Prediction of BRCA2-association in hereditary breast carcinomas using array-CGH.

Abstract:

:Germline mutations in BRCA1/2 increase the lifetime risk for breast and ovarian cancer dramatically. Identification of such mutations is important for optimal treatment decisions and pre-symptomatic mutation screening in family members. Although current DNA diagnostics is able to identify many different mutations, it remains unclear, how many BRCA2-associated breast cancer cases remain unidentified as such. In addition, mutation scanning detects many unclassified variants (UV) for which the clinical relevance is uncertain. Therefore, our aim was to develop a test to identify BRCA2-association in breast tumors based on the genomic signature. A BRCA2-classifier was built using array-CGH profiles of 28 BRCA2-mutated and 28 sporadic breast tumors. The classifier was validated on an independent group of 19 BRCA2-mutated and 19 sporadic breast tumors. Subsequently, we tested 89 breast tumors from suspected hereditary breast (and ovarian) cancer (HBOC) families, in which either no BRCA1/2 mutation or an UV had been found by routine diagnostics. The classifier showed a sensitivity of 89% and specificity of 84% on the validation set of known BRCA2-mutation carriers and sporadic tumor cases. Of the 89 HBOC cases, 17 presented a BRCA2-like profile. In three of these cases additional indications for BRCA2-deficiency were found. Chromosomal aberrations that were specific for BRCA2-mutated tumors included loss on chromosome arm 13q and 14q, and gain on 17q. Since we could separate BRCA1-like, BRCA2-like, and sporadic-like tumors, using our current BRCA2- and previous BRCA1-classifier, this method of breast tumor classification could be applied as additional test for current diagnostics to help clinicians in decision making and classifying sequence variants of unknown significance.

authors

Joosse SA,Brandwijk KI,Devilee P,Wesseling J,Hogervorst FB,Verhoef S,Nederlof PM

doi

10.1007/s10549-010-1016-7

subject

Has Abstract

pub_date

2012-04-01 00:00:00

pages

379-89

issue

2

eissn

0167-6806

issn

1573-7217

journal_volume

132

pub_type

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