Detection of germline CNVs from gene panel data: benchmarking the state of the art.

Germline copy number variants (CNVs) play a significant role in hereditary diseases. However, the accurate detection of CNVs from targeted next-generation sequencing (NGS) gene panel data remains a challenging task. Several tools for calling CNVs within this context have been published to date, but the available benchmarks suffer from limitations, including testing on simulated data, testing on small datasets, and testing a small subset of published tools.

vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines.

Motivation: Germline variant classification allows accurate genetic diagnosis and risk assessment. However, it is a tedious iterative process integrating information from several sources and types of evidence. It should follow gene-specific (if available) or general updated international guidelines.

Paired Somatic-Germline Testing of 15 Polyposis and Colorectal Cancer-Predisposing Genes Highlights the Role of APC Mosaicism in de Novo Familial Adenomatous Polyposis.

Familial adenomatous polyposis (FAP) is an autosomal dominant syndrome responsible for 1% of colorectal cancers (CRCs). Up to 90% of classic FAPs are caused by inactivating mutations in APC, and mosaicism has been previously reported in 20% of de novo cases, usually linked to milder phenotypic manifestations. This study aimed to explore the prevalence of mosaicism in 11 unsolved cases of classic FAP and to evaluate the diagnostic yield of somatic testing.

CNVfilteR: an R/Bioconductor package to identify false positives produced by germline NGS CNV detection tools.

Summary: Germline copy-number variants (CNVs) are relevant mutations for multiple genetics fields, such as the study of hereditary diseases. However, available benchmarks show that all next-generation sequencing (NGS) CNV calling tools produce false positives. We developed CNVfilteR, an R package that uses the single-nucleotide variant calls usually obtained in germline NGS pipelines to identify those false positives.

Pathogenic Variants are Associated with Triple-Negative Breast Cancer in a Spanish Hereditary Breast and Ovarian Cancer Cohort.

Only a small fraction of hereditary breast and/or ovarian cancer (HBOC) cases are caused by germline variants in the high-penetrance breast cancer 1 and 2 genes ( and . BRCA1-associated ring domain 1 (), nuclear partner of , has been suggested as a potential HBOC risk gene, although its prevalence and penetrance are variable according to populations and type of tumor. We aimed to investigate the prevalence of truncating variants in a cohort of patients with clinical suspicion of HBOC.

Screening of CNVs using NGS data improves mutation detection yield and decreases costs in genetic testing for hereditary cancer.

Introduction: Germline CNVs are important contributors to hereditary cancer. In genetic diagnostics, multiplex ligation-dependent probe amplification (MLPA) is commonly used to identify them. However, MLPA is time-consuming and expensive if applied to many genes, hence many routine laboratories test only a subset of genes of interest.

Evaluation of CNV detection tools for NGS panel data in genetic diagnostics.

Although germline copy-number variants (CNVs) are the genetic cause of multiple hereditary diseases, detecting them from targeted next-generation sequencing data (NGS) remains a challenge. Existing tools perform well for large CNVs but struggle with single and multi-exon alterations. The aim of this work is to evaluate CNV calling tools working on gene panel NGS data and their suitability as a screening step before orthogonal confirmation in genetic diagnostics strategies.

Exploring the Role of Mutations in Fanconi Anemia Genes in Hereditary Cancer Patients.

Fanconi anemia (FA) is caused by biallelic mutations in FA genes. Monoallelic mutations in five of these genes ( and ) increase the susceptibility to breast/ovarian cancer and are used in clinical diagnostics as bona-fide hereditary cancer genes. Increasing evidence suggests that monoallelic mutations in other FA genes could predispose to tumor development, especially breast cancer.