Incorporating tumour pathology information into breast cancer risk prediction algorithms

Mavaddat, Nasim, Rebbeck, Timothy R., Lakhani, Sunil R., Easton, Douglas F. and Antoniou, Antonis C. (2010) Incorporating tumour pathology information into breast cancer risk prediction algorithms. Breast Cancer Research, 12 3: R28 - 1-R28 - 12. doi:10.1186/bcr2576

Author Mavaddat, Nasim
Rebbeck, Timothy R.
Lakhani, Sunil R.
Easton, Douglas F.
Antoniou, Antonis C.
Title Incorporating tumour pathology information into breast cancer risk prediction algorithms
Journal name Breast Cancer Research   Check publisher's open access policy
ISSN 1465-5411
Publication date 2010-05-18
Sub-type Article (original research)
DOI 10.1186/bcr2576
Open Access Status DOI
Volume 12
Issue 3
Start page R28 - 1
End page R28 - 12
Total pages 12
Place of publication London, United Kingdom
Publisher Current Medicine Group
Collection year 2011
Language eng
Formatted abstract

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.


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.


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.


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.  © 2010 Mavaddat et al.; licensee BioMed Central Ltd.
Keyword BRCA2 Mutation Carriers
Progesterone receptor carriers
Tumor marker
Estrogen receptor
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Article number R28, pp. 1-12.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Faculty of Health and Behavioural Sciences -- Publications
Official 2011 Collection
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 29 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 36 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Sun, 06 Feb 2011, 00:10:23 EST