Assessing the Phenotype of a Homologous Recombination Deficiency Using High Resolution Array-Based Comparative Genome Hybridization in Ovarian Cancer.

Ovarian cancer (OC) cells with homologous recombination deficiency (HRD) accumulate genomic scars (LST, TAI, and LOH) over a value of 42 in sum. PARP inhibitors can treat OC with HRD. The detection of HRD can be done directly by imaging these genomic scars, or indirectly by detecting mutations in the genes involved in HR. We show that HRD detection is also possible using high-resolution aCGH. A total of 30 OCs were analyzed retrospectively with high-resolution arrays as a test set and 19 OCs prospectively as a validation set. Mutation analysis was performed by HBOC TruRisk V2 panel to detect HR-relevant mutations. CNVs were clustered with respect to the involved HR genes versus the OC cases. In prospective validation, the HRD status determined by aCGH was compared with external HRD assessments. Two BRCA mutation carriers did not have HRD. OC could approximately differentiate into two groups with characteristic CNV patterns with different survival rates. Mutation frequencies have a linear regression on the HRD score. Mutations in individual HR-relevant genes do not always indicate HRD. This may depend on the mutation frequency in tumor cells. The aCGH shows the genomic scars of an HRD inexpensively and directly.

Generation of a Specific Fluorescence In Situ Hybridization Test for the Detection of Ovarian Carcinoma Cells.

Examinations of ovarian cancer cells require the ability to identify tumor cells. Array-based comparative genome hybridization (aCGH) on 30 ovarian carcinomas (OC) identified three genomic loci (8q24.23; 17p12; 18q22.3) over- or under-represented in OC. A fluorescence in situ hybridization (FISH) probe of these three loci is intended to identify tumor cells by their signal pattern deviating from a diploid pattern. Human DNA from these three loci is isolated from bacterial artificial chromosomes (BAC), amplified and labeled with fluorescent dyes. After a standard FISH procedure, 71 OC suspensions from primary tumors, three OC cell lines, three lymphocyte suspensions, and one mesenchymal cell line LP-3 are analyzed with a fluorescence microscope. On average, 15% of the lymphocytes deviate from the expected diploid signal pattern, giving a cut-off of 36%. If this value is exceeded, tumor cells are detected. The mesenchymal cell line LP-3 shows only 21% as a negative control. The OC cell lines as positive controls exceed this value at 38%, 67%, and 54%. Of the 71 OC primary cultures, four cases fell below this cut-off as false negatives. In the two-sample t-test, the percentages of conspicuous signal patterns differ significantly.

EMQN best practice guidelines for genetic testing in hereditary breast and ovarian cancer.

Hereditary Breast and Ovarian Cancer (HBOC) is a genetic condition associated with increased risk of cancers. The past decade has brought about significant changes to hereditary breast and ovarian cancer (HBOC) diagnostic testing with new treatments, testing methods and strategies, and evolving information on genetic associations. These best practice guidelines have been produced to assist clinical laboratories in effectively addressing the complexities of HBOC testing, while taking into account advancements since the last guidelines were published in 2007. These guidelines summarise cancer risk data from recent studies for the most commonly tested high and moderate risk HBOC genes for laboratories to refer to as a guide. Furthermore, recommendations are provided for somatic and germline testing services with regards to clinical referral, laboratory analyses, variant interpretation, and reporting. The guidelines present recommendations where 'must' is assigned to advocate that the recommendation is essential; and 'should' is assigned to advocate that the recommendation is highly advised but may not be universally applicable. Recommendations are presented in the form of shaded italicised statements throughout the document, and in the form of a table in supplementary materials (Table S4). Finally, for the purposes of encouraging standardisation and aiding implementation of recommendations, example report wording covering the essential points to be included is provided for the most common HBOC referral and reporting scenarios. These guidelines are aimed primarily at genomic scientists working in diagnostic testing laboratories.

Limitations in next-generation sequencing-based genotyping of breast cancer polygenic risk score loci.

Considering polygenic risk scores (PRSs) in individual risk prediction is increasingly implemented in genetic testing for hereditary breast cancer (BC) based on next-generation sequencing (NGS). To calculate individual BC risks, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) with the inclusion of the BCAC 313 or the BRIDGES 306 BC PRS is commonly used. The PRS calculation depends on accurately reproducing the variant allele frequencies (AFs) and, consequently, the distribution of PRS values anticipated by the algorithm. Here, the 324 loci of the BCAC 313 and the BRIDGES 306 BC PRS were examined in population-specific database gnomAD and in real-world data sets of five centers of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC), to determine whether these expected AFs can be reproduced by NGS-based genotyping. Four PRS loci were non-existent in gnomAD v3.1.2 non-Finnish Europeans, further 24 loci showed noticeably deviating AFs. In real-world data, between 11 and 23 loci were reported with noticeably deviating AFs, and were shown to have effects on final risk prediction. Deviations depended on the sequencing approach, variant caller and calling mode (forced versus unforced) employed. Therefore, this study demonstrates the necessity to apply quality assurance not only in terms of sequencing coverage but also observed AFs in a sufficiently large cohort, when implementing PRSs in a routine diagnostic setting. Furthermore, future PRS design should be guided by the technical reproducibility of expected AFs across commonly used genotyping methods, especially NGS, in addition to the observed effect sizes.

Quality assurance within the context of genome diagnostics (a german perspective).

The rapid and dynamic implementation of Next-Generation Sequencing (NGS)-based assays has revolutionized genetic testing, and in the near future, nearly all molecular alterations of the human genome will be diagnosable via massive parallel sequencing. While this progress will further corroborate the central role of human genetics in the multidisciplinary management of patients with genetic disorders, it must be accompanied by quality assurance measures in order to allow the safe and optimal use of knowledge ascertained from genome diagnostics. To achieve this, several valuable tools and guidelines have been developed to support the quality of genome diagnostics. In this paper, authors with experience in diverse aspects of genomic analysis summarize the current status of quality assurance in genome diagnostics, with the aim of facilitating further standardization and quality improvement in one of the core competencies of the field.