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. Thus, it is the main burden of the incorporation of next-generation sequencing into the clinical setting. RESULTS: We created the vaRiants in HC (vaRHC) R package to assist the process of variant classification in hereditary cancer by: (i) collecting information from diverse databases; (ii) assigning or denying different types of evidence according to updated American College of Molecular Genetics and Genomics/Association of Molecular Pathologist gene-specific criteria for ATM, CDH1, CHEK2, MLH1, MSH2, MSH6, PMS2, PTEN, and TP53 and general criteria for other genes; (iii) providing an automated classification of variants using a Bayesian metastructure and considering CanVIG-UK recommendations; and (iv) optionally printing the output to an .xlsx file. A validation using 659 classified variants demonstrated the robustness of vaRHC, presenting a better criteria assignment than Cancer SIGVAR, an available similar tool. AVAILABILITY AND IMPLEMENTATION: The source code can be consulted in the GitHub repository (https://github.com/emunte/vaRHC) Additionally, it will be submitted to CRAN soon.

Improving Genetic Testing in Hereditary Cancer by RNA Analysis: Tools to Prioritize Splicing Studies and Challenges in Applying American College of Medical Genetics and Genomics Guidelines.

RNA analyses are a potent tool to identify spliceogenic effects of DNA variants, although they are time-consuming and cannot always be performed. We present splicing assays of 20 variants that represent a variety of mutation types in 10 hereditary cancer genes and attempt to incorporate these results into American College of Medical Genetics and Genomics (ACMG) classification guidelines. Sixteen single-nucleotide variants, 3 exon duplications, and 1 single-exon deletion were selected and prioritized by in silico algorithms. RNA was extracted from short-term lymphocyte cultures to perform RT-PCR and Sanger sequencing, and allele-specific expression was assessed whenever possible. Aberrant transcripts were detected in 14 variants (70%). Variant interpretation was difficult, especially comparing old classification standards to generic ACMG guidelines and a proposal was devised to weigh functional analyses at RNA level. According to the ACMG guidelines, only 12 variants were reclassified as pathogenic/likely pathogenic because the other two variants did not gather enough evidence. This study highlights the importance of RNA studies to improve variant classification. However, it also indicates the challenge of incorporating these results into generic ACMG guidelines and the need to refine these criteria gene specifically. Nevertheless, 60% of variants were reclassified, thus improving genetic counseling and surveillance for carriers of these variants.

Haplotype analysis of the internationally distributed BRCA1 c.3331_3334delCAAG founder mutation reveals a common ancestral origin in Iberia.

BACKGROUND: The BRCA1 c.3331_3334delCAAG founder mutation has been reported in hereditary breast and ovarian cancer families from multiple Hispanic groups. We aimed to evaluate BRCA1 c.3331_3334delCAAG haplotype diversity in cases of European, African, and Latin American ancestry. METHODS: BC mutation carrier cases from Colombia (n = 32), Spain (n = 13), Portugal (n = 2), Chile (n = 10), Africa (n = 1), and Brazil (n = 2) were genotyped with the genome-wide single nucleotide polymorphism (SNP) arrays to evaluate haplotype diversity around BRCA1 c.3331_3334delCAAG. Additional Portuguese (n = 13) and Brazilian (n = 18) BC mutation carriers were genotyped for 15 informative SNPs surrounding BRCA1. Data were phased using SHAPEIT2, and identical by descent regions were determined using BEAGLE and GERMLINE. DMLE+ was used to date the mutation in Colombia and Iberia. RESULTS: The haplotype reconstruction revealed a shared 264.4-kb region among carriers from all six countries. The estimated mutation age was ~ 100 generations in Iberia and that it was introduced to South America early during the European colonization period. CONCLUSIONS: Our results suggest that this mutation originated in Iberia and later introduced to Colombia and South America at the time of Spanish colonization during the early 1500s. We also found that the Colombian mutation carriers had higher European ancestry, at the BRCA1 gene harboring chromosome 17, than controls, which further supported the European origin of the mutation. Understanding founder mutations in diverse populations has implications in implementing cost-effective, ancestry-informed screening.

Comprehensive analysis and ACMG-based classification of CHEK2 variants in hereditary cancer patients.

CHEK2 variants are associated with intermediate breast cancer risk, among other cancers. We aimed to comprehensively describe CHEK2 variants in a Spanish hereditary cancer (HC) cohort and adjust the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP) guidelines for their classification. First, three CHEK2 frequent variants were screened in a retrospective Hereditary Breast and Ovarian Cancer cohort of 516 patients. After, the whole CHEK2 coding region was analyzed by next-generation sequencing in 1848 prospective patients with HC suspicion. We refined ACMG-AMP criteria and applied different combined rules to classify CHEK2 variants and define risk alleles. We identified 10 CHEK2 null variants, 6 missense variants with discordant interpretation in ClinVar database, and 35 additional variants of unknown significance. Twelve variants were classified as (likely)-pathogenic; two can also be considered "established risk-alleles" and one as "likely risk-allele." The prevalence of (likely)-pathogenic variants in the HC cohort was 0.8% (1.3% in breast cancer patients and 1.0% in hereditary nonpolyposis colorectal cancer patients). Here, we provide ACMG adjustment guidelines to classify CHEK2 variants. We hope that this study would be useful for variant classification of other genes with low effect variants.

Does multilocus inherited neoplasia alleles syndrome have severe clinical expression?

IMPORTANCE: Genetic testing of hereditary cancer using comprehensive gene panels can identify patients with more than one pathogenic mutation in high and/or moderate-risk-associated cancer genes. This phenomenon is known as multilocus inherited neoplasia alleles syndrome (MINAS), which has been potentially linked to more severe clinical manifestations. OBJECTIVE: To determine the prevalence and clinical features of MINAS in a large cohort of adult patients with hereditary cancer homogeneously tested with the same gene panel. PATIENTS AND METHODS: A cohort of 1023 unrelated patients with suspicion of hereditary cancer was screened using a validated panel including up to 135 genes associated with hereditary cancer and phakomatoses. RESULTS: Thirteen (1.37%) patients harbouring two pathogenic mutations in dominant cancer-predisposing genes were identified, representing 5.7% (13/226) of patients with pathogenic mutations. Most (10/13) of these cases presented clinical manifestations associated with only one of the mutations identified. One case showed mutations in MEN1 and MLH1 and developed tumours associated with both cancer syndromes. Interestingly, three of the double mutants had a young age of onset or severe breast cancer phenotype and carried mutations in moderate to low-risk DNA damage repair-associated genes; two of them presented biallelic inactivation of CHEK2. We included these two patients for the sake of their clinical interest although we are aware that they do not exactly fulfil the definition of MINAS since both mutations are in the same gene. CONCLUSIONS AND RELEVANCE: Genetic analysis of a broad cancer gene panel identified the largest series of patients with MINAS described in a single study. Overall, our data do not support the existence of more severe manifestations in double mutants at the time of diagnosis although they do confirm previous evidence of severe phenotype in biallelic CHEK2 and other DNA repair cancer-predisposing genes.

Tumor xenograft modeling identifies an association between TCF4 loss and breast cancer chemoresistance.

Understanding the mechanisms of cancer therapeutic resistance is fundamental to improving cancer care. There is clear benefit from chemotherapy in different breast cancer settings; however, knowledge of the mutations and genes that mediate resistance is incomplete. In this study, by modeling chemoresistance in patient-derived xenografts (PDXs), we show that adaptation to therapy is genetically complex and identify that loss of transcription factor 4 (TCF4; also known as ITF2) is associated with this process. A triple-negative BRCA1-mutated PDX was used to study the genetics of chemoresistance. The PDX was treated in parallel with four chemotherapies for five iterative cycles. Exome sequencing identified few genes with de novo or enriched mutations in common among the different therapies, whereas many common depleted mutations/genes were observed. Analysis of somatic mutations from The Cancer Genome Atlas (TCGA) supported the prognostic relevance of the identified genes. A mutation in TCF4 was found de novo in all treatments, and analysis of drug sensitivity profiles across cancer cell lines supported the link to chemoresistance. Loss of TCF4 conferred chemoresistance in breast cancer cell models, possibly by altering cell cycle regulation. Targeted sequencing in chemoresistant tumors identified an intronic variant of TCF4 that may represent an expression quantitative trait locus associated with relapse outcome in TCGA. Immunohistochemical studies suggest a common loss of nuclear TCF4 expression post-chemotherapy. Together, these results from tumor xenograft modeling depict a link between altered TCF4 expression and breast cancer chemoresistance.

Benchmarking of Whole Exome Sequencing and Ad Hoc Designed Panels for Genetic Testing of Hereditary Cancer.

Next generation sequencing panels have been developed for hereditary cancer, although there is some debate about their cost-effectiveness compared to exome sequencing. The performance of two panels is compared to exome sequencing. Twenty-four patients were selected: ten with identified mutations (control set) and fourteen suspicious of hereditary cancer but with no mutation (discovery set). TruSight Cancer (94 genes) and a custom panel (122 genes) were assessed alongside exome sequencing. Eighty-three genes were targeted by the two panels and exome sequencing. More than 99% of bases had a read depth of over 30x in the panels, whereas exome sequencing covered 94%. Variant calling with standard settings identified the 10 mutations in the control set, with the exception of MSH6 c.255dupC using TruSight Cancer. In the discovery set, 240 unique non-silent coding and canonic splice-site variants were identified in the panel genes, 7 of them putatively pathogenic (in ATM, BARD1, CHEK2, ERCC3, FANCL, FANCM, MSH2). The three approaches identified a similar number of variants in the shared genes. Exomes were more expensive than panels but provided additional data. In terms of cost and depth, panels are a suitable option for genetic diagnostics, although exomes also identify variants in non-targeted genes.

A comprehensive custom panel design for routine hereditary cancer testing: preserving control, improving diagnostics and revealing a complex variation landscape.

We wanted to implement an NGS strategy to globally analyze hereditary cancer with diagnostic quality while retaining the same degree of understanding and control we had in pre-NGS strategies. To do this, we developed the I2HCP panel, a custom bait library covering 122 hereditary cancer genes. We improved bait design, tested different NGS platforms and created a clinically driven custom data analysis pipeline. The I2HCP panel was developed using a training set of hereditary colorectal cancer, hereditary breast and ovarian cancer and neurofibromatosis patients and reached an accuracy, analytical sensitivity and specificity greater than 99%, which was maintained in a validation set. I2HCP changed our diagnostic approach, involving clinicians and a genetic diagnostics team from panel design to reporting. The new strategy improved diagnostic sensitivity, solved uncertain clinical diagnoses and identified mutations in new genes. We assessed the genetic variation in the complete set of hereditary cancer genes, revealing a complex variation landscape that coexists with the disease-causing mutation. We developed, validated and implemented a custom NGS-based strategy for hereditary cancer diagnostics that improved our previous workflows. Additionally, the existence of a rich genetic variation in hereditary cancer genes favors the use of this panel to investigate their role in cancer risk.

Investigating the effect of 28 BRCA1 and BRCA2 mutations on their related transcribed mRNA.

Germline inactivating mutations in the BRCA1 and BRCA2 genes are responsible for hereditary breast and ovarian cancer syndrome (HBOCS). Genetic testing of these genes identifies a significant proportion of variants of uncertain significance (VUS). Elucidation of the clinical impact of these variants is an important challenge in genetic diagnostics and counseling. In this study, we assess the RNA effect of 28 BRCA1 and BRCA2 VUS identified in our set of HBOCS families with the aim of gaining insight into their clinical relevance. mRNA was extracted from VUS carriers and controls lymphocytes cultured for 5-6 days and treated with puromycin. RNA was reverse transcribed to perform transcriptional analysis for the study of splicing aberrations. In silico prediction tools were used to select those variants most likely to affect the RNA splicing process. Six out of the 28 variants analyzed showed an aberrant splicing pattern and could therefore be classified as probably pathogenic mutations. Reclassification of VUS improves the genetic counseling and clinical surveillance of carriers of these mutations and highlights the importance of RNA studies in routine diagnostic laboratories.

Assessing associations between the AURKA-HMMR-TPX2-TUBG1 functional module and breast cancer risk in BRCA1/2 mutation carriers.

While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood approach. The association of HMMR rs299290 with breast cancer risk in BRCA1 mutation carriers was confirmed: per-allele hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.04-1.15, p = 1.9 x 10(-4) (false discovery rate (FDR)-adjusted p = 0.043). Variation in CSTF1, located next to AURKA, was also found to be associated with breast cancer risk in BRCA2 mutation carriers: rs2426618 per-allele HR = 1.10, 95% CI 1.03-1.16, p = 0.005 (FDR-adjusted p = 0.045). Assessment of pairwise interactions provided suggestions (FDR-adjusted pinteraction values > 0.05) for deviations from the multiplicative model for rs299290 and CSTF1 rs6064391, and rs299290 and TUBG1 rs11649877 in both BRCA1 and BRCA2 mutation carriers. Following these suggestions, the expression of HMMR and AURKA or TUBG1 in sporadic breast tumors was found to potentially interact, influencing patients' survival. Together, the results of this study support the hypothesis of a causative link between altered function of AURKA-HMMR-TPX2-TUBG1 and breast carcinogenesis in BRCA1/2 mutation carriers.

ICO amplicon NGS data analysis: a Web tool for variant detection in common high-risk hereditary cancer genes analyzed by amplicon GS Junior next-generation sequencing.

Next-generation sequencing (NGS) has revolutionized genomic research and is set to have a major impact on genetic diagnostics thanks to the advent of benchtop sequencers and flexible kits for targeted libraries. Among the main hurdles in NGS are the difficulty of performing bioinformatic analysis of the huge volume of data generated and the high number of false positive calls that could be obtained, depending on the NGS technology and the analysis pipeline. Here, we present the development of a free and user-friendly Web data analysis tool that detects and filters sequence variants, provides coverage information, and allows the user to customize some basic parameters. The tool has been developed to provide accurate genetic analysis of targeted sequencing of common high-risk hereditary cancer genes using amplicon libraries run in a GS Junior System. The Web resource is linked to our own mutation database, to assist in the clinical classification of identified variants. We believe that this tool will greatly facilitate the use of the NGS approach in routine laboratories.

Functional and structural analysis of C-terminal BRCA1 missense variants.

Germline inactivating mutations in BRCA1 and BRCA2 genes are responsible for Hereditary Breast and Ovarian Cancer Syndrome (HBOCS). Genetic testing of these genes is available, although approximately 15% of tests identify variants of uncertain significance (VUS). Classification of these variants into pathogenic or non-pathogenic type is an important challenge in genetic diagnosis and counseling. The aim of the present study is to functionally assess a set of 7 missense VUS (Q1409L, S1473P, E1586G, R1589H, Y1703S, W1718L and G1770V) located in the C-terminal region of BRCA1 by combining in silico prediction tools and structural analysis with a transcription activation (TA) assay. The in silico prediction programs gave discrepant results making its interpretation difficult. Structural analysis of the three variants located in the BRCT domains (Y1703S, W1718L and G1770V) reveals significant alterations of BRCT structure. The TA assay shows that variants Y1703S, W1718L and G1770V dramatically compromise the transcriptional activity of BRCA1, while variants Q1409L, S1473P, E1586G and R1589H behave like wild-type BRCA1. In conclusion, our results suggest that variants Y1703S, W1718L and G1770V can be classified as likely pathogenic BRCA1 mutations.

Next-generation sequencing meets genetic diagnostics: development of a comprehensive workflow for the analysis of BRCA1 and BRCA2 genes.

Next-generation sequencing (NGS) is changing genetic diagnosis due to its huge sequencing capacity and cost-effectiveness. The aim of this study was to develop an NGS-based workflow for routine diagnostics for hereditary breast and ovarian cancer syndrome (HBOCS), to improve genetic testing for BRCA1 and BRCA2. A NGS-based workflow was designed using BRCA MASTR kit amplicon libraries followed by GS Junior pyrosequencing. Data analysis combined Variant Identification Pipeline freely available software and ad hoc R scripts, including a cascade of filters to generate coverage and variant calling reports. A BRCA homopolymer assay was performed in parallel. A research scheme was designed in two parts. A Training Set of 28 DNA samples containing 23 unique pathogenic mutations and 213 other variants (33 unique) was used. The workflow was validated in a set of 14 samples from HBOCS families in parallel with the current diagnostic workflow (Validation Set). The NGS-based workflow developed permitted the identification of all pathogenic mutations and genetic variants, including those located in or close to homopolymers. The use of NGS for detecting copy-number alterations was also investigated. The workflow meets the sensitivity and specificity requirements for the genetic diagnosis of HBOCS and improves on the cost-effectiveness of current approaches.

Assessing the RNA effect of 26 DNA variants in the BRCA1 and BRCA2 genes.

Comprehensive genetic testing of the breast cancer susceptibility genes BRCA1 and BRCA2 identified approximately 16% of variants of unknown significance (VUS), a significant proportion of which could affect the correct splicing of the genes. Our aim is to establish a workflow for classifying VUS in these complex genes, the first stage of which is splicing analysis. We used a combined approach consisting of five in silico splicing prediction programs and RT-PCR analysis for a set of 26 variants not previously studied at the mRNA level and six variants that had already been studied, four of which were used as positive controls as they were found to affect the splicing of these genes and the other two were used as negative controls. We identified a splicing defect in 8 of the 26 newly studied variants and ruled out splicing alteration in the remaining 18 variants. The results for the four positive and the two negative control variants were consistent with results presented in the literature. Our results strongly suggest that the combination of RNA analysis and in silico programs is an important step towards the classification of VUS. The results revealed a very high correlation between experimental data and in silico programs when using tools for predicting acceptor/donor sites but a lower correlation in the case of tools for identifying ESE elements.

Characterization of BRCA1 and BRCA2 splicing variants: a collaborative report by ENIGMA consortium members.

Mutations in BRCA1 and BRCA2 predispose carriers to early onset breast and ovarian cancer. A common problem in clinical genetic testing is interpretation of variants with unknown clinical significance. The Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium was initiated to evaluate and implement strategies to characterize the clinical significance of BRCA1 and BRCA2 variants. As an initial project of the ENIGMA Splicing Working Group, we report splicing and multifactorial likelihood analysis of 25 BRCA1 and BRCA2 variants from seven different laboratories. Splicing analysis was performed by reverse transcriptase PCR or mini gene assay, and sequencing to identify aberrant transcripts. The findings were compared to bioinformatic predictions using four programs. The posterior probability of pathogenicity was estimated using multifactorial likelihood analysis, including co-occurrence with a deleterious mutation, segregation and/or report of family history. Abnormal splicing patterns expected to lead to a non-functional protein were observed for 7 variants (BRCA1 c.441+2T>A, c.4184_4185+2del, c.4357+1G>A, c.4987-2A>G, c.5074G>C, BRCA2 c.316+5G>A, and c.8754+3G>C). Combined interpretation of splicing and multifactorial analysis classified an initiation codon variant (BRCA2 c.3G>A) as likely pathogenic, uncertain clinical significance for 7 variants, and indicated low clinical significance or unlikely pathogenicity for another 10 variants. Bioinformatic tools predicted disruption of consensus donor or acceptor sites with high sensitivity, but cryptic site usage was predicted with low specificity, supporting the value of RNA-based assays. The findings also provide further evidence that clinical RNA-based assays should be extended from analysis of invariant dinucleotides to routinely include all variants located within the donor and acceptor consensus splicing sites. Importantly, this study demonstrates the added value of collaboration between laboratories, and across disciplines, to collate and interpret information from clinical testing laboratories to consolidate patient management.

Identification of a new complex rearrangement affecting exon 20 of BRCA1.

In this study, we present a novel complex rearrangement in the BRCA1 gene. The genomic rearrangement was identified using one of the two commercially available MLPA BRCA1 kits but was not confirmed with the other. In this report, we present the full characterization at the DNA and RNA levels of a new partial deletion of exon 20 of BRCA1. This is a complex deletion with four breakpoints which promotes aberrant splicing with partial deletion of exon 20 plus the insertion of a cryptic exon corresponding to a fragment of intron 20. The aberrant splicing generates an abnormal transcript with a frameshift that will result in a truncated BRCA1 protein.

Identification and comprehensive characterization of large genomic rearrangements in the BRCA1 and BRCA2 genes.

Large genomic rearrangements are estimated to account for approximately 5-10% of all disease-causing mutations in BRCA1 and BRCA2 genes in patients with hereditary breast and ovarian cancer syndrome (HBOC). We use MRC-Holland Multiplex Ligation-dependent Probe Amplification (MLPA) to screen for such rearrangements in patients with HBOC and as a first step in our genetic testing workflow. The technique was applied to a set of 310 independent patients and detected eight different copy number alterations, corresponding to 2.6% of the studied samples. MLPA was also found to identify point mutations located in probe sequences. As commercial MLPA tests are not suitable for determining the specific breakpoints or for defining the exact extent of rearrangements, we applied a set of different complementary techniques to characterize these genetic alterations with greater precision. Long-range PCR amplification, RNA analysis, SNP-array chips, non-commercial MLPA probes, and FISH analysis were used to fully define the extent and mechanism of each alteration. In BRCA1, six rearrangements were characterized: deletion of E22, duplication of E9-E24, deletion of E16-E23, deletion of E1-E13, deletion of E1-E2 and duplication of E1-E2. In BRCA2, we studied a deletion of E15-E16 and a deletion of E1-E24. To the best of our knowledge, this is the most comprehensive study of the nature and underlying molecular causes of these mutational events in the BRCA1/2 genes.