A group of 83 Spanish BC/OC families were analysed for BRCA1 germ-line mutations. Analysis of the entire coding sequence was carried out by SSCP and PTT. We identified 5 frameshift mutations: 185delAG (2 times), 189insTGTC, 1241delAC, and 5537delA and 3 missense mutations in BRCA1: 330A G G, 1240C G
Association between BRCA1 and BRCA2 mutations and cancer phenotype in Spanish breast/ovarian cancer families: Implications for genetic testing
✍ Scribed by Miguel de la Hoya; Ana Osorio; Javier Godino; Sara Sulleiro; Alicia Tosar; Pedro Perez-Segura; Cristina Fernandez; Raquel Rodríguez; Eduardo Díaz-Rubio; Javier Benítez; Peter Devilee; Trinidad Caldés
- Publisher
- John Wiley and Sons
- Year
- 2001
- Tongue
- French
- Weight
- 86 KB
- Volume
- 97
- Category
- Article
- ISSN
- 0020-7136
- DOI
- 10.1002/ijc.1627
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✦ Synopsis
Abstract
Index cases from a clinically relevant cohort of 102 Spanish families with at least 3 cases of breast and/or ovarian cancer (at least 1 case diagnosed before age 50) in the same lineage were screened for germline mutations in the entire coding sequence and intron boundaries of the breast cancer susceptibility genes BRCA1 and BRCA2. Overall, the prevalence of mutations was 43% in female breast/ovarian cancer families, 15% in female breast cancer families and 100% in male breast cancer families. Three recurrent mutations (185delAG, 589delCT and A1708E) explained 63% of BRCA1‐related families. Early age at diagnosis of breast cancer, ovarian cancer, bilateral breast cancer, concomitant breast/ovarian cancer in a single patient and prostate cancer but not unilateral breast cancer were associated with BRCA1 and BRCA2 mutations. Male breast cancer was associated with BRCA2 mutations. The presence of male breast cancer was the only cancer phenotype that distinguished BRCA2‐ from BRCA1‐related families. We have developed a logistic regression model for predicting the probability of harbouring a mutation in either BRCA1 or BRCA2 as a function of the cancer phenotype present in the family. The predictive positive and negative values of this model were 77.4% and 79%, respectively (probability cutoff of 30%). The findings of our work may be a useful tool for increasing the cost‐effectiveness of genetic testing in familial cancer clinics. © 2001 Wiley‐Liss, Inc.
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