Objective
Breast cancer is one of the most common cancers affecting women, with more than 330,000 new cases diagnosed in the European Union in 2008. It is crucial to understand the genetic causes behind this fatal disease to better stratify women at higher risk and to reduce breast cancer incidence. Inherited susceptibility to breast cancer is largely due to polygenic variation, and only about 30-35% of familial cases are explained by known risk loci. The central aims of this proposal are to identify new genetic risk loci, by redesigning breast cancer susceptibility studies, and to unravel the role of cis-regulatory variation in disease risk and tumour biology.
Recent data suggests that most unidentified risk loci are cis-regulatory, affecting the expression of both close and distant target genes. We propose a novel approach to identify susceptibility loci that focuses on variants with known regulatory potential. Differential allelic expression (DAE) is a robust technique to identify cis-regulatory loci, and we will perform the first case-control study using DAE as a quantitative trait.
We also aim at understanding the interaction between cis-regulation and mutations, both germline and somatic. We have evidence that common BRCA2 and TP53 haplotypes correlate with different levels of gene expression, and we are interested in understanding how these modulate penetrance of BRCA2 germline mutations in carriers and the clinical characteristics of tumours harbouring somatic TP53 mutations.
Our studies will impact on breast cancer incidence and understanding of tumour biology. The identification of novel breast cancer risk loci will improve individual risk assessment, stratification of patients at higher risk, pre-disease management and public health as whole. Dissection of biological mechanisms under-pinning risk will impart new understanding of tumour biology and will contribute towards developing future therapies.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- medical and health scienceshealth sciencespublic health
- medical and health sciencesclinical medicineoncologybreast cancer
- natural sciencesbiological sciencesgeneticsmutation
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Call for proposal
FP7-PEOPLE-2011-CIG
See other projects for this call
Coordinator
8005 139 Faro
Portugal