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Risk Estimation as a Decision-Making Tool for Genetic Analysis of the Breast Cancer Susceptibility Genes.
- Source :
- Disease Markers; 1999, Vol. 15 Issue 1-3, p53, 13p
- Publication Year :
- 1999
-
Abstract
- For genetic counselling of a woman on familial breast cancer, an accurate evaluation of the probability that she carries a germ-line mutation is needed to assist in making decisions about genetic-testing. We used data from eight collaborating centres comprising 618 families (346 breast cancer only, 239 breast or ovarian cancer) recruited as research families or counselled for familial breast cancer, representing a broad range of family structures.  Screening was performed in affected women from 618 families for germ-line mutations in BRCA1 and in 176 families for BRCA2 mutations, using different methods including SSCP, CSGE, DGGE, FAMA and PTT analysis followed by direct sequencing.  Germ-line BRCA1 mutations were detected in 132 families and BRCA2 mutations in 16 families.  The probability of being a carrier of a dominant breast cancer gene was calculated for the screened individual under the established genetic model for breast cancer susceptibility, first, with parameters for age-specific penetrances for breast cancer only [7] and, second, with age-specific penetrances for ovarian cancer in addition [20].  Our results indicate that the estimated probability of carrying a dominant breast cancer gene gives a direct measure of the likelihood of detecting mutations in BRCA1 and BRCA2.  For breast/ovarian cancer families, the genetic model according to Narod et al. [20] is preferable for calculating the proband's genetic risk, and gives detection rates that indicate a 50% sensitivity of the gene test.  Due to the incomplete BRCA2 screening of the families, we cannot yet draw any conclusions with respect to the breast cancer only families. [ABSTRACT FROM AUTHOR]
- Subjects :
- BREAST cancer
GENES
ANALYTICAL chemistry
Subjects
Details
- Language :
- English
- ISSN :
- 02780240
- Volume :
- 15
- Issue :
- 1-3
- Database :
- Complementary Index
- Journal :
- Disease Markers
- Publication Type :
- Academic Journal
- Accession number :
- 6375173
- Full Text :
- https://doi.org/10.1155/1999/238375