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Mutations in  BRCA1  and  BRCA2  confer high risks of breast cancer and ovarian cancer. The risk prediction algorithm BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) may be used to compute the probabilities of carrying mutations in  BRCA1  and  BRCA2  and help to target mutation screening. Tumours from  BRCA1  and  BRCA2  mutation carriers display distinctive pathological features that could be used to better discriminate between  BRCA1  mutation carriers,  BRCA2  mutation carriers and noncarriers. In particular, oestrogen receptor (ER)-negative status, triple-negative (TN) status, and expression of basal markers are predictive of  BRCA1  mutation carrier status.    Methods  We extended BOADICEA by treating breast cancer subtypes as distinct disease end points. Age-specific expression of phenotypic markers in a series of tumours from 182  BRCA1  mutation carriers, 62  BRCA2  mutation carriers and 109 controls from the Breast Cancer Linkage Consortium, and over 300,000 tumours from the general population obtained from the Surveillance Epidemiology, and End Results database, were used to calculate age-specific and genotype-specific incidences of each disease end point. The probability that an individual carries a  BRCA1  or  BRCA2  mutation given their family history and tumour marker status of family members was computed in sample pedigrees.    Results  The cumulative risk of ER-negative breast cancer by age 70 for  BRCA1  mutation carriers was estimated to be 55% and the risk of ER-positive disease was 18%. The corresponding risks for  BRCA2  mutation carriers were 21% and 44% for ER-negative and ER-positive disease, respectively. The predicted  BRCA1  carrier probabilities among ER-positive breast cancer cases were less than 1% at all ages. For women diagnosed with breast cancer below age 50 years, these probabilities rose to more than 5% in ER-negative breast cancer, 7% in TN disease and 24% in TN breast cancer expressing both CK5/6 and CK14 cytokeratins. Large differences in mutation probabilities were observed by combining ER status and other informative markers with family history.    Conclusions  This approach combines both full pedigree and tumour subtype data to predict  BRCA1/ 2 carrier probabilities. Prediction of  BRCA1/2  carrier status, and hence selection of women for mutation screening, may be substantially improved by combining tumour pathology with family history of cancer.

Incorporating tumour pathology information into breast cancer risk prediction algorithms