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Clinically Applicable Models to Characterize BRCA1 and BRCA2 Variants of Uncertain Significance

Authors :
Amanda E. Toland
Kevin Sweet
Xiao Ping Zhou
Andrew D. Spearman
Fergus J. Couch
Jane McLennan
Publication Year :
2008
Publisher :
American Society of Clinical Oncology, 2008.

Abstract

PurposeTwenty percent of individuals with a strong family and/or personal history of breast and ovarian cancer carry a deleterious mutation in BRCA1 or BRCA2. Identification of mutations in these genes is extremely beneficial for patients pursuing risk reduction strategies. Approximately 7% of individuals who have genetic testing of BRCA1 and BRCA2 carry a variant of uncertain significance (VUS), making clinical management less certain. The majority of identified VUS occur only in one to two individuals; these variants are not able to be classified using current classification models with segregation analysis components.MethodsTo develop a clinically applicable method that can predict the pathogenicity of VUS that does not require familial information or segregation analysis, we identified characteristics of breast or ovarian tumors that distinguished sporadic tumors from tumors with BRCA1 or BRCA2 mutations. Study participants included individuals with known deleterious mutations in BRCA1 or BRCA2 and individuals with classified or unclassified BRCA variants.ResultsWe applied the models to 57 tumors with 43 different deleterious BRCA mutations and 57 tumors with 54 unique classified and unclassified BRCA variants. Of the 33 previously unclassified VUS studied, we found evidence of neutrality for 21.ConclusionOur models showed 98% sensitivity and 76% specificity for predicting classified DNA changes. We classified 64% of unknown variants as neutral. Classification of VUS as neutral will have immediate benefit for those individuals and their family members. These models are adaptable for the clinic and will be useful for individuals with limited available family history.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....9b2c8647c20762972f7d9b4dc153c8b1