Consistency of variant interpretations among bioinformaticians and clinical geneticists in hereditary cancer panels.

Next-generation sequencing (NGS) is used increasingly in hereditary cancer patients' (HCP) management. While enabling evaluation of multiple genes simultaneously, the technology brings to light the dilemma of variant interpretation. Here, we aimed to reveal the underlying reasons for the discrepancy in the evidence titles used during variant classification according to ACMG guidelines by two different bioinformatic specialists (BIs) and two different clinical geneticists (CGs). We evaluated final reports of 1920 cancer patients and 189 different variants from 285 HCP were enrolled to the study. A total of 173 of these variants were classified as pathogenic (n = 132) and likely pathogenic (n = 41) by the BI and an additional 16 variants, that were classified as VUS by at least one interpreter and their classification would change the clinical management, were compared for their evidence titles between different specialists. The attributed evidence titles and the final classification of the variants among BIs and CGs were compared. The discrepancy between P/LP final reports was 22.5%. The discordance between CGs was 30% whereas the discordance between two BIs was almost 75%. The use of PVS1, PS3, PP3, PP5, PM1, PM2, BP1, BP4 criteria markedly varied from one expert to another. This difference was particularly noticeable in PP3, PP5, and PM1 evidence and mostly in the variants affecting splice sites like BRCA1(NM_007294.4) c.4096 + 1 G > A and CHEK2(NM_007194.4) c.592 + 3 A > T. With recent advancements in precision medicine, the importance of variant interpretations is emerging. Our study shows that variant interpretation is subjective process that is in need of concrete definitions for accurate and standard interpretation.

Determining the accuracy of next generation sequencing based copy number variation analysis in Hereditary Breast and Ovarian Cancer.

BACKGROUND: Copy number variations (CNVs) are commonly associated with malignancies, including hereditary breast and ovarian cancers. Next generation sequencing (NGS) provides solutions for CNV detection in a single run. This study aimed to compare the accuracy of CNV detection by NGS analyzing tool against Multiplex Ligation Dependent Probe Amplification (MLPA). RESEARCH DESIGN AND METHODS: In total, 1276 cases were studied by targeted NGS panels and 691 cases (61 calls in 58 NGS-CNV positive and 633 NGS-CNV negative cases) were validated by MLPA. RESULTS: Twenty-eight (46%) NGS-CNV positive calls were consistent, whereas 33 (54%) calls showed discordance with MLPA. Two cases were detected as SNV by the NGS and CNV by the MLPA analysis. In total, 2% of the cases showed an MLPA confirmed CNV region in BRCA1/2. The results of this study showed that despite the high false positive call rate of the NGS-CNV algorithm, there were no false negative calls. The cases that were determined to be negative by the NGS and positive by the MLPA were actually carrying SNVs that were located on the MLPA probe binding sites. CONCLUSION: The diagnostic performance of NGS-CNV analysis is promising; however, the need for confirmation by different methods remains.