Performance of In Silico Prediction Tools for the Detection of Germline Copy Number Variations in Cancer Predisposition Genes in 4208 Female Index Patients with Familial Breast and Ovarian Cancer

A deep intronic recurrent CHEK2 variant c.1009-118_1009-87delinsC affects pre-mRNA splicing and contributes to hereditary breast cancer predisposition

Germline CHEK2 pathogenic variants confer an increased risk of female breast cancer (FBC). Here we describe a recurrent germline intronic variant c.1009-118_1009-87delinsC, which showed a splice acceptor shift in RNA analysis, introducing a premature stop codon (p.Tyr337PhefsTer37). The variant was found in 21/10,204 (0.21%) Czech FBC patients compared to 1/3250 (0.03%) controls (p = 0.04) and in 4/3639 (0.11%) FBC patients from an independent German dataset. In addition, we found this variant in 5/2966 (0.17%) Czech (but none of the 443 German) ovarian cancer patients, three of whom developed early-onset tumors. Based on these observations, we classified this variant as likely pathogenic.

Clinical implications of incorporating genetic and non-genetic risk factors in CanRisk-based breast cancer risk prediction

BACKGROUND

Breast cancer (BC) risk prediction models consider cancer family history (FH) and germline pathogenic variants (PVs) in risk genes. It remains elusive to what extent complementation with polygenic risk score (PRS) and non-genetic risk factor (NGRFs) data affects individual intensified breast surveillance (IBS) recommendations according to European guidelines.

METHODS

For 425 cancer-free women with cancer FH (mean age 40·6 years, range 21-74), recruited in France, Germany and the Netherlands, germline PV status, NGRFs, and a 306 variant-based PRS (PRS306) were assessed to calculate estimated lifetime risks (eLTR) and estimated 10-year risks (e10YR) using CanRisk. The proportions of women changing country-specific European risk categories for IBS recommendations, i.e. ≥20 % and ≥30 % eLTR, or ≥5 % e10YR were determined.

FINDINGS

Of the women with non-informative PV status, including PRS306 and NGRFs changed clinical recommendations for 31·0 %, (57/184, 20 % eLTR), 15·8 % (29/184, 30 % eLTR) and 22·4 % (41/183, 5 % e10YR), respectively whereas of the women tested negative for a PV observed in their family, clinical recommendations changed for 16·7 % (25/150), 1·3 % (2/150) and 9·5 % (14/147). No change was observed for 82 women with PVs in high-risk genes (BRCA1/2, PALB2). Combined consideration of eLTRs and e10YRs identified BRCA1/2 PV carriers benefitting from IBS <30 years, and women tested non-informative/negative for whom IBS may be postponed.

INTERPRETATION

For women who tested non-informative/negative, PRS and NGRFs have a considerable impact on IBS recommendations. Combined consideration of eLTRs and e10YRs allows personalizing IBS starting age.

FUNDING

Horizon 2020, German Cancer Aid, Federal Ministry of Education and Research, Köln Fortune.

Pathogenic germline variants in SMARCA4 and further cancer predisposition genes in early onset ovarian cancer

To assess the role of germline pathogenic variants (PVs) in SMARCA4 and further established ovarian cancer (OC) predisposition genes in early onset OC, we investigated a clinical cohort of 206 unrelated OC index patients with an age at diagnosis of OC ≤40 years using an extended panel of 24 (candidate) cancer predisposition genes. PVs in established OC predisposition genes were most frequent in patients with high grade serous OC (21/62, 33.9%), comparatively rare in patients with epithelial OC other than high grade serous (5/74, 6.8%) or borderline ovarian tumours (2/39, 5.1%) and absent in mucinous OC (0/27). We demonstrate that germline PVs in SMARCA4 unlikely predispose for early onset OC other than SCCOHT.

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 analysing 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.

Evaluation of copy number variants for genetic hearing loss: a review of current approaches and recent findings

Structural variation includes a change in copy number, orientation, or location of a part of the genome. Copy number variants (CNVs) are a common cause of genetic hearing loss, comprising nearly 20% of diagnosed cases. While large deletions involving the gene STRC are the most common pathogenic CNVs, a significant proportion of known hearing loss genes also contain pathogenic CNVs. In this review, we provide an overview of currently used methods for detection of CNVs in genes known to cause hearing loss including molecular techniques such as multiplex ligation probe amplification (MLPA) and digital droplet polymerase chain reaction (ddPCR), array-CGH and single-nucleotide polymorphism (SNP) arrays, as well as techniques for detection of CNVs using next-generation sequencing data analysis including targeted gene panel, exome, and genome sequencing data. In addition, in this review, we compile published data on pathogenic hearing loss CNVs to provide an up-to-date overview. We show that CNVs have been identified in 29 different non-syndromic hearing loss genes. An understanding of the contribution of CNVs to genetic hearing loss is critical to the current diagnosis of hearing loss and is crucial for future gene therapies. Thus, evaluation for CNVs is required in any modern pipeline for genetic diagnosis of hearing loss.