Purpose: Detection of predisposing copy number variants (CNV) in 330 families affected with hereditary breast and ovarian cancer (HBOC).
Methods: In order to complement mutation detection with Illumina's TruSight Cancer panel, we designed a customized high-resolution 8 × 60k array for CGH (aCGH) that covers all 94 genes from the panel.
Results: Copy number variants with immediate clinical relevance were detected in 12 families (3.6%). Besides 3 known CNVs in CHEK2, RAD51C, and BRCA1, we identified 3 novel pathogenic CNVs in BRCA1 (deletion of exons 4-13, deletion of exons 12-18) and ATM (deletion exons 57-63) plus an intragenic duplication of BRCA2 (exons 3-11) and an intronic BRCA1 variant with unknown pathogenicity. The precision of high-resolution aCGH enabled straight forward breakpoint amplification of a BRCA1 deletion which subsequently allowed for fast and economic CNV verification in family members of the index patient. Furthermore, we used our aCGH data to validate an algorithm that was able to detect all identified copy number changes from next-generation sequencing (NGS) data.
Conclusions: Copy number detection is a mandatory analysis in HBOC families at least if no predisposing mutations were found by sequencing. Currently, high-resolution array CGH is our first choice of method of analysis due to unmatched detection precision. Although it seems possible to detect CNV from sequencing data, there currently is no satisfying tool to do so in a routine diagnostic setting.
Keywords: Array CGH; Breast cancer; Copy number; Ovarian cancer.