the very high risk genes – BRCA1 and BRCA 2 – are extremely helpful, but only relevant for less than one per cent of the population, while tests on the common SNP genetic variants provide important information for all women.

SNPs are variations in our DNA building block (nucleotide) that are different for each person and everyone has thousands of these. They can generate biological variations between people, which can influence appearance, disease susceptibility or response to drugs.

Here at Genesis, we’ve been able to replicate the JNCI results in two population groups of women. In 2,000 women with a family history, we were able to show a two-fold difference in risks between the bottom 20 per cent of SNP risk values and the top 20 per cent, using just the first 18 most important of the SNPs.

Similarly, in nearly 9,000 women in our population-based PROCAS study, the 18 SNPs have an even bigger differential, similar to the JNCI study.

This new piece of research in the JNCI has tested 77 SNPs – including the 18 that we have tested. Adding a further 17 newly identified SNPs will therefore allow us to more accurately predict a women’s chance of breast cancer, especially if they are not already known to be at high risk.

In terms of preventing the disease, it means that we can give more high risk women including those with no already identified risk factors earlier, more frequent screening and access to preventative drugs.”