Incorporating tumour pathology information into breast cancer risk prediction algorithms

Abstract

Introduction: 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.

Figure 1

Proportion of oestrogen receptor-negative tumours from the general population. Oestrogen receptor (ER)-negative tumours as a proportion of all invasive breast cancers tested for ER expression in unselected females from the general population. Data from the Surveillance Epidemiology, and End Results database 1990 to 2006 [27].

Figure 2

Incidence rates of oestrogen receptor-negative disease, oestrogen receptor-positive disease and all breast cancers. Incidence rates per 100,000 individuals of oestrogen receptor (ER)-negative disease, ER-positive disease and all breast cancers in (a) BRCA1 carriers, (b) BRCA2 carriers and (c) noncarriers, corresponding to women born after 1950.

Figure 3

Average cumulative risk for oestrogen receptor-negative disease, oestrogen receptor-positive disease and all breast cancers. Average cumulative risk for oestrogen receptor (ER)-negative disease, ER-positive disease and all breast cancers in (a) BRCA1 carriers, (b) BRCA2 carriers, and (c) noncarriers, corresponding to women born after 1950.

Figure 4

Influence of tumour pathology on mutation carrier probabilities for a single affected individual. Mutation carrier probabilities for a single affected individual with no knowledge of family history of breast cancer: BRCA1 carrier probabilities are shown in relation to (a) oestrogen receptor (ER) status, (b) tumour-negative (TN) status, when the tumour is known to be ER-negative, and (c) cytokeratin (CK)5/6 and/or CK14 expression when the tumour is known to be TN. In (c) scenarios where both basal markers have been tested (**) or where only CK5/6 has been tested (*) are shown. BRCA2 carrier probabilities are shown in relation to (d) TN status when the tumour is known to be ER-negative.

Figure 5

Mutation carrier probabilities for a pedigree where sequentially more tumour pathology information is available. CK, cytokeratin; ER, oestrogen receptor; TN, triple negative.

Figure 6

Influence of oestrogen receptor status on carrier probabilities when the proband tested negative for mutations. ER, oestrogen receptor.