Identification of breast cancer predisposition genes through integration of tumour sequencing and case-control analyses
Session type: Poster / e-Poster / Silent Theatre session
The genetic cause of up to 50% of breast cancer (BC) families are not explained by a known predisposition gene. Identifying causative genes can have a major impact on managing the breast cancer risk for these individual and their families. In a BC case/control analysis of over 12,000 participants, numerous novel candidate genes were identified based on an excess of LoF mutations in cases versus controls, including NTHL1 (39 vs 15), CCDC60 (30 vs 13), BLM (22 vs 8), PARP2 (10 vs 2), RAD51C (18 vs 2) and WRN (34 vs 19). Individually, mutations in these and other candidate genes are rare with most appearing to convey only a low to moderate BC risk. Given this scenario, current case/control studies will remain substantially underpowered to establish a clear role for such genes in BC predisposition in isolation. However, sequencing data from tumors from carriers of germline variants can be used to identify characteristic somatic inactivation events and “mutational signatures” to provide powerful orthogonal evidence for involvement of that gene in cancer predisposition.
We are performing targeted, whole exome and whole genome sequencing of BC from carriers of mutations in lead candidate from the case/control data to identify bi-allelic inactivation of the candidate gene and associated mutational signatures.
We show that RAD51C, a gene formerly only associated with ovarian cancer predisposition, undergoes bi-allelic inactivation only in triple negative breast cancers and this is associated with homologous recombination repair deficiency and associated mutational signature 3.
In conclusion, we show that mutations in novel genes are very rare, making confident assertions about their role in breast cancer predisposition difficult. The addition of tumour sequencing that allows for identification of accompanying loss of the wild type allele and/or a characteristic mutational signatures, can significantly improve the power to discover new breast cancer genes.