The ENIGMA research consortium develops and applies methods to determine clinical significance of variants in hereditary breast and ovarian cancer genes. An ENIGMA BRCA1/2 classification sub-group, formed in 2015 as a ClinGen external expert panel, evolved into a ClinGen internal Variant Curation Expert Panel (VCEP) to align with Food and Drug Administration recognized processes for ClinVar contributions.The VCEP reviewed American College of Medical Genetics and Genomics/Association of Molecular Pathology (ACMG/AMP) classification criteria for relevance to interpreting BRCA1 and BRCA2 variants. Statistical methods were used to calibrate evidence strength for different data types. Pilot specifications were tested on 40 variants and documentation revised for clarity and ease of use.The original criterion descriptions for 13 evidence codes were considered non-applicable or overlapping with other criteria. Scenario of use was extended or re-purposed for eight codes. Extensive analysis and/or data review informed specification descriptions and weights for all codes. Specifications were applied to pilot variants with pre-existing ClinVar classification as follows: 13 uncertain significance or conflicting, 14 pathogenic and/or likely pathogenic, and 13 benign and/or likely benign. Review resolved classification for 11/13 uncertain significance or conflicting variants and retained or improved confidence in classification for the remaining variants.Alignment of pre-existing ENIGMA research classification processes with ACMG/AMP classification guidelines highlighted several gaps in the research processes and the baseline ACMG/AMP criteria. Calibration of evidence strength was key to justify utility and strength of different data types for gene-specific application. The gene-specific criteria demonstrated value for improving ACMG/AMP-aligned classification of BRCA1 and BRCA2 variants.

Since first publication of the American College of Medical Genetics and Genomics/Association for Medical Pathology (ACMG/AMP) variant classification guidelines, additional recommendations for application of certain criteria have been released (https://clinicalgenome.org/docs/), to improve their application in the diagnostic setting. However, none have addressed use of the PS4 and PP4 criteria, capturing patient presentation as evidence towards pathogenicity. Application of PS4 can be done through traditional case-control studies, or "proband counting" within or across clinical testing cohorts. Review of the existing PS4 and PP4 specifications for Hereditary Cancer Gene Variant Curation Expert Panels revealed substantial differences in the approach to defining specifications. Using BRCA1, BRCA2 and TP53 as exemplar genes, we calibrated different methods proposed for applying the "PS4 proband counting" criterion. For each approach, we considered limitations, non-independence with other ACMG/AMP criteria, broader applicability, and variability in results for different datasets. Our findings highlight inherent overlap of proband-counting methods with ACMG/AMP frequency codes, and the importance of calibration to derive dataset-specific code weights that can account for potential between-dataset differences in ascertainment and other factors. Our work emphasizes the advantages and generalizability of logistic regression analysis over simple proband-counting approaches to empirically determine the relative predictive capacity and weight of various personal clinical features in the context of multigene panel testing, for improved variant interpretation. We also provide a general protocol, including instructions for data formatting and a web-server for analysis of personal history parameters, to facilitate dataset-specific calibration analyses required to use such data for germline variant classification.

The relevance of large copy number variants (CNVs) to hereditary disorders has been long recognized, and population sequencing efforts have chronicled many common structural variants (SVs). However, limited data are available on the clinical contribution of rare germline SVs. Here, a detailed characterization of SVs identified using targeted next-generation sequencing was performed. Across 50 genes associated with hereditary cancer and cardiovascular disorders, a minimum of 828 unique SVs were reported, including 584 fully characterized SVs. Almost 40% of CNVs were <5 kb, with one in three deletions impacting a single exon. Additionally, 36 mid-range deletions/duplications (50 to 250 bp), 21 mobile element insertions, 6 inversions, and 27 complex rearrangements were detected. This data set was used to model SV detection in a bioinformatics pipeline solely relying on read depth, which revealed that genome sequencing (30x) allows detection of 71%, a 500x panel only targeting coding regions 53%, and exome sequencing (100x) <20% of characterized SVs. SVs accounted for 14.1% of all unique pathogenic variants, supporting the importance of SVs in hereditary disorders. Robust SV detection requires an ensemble of variant-calling algorithms that utilize sequencing of intronic regions. These algorithms should use distinct data features representative of each class of mutational mechanism, including recombination between two sequences sharing high similarity, covariants inserted between CNV breakpoints, and complex rearrangements containing inverted sequences. (J Mol Diagn 2021, 23: 612e629; https://doi.org/10.1016/j.jmoldx.2021.01.015)

Recent advancements in next-generation sequencing have greatly expanded the use of multi-gene panel testing for hereditary cancer risk. Although genetic testing helps guide clinical diagnosis and management, testing recommendations are based on personal and family history of cancer and ethnicity, and many carriers are being missed. Herein, we report the results from 23,179 individuals who were referred for 30-gene next-generation sequencing panel testing for hereditary cancer risk, independent of current testing guidelines-38.7% of individuals would not have met National Comprehensive Cancer Network criteria for genetic testing. We identified a total of 2811 pathogenic variants in 2698 individuals for an overall pathogenic frequency of 11.6/0 (9.1%, excluding common low-penetrance alleles). Among individuals of Ashkenazi Jewish descent, three-quarters of pathogenic variants were outside of the three common BRCA1 and BRCA2 founder alleles. Across all ethnic groups, pathogenic variants in BRCA1 and BRCA2 occurred most frequently, but the contribution of pathogenic variants in other genes on the panel varied. Finally, we found that 21.7% of individuals with pathogenic variants in genes with well-established genetic testing recommendations did not meet corresponding National Comprehensive Cancer Network criteria. Taken together, the results indicate that more individuals are at genetic risk for hereditary cancer than are identified by current testing guidelines and/or use of single-gene or single-site testing.

DNA damage by ultraviolet (UV) light poses a risk for mutagenesis and a potential hindrance for cell cycle progression. Cells cope with UV-induced DNA damage through two general strategies to repair the damaged nucleotides and to promote cell cycle progression in the presence of UV-damaged DNA. Defining the genetic pathways and understanding how they function together to enable effective tolerance to UV remains an important area of research. The structural maintenance of chromosomes (SMC) proteins form distinct complexes that maintain genome stability during chromosome segregation, homologous recombination, and DNA replication. Using a forward genetic screen, we identified two alleles of smc-5 that exacerbate UV sensitivity in Caenorhabditis elegans. Germ cells of smc-5-defective animals show reduced proliferation, sensitivity to perturbed replication, chromatin bridge formation, and accumulation of RAD-51 foci that indicate the activation of homologous recombination at DNA double-strand breaks. Mutations in the translesion synthesis polymerase polh-1 act synergistically with smc-5 mutations in provoking genome instability after UV-induced DNA damage. In contrast, the DNA damage accumulation and sensitivity of smc-5 mutant strains to replication impediments are suppressed by mutations in the C. elegans BRCA1/BARD1 homologs, brc-1 and brd-1. We propose that SMC-5/6 promotes replication fork stability and facilitates recombination-dependent repair when the BRC-1/BRD-1 complex initiates homologous recombination at stalled replication forks. Our data suggest that BRC-1/BRD-1 can both promote and antagonize genome stability depending on whether homologous recombination is initiated during DNA double-strand break repair or during replication stalling.

RBX1 (RING box protein 1), also known as ROC1 (Regulator of Cullin 1), is an essential component of SCF (Skp1/Cullins/F-box) E3 ubiquitin ligases, which target diverse proteins for proteasome-mediated degradation. Our recent study showed that RBX1 silencing triggered a DNA damage response (DDR) leading to G(2)-M arrest, senescence, and apoptosis, with the mechanism remaining elusive. Here, we show that, in human cancer cells, RBX1 silencing causes the accumulation of DNA replication licensing proteins CDT1 and ORC1, leading to DNA double-strand breaks, DDR, G(2) arrest, and, eventually, aneuploidy. Whereas CHK1 activation by RBX1 silencing is responsible for the G(2) arrest, enhanced DNA damage renders cancer cells more sensitive to radiation. In Caenorhabditis elegans, RBX-1 silencing causes CDT-1 accumulation, triggering DDR in intestinal cells, which is largely abrogated by simultaneous CDT-1 silencing. RBX-1 silencing also induces lethality during development of embryos and in adulthood. Thus, RBX1 E3 ligase is essential for the maintenance of mammalian genome integrity and the proper development and viability in C. elegans.

Left atrial (LA) volume is an important prognostic factor in cardiovascular disease. Multidetector computed tomography (MDCT) is an emerging cardiac imaging modality; however, its accuracy in measuring the LA volume has not been well studied. The aim of our study was to determine the accuracy of MDCT in quantifying the LA volume. A total of 48 patients underwent MDCT and 2-dimensional (2D) echocardiography (2DE) on the same day. The area length and Simpson's methods were used to obtain the 2D echocardiographic LA volume. The LA volume assessment by MDCT was obtained using the modified Simpson's method. Four artificial phantoms were created, and their true volume was assessed by an independent observer using both imaging modalities. The correlation between the LA volume by MDCT and 2DE was significant (r = 0.68). The mean 2D echocardiographic LA volume was lower than the LA volume obtained with MDCT (2DE 79 +/- 37 vs MDCT 103 +/- 32, p <0.05). In the phantom experiment, the volume obtained using MDCT and 2DE correlated significantly with the true volume (r = 0.97, p <0.05 vs r = 0.96, p <0.05, respectively). However, the mean 2D echocardiographic phantom volume was 16% lower than the true volume (2DE, Simpson's method 53 +/- 24 vs the true volume 61 +/- 24, p <0.05). The mean volume calculated using MDCT did not differ from the true volume (MDCT 60 +/- 21 vs true volume 61 +/- 24, p = NS). 2DE appeared to systematically underestimate the LA volume compared to phantom and cardiac MDCT, suggesting that different normal cutoff values should be used for each modality. In conclusion, LA volume quantification using MDCT is an accurate and feasible method. (C) 2010 Elsevier Inc. All rights reserved. (Am J Cardiol 2010;106:104-109)