Early warning improves outcomes
Breast cancer affects nearly 250,000 women a year in the EU and more than 20,000 in Australia. The identification of women at high risk of the disease could be a gamechanger in terms of survival rates.
If we know who is most likely to develop the disease, it might even be possible to avoid the disease altogether through intensive screening, chemoprevention or prophylactic surgery.
BRIDGES, or Breast Cancer Risk after Diagnostic Gene Sequencing, is a Horizon 2020-funded initiative co-ordinated by the Leiden University Medical Centre, in the Netherlands, aimed to do just that, bringing together a multidisciplinary team, data and expertise from clinical genetics, epidemiology, bioinformatics, statistics, and gene biology.
In Australia, researchers from QIMR Berghofer Medical Research Institute and the University of Melbourne were partners in the scheme, partly funded by the National Health and Medical Research Council (NHMRC) through its Funding Scheme targeting Australian-EU Collaborative Research.
The collaboration used the data it collected to develop a tool able to combine various risk factors into a single risk-score – the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA). This risk model incorporates the effects of genetic risk factors and other risk factors such as BMI and hormonal status.
“The idea to combine various risk factors into a single risk calculation is in itself not particularly novel,” says Professor Peter Devilee of the Leiden University Medical Centre in the Netherlands. “The point is one needs to have a good idea of the nature and magnitude of the risk factors involved, as well as a large enough dataset to show how they behave in combination.”
And large datasets were a hallmark of BRIDGES. Its strength lies in how it built upon the huge resources established through the Cancer Association Consortium and ENIGMA consortia, with clinical data obtained from 120,000 people.