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In Vivo and Ex Vivo Approaches to Study Ovarian Cancer Metastatic Colonization of Milky Spot Structures in Peritoneal Adipose
Published on: October 14, 2015
BRCA1 and BRCA2 mutations account for a large proportion of ovarian carcinoma cases
Tuya Pal1, Jenny Permuth-Wey, Judith A Betts
1Division of Cancer Prevention and Control, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33617, USA.
Background:
It is believed that BRCA1 and BRCA2 germline mutations account for the majority of hereditary ovarian carcinomas; however, to the authors' knowledge, there are scant data on the prevalence and spectrum of mutations, genotype/phenotype correlations, tumor histology, and family history characteristics. To address this gap, the authors conducted a population-based study of 232 incident epithelial ovarian carcinomas in the Tampa Bay area.
Methods:
Genetic testing for the BRCA1 and BRCA2 genes was performed through full sequencing and BRCA1 rearrangement testing.
Results:
Of 209 women with invasive ovarian carcinoma, 32 women (15.3%) had mutations in BRCA1 or BRCA2, including 20 BRCA1 mutations and 12 BRCA2 mutations. Of the BRCA2 mutations, 58% were outside the "ovarian cancer cluster region" (OCCR). Variants of uncertain significance were detected in 8.2% of women with invasive ovarian carcinoma. No mutations were identified in women with borderline or invasive mucinous tumors. Among the BRCA mutation-positive women, 63% had serous tumors. A family history of breast and/or ovarian carcinoma was reported in 65%, 75%, and 43.5% of relatives of BRCA1 carriers, BRCA2 carriers, and non-BRCA1/BRCA2 carriers, respectively.
Conclusions:
The data from this study suggested that 1) previous studies may have underestimated the frequency of BRCA1 and BRCA2 mutations in ovarian carcinomas, especially outside the OCCR; 2) it may be reasonable to offer genetic counseling to any woman with an invasive, nonmucinous epithelial ovarian tumor; and 3) among patients with invasive ovarian carcinoma, family history is not sufficiently accurate to predict mutation status.
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