Project description
Advancing breast cancer risk prediction
Breast cancer risk prediction has significantly improved over the years by taking both genetic and lifestyle factors into consideration. Identifying women at high risk is crucial for deciding on the appropriate prevention strategy. However, we lack essential risk information of gene variants, which poses a challenge for genetic counselling. The primary objective of the EU-funded BRIDGES project is to establish the precise association between specific genes on multigene panels and the risk of breast cancer. The consortium will use data from breast cancer studies, sequence breast cancer susceptibility genes in large populations, and integrate the data with other risk factors into a comprehensive risk model. This user-friendly tool will offer personalised risk estimates for informed clinical decisions.
Objective
Breast cancer affects more than 360,000 women per year in the EU and causes more than 90,000 deaths. Identification of women at high risk of the disease can lead to disease prevention through intensive screening, chemoprevention or prophylactic surgery. Breast cancer risk is determined by a combination of genetic and lifestyle risk factors. The advent of next generation sequencing has opened up the opportunity for testing in many disease genes, and diagnostic gene panel testing is being introduced in many EU countries. However, the cancer risks associated with most variants in most genes are unknown. This leads to a major problem in appropriate counselling and management of women undergoing panel testing.
In this project, we aim to build a knowledge base that will allow identification of women at high-risk of breast cancer, in particular through comprehensive evaluation of DNA variants in known and suspected breast cancer genes. We will exploit the huge resources established through the Breast Cancer Association Consortium (BCAC) and ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles). We will expand the existing datasets by sequencing all known breast cancer susceptibility genes in 20,000 breast cancer cases and 20,000 controls from population-based studies, and 10,000 cases from multiple case families. Sequence data will be integrated with in-silico and functional data, with data on other known risk factors, to generate a comprehensive risk model that can provide personalised risk estimates. We will develop online tools to aid the interpretation of gene variants and provide risk estimates in a user-friendly format, to help genetic counsellors and patients worldwide to make informed clinical decisions. We will evaluate the acceptability and utility of comprehensive gene panel testing in the clinical genetics context.
Fields of science
Keywords
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
2333 ZA Leiden
Netherlands