Germline Copy Number Variants Research Articles

A genome wide association study to identify germline copy number variants associated with cancer cachexia: a preliminary analysis

A genome wide association study to identify germline copy number variants associated with cancer cachexia: a preliminary analysis

ECOLE: Learning to call copy number variants on whole exome sequencing data.

Copy number variants (CNV) are shown to contribute to the etiology of several genetic disorders. Accurate detection of CNVs on whole exome sequencing (WES) data has been a long sought-after goal for use in clinics. This was not possible despite recent improvements in performance because algorithms mostly suffer from low precision and even lower recall on expert-curated gold standard call sets. Here, we present a deep learning-based somatic and germline CNV caller for WES data, named ECOLE. Based on a variant of the transformer architecture, the model learns to call CNVs per exon, using high-confidence calls made on matched WGS samples. We further train and fine-tune the model with a small set of expert calls via transfer learning. We show that ECOLE achieves high performance on human expert labelled data for the first time with 68.7% precision and 49.6% recall. This corresponds to precision and recall improvements of 18.7% and 30.8% over the next best-performing methods, respectively. We also show that the same fine-tuning strategy using tumor samples enables ECOLE to detect RT-qPCR-validated variations in bladder cancer samples without the need for a control sample. ECOLE is available at https://github.com/ciceklab/ECOLE .

Validating Clinical Exome Sequencing (CES) Test for Copy Number Variation (CNV) Analysis in Patients with Autism Spectrum Disorder

A routine methodologies to detect germline copy number variants (CNVs) are ArrayCGH, and SNParray, while clinical exome sequencing (CES) it is not a standard methods used in clinical settings. This study aims to investigate the efficiency of CNVs identification by CES in the diagnosis of Autism spectrum disorder (ASD) based on a Italian cohort. In this cohort study, 50 patients with ASD diagnosis were recruited for ASD screening. Simultaneous CNVs and single nucleotide variation (SNV) analysis was conducted to identify the anomalies that can cause ASD phenotype. A total of 13 patients were identified with a causative CNVs among 15 (86.67%) SNP array positive patients. Showing that CES data can be used for detecting clinically relevant CNVs with high sensitivity for use in clinical diagnostic settings.

Copy Number Variations in Pancreatic Cancer: From Biological Significance to Clinical Utility.

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, characterized by high tumor heterogeneity and a poor prognosis. Inter- and intra-tumoral heterogeneity in PDAC is a major obstacle to effective PDAC treatment; therefore, it is highly desirable to explore the tumor heterogeneity and underlying mechanisms for the improvement of PDAC prognosis. Gene copy number variations (CNVs) are increasingly recognized as a common and heritable source of inter-individual variation in genomic sequence. In this review, we outline the origin, main characteristics, and pathological aspects of CNVs. We then describe the occurrence of CNVs in PDAC, including those that have been clearly shown to have a pathogenic role, and further highlight some key examples of their involvement in tumor development and progression. The ability to efficiently identify and analyze CNVs in tumor samples is important to support translational research and foster precision oncology, as copy number variants can be utilized to guide clinical decisions. We provide insights into understanding the CNV landscapes and the role of both somatic and germline CNVs in PDAC, which could lead to significant advances in diagnosis, prognosis, and treatment. Although there has been significant progress in this field, understanding the full contribution of CNVs to the genetic basis of PDAC will require further research, with more accurate CNV assays such as single-cell techniques and larger cohorts than have been performed to date.

Exome Sequencing Identifies Multiple Genetic Diagnoses in Children with Syndromic Growth Disorders

To evaluate the presence of multiple genetic diagnoses in syndromic growth disorders. We carried out a cross-sectional study to evaluate 115 patients with syndromic tall (n=24) or short stature (n=91) of unknown cause from a tertiary referral center for growth disorders. Exome sequencing was performed to assess germline single nucleotide, InDel, and copy number variants. All variants were classified according to ACMG/AMP guidelines. The main outcome measured was the frequency of multiple genetic diagnoses in a cohort of children with syndromic growth disorders. The total diagnostic yield of the cohort was 54.8% (63/115). Six patients had multiple genetic diagnoses (tall stature group=2; short stature group=4). The proportion of multiple diagnoses within total cases was 5.2% (6/115), and within solved cases was 9.5% (6/63). No characteristics were significantly more frequent when compared with patients with single or multiple genetic findings. Among patients with multiple diagnoses, 3 had syndromes with overlapping clinical features, and the others had syndromes with distinct phenotypes. Recognition of multiple genetic diagnoses as a possibility in complex cases of syndromic growth disorders opens a new perspective on treatment and genetic counseling for affected patients, defying the medical common sense of trying to fit all findings into one diagnosis.

RB1 screening of retinoblastoma patients in Sri Lanka using targeted next generation sequencing (NGS) and gene ratio analysis copy enumeration PCR (GRACE-PCR)

BackgroundRetinoblastoma (RB) a tumour affecting those under 5 years, has a prevalence of 1 in 20,000, with around twenty new diagnoses per year in Sri Lanka. Unilateral and bilateral RB presents around 24 and 15 months respectively. Approximately 10% are familial. Systematic genetic testing for germline pathogenic variants of RB1, the only gene associated with an inherited risk of RB, is unavailable in Sri Lanka. Genetic testing optimizes management of affected children and at-risk siblings. This study aimed to develop accessible genetic testing to identify children with a germline pathogenic variant of RB1 in Sri Lanka.MethodsTargeted next generation sequencing (NGS) for detecting pathogenic sequence variants and Gene Ratio Analysis Copy Enumeration PCR (GRACE-PCR) for detecting RB1 copy number variations (CNVs) were performed for 49 consecutive RB patients treated between 2016 and 2020 at the designated RB care unit, Lady Ridgway hospital, Colombo. Patients (bilateral RB (n = 18; 37%), unilateral n = 31) were recruited following ethical clearance and informed consent.ResultsThere were 26 (53%) females. Mean age at diagnosis was 18 months. Thirty-five patients (71%) had undergone enucleation. Germline pathogenic variants of RB1 identified in 22/49 (45%) patients including 18 (37%; 12 bilateral and 6 unilateral) detected by targeted NGS (2 missense, 7 stop gained, 1 splice donor, 8 frameshift variants). Six were previously undescribed, likely pathogenic frameshift variants. Four bilateral RB patients had GRACE-PCR detected CNVs including one whole RB1, two intragenic deletions (exon 12/13; exon 11 and 23) and a partial duplication of exon 27. The only familial case (affected mother and child) shared the duplication. Only 2 of 4 CNVs and 10 of 18 pathogenic variants were confirmed by whole exome sequencing and Sanger sequencing respectively, due to funding limitations.ConclusionsThe study identified pathogenic or likely pathogenic germline RB1 sequence variants and copy number variants in 16/18 (89%) bilateral and 6/31(19%) unilateral cases, which is comparable to worldwide data (10–15% unilateral, 80–85% bilateral). Targeted NGS combined with GRACE-PCR significantly reduce the cost of RB1 testing in Sri Lanka, and may widen access for genetic diagnosis of RB patients in other low and middle income countries.

Germline pathogenic variants in neuroblastoma patients are enriched in BARD1 and predict worse survival.

Neuroblastoma is an embryonal cancer of the developing sympathetic nervous system. The genetic contribution of rare pathogenic or likely pathogenic germline variants in patients without a family history remains unclear. Germline DNA sequencing was performed on 786 neuroblastoma patients. The frequency of rare cancer predisposition gene pathogenic or likely pathogenic variants in patients was compared with 2 cancer-free control cohorts. Matched tumor DNA sequencing was evaluated for second hits, and germline DNA array data from 5585 neuroblastoma patients and 23 505 cancer-free control children were analyzed to identify rare germline copy number variants. Patients with germline pathogenic or likely pathogenic variants were compared with those without to test for association with clinical characteristics, tumor features, and survival. We observed 116 pathogenic or likely pathogenic variants involving 13.9% (109 of 786) of neuroblastoma patients, representing a statistically significant excess burden compared with cancer-free participants (odds ratio [OR] = 1.60, 95% confidence interval [CI] = 1.27 to 2.00). BARD1 harbored the most statistically significant enrichment of pathogenic or likely pathogenic variants (OR = 32.30, 95% CI = 6.44 to 310.35). Rare germline copy number variants disrupting BARD1 were identified in patients but absent in cancer-free participants (OR = 29.47, 95% CI = 1.52 to 570.70). Patients harboring a germline pathogenic or likely pathogenic variant had a worse overall survival compared with those without (P = 8.6 x 10-3). BARD1 is an important neuroblastoma predisposition gene harboring both common and rare germline pathogenic or likely pathogenic variations. The presence of any germline pathogenic or likely pathogenic variant in a cancer predisposition gene was independently predictive of worse overall survival. As centers move toward paired tumor-normal sequencing at diagnosis, efforts should be made to centralize data and provide an infrastructure to support cooperative longitudinal prospective studies of germline pathogenic variation.

Clinical validation of a single NGS targeted panel pipeline using the KAPA HyperChoice system for detection of germline, somatic and mitochondrial sequence and copy number variants

ABSTRACT Background Comprehensive molecular diagnostics are highly dependent on the technical performance of next-generation sequencing (NGS) pipelines, which are assessed by data quality, cost, turnaround time, and accuracy of detecting a range of sequence and copy number variants. Methods A dataset of 285 clinically validated cases (205 retrospective and 80 prospective), carrying complex sequence and copy number variants and thousands of genetic polymorphisms underwent a clinical validation of the KAPA HyperChoice target enrichment system with parallel sample fidelity assessment across a number of NGS panels. The analysis included assessment of peripheral blood, urine, muscle and FFPE tissues. Results High-quality and exceptionally uniform data with 100% coverage of all targeted panels were obtained, resulting in complete sensitivity and specificity for all variant types across nearly all panels and tissue types. Overall reduction in cost and turnaround times was obtained with the implementation of a parallel genotyping sample fidelity system. Conclusion Results of the laboratory quality improvement study focused on a single NGS pipeline that includes both nuclear and mitochondrial genomes demonstrated utility in the clinical setting to assess a range of referral reasons, necessary due to the complex molecular etiology of human genetic disorders, while reducing costs and turnaround times.

Co-Occurrence of Germline Genomic Variants and Copy Number Variations in Hereditary Breast and Colorectal Cancer Patients.

Hereditary Breast and Ovarian Cancer (HBOC) syndrome is an autosomal dominant disease associated with a high risk of developing breast, ovarian, and other malignancies. Lynch syndrome is caused by mutations in mismatch repair genes predisposing to colorectal and endometrial cancers, among others. A rare phenotype overlapping hereditary colorectal and breast cancer syndromes is poorly characterized. Three breast and colorectal cancer unrelated patients fulfilling clinical criteria for HBOC were tested by whole exome sequencing. A family history of colorectal cancer was reported in two patients (cases 2 and 3). Several variants and copy number variations were identified, which potentially contribute to the cancer risk or prognosis. All patients presented copy number imbalances encompassing PMS2 (two deletions and one duplication), a known gene involved in the DNA mismatch repair pathway. Two patients showed gains covering the POLE2 (cases 1 and 3), which is associated with DNA replication. Germline potentially damaging variants were found in PTCH1 (patient 3), MAT1A, and WRN (patient 2). Overall, concurrent genomic alterations were described that may increase the risk of cancer appearance in HBOC patients with breast and colorectal cancers.

Germline CNV Detection through Whole-Exome Sequencing (WES) Data Analysis Enhances Resolution of Rare Genetic Diseases.

Whole-Exome Sequencing (WES) has proven valuable in the characterization of underlying genetic defects in most rare diseases (RDs). Copy Number Variants (CNVs) were initially thought to escape detection. Recent technological advances enabled CNV calling from WES data with the use of accurate and highly sensitive bioinformatic tools. Amongst 920 patients referred for WES, 454 unresolved cases were further analysed using the ExomeDepth algorithm. CNVs were called, evaluated and categorized according to ACMG/ClinGen recommendations. Causative CNVs were identified in 40 patients, increasing the diagnostic yield of WES from 50.7% (466/920) to 55% (506/920). Twenty-two CNVs were available for validation and were all confirmed; of these, five were novel. Implementation of the ExomeDepth tool promoted effective identification of phenotype-relevant and/or novel CNVs. Among the advantages of calling CNVs from WES data, characterization of complex genotypes comprising both CNVs and SNVs minimizes cost and time to final diagnosis, while allowing differentiation between true or false homozygosity, as well as compound heterozygosity of variants in AR genes. The use of a specific algorithm for calling CNVs from WES data enables ancillary detection of different types of causative genetic variants, making WES a critical first-tier diagnostic test for patients with RDs.

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)-present in some but not all cells-remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p= 2.68e-4), with recurrent somatic deletions of exons 1-5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5' deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk.

Germline loss-of-function PAM variants are enriched in subjects with pituitary hypersecretion.

Pituitary adenomas (PAs) are common, usually benign tumors of the anterior pituitary gland which, for the most part, have no known genetic cause. PAs are associated with major clinical effects due to hormonal dysregulation and tumoral impingement on vital brain structures. PAM encodes a multifunctional protein responsible for the essential C-terminal amidation of secreted peptides. Following the identification of a loss-of-function variant (p.Arg703Gln) in the peptidylglycine a-amidating monooxygenase (PAM) gene in a family with pituitary gigantism, we investigated 299 individuals with sporadic PAs and 17 familial isolated PA kindreds for PAM variants. Genetic screening was performed by germline and tumor sequencing and germline copy number variation (CNV) analysis. In germline DNA, we detected seven heterozygous, likely pathogenic missense, truncating, and regulatory SNVs. These SNVs were found in sporadic subjects with growth hormone excess (p.Gly552Arg and p.Phe759Ser), pediatric Cushing disease (c.-133T>C and p.His778fs), or different types of PAs (c.-361G>A, p.Ser539Trp, and p.Asp563Gly). The SNVs were functionally tested in vitro for protein expression and trafficking by Western blotting, splicing by minigene assays, and amidation activity in cell lysates and serum samples. These analyses confirmed a deleterious effect on protein expression and/or function. By interrogating 200,000 exomes from the UK Biobank, we confirmed a significant association of the PAM gene and rare PAM SNVs with diagnoses linked to pituitary gland hyperfunction. The identification of PAM as a candidate gene associated with pituitary hypersecretion opens the possibility of developing novel therapeutics based on altering PAM function.

Abstract 6064: Patient-partnered research enables germline characterization of angiosarcoma predisposition genes

Abstract Background: Angiosarcoma (ASC) represents 1-2% of soft tissue sarcomas. Due to its rarity, to date, no large-scale studies have been done to systematically identify ASC-predisposition genes and the broader landscape of pathogenic germline variants in patients with ASC remains unclear. Methods: Through the Angiosarcoma Project, an ongoing patient-partnered research approach that allows patients living anywhere in the U.S. or Canada with angiosarcoma to participate through a website, blood and saliva samples were collected from more than 300 patients and whole-exome-sequencing was performed. Machine-learning frameworks were used to identify germline short variants (SNPs, indels) and rare germline copy number variants (CNVs). The pathogenicity of variants in 107 curated cancer-predisposition and sarcoma-related genes were evaluated according to the ACMG guidelines. A short-variant-based gene-burden analysis was then performed using 223 unrelated ASC patients and 4557 ancestry-matched unrelated cancer-free controls. Results: In total, 38 patients (17.04%) carried at least one pathogenic short variant, including 37 carrying germline heterozygous pathogenic variants in POT1 (9, 4.04%), BRCA2 (3, 1.35%), CHEK2 (3, 1.35%), MUTYH (3, 1.35%), BRCA1 (2, 0.90%), PRF1 (2, 0.90%), ERCC3 (1, 0.45%), TP53 (2, 0.90%), ATM (1, 0.45%), TSHR (1, 0.45%), TSC2 (1, 0.45%), SDHA (1, 0.45%), SBDS (1, 0.45%), MSH6 (1, 0.45%), MITF (1, 0.45%), MET (1, 0.45%), LZTR1 (1, 0.45%), FH (1, 0.45%), ERCC2 (1, 0.45%), XPC (1, 0.45%). In addition, one patient harbored pathogenic short variants in both BRCA1 and ERCC3. In the 8 unique CNVs detected in 10 (4.55%) patients, 6 were classified as pathogenic including 3 heterozygous duplications overlapping MSH2, LZTR1, SMARCB1, and 3 heterozygous deletions overlapping NF1, MSH2, and WRN. Two unique heterozygous duplications met VUS criteria including one overlapping ERCC2 and one overlapping SMARCB1. In a comparison between ASC patients and cancer-free controls of predominantly European ancestry, we found ASC patients tobe 40 times more likely to carry a pathogenic variant in POT1 (OR: 42.91, CI: [15.40-174.08], q < 0.001, p < 0.001), while TP53 was nominally significant (OR: 7.37, CI: [1.19 - 41.13], p = 0.037). Conclusion: We confirmed prior observations of POT1 being responsible for ASC and called for attention to investigate the effect of germline CNVs in ASC. Overall, the elucidation of various germline elements associated with ASC risk highlighted the value and importance of patient-partnered research, particularly for rare cancers, and the analysis support using germline testing of patients for more precise clinical management. Citation Format: Hoyin Chu, Marissa Hollyer, Seunghun Han, Sabrina Y. Camp, Riaz Gillani, Eliezer Van Allen, Nikhil Wagle, Corrie A. Painter, Saud H. AlDubayan. Patient-partnered research enables germline characterization of angiosarcoma predisposition genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6064.

Hereditary cancer predispositions: Comparison of multigene panel sequencing on fresh-frozen breast/ovarian tumor versus blood.

In breast or ovarian cancer (BC/OC) patients with evocative personal and/or family history, multigene panel sequencing is performed on blood to diagnose hereditary predispositions. Additionally, BRCA1/BRCA2 testing can be performed on tumor sample for therapeutic purpose. The accuracy of multigene panel tumor analysis on BC/OC to detect predisposing germline pathogenic variants (gPV) has not been precisely assessed. By comparing sequencing data from blood and fresh-frozen tumor we show that tumor genomic instability causes pitfalls to consider when performing tumor testing to detect gPV. Even if loss of heterozygosity increases germline signal in most cases, somatic copy number variants (CNV) can mask germline CNV and collapse point gPV variant allele frequency (VAF). Moreover, VAF does not allow an accurate distinction between germline and somatic pathogenic variants.

ConanVarvar: a versatile tool for the detection of large syndromic copy number variation from whole-genome sequencing data

BackgroundA wide range of tools are available for the detection of copy number variants (CNVs) from whole-genome sequencing (WGS) data. However, none of them focus on clinically-relevant CNVs, such as those that are associated with known genetic syndromes. Such variants are often large in size, typically 1–5 Mb, but currently available CNV callers have been developed and benchmarked for the discovery of smaller variants. Thus, the ability of these programs to detect tens of real syndromic CNVs remains largely unknown.ResultsHere we present ConanVarvar, a tool which implements a complete workflow for the targeted analysis of large germline CNVs from WGS data. ConanVarvar comes with an intuitive R Shiny graphical user interface and annotates identified variants with information about 56 associated syndromic conditions. We benchmarked ConanVarvar and four other programs on a dataset containing real and simulated syndromic CNVs larger than 1 Mb. In comparison to other tools, ConanVarvar reports 10–30 times less false-positive variants without compromising sensitivity and is quicker to run, especially on large batches of samples.ConclusionsConanVarvar is a useful instrument for primary analysis in disease sequencing studies, where large CNVs could be the cause of disease.

Association of self-identified race and genetic ancestry with the immunogenomic landscape of primary prostate cancer.

The genomic and immune landscapes of prostate cancer differ by self-identified race. However, few studies have examined the genome-wide copy number landscape and immune content of matched cohorts with genetic ancestry data and clinical outcomes. Here, we assessed prostate cancer somatic copy number alterations (sCNA) and tumor immune content of a grade-matched, surgically treated cohort of 145 self-identified Black (BL) and 145 self-identified White (WH) patients with genetic ancestry estimation. A generalized linear model adjusted with age, preoperative prostate-specific antigen (PSA), and Gleason Grade Group and filtered for germline copy number variations (gCNV) identified 143 loci where copy number varied significantly by percent African ancestry, clustering on chromosomes 6p, 10q, 11p, 12p, and 17p. Multivariable Cox regression models adjusted for age, preoperative PSA levels, and Gleason Grade Group revealed that chromosome 8q gains (including MYC) were significantly associated with biochemical recurrence and metastasis, independent of genetic ancestry. Finally, Treg density in BL and WH patients was significantly correlated with percent genome altered, and these findings were validated in the TCGA cohort. Taken together, our findings identify specific sCNA linked to genetic ancestry and outcome in primary prostate cancer and demonstrate that Treg infiltration varies by global sCNA burden in primary disease.

A comparison of algorithms for identifying copy number variants in family-based whole-exome sequencing data and its implications in inheritance pattern analysis

There remain challenges in accurately identifying constitutional or germline copy number variants (gCNVs) based on whole-exome sequencing data that have implications for genetic diagnosis for ‘rare undiagnosed disease’ in the clinical setting. Although multiple algorithms have been proposed, a systematic comparison of these algorithms for calling gCNVs and analyzing inherited pattern have yet to be fully conducted. Therefore, we empirically compared seven exome-based algorithms, including XHMM, CLAMMS, CODEX2, ExomeDepth, DECoN, CN.MOPS, and GATK gCNV, for calling gCNVs in 151 individuals from 44 pedigrees, together with the gold standard of genotyping-derived gCNVs in the same cohort for the performance assessment. These algorithms demonstrated varied powers in identifying gCNVs, although the distribution of gCNVs size was similar. The number of shared gCNVs across these algorithms was limited (e.g., only four gCNVs shared among seven algorithms); however, several algorithms showed varying degrees of consistency (e.g., 1,843 gCNVs shared between DECoN and ExomeDepth). CLAMMS and CODEX2 outperformed the remaining algorithms according to a relatively higher F-score (i.e., 0.145 and 0.152, respectively). In addition, these algorithms exhibited different Mendelian inconsistencies of gCNVs and significant challenges remained in inheritance pattern analysis. In conclusion, selecting good algorithms may have important implications in gCNVs-based inheritance pattern analysis for family-based studies.

Copy Number Variations (CNVs) Account for 10.8% of Pathogenic Variants in Patients Referred for Hereditary Cancer Testing.

Germline copy number variation (CNV) is a type of genetic variant that predisposes significantly to inherited cancers. Today, next-generation sequencing (NGS) technologies have contributed to multi gene panel analysis in clinical practice. A total of 2,163 patients were screened for cancer susceptibility, using a solution-based capture method. A panel of 52 genes was used for targeted NGS. The capture-based approach enables computational analysis of CNVs from NGS data. We studied the performance of the CNV module of the commercial software suite SeqPilot (JSI Medical Systems) and of the non-commercial tool panelcn.MOPS. Additionally, we tested the performance of digital multiplex ligation-dependent probe amplification (digitalMLPA). Pathogenic/likely pathogenic variants (P/LP) were identified in 464 samples (21.5%). CNV accounts for 10.8% (50/464) of pathogenic variants, referring to deletion/duplication of one or more exons of a gene. In patients with breast and ovarian cancer, CNVs accounted for 10.2% and 6.8% of pathogenic variants, respectively. In colorectal cancer patients, CNV accounted for 28.6% of pathogenic/likely pathogenic variants. In silico CNV detection tools provide a viable and cost-effective method to identify CNVs from NGS experiments. CNVs constitute a substantial percentage of P/LP variants, since they represent up to one of every ten P/LP findings identified by NGS multigene analysis; therefore, their evaluation is highly recommended to improve the diagnostic yield of hereditary cancer analysis.

Copy number variants as modifiers of breast cancer risk for BRCA1/BRCA2 pathogenic variant carriers

The contribution of germline copy number variants (CNVs) to risk of developing cancer in individuals with pathogenic BRCA1 or BRCA2 variants remains relatively unknown. We conducted the largest genome-wide analysis of CNVs in 15,342 BRCA1 and 10,740 BRCA2 pathogenic variant carriers. We used these results to prioritise a candidate breast cancer risk-modifier gene for laboratory analysis and biological validation. Notably, the HR for deletions in BRCA1 suggested an elevated breast cancer risk estimate (hazard ratio (HR) = 1.21), 95% confidence interval (95% CI = 1.09–1.35) compared with non-CNV pathogenic variants. In contrast, deletions overlapping SULT1A1 suggested a decreased breast cancer risk (HR = 0.73, 95% CI 0.59-0.91) in BRCA1 pathogenic variant carriers. Functional analyses of SULT1A1 showed that reduced mRNA expression in pathogenic BRCA1 variant cells was associated with reduced cellular proliferation and reduced DNA damage after treatment with DNA damaging agents. These data provide evidence that deleterious variants in BRCA1 plus SULT1A1 deletions contribute to variable breast cancer risk in BRCA1 carriers.

Algorithmic improvements for discovery of germline copy number variants in next-generation sequencing data

BackgroundCopy number variants (CNVs) play a significant role in human heredity and disease. However, sensitive and specific characterization of germline CNVs from NGS data has remained challenging, particularly for hybridization-capture data in which read counts are the primary source of copy number information.ResultsWe describe two algorithmic adaptations that improve CNV detection accuracy in a Hidden Markov Model (HMM) context. First, we present a method for computing target- and copy number-specific emission distributions. Second, we demonstrate that the Pointwise Maximum a posteriori (PMAP) HMM decoding procedure yields improved sensitivity for small CNV calls compared to the more common Viterbi HMM decoder. We develop a prototype implementation, called Cobalt, and compare it to other CNV detection tools using sets of simulated and previously detected CNVs with sizes spanning a single exon to a full chromosome.ConclusionsIn both the simulation and previously detected CNV studies Cobalt shows similar sensitivity but significantly fewer false positive detections compared to other callers. Overall sensitivity is 80–90% for deletion CNVs spanning 1–4 targets and 90–100% for larger deletion events, while sensitivity is somewhat lower for small duplication CNVs.