A New Set of in Silico Tools to Support the Interpretation of ATM Missense Variants Using Graphical Analysis.

Establishing the pathogenic nature of variants in ATM, a gene associated with breast cancer and other hereditary cancers, is crucial for providing patients with adequate care. Unfortunately, achieving good variant classification is still difficult. To address this challenge, we extended the range of in silico tools with a series of graphical tools devised for the analysis of computational evidence by health care professionals. We propose a family of fast and easy-to-use graphical representations in which the impact of a variant is considered relative to other pathogenic and benign variants. To illustrate their value, the representations are applied to three problems in variant interpretation. The assessment of computational pathogenicity predictions showed that the graphics provide an intuitive view of prediction reliability, complementing and extending conventional numerical reliability indexes. When applied to variant of unknown significance populations, the representations shed light on the nature of these variants and can be used to prioritize variants of unknown significance for further studies. In a third application, the graphics were used to compare the two versions of the ATM-adapted American College of Medical Genetics and Genomics and Association for Molecular Pathology guidelines, obtaining valuable information on their relative virtues and weaknesses. Finally, a server [ATMision (ATM missense in silico interpretation online)] was generated for users to apply these representations in their variant interpretation problems, to check the ATM-adapted guidelines' criteria for computational evidence on their variant(s) and access different sources of information.

An spanish study of secondary findings in families affected with mendelian disorders: choices, prevalence and family history.

Clinical exome sequencing has the potential to identify pathogenic variants unrelated to the purpose of the study (secondary findings, SFs). Data describing actual choices of SFs in participants in a clinical setting and factors influencing their decision are virtually non-existant in Europe. In this work, we report the acceptance rate of SFs, calculate their prevalence and study factors associated with the decision in a cohort of patients affected with a rare genetic disorder in a Spanish Hospital. Finally, we re-examine the presence of previously non reported family history in positive cases. We retrospectively reviewed informed consent choices and SF results from 824 unrelated probands affected with rare genetic disorders who underwent whole-genome or exome sequencing. Ninety percent of families (740/824) affected with rare disorders wished to be informed of SFs. Declining SFs was associated with a prenatal setting (30% vs. 8.7%, p = 0.025), consanguinity (19% vs. 8.7%, p = 0.013), male gender (10.6% vs. 1.5%, p = 0.00865) and the proband being a minor (10.6% vs. 1.5%, p = 0.014). Overall, 27 pathogenic or likely pathogenic variants were identified in 27 individuals, with an SF prevalence of 3.6%. Disclosure of SFs increased the percentage of positive family histories and resulted in early diagnosis or changes in the management of 10 individuals from five families. We show that the acceptance of SFs in Spain is high and the disclosure of SFs leads to a clinically meaningful change in the medical management of individuals.

Preclinical In Vivo Validation of the RAD51 Test for Identification of Homologous Recombination-Deficient Tumors and Patient Stratification.

PARP inhibitors (PARPi) are approved drugs for platinum-sensitive, high-grade serous ovarian cancer (HGSOC) and for breast, prostate, and pancreatic cancers (PaC) harboring genetic alterations impairing homologous recombination repair (HRR). Detection of nuclear RAD51 foci in tumor cells is a marker of HRR functionality, and we previously established a test to detect RAD51 nuclear foci. Here, we aimed to validate the RAD51 score cut off and compare the performance of this test to other HRR deficiency (HRD) detection methods. Laboratory models from BRCA1/BRCA2-associated breast cancer, HGSOC, and PaC were developed and evaluated for their response to PARPi and cisplatin. HRD in these models and patient samples was evaluated by DNA sequencing of HRR genes, genomic HRD tests, and RAD51 foci detection. We established patient-derived xenograft models from breast cancer (n = 103), HGSOC (n = 4), and PaC (n = 2) that recapitulated patient HRD status and treatment response. The RAD51 test showed higher accuracy than HRR gene mutations and genomic HRD analysis for predicting PARPi response (95%, 67%, and 71%, respectively). RAD51 detection captured dynamic changes in HRR status upon acquisition of PARPi resistance. The accuracy of the RAD51 test was similar to HRR gene mutations for predicting platinum response. The predefined RAD51 score cut off was validated, and the high predictive value of the RAD51 test in preclinical models was confirmed. These results collectively support pursuing clinical assessment of the RAD51 test in patient samples from randomized trials testing PARPi or platinum-based therapies. SIGNIFICANCE: This work demonstrates the high accuracy of a histopathology-based test based on the detection of RAD51 nuclear foci in predicting response to PARPi and cisplatin.

BRCA1 and BRCA2 whole cDNA analysis in unsolved hereditary breast/ovarian cancer patients.

Germline pathogenic variants in BRCA1 and BRCA2 genes (BRCA1/2) explain an important fraction of hereditary breast/ovarian cancer (HBOC) cases. Genetic testing generally involves examining coding regions and exon/intron boundaries, thus the frequency of deleterious variants in non-coding regions is unknown. Here we analysed BRCA1/2 whole cDNA in a large cohort of 320 unsolved high-risk HBOC cases in order to identify potential splicing alterations explained by variants in BRCA1/2 deep intronic regions. Whole RNA splicing profiles were analysed by RT-PCR using Sanger sequencing or high-resolution electrophoresis in a QIAxcel instrument. Known predominant BRCA1/2 alternative splicing events were detected, together with two novel events BRCA1 ▼21 and BRCA2 Δ18q_27p. BRCA2 exon 3 skipping was detected in one patient (male) affected with breast cancer, caused by a known Portuguese founder mutation (c.156_157insAluYa5). An altered BRCA2 splicing pattern was detected in three patients, consisting in the up-regulation of ▼20A, Δ22 and ▼20A+Δ22 transcripts. In silico analysis and semi-quantitative data identified the polymorphism BRCA2 c.8755-66T>C as a potential modifier of Δ22 levels. Our findings suggest that mRNA alterations in BRCA1/2 caused by deep intronic variants are rare in Spanish population. However, RNA analysis complements DNA-based strategies allowing the identification of alterations that could go undetected by conventional testing.

Role of Splicing Regulatory Elements and In Silico Tools Usage in the Identification of Deep Intronic Splicing Variants in Hereditary Breast/Ovarian Cancer Genes.

The contribution of deep intronic splice-altering variants to hereditary breast and ovarian cancer (HBOC) is unknown. Current computational in silico tools to predict spliceogenic variants leading to pseudoexons have limited efficiency. We assessed the performance of the SpliceAI tool combined with ESRseq scores to identify spliceogenic deep intronic variants by affecting cryptic sites or splicing regulatory elements (SREs) using literature and experimental datasets. Our results with 233 published deep intronic variants showed that SpliceAI, with a 0.05 threshold, predicts spliceogenic deep intronic variants affecting cryptic splice sites, but is less effective in detecting those affecting SREs. Next, we characterized the SRE profiles using ESRseq, showing that pseudoexons are significantly enriched in SRE-enhancers compared to adjacent intronic regions. Although the combination of SpliceAI with ESRseq scores (considering ∆ESRseq and SRE landscape) showed higher sensitivity, the global performance did not improve because of the higher number of false positives. The combination of both tools was tested in a tumor RNA dataset with 207 intronic variants disrupting splicing, showing a sensitivity of 86%. Following the pipeline, five spliceogenic deep intronic variants were experimentally identified from 33 variants in HBOC genes. Overall, our results provide a framework to detect deep intronic variants disrupting splicing.

Evaluation of the association of heterozygous germline variants in NTHL1 with breast cancer predisposition: an international multi-center study of 47,180 subjects.

Bi-allelic loss-of-function (LoF) variants in the base excision repair (BER) gene NTHL1 cause a high-risk hereditary multi-tumor syndrome that includes breast cancer, but the contribution of heterozygous variants to hereditary breast cancer is unknown. An analysis of 4985 women with breast cancer, enriched for familial features, and 4786 cancer-free women revealed significant enrichment for NTHL1 LoF variants. Immunohistochemistry confirmed reduced NTHL1 expression in tumors from heterozygous carriers but the NTHL1 bi-allelic loss characteristic mutational signature (SBS 30) was not present. The analysis was extended to 27,421 breast cancer cases and 19,759 controls from 10 international studies revealing 138 cases and 93 controls with a heterozygous LoF variant (OR 1.06, 95% CI: 0.82-1.39) and 316 cases and 179 controls with a missense variant (OR 1.31, 95% CI: 1.09-1.57). Missense variants selected for deleterious features by a number of in silico bioinformatic prediction tools or located within the endonuclease III functional domain showed a stronger association with breast cancer. Somatic sequencing of breast cancers from carriers indicated that the risk associated with NTHL1 appears to operate through haploinsufficiency, consistent with other described low-penetrance breast cancer genes. Data from this very large international multicenter study suggests that heterozygous pathogenic germline coding variants in NTHL1 may be associated with low- to moderate- increased risk of breast cancer.

A Collaborative Effort to Define Classification Criteria for ATM Variants in Hereditary Cancer Patients.

BACKGROUND: Gene panel testing by massive parallel sequencing has increased the diagnostic yield but also the number of variants of uncertain significance. Clinical interpretation of genomic data requires expertise for each gene and disease. Heterozygous ATM pathogenic variants increase the risk of cancer, particularly breast cancer. For this reason, ATM is included in most hereditary cancer panels. It is a large gene, showing a high number of variants, most of them of uncertain significance. Hence, we initiated a collaborative effort to improve and standardize variant classification for the ATM gene. METHODS: Six independent laboratories collected information from 766 ATM variant carriers harboring 283 different variants. Data were submitted in a consensus template form, variant nomenclature and clinical information were curated, and monthly team conferences were established to review and adapt American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) criteria to ATM, which were used to classify 50 representative variants. RESULTS: Amid 283 different variants, 99 appeared more than once, 35 had differences in classification among laboratories. Refinement of ACMG/AMP criteria to ATM involved specification for twenty-one criteria and adjustment of strength for fourteen others. Afterwards, 50 variants carried by 254 index cases were classified with the established framework resulting in a consensus classification for all of them and a reduction in the number of variants of uncertain significance from 58% to 42%. CONCLUSIONS: Our results highlight the relevance of data sharing and data curation by multidisciplinary experts to achieve improved variant classification that will eventually improve clinical management.

Assessment of blind predictions of the clinical significance of BRCA1 and BRCA2 variants.

Testing for variation in BRCA1 and BRCA2 (commonly referred to as BRCA1/2), has emerged as a standard clinical practice and is helping countless women better understand and manage their heritable risk of breast and ovarian cancer. Yet the increased rate of BRCA1/2 testing has led to an increasing number of Variants of Uncertain Significance (VUS), and the rate of VUS discovery currently outpaces the rate of clinical variant interpretation. Computational prediction is a key component of the variant interpretation pipeline. In the CAGI5 ENIGMA Challenge, six prediction teams submitted predictions on 326 newly-interpreted variants from the ENIGMA Consortium. By evaluating these predictions against the new interpretations, we have gained a number of insights on the state of the art of variant prediction and specific steps to further advance this state of the art.

Incorporation of semi-quantitative analysis of splicing alterations for the clinical interpretation of variants in BRCA1 and BRCA2 genes.

BRCA1 and BRCA2 (BRCA1/2) genetic variants that disrupt messenger RNA splicing are commonly associated with increased risks of developing breast/ovarian cancer. The majority of splicing studies published to date rely on qualitative methodologies (i.e., Sanger sequencing), but it is necessary to incorporate semi-quantitative or quantitative approaches to accurately interpret the clinical significance of spliceogenic variants. Here, we characterize the splicing impact of 31 BRCA1/2 variants using semi-quantitative capillary electrophoresis of fluorescent amplicons (CE), Sanger sequencing and allele-specific assays. A total of 14 variants were found to disrupt splicing. Allelic-specific assays could be performed for BRCA1 c.302-1G>A and BRCA2 c.516+2T>A, c.1909+1G>A, c.8332-13T>G, c.8332-2A>G, c.8954-2A>T variants, showing a monoallelic contribution to full-length transcript expression that was concordant with semi-quantitative data. The splicing fraction of alternative and aberrant transcripts was also measured by CE, facilitating variant interpretation. Following Evidence-based Network for the Interpretation of Germline Mutant Alleles criteria, we successfully classified eight variants as pathogenic (Class 5), five variants as likely pathogenic (Class 4), and 14 variants as benign (Class 1). We also provide splicing data for four variants classified as uncertain (Class 3), which produced a "leaky" splicing effect or introduced a missense change in the protein sequence, that will require further assessment to determine their clinical significance.

BRCA1- and BRCA2-specific in silico tools for variant interpretation in the CAGI 5 ENIGMA challenge.

BRCA1 and BRCA2 (BRCA1/2) germline variants disrupting the DNA protective role of these genes increase the risk of hereditary breast and ovarian cancers. Correct identification of these variants then becomes clinically relevant, because it may increase the survival rates of the carriers. Unfortunately, we are still unable to systematically predict the impact of BRCA1/2 variants. In this article, we present a family of in silico predictors that address this problem, using a gene-specific approach. For each protein, we have developed two tools, aimed at predicting the impact of a variant at two different levels: Functional and clinical. Testing their performance in different datasets shows that specific information compensates the small number of predictive features and the reduced training sets employed to develop our models. When applied to the variants of the BRCA1/2 (ENIGMA) challenge in the fifth Critical Assessment of Genome Interpretation (CAGI 5) we find that these methods, particularly those predicting the functional impact of variants, have a good performance, identifying the large compositional bias towards neutral variants in the CAGI sample. This performance is further improved when incorporating to our prediction protocol estimates of the impact on splicing of the target variant.

Screening of BRCA1/2 deep intronic regions by targeted gene sequencing identifies the first germline BRCA1 variant causing pseudoexon activation in a patient with breast/ovarian cancer.

BACKGROUND: Genetic analysis of BRCA1 and BRCA2 for the diagnosis of hereditary breast and ovarian cancer (HBOC) is commonly restricted to coding regions and exon-intron boundaries. Although germline pathogenic variants in these regions explain about ~20% of HBOC cases, there is still an important fraction that remains undiagnosed. We have screened BRCA1/2 deep intronic regions to identify potential spliceogenic variants that could explain part of the missing HBOC susceptibility. METHODS: We analysed BRCA1/2 deep intronic regions by targeted gene sequencing in 192 high-risk HBOC families testing negative for BRCA1/2 during conventional analysis. Rare variants (MAF <0.005) predicted to create/activate splice sites were selected for further characterisation in patient RNA. The splicing outcome was analysed by RT-PCR and Sanger sequencing, and allelic imbalance was also determined when heterozygous exonic loci were present. RESULTS: A novel transcript was detected in BRCA1 c.4185+4105C>T variant carrier. This variant promotes the inclusion of a pseudoexon in mature mRNA, generating an aberrant transcript predicted to encode for a non-functional protein. Quantitative and allele-specific assays determined haploinsufficiency in the variant carrier, supporting a pathogenic effect for this variant. Genotyping of 1030 HBOC cases and 327 controls did not identify additional carriers in Spanish population. CONCLUSION: Screening of BRCA1/2 intronic regions has identified the first BRCA1 deep intronic variant associated with HBOC by pseudoexon activation. Although the frequency of deleterious variants in these regions appears to be low, our study highlights the importance of studying non-coding regions and performing comprehensive RNA assays to complement genetic diagnosis.

Alternative transcript imbalance underlying breast cancer susceptibility in a family carrying PALB2 c.3201+5G>T.

PURPOSE: Disruption of splicing motifs by genetic variants can affect the correct generation of mature mRNA molecules leading to aberrant transcripts. In some cases, variants may alter the physiological transcription profile composed of several transcripts, and an accurate in vitro evaluation is crucial to establish their pathogenicity. In this study, we have characterized a novel PALB2 variant c.3201+5G>T identified in a breast cancer family. METHODS: Peripheral blood RNA was analyzed in two carriers and ten controls by RT-PCR and Sanger sequencing. The splicing profile was also characterized by semi-quantitative capillary electrophoresis and quantitative PCR. RAD51 foci formation and PALB2 LOH status were evaluated in primary breast tumor samples from the carriers. RESULTS: PALB2 c.3201+5G>T disrupts intron 11 donor splice site and modifies the abundance of several alternative transcripts (∆11, ∆12, and ∆11,12), also present in control samples. All transcripts are predicted to encode for non-functional proteins. Semi-quantitative and quantitative analysis of PALB2 full-length transcript indicated haploinsufficiency in carriers. One tumor exhibited PALB2 LOH and RAD51 assay indicated homologous recombination deficiency in both tumors. CONCLUSIONS: Our results support a pathogenic classification for PALB2 c.3201+5G>T, highlighting the impact of variants causing an imbalanced expression of natural RNA isoforms in cancer susceptibility.

A RAD51 assay feasible in routine tumor samples calls PARP inhibitor response beyond BRCA mutation.

Poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) are effective in cancers with defective homologous recombination DNA repair (HRR), including BRCA1/2-related cancers. A test to identify additional HRR-deficient tumors will help to extend their use in new indications. We evaluated the activity of the PARPi olaparib in patient-derived tumor xenografts (PDXs) from breast cancer (BC) patients and investigated mechanisms of sensitivity through exome sequencing, BRCA1 promoter methylation analysis, and immunostaining of HRR proteins, including RAD51 nuclear foci. In an independent BC PDX panel, the predictive capacity of the RAD51 score and the homologous recombination deficiency (HRD) score were compared. To examine the clinical feasibility of the RAD51 assay, we scored archival breast tumor samples, including PALB2-related hereditary cancers. The RAD51 score was highly discriminative of PARPi sensitivity versus PARPi resistance in BC PDXs and outperformed the genomic test. In clinical samples, all PALB2-related tumors were classified as HRR-deficient by the RAD51 score. The functional biomarker RAD51 enables the identification of PARPi-sensitive BC and broadens the population who may benefit from this therapy beyond BRCA1/2-related cancers.

Multigene panel testing beyond BRCA1/2 in breast/ovarian cancer Spanish families and clinical actionability of findings.

PURPOSE: Few and small studies have been reported about multigene testing usage by massively parallel sequencing in European cancer families. There is an open debate about what genes should be tested, and the actionability of some included genes is under research. METHODS: We investigated a panel of 34 known high/moderate-risk cancer genes, including 16 related to breast or ovarian cancer (BC/OC) genes, and 63 candidate genes to BC/OC in 192 clinically suspicious of hereditary breast/ovarian cancer (HBOC) Spanish families without pathogenic variants in BRCA1 or BRCA2 (BRCA1/2). RESULTS: We identified 16 patients who carried a high- or moderate-risk pathogenic variant in eight genes: 4 PALB2, 3 ATM, 2 RAD51D, 2 TP53, 2 APC, 1 BRIP1, 1 PTEN and 1 PMS2. These findings led to increased surveillance or prevention options in 12 patients and predictive testing in their family members. We detected 383 unique variants of uncertain significance in known cancer genes, of which 35 were prioritized in silico. Eighteen loss-of-function variants were detected in candidate BC/OC genes in 17 patients (1 BARD1, 1 ERCC3, 1 ERCC5, 2 FANCE, 1 FANCI, 2 FANCL, 1 FANCM, 1 MCPH1, 1 PPM1D, 2 RBBP8, 3 RECQL4 and 1 with SLX4 and XRCC2), three of which also carry pathogenic variants in known cancer genes. CONCLUSIONS: Eight percent of the BRCA1/2 negative patients carry pathogenic variants in other actionable genes. The multigene panel usage improves the diagnostic yield in HBOC testing and it is an effective tool to identify potentially new candidate genes.

Computational Tools for Splicing Defect Prediction in Breast/Ovarian Cancer Genes: How Efficient Are They at Predicting RNA Alterations?

In silico tools for splicing defect prediction have a key role to assess the impact of variants of uncertain significance. Our aim was to evaluate the performance of a set of commonly used splicing in silico tools comparing the predictions against RNA in vitro results. This was done for natural splice sites of clinically relevant genes in hereditary breast/ovarian cancer (HBOC) and Lynch syndrome. A study divided into two stages was used to evaluate SSF-like, MaxEntScan, NNSplice, HSF, SPANR, and dbscSNV tools. A discovery dataset of 99 variants with unequivocal results of RNA in vitro studies, located in the 10 exonic and 20 intronic nucleotides adjacent to exon-intron boundaries of BRCA1, BRCA2, MLH1, MSH2, MSH6, PMS2, ATM, BRIP1, CDH1, PALB2, PTEN, RAD51D, STK11, and TP53, was collected from four Spanish cancer genetic laboratories. The best stand-alone predictors or combinations were validated with a set of 346 variants in the same genes with clear splicing outcomes reported in the literature. Sensitivity, specificity, accuracy, negative predictive value (NPV) and Mathews Coefficient Correlation (MCC) scores were used to measure the performance. The discovery stage showed that HSF and SSF-like were the most accurate for variants at the donor and acceptor region, respectively. The further combination analysis revealed that HSF, HSF+SSF-like or HSF+SSF-like+MES achieved a high performance for predicting the disruption of donor sites, and SSF-like or a sequential combination of MES and SSF-like for predicting disruption of acceptor sites. The performance confirmation of these last results with the validation dataset, indicated that the highest sensitivity, accuracy, and NPV (99.44%, 99.44%, and 96.88, respectively) were attained with HSF+SSF-like or HSF+SSF-like+MES for donor sites and SSF-like (92.63%, 92.65%, and 84.44, respectively) for acceptor sites. We provide recommendations for combining algorithms to conduct in silico splicing analysis that achieved a high performance. The high NPV obtained allows to select the variants in which the study by in vitro RNA analysis is mandatory against those with a negligible probability of being spliceogenic. Our study also shows that the performance of each specific predictor varies depending on whether the natural splicing sites are donors or acceptors.

BRCA1 and BRCA2 5' noncoding region variants identified in breast cancer patients alter promoter activity and protein binding.

The widespread use of next generation sequencing for clinical testing is detecting an escalating number of variants in noncoding regions of the genome. The clinical significance of the majority of these variants is currently unknown, which presents a significant clinical challenge. We have screened over 6,000 early-onset and/or familial breast cancer (BC) cases collected by the ENIGMA consortium for sequence variants in the 5' noncoding regions of BC susceptibility genes BRCA1 and BRCA2, and identified 141 rare variants with global minor allele frequency < 0.01, 76 of which have not been reported previously. Bioinformatic analysis identified a set of 21 variants most likely to impact transcriptional regulation, and luciferase reporter assays detected altered promoter activity for four of these variants. Electrophoretic mobility shift assays demonstrated that three of these altered the binding of proteins to the respective BRCA1 or BRCA2 promoter regions, including NFYA binding to BRCA1:c.-287C>T and PAX5 binding to BRCA2:c.-296C>T. Clinical classification of variants affecting promoter activity, using existing prediction models, found no evidence to suggest that these variants confer a high risk of disease. Further studies are required to determine if such variation may be associated with a moderate or low risk of BC.