The rapid integration of genomic technologies in clinical diagnostics has resulted in the detection of a multitude of missense variants whose clinical significance is often unknown. As a result, a plethora of computational tools have been developed to facilitate variant interpretation. However, choosing an appropriate software from such a broad range of tools can be challenging; therefore, systematic benchmarking with high-quality, independent datasets is critical. Using three independent benchmarking datasets compiled from the ClinVar database, we evaluated the performance of ten widely used prediction algorithms with missense variants from 21 clinically relevant genes, including BRCA1 and BRCA2. A fourth dataset consisting of 1053 missense variants was also used to investigate the impact of type 1 circularity on their performance. The performance of the prediction algorithms varied widely across datasets. Based on Matthews Correlation Coefficient and Area Under the Curve, SNPs&GO and PMut consistently displayed an overall above-average performance across the datasets. Most of the tools demonstrated greater sensitivity and negative predictive values at the expense of lower specificity and positive predictive values. We also demonstrated that type 1 circularity significantly impacts the performance of these tools and, if not accounted for, may confound the selection of the best performing algorithms.

Germline mutations in the BRCA1 and BRCA2 genes are responsible for hereditary breast and ovarian cancer syndrome. Germline and somatic BRCA1/2 mutations may define therapeutic targets and refine cancer treatment options. However, routine BRCA diagnostic approaches cannot reveal the exact time and origin of BRCA1/2 mutation formation, and thus, the fine details of their contribution to tumor progression remain less clear. Here, we establish a diagnostic pipeline using high-resolution microscopy and laser microcapture microscopy to test for BRCA1/2 mutations in the tumor at the single-cell level, followed by deep next-generation sequencing of various tissues from the patient. To demonstrate the power of our approach, here, we describe a detailed single-cell-level analysis of an ovarian cancer patient we found to exhibit constitutional somatic mosaicism of a pathogenic BRCA2 mutation. Employing next-generation sequencing, BRCA2 c.7795G>T, p.(Glu2599Ter) was detected in 78% of reads in DNA extracted from ovarian cancer tissue and 25% of reads in DNA derived from peripheral blood, which differs significantly from the expected 50% of a hereditary mutation. The BRCA2 mutation was subsequently observed at 17–20% levels in the normal ovarian and buccal tissue of the patient. Together, our findings suggest that this mutation occurred early in embryonic development. Characterization of the mosaic mutation at the single-cell level contributes to a better understanding of BRCA mutation formation and supports the concept that the combination of single-cell and next-generation sequencing methods is advantageous over traditional mutational analysis methods. This study is the first to characterize constitutional mosaicism down to the single-cell level, and it demonstrates that BRCA2 mosaicism occurring early during embryogenesis can drive tumorigenesis in ovarian cancer.

The members of the evolutionary conserved actin-binding Ezrin, Radixin and Moesin (ERM) protein family are involved in numerous key cellular processes in the cytoplasm. In the last decades, ERM proteins, like actin and other cytoskeletal components, have also been shown to be functional components of the nucleus; however, the molecular mechanism behind their nuclear activities remained unclear. Therefore, our primary aim was to identify the nuclear protein interactome of the single Drosophila ERM protein, Moesin. We demonstrate that Moesin directly interacts with the Mediator complex through direct binding to its Med15 subunit, and the presence of Moesin at the regulatory regions of the Hsp70Ab heat shock gene was found to be Med15-dependent. Both Moesin and Med15 bind to heat shock factor (Hsf), and they are required for proper Hsp gene expression under physiological conditions. Moreover, we confirmed that Moesin, Med15 and Hsf are able to bind the monomeric form of actin and together they form a complex in the nucleus. These results elucidate a mechanism by which ERMs function within the nucleus. Finally, we present the direct interaction of the human orthologues of Drosophila Moesin and Med15, which highlights the evolutionary significance of our finding.