Large genomic rearrangements (LGRs), occurring as copy number alterations (CNAs), represent a clinically relevant class of pathogenic or likely pathogenic variants (P LPVs) in BRCA1/2 (BRCA) genes in ovarian cancer (OC). We evaluated the performance of a high-resolution algorithm integrated into a commercial homologous recombination deficiency (HRD) assay to improve the identification of clinically actionable CNAs in BRCA genes by formalin-fixed paraffin-embedded (FFPE) samples. A total of 760 OC samples were analyzed using a commercial HRD assay incorporating a bioinformatics algorithm for CNA detection. The algorithm was additionally applied to additional homologous recombination repair (HRR) genes, and associations between CNA events and genomic instability (GI) were evaluated. The algorithm demonstrated high sensitivity for both gene and exon-level CNA. The high correlation between CNA positivity cases and GI, in the absence of P/LPVs BRCA single-nucleotide or indels variants, emphasizes the value of integrating CNA detection into routine HRD testing workflows. The extended analysis of additional HRR genes enabled broader characterization of clinically relevant CNAs. This study enables reliable identification of clinically relevant BRCA LGRs from FFPE within HRD testing, supporting a tumor-first diagnostic strategy. This approach may expand the identification of OC patients potentially eligible for PARP inhibitor therapy.
Bonis et al. (Wed,) studied this question.