Sequence analysis of BRCA1 and BRCA2: Correlation of mutations with family history and ovarian cancer risk

Thomas S. Frank, Susan A. Manley, Olufunmilayo I. Olopade, Shelly Cummings, Judy E. Garber, Barbara Bernhardt, Karen Antman, Donna Russo, Marie E. Wood, Lisa Mullineau, Claudine Isaacs, Beth Peshkin, Saundra Buys, Vicki Venne, Peter T. Rowley, Starlene Loader, Kenneth Offit, Mark Robson, Heather Hampel, Dara BrenerEric P. Winer, Shelly Clark, Barbara Weber, Louise C. Strong, Paula Rieger, Melody McClure, Brian E. Ward, Donna Shattuck-Eidens, Arnold Oliphant, Mark H. Skolnick, Alun Thomas

Research output: Contribution to journalArticlepeer-review

416 Scopus citations

Abstract

Purpose: Previous studies of mutations in BRCA1 or BRCA2 have used detection methods that may underestimate the actual frequency of mutations and have analyzed women using heterogeneous criteria for risk of hereditary cancer. Patients and Methods: A total of 238 women with breast cancer before age 50 or ovarian cancer at any age and at least one first- or second-degree relative with either diagnosis underwent sequence analysis of BRCA1 followed by analysis of BRCA2 (except for 27 women who declined analysis of BRCA2 after a deleterious mutation was discovered in BRCA1). Results were correlated with personal and family history of malignancy. Results: Deleterious mutations were identified in 94 (39%) women, including 59 of 117 (50%) from families with ovarian cancer and 35 of 121 (29%) from families without ovarian cancer. Mutations were identified in 14 of 70 (20%) women with just one other relative who developed breast cancer before age 50. In women with breast cancer, mutations in BRCA1 and BRCA2 were associated with a 10-fold increased risk of subsequent ovarian carcinoma (P = .005). Conclusion: Because mutations in BRCA1 and BRCA2 in women with breast cancer are associated with an increased risk of ovarian cancer, analysis of these genes should be considered for women diagnosed with breast cancer who have a high probability of carrying a mutation according to the statistical model developed with these data.

Original languageEnglish (US)
Pages (from-to)2417-2425
Number of pages9
JournalJournal of Clinical Oncology
Volume16
Issue number7
DOIs
StatePublished - Jul 1998

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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