Risk models for familial ovarian and breast cancer

Genet Epidemiol. 2000 Feb;18(2):173-90. doi: 10.1002/(SICI)1098-2272(200002)18:2<173::AID-GEPI6>3.0.CO;2-R.


We investigated risk models for the inherited susceptibility of breast and ovarian cancer, using data from both high-risk families and a population based series of ovarian cancer. The first data set consisted of 112 families containing two or more relatives with epithelial ovarian cancer. BRCA1 and BRCA2 germline mutations were detected in 50% of these families. The second study involved 374 ovarian cancer cases, unselected for family history, who had DNA samples analyzed for BRCA1 mutations. Twelve women were found to be carriers. We constructed genetic models for ovarian and breast cancer using the computer program MENDEL. In the first study, we modeled the effects of BRCA1 and BRCA2 simultaneously and allowed for a third gene predisposing to ovarian cancer. None of the models fitted gave significant evidence for a third gene. Population frequencies of BRCA1 and BRCA2 mutations were estimated to be 0. 00128 and 0.00172, respectively. Our results suggest that BRCA1 and BRCA2 may be sufficient to explain the majority of familial ovarian cancer and that families without mutations can be explained by sensitivity of mutation testing and chance clusters of sporadic cases. Using data on the families of the 12 mutation carriers in the second study, we estimated age-specific ovarian and breast cancer risks for BRCA1 mutation carriers. Under the best-fitting model, the cumulative ovarian cancer risk was 66% by age 70, and the corresponding breast cancer risk was 45%. The high penetrance estimate for ovarian cancer, compared with other studies, suggests that modifying genetic or environmental factors may be important determinants of risk.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms / genetics*
  • Female
  • Gene Frequency
  • Genes, BRCA1
  • Genes, Tumor Suppressor
  • Humans
  • Likelihood Functions
  • Models, Genetic*
  • Mutation
  • Ovarian Neoplasms / genetics*
  • Penetrance
  • Risk*