[Germline mutation of BRCA1 gene in Polish families with strong aggregation of breast and/or ovarian cancer based on coding sequence analysis using the SSCP method].

The aim of the study was to identify possible BRCA1 germline mutations in Polish families with strong aggregation of breast and/or ovarian cancer. Identification was based on analysis of the entire coding region using SSCP--"Phast System" technique. The study group consisted of 34 women with breast or/and ovarian cancer from families with aggregation of breast and/or ovarian cancer referred from the Oncology Center in Szczecin. Breast and ovarian cancer cases were revealed in 16 families, breast cancer in 17 and ovarian cancer in 1 family. Blood samples for genetic analyses were taken from at least one affected woman from each family. As a rule, samples were taken from the youngest woman. Genomic DNA was prepared from peripheral blood leukocytes with the nonenzymatic rapid method described by Lahiri and Nurnberger. The entire coding region of the BRCA1 gene was screened for the presence of germline mutations by use of Single Stranded Conformation Polymorphism (SSCP) followed by direct sequencing of variants. Primers used for PCR amplification of the BRCA1 gene have been described in the Breast Cancer Information Core (BIC) database. Samples were sequenced with the use of fluorescent dideoxy-chain terminators from the ABI Prism Kit (PE Biosystems) and model 373 automated sequencer (PE Biosystems). Four mutations were found in exon 5 (4/9) and three in exon 11 (3/9) of the BRCA1 gene. The two mutations in exon 20--5382insC (2/9) could not be identified using SSCP and required sequencing. Three BRCA1 abnormalities--C61G, 3819de15 and 5382insC, were the most frequent mutations detected in Polish families with strong aggregation of breast and/or ovarian cancers. These three abnormalities were most frequent in hereditary breast-ovarian cancer syndrome (6/9), followed by hereditary breast cancer-site specific syndrome (3/9). The present study and literature data suggest that the most effective strategy for DNA testing for cancer susceptibility genes is to identify the type and frequency of mutations in families with strong familial aggregation of cancers.