Tumors harboring homologous recombination deficiency (HRD) are considered optimal candidates for poly(ADP-ribose) polymerase 1 (PARP) inhibitor treatment. Such deficiency can be detected by analyzing breast cancer type (BRCA)1/2 gene mutations, as well as mutations in other genes of the homologous recombination pathway. The algorithmic measurement of the HRD effect by identifying genomic instability (GI) has been used as biomarker. As compared with the direct measurement of somatic gene alterations, this approach increases the number of patients who could benefit from PARP inhibitor treatment. In the present study, the performance of the Oncoscan CNV assay, accompanied by appropriate bioinformatic algorithms, was evaluated for its performance in GI calculation and was compared with that of a validated next-generation sequencing (NGS) test (myChoice HRD test). In addition, the clinical utility of the GI score (GIS) and BRCA1/2 tumor analysis were investigated in a cohort of 444 patients with ovarian cancer. For that reason, single nucleotide polymorphism (SNP) arrays and appropriate bioinformatics algorithms were used to calculate GIS in 29 patients with ovarian cancer with known GIS status using a validated NGS test. Furthermore, BRCA1/2 analysis results were compared between the aforementioned assay and the amplicon-based Oncomine^™ BRCA Research Assay. BRCA1/2 analysis was performed in 444 patients with ovarian cancer, while GIS was calculated in 175 BRCA1/2-negative cases. The bioinformatics algorithm developed for GIS calculation in combination with NGS BRCA1/2 analysis (RediScore), and the OncoscanR pipeline exhibited a high overall agreement with the validated test (93.1%). In addition, the Oncomine NGS assay had a 100% agreement with the validated test. The BRCA1/2 mutation frequency was 26.5% in the examined patients with ovarian cancer. GIS was positive in 40% of the BRCA1/2-negative cases. The RediScore bioinformatics algorithm developed for GIS calculation in combination with NGS BRCA1/2 analysis is a viable and effective approach for HRD calculation in patients with ovarian cancer, offering a positive prediction for PARP inhibitor responsiveness in 55% of the patients.

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