Next-Generation Sequencing-Based Detection of Germline Copy Number Variations in BRCA1/BRCA2: Validation of a One-Step Diagnostic Workflow

Imaging surveillance in multiple endocrine neoplasia type 1: Ten years of experience with somatostatin receptor positron emission tomography

Guidelines for multiple endocrine neoplasia type 1 (MEN1) recommend intensive imaging surveillance without specifying a superior regimen, including the role of somatostatin receptor imaging (SRI) with positron emission tomography (PET). The primary outcomes were to: (1) Assess change in treatment of duodenal-pancreatic neuroendocrine neoplasms (DP-NENs), bronchopulmonary NENs, and thymic tumors attributed to use of SRI PET/computed tomography (CT) and (2) estimate radiation from imaging and risk of cancer death attributed to imaging radiation. This was a retrospective single center study, including all MEN1 patients, who had had at least one SRI PET/CT. A total of 60 patients, median age 42 (range 21-54) years, median follow-up 6 (range 1-10) years were included. Of 470 cross sectional scans (MRI, CT, SRI PET/CT), 209 were SRI PET/CT. The additional information from SRI PET had implications in 1/14 surgical interventions and 2/12 medical interventions. The estimated median radiation dose per patient was 104 (range 51-468) mSv of which PET contributed with 13 (range 5-55) mSv and CT with 91 mSv (range 46-413 mSv), corresponding to an estimated increased median risk of cancer death of 0.5% during 6 years follow-up. SRI PET had a significant impact on 3/26 decisions to intervene in 60 MEN1 patients followed for a median of 6 years with SRI PET/CT as the most frequently used modality. The surveillance program showed a high radiation dose. Multi-modality imaging strategies designed to minimize radiation exposure should be considered. Based on our findings, SRI-PET combined with CT cannot be recommended for routine surveillance in MEN1 patients.

Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci

BACKGROUND

Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.

METHODS

Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types.

RESULTS

We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.

CONCLUSIONS

CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

A Validation Framework for Somatic Copy Number Detection in Targeted Sequencing Panels

Somatic copy number alterations (SCNAs) in tumors are clinically significant diagnostic, prognostic, and predictive biomarkers. SCNA detection from targeted next-generation sequencing panels is increasingly common in clinical practice; however, detailed descriptions of optimization and validation of SCNA pipelines for small targeted panels are limited. This study describes the validation and implementation of a tumor-only SCNA pipeline using CNVkit, augmented with custom modules and optimized for clinical implementation by testing reference materials and clinical tumor samples with different classes of copy number variation (CNV; amplification, single copy loss, and biallelic loss). Using wet-bench and in silico methods, various parameters impacting CNV calling, including assay-intrinsic variables (establishment of normal reference and sequencing coverage), sample-intrinsic variables (tumor purity and sample quality), and CNV algorithm-intrinsic variables (bin size), were optimized. The pipeline was trained and tested on an optimization cohort and validated using an independent cohort with a sensitivity and specificity of 100% and 93%, respectively. Using custom modules, intragenic CNVs with breakpoints within tumor suppressor genes were uncovered. Using the validated pipeline, re-analysis of 28 pediatric solid tumors that had been previously profiled for mutations identified SCNAs in 86% (24/28) samples, with 46% (13/28) samples harboring findings of potential clinical relevance. Our report highlights the importance of rigorous establishment of performance characteristics of SCNA pipelines and presents a detailed validation framework for optimal SCNA detection in targeted sequencing panels.

BRCA1 and Breast Cancer: Molecular Mechanisms and Therapeutic Strategies

Breast cancer susceptibility gene 1 (BRCA1) is a tumor suppressor gene, which is mainly involved in the repair of DNA damage, cell cycle regulation, maintenance of genome stability, and other important physiological processes. Mutations or defects in the BRCA1 gene significantly increase the risk of breast, ovarian, prostate, and other cancers in carriers. In this review, we summarized the molecular functions and regulation of BRCA1 and discussed recent insights into the detection and treatment of BRCA1 mutated breast cancer.

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.

Prevalence of BRCA1 and BRCA2 Mutations Among Patients With Ovarian, Primary Peritoneal, and Fallopian Tube Cancer in India: A Multicenter Cross-Sectional Study

PURPOSE

There are deficient data on prevalence of germline mutations in breast cancer susceptibility genes 1 and 2 (BRCA1/BRCA2) in Indian patients with ovarian cancer who are not selected by clinical features.

METHODS

This prospective, cross-sectional, noninterventional study in nine Indian centers included patients with newly diagnosed or relapsed epithelial ovarian, primary peritoneal, or fallopian tube cancer. The primary objective was to assess the prevalence of BRCA1/BRCA2 mutations, and the secondary objective was to correlate BRCA1/BRCA2 status with clinicopathologic characteristics. Mutation testing was performed by a standard next-generation sequencing assay.

RESULTS

Between March 2018 and December 2018, 239 patients with a median age of 53.0 (range, 23.0-86.0 years) years were included, of whom 203 (84.9%) had newly diagnosed disease, 36 (15.1%) had family history of ovarian or breast cancer, and 159 (66.5%) had serous subtype of epithelial ovarian cancer. Germline pathogenic or likely pathogenic mutations in BRCA1 and BRCA2 were detected in 37 (15.5%; 95% CI, 11.1 to 20.7) and 14 (5.9%; 95% CI, 3.2 to 9.6) patients, respectively, whereas variants of uncertain significance in these genes were seen in four (1.7%; 95% CI, 0.5 to 4.2) and six (2.5%; 95% CI, 0.9 to 5.4) patients, respectively. The prevalence of pathogenic or likely pathogenic BRCA mutations in patients with serous versus nonserous tumors, with versus without relevant family history, and ≤ 50 years versus > 50 years, were 40 of 159 (25.2%; 95% CI, 18.6 to 32.6) versus 11 of 80 (13.8%; 95% CI, 7.1 to 23.3; P = .0636), 20 of 36 (55.6%; 95% CI, 38.1 to 72.1) versus 41 of 203 (20.2%; 95% CI, 14.9 to 26.4; P < .0001), and 20 of 90 (22.2%; 95% CI, 14.1 to 32.2) versus 31 of 149 (20.8%; 95% CI, 14.6 to 28.2; P = .7956), respectively.

CONCLUSION

There is a high prevalence of pathogenic or likely pathogenic germline BRCA mutations in Indian patients with ovarian cancer.

Germline copy number variations in BRCA1/2 negative families: Role in the molecular etiology of hereditary breast cancer in Tunisia

Hereditary breast cancer accounts for 5-10% of all breast cancer cases. So far, known genetic risk factors account for only 50% of the breast cancer genetic component and almost a quarter of hereditary cases are carriers of pathogenic mutations in BRCA1/2 genes. Hence, the genetic basis for a significant fraction of familial cases remains unsolved. This missing heritability may be explained in part by Copy Number Variations (CNVs). We herein aimed to evaluate the contribution of CNVs to hereditary breast cancer in Tunisia. Whole exome sequencing was performed for 9 BRCA negative cases with a strong family history of breast cancer and 10 matched controls. CNVs were called using the ExomeDepth R-package and investigated by pathway analysis and web-based bioinformatic tools. Overall, 483 CNVs have been identified in breast cancer patients. Rare CNVs affecting cancer genes were detected, of special interest were those disrupting APC2, POU5F1, DOCK8, KANSL1, TMTC3 and the mismatch repair gene PMS2. In addition, common CNVs known to be associated with breast cancer risk have also been identified including CNVs on APOBECA/B, UGT2B17 and GSTT1 genes. Whereas those disrupting SULT1A1 and UGT2B15 seem to correlate with good clinical response to tamoxifen. Our study revealed new insights regarding CNVs and breast cancer risk in the Tunisian population. These findings suggest that rare and common CNVs may contribute to disease susceptibility. Those affecting mismatch repair genes are of interest and require additional attention since it may help to select candidates for immunotherapy leading to better outcomes.

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

Simple Summary

The identification of germline copy number variants (CNVs) by targeted nextgeneration sequencing frequently relies on in silico prediction tools with unknown sensitivities. We investigated the performances of four in silico CNV prediction tools in 17 cancer predisposition genes in a large series of 4208 female index patients with familial breast and/or ovarian cancer. We identified 77 CNVs in 76 out of 4208 patients; six CNVs were missed by at least one of the prediction tools. Experimental verification of in silico predicted CNVs is required due to high frequencies of false positive predictions. For female index patients with familial breast and/or ovarian cancer, CNV detection should not be restricted to BRCA1/2 due to the relevant proportion of CNVs in further cancer predisposition genes.

Abstract

The identification of germline copy number variants (CNVs) by targeted next-generation sequencing (NGS) frequently relies on in silico CNV prediction tools with unknown sensitivities. We investigated the performances of four in silico CNV prediction tools, including one commercial (Sophia Genetics DDM) and three non-commercial tools (ExomeDepth, GATK gCNV, panelcn.MOPS) in 17 cancer predisposition genes in 4208 female index patients with familial breast and/or ovarian cancer (BC/OC). CNV predictions were verified via multiplex ligation-dependent probe amplification. We identified 77 CNVs in 76 out of 4208 patients (1.81%); 33 CNVs were identified in genes other than BRCA1/2, mostly in ATM, CHEK2, and RAD51C and less frequently in BARD1, MLH1, MSH2, PALB2, PMS2, RAD51D, and TP53. The Sophia Genetics DDM software showed the highest sensitivity; six CNVs were missed by at least one of the non-commercial tools. The positive predictive values ranged from 5.9% (74/1249) for panelcn.MOPS to 79.1% (72/91) for ExomeDepth. Verification of in silico predicted CNVs is required due to high frequencies of false positive predictions, particularly affecting target regions at the extremes of the GC content or target length distributions. CNV detection should not be restricted to BRCA1/2 due to the relevant proportion of CNVs in further BC/OC predisposition genes.

Comprehensive Constitutional Genetic and Epigenetic Characterization of Lynch-Like Individuals

The causal mechanism for cancer predisposition in Lynch-like syndrome (LLS) remains unknown. Our aim was to elucidate the constitutional basis of mismatch repair (MMR) deficiency in LLS patients throughout a comprehensive (epi)genetic analysis. One hundred and fifteen LLS patients harboring MMR-deficient tumors and no germline MMR mutations were included. Mutational analysis of 26 colorectal cancer (CRC)-associated genes was performed. Pathogenicity of MMR variants was assessed by splicing and multifactorial likelihood analyses. Genome-wide methylome analysis was performed by the Infinium Human Methylation 450K Bead Chip. The multigene panel analysis revealed the presence of two MMR gene truncating mutations not previously found. Of a total of 15 additional MMR variants identified, five -present in 6 unrelated individuals- were reclassified as pathogenic. In addition, 13 predicted deleterious variants in other CRC-predisposing genes were found in 12 probands. Methylome analysis detected one constitutional MLH1 epimutation, but no additional differentially methylated regions were identified in LLS compared to LS patients or cancer-free individuals. In conclusion, the use of an ad-hoc designed gene panel combined with pathogenicity assessment of variants allowed the identification of deleterious MMR mutations as well as new LLS candidate causal genes. Constitutional epimutations in non-LS-associated genes are not responsible for LLS.

Co-occurrence of germline BRCA1 and CDH1 pathogenic variants

INTRODUCTION

We report a very rare case of familial breast cancer and diffuse gastric cancer, with germline pathogenic variants in both BRCA1 and CDH1 genes. To the best of our knowledge, this is the first report of such an association.Family description: The proband is a woman diagnosed with breast cancer at the age of 52 years. She requested genetic counselling in 2012, at the age of 91 years, because of a history of breast cancer in her daughter, her sister, her niece and her paternal grandmother and was therefore concerned about her relatives. Her sister and maternal aunt also had gastric cancer. She was tested for several genes associated with hereditary breast cancer.

RESULTS

A large deletion of BRCA1 from exons 1 to 7 and two CDH1 pathogenic cis variants were identified.

CONCLUSION

This complex situation is challenging for genetic counselling and management of at-risk individuals.

Comprehensive profiling of BRCA1 and BRCA2 variants in breast and ovarian cancer in Chinese patients

The identification and interpretation of germline BRCA1/2 variants become increasingly important in breast and ovarian cancer (OC) treatment. However, there is no comprehensive analysis of the germline BRCA1/2 variants in a Chinese population. Here we performed a systematic review and meta-analysis on such variants from 94 publications. A total of 2,128 BRCA1/2 variant records were extracted, including 601 from BRCA1 and 632 from BRCA2. In addition, 414, 734, 449, and 307 variants were also recorded in the BIC, ClinVar, ENIGMA, and UMD databases, respectively, and 579 variants were newly reported. Subsequent analysis showed that the overall germline BRCA1/2 pathogenic variant frequency was 5.7% and 21.8% in Chinese breast and OC, respectively. Populations with high-risk factors exhibited a higher pathogenic variant percentage. Furthermore, the variant profile in Chinese is distinct from that in other ethnic groups with no distinct founder pathogenic variants. We also tested our in-house American College of Medical Genetics-guided pathogenicity interpretation procedure for Chinese BRCA1/2 variants. Our results achieved a consistency of 91.2-97.6% (5-grade classification) or 98.4-100% (2-grade classification) with public databases. In conclusion, this study represents the first comprehensive meta-analysis of Chinese BRCA1/2 variants and validates our in-house pathogenicity interpretation procedure, thereby providing guidance for further PARP inhibitor development and companion diagnostics in the Chinese population.

Novel bioinformatics quality control metric for next-generation sequencing experiments in the clinical context

As the use of next-generation sequencing (NGS) for the Mendelian diseases diagnosis is expanding, the performance of this method has to be improved in order to achieve higher quality. Typically, performance measures are considered to be designed in the context of each application and, therefore, account for a spectrum of clinically relevant variants. We present EphaGen, a new computational methodology for bioinformatics quality control (QC). Given a single NGS dataset in BAM format and a pre-compiled VCF-file of targeted clinically relevant variants it associates this dataset with a single arbiter parameter. Intrinsically, EphaGen estimates the probability to miss any variant from the defined spectrum within a particular NGS dataset. Such performance measure virtually resembles the diagnostic sensitivity of given NGS dataset. Here we present case studies of the use of EphaGen in context of BRCA1/2 and CFTR sequencing in a series of 14 runs across 43 blood samples and 504 publically available NGS datasets. EphaGen is superior to conventional bioinformatics metrics such as coverage depth and coverage uniformity. We recommend using this software as a QC step in NGS studies in the clinical context. Availability: https://github.com/m4merg/EphaGen or https://hub.docker.com/r/m4merg/ephagen.

Novel Pathogenic Variants in a Cassette Exon of CCM2 in Patients With Cerebral Cavernous Malformations

Autosomal dominant cerebral cavernous malformation (CCM) represents a genetic disorder with a high mutation detection rate given that stringent inclusion criteria are used and copy number variation analyses are part of the diagnostic workflow. Pathogenic variants in either CCM1 (KRIT1), CCM2 or CCM3 (PDCD10) can be identified in 87–98% of CCM families with at least two affected individuals. However, the interpretation of novel sequence variants in the 5′-region of CCM2 remains challenging as there are various alternatively spliced transcripts and different transcription start sites. Comprehensive genetic and clinical data of CCM2 patients with variants in cassette exons that are either skipped or included into alternative CCM2 transcripts in the splicing process can significantly facilitate clinical variant interpretation. We here report novel pathogenic CCM2 variants in exon 3 and the adjacent donor splice site, describe the natural history of CCM disease in mutation carriers and provide further evidence for the classification of the amino acids encoded by the nucleotides of this cassette exon as a critical region within CCM2. Finally, we illustrate the advantage of a combined single nucleotide and copy number variation detection approach in NGS-based CCM1/CCM2/CCM3 gene panel analyses which can significantly reduce diagnostic turnaround time.

Identification of novel BRCA1 large genomic rearrangements by a computational algorithm of amplicon-based Next-Generation Sequencing data

Background

Genetic testing for BRCA1/2 germline mutations in hereditary breast/ovarian cancer patients requires screening for single nucleotide variants, small insertions/deletions and large genomic rearrangements (LGRs). These studies have long been run by Sanger sequencing and multiplex ligation-dependent probe amplification (MLPA). The recent introduction of next-generation sequencing (NGS) platforms dramatically improved the speed and the efficiency of DNA testing for nucleotide variants, while the possibility to correctly detect LGRs by this mean is still debated. The purpose of this study was to establish whether and to which extent the development of an analytical algorithm could help us translating NGS sequencing via an Ion Torrent PGM platform into a tool suitable to identify LGRs in hereditary breast-ovarian cancer patients.

Methods

We first used NGS data of a group of three patients (training set), previously screened in our laboratory by conventional methods, to develop an algorithm for the calculation of the dosage quotient (DQ) to be compared with the Ion Reporter (IR) analysis. Then, we tested the optimized pipeline with a consecutive cohort of 85 uncharacterized probands (validation set) also subjected to MLPA analysis. Characterization of the breakpoints of three novel BRCA1 LGRs was obtained via long-range PCR and direct sequencing of the DNA products.

Results

In our cohort, the newly defined DQ-based algorithm detected 3/3 BRCA1 LGRs, demonstrating 100% sensitivity and 100% negative predictive value (NPV) (95% CI [87.6–99.9]) compared to 2/3 cases detected by IR (66.7% sensitivity and 98.2% NPV (95% CI [85.6–99.9])). Interestingly, DQ and IR shared 12 positive results, but exons deletion calls matched only in five cases, two of which confirmed by MLPA. The breakpoints of the 3 novel BRCA1 deletions, involving exons 16–17, 21–22 and 20, have been characterized.

Conclusions

Our study defined a DQ-based algorithm to identify BRCA1 LGRs using NGS data. Whether confirmed on larger data sets, this tool could guide the selection of samples to be subjected to MLPA analysis, leading to significant savings in time and money.

Detection of BRCA1/2 large genomic rearrangements in breast and ovarian cancer patients: an overview of the current methods

Introduction: Currently, genetic testing of BRCA1/2 genes includes screening for single-nucleotide variants, small insertions/deletions, and copy number variations (CNVs). In fact, many studies document the involvement of BRCA1/2 gene rearrangements in genetic predisposition to breast and ovarian cancer. Large genomic rearrangements (LGRs) of BRCA1 may account for up to one-third of all disease-causing alterations in various populations, while LGRs in BRCA2 are less frequently observed. Areas covered: We aimed to present an overview of current technologies employed in molecular diagnosis of BRCA1/2 LGRs. The most relevant literature papers, showing the application of new strategies, were considered. Expert opinion: Currently, the progress of next-generation sequencing (NGS) technologies allows for the validation of new pipelines able to provide rapid and effective results, ensuring the sensitivity and specificity requested for the detection of BRCA1/2 LGRs. Multiplex ligation-dependent probe amplification remains the gold standard to confirm NGS CNVs results and to perform fast screening in families where a pathogenic rearrangement has been detected in a proband.

Germline mutation landscape of Chinese patients with familial breast/ovarian cancer in a panel of 22 susceptibility genes

Genetic testing for germline mutations in BRCA1/2 of patients with breast cancer (BC) is part of routine patient care. However, BRCA1/2 mutations account only for a fraction of familial BC. A custom panel of 22 gene sequencing was performed on each patient. Among the 481 female patients, 135 patients were detected to carry pathogenic (P)/likely pathogenic (LP) mutations (28.1%), which corresponded to 12 different cancer predisposition genes [14.6% (70/481) on BRCA1 gene, 5.0% (24/481) on BRCA2 gene, 8.5% (41/481) on non‐BRCA1/2 genes]. Moreover, 24.7% (119/481) of patients had mutation of unknown significance (VUS) in these genes. The most common (8/481) pathogenic mutation is BRCA1 c.5470_5477del, while BRIP1 2392 C > T of patients was detected. All the mutations detected were mainly seen in the homologous recombinant repair pathway. Compared to BRCA2 mutation, BRCA1 mutation is higher in younger female patients (P < 0.01). Some pathogenic mutations were detected in the patients’ familiy members without the past history of tumor and 92 novel mutations were detected (31 on BRCA including 2 P, 16 LP, 13 VUS; 61 on non‐BRCA1/2 including 9 LP, 52 VUS). The detection rate of BRCA1/2 mutations was higher in patients with three or more cancer family members than those with one or two. However, the difference was not statistically different. The results suggest that multigene panel testing can increase mutation detection rate for high‐risk BC patients. Detailed family history can help to categorize new mutations.

Rapid detection of copy number variations and point mutations in BRCA1/2 genes using a single workflow by ion semiconductor sequencing pipeline

Molecular analysis of BRCA1 (MIM# 604370) and BRCA2 (MIM #600185) genes is essential for familial breast and ovarian cancer prevention and treatment. An efficient, rapid, cost-effective accurate strategy for the detection of pathogenic variants is crucial. Mutations detection of BRCA1/2 genes includes screening for single nucleotide variants (SNVs), small insertions or deletions (indels), and Copy Number Variations (CNVs). Sanger sequencing is unable to identify CNVs and therefore Multiplex Ligation Probe amplification (MLPA) or Multiplex Amplicon Quantification (MAQ) is used to complete the BRCA1/2 genes analysis. The rapid evolution of Next Generation Sequencing (NGS) technologies allows the search for point mutations and CNVs with a single platform and workflow. In this study we test the possibilities of NGS technology to simultaneously detect point mutations and CNVs in BRCA1/2 genes, using the Oncomine^TM BRCA Research Assay on Personal Genome Machine (PGM) Platform with Ion Reporter Software for sequencing data analysis (Thermo Fisher Scientific). Comparison between the NGS-CNVs, MLPA and MAQ results shows how the NGS approach is the most complete and fast method for the simultaneous detection of all BRCA mutations, avoiding the usual time consuming multistep approach in the routine diagnostic testing of hereditary breast and ovarian cancers.

Fast Detection of a BRCA2 Large Genomic Duplication by Next Generation Sequencing as a Single Procedure: A Case Report

The aim of this study was to verify the reliability of a next generation sequencing (NGS)-based method as a strategy to detect all possible BRCA mutations, including large genomic rearrangements. Genomic DNA was obtained from a peripheral blood sample provided by a patient from Southern Italy with early onset breast cancer and a family history of diverse cancers. BRCA molecular analysis was performed by NGS, and sequence data were analyzed using two software packages. Comparative genomic hybridization (CGH) array was used as confirmatory method. A novel large duplication, involving exons 4-26, of BRCA2 was directly detected in the patient by NGS workflow including quantitative analysis of copy number variants. The duplication observed was also found by CGH array, thus confirming its extent. Large genomic rearrangements can affect the BRCA1/2 genes, and thus contribute to germline predisposition to familial breast and ovarian cancers. The frequency of these mutations could be underestimated because of technical limitations of several routinely used molecular analysis, while their evaluation should be included also in these molecular testing. The NGS-based strategy described herein is an effective procedure to screen for all kinds of BRCA mutations.