Germline ATM mutational analysis in BRCA1/BRCA2 negative hereditary breast cancer families by MALDI-TOF mass spectrometry

Biallelic inactivation of ATM gene causes the rare autosomal recessive disorder Ataxia-telangiectasia (A-T). Female relatives of A-T patients have a two-fold higher risk of developing breast cancer (BC) compared with the general population. ATM mutation carrier identification is laborious and expensive, therefore, a more rapid and directed strategy for ATM mutation profiling is needed. We designed a case-control study to determine the prevalence of 32 known ATM mutations causing A-T in Spanish population in 323 BRCA1/BRCA2 negative hereditary breast cancer (HBC) cases and 625 matched Spanish controls. For the detection of the 32 ATM mutations we used the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry technique. We identified one patient carrier of the c.8264_8268delATAAG ATM mutation. This mutation was not found in the 625 controls. These results suggest a low frequency of these 32 A-T causing mutations in the HBC cases in our population. Further case-control studies analyzing the entire coding and flanking sequences of the ATM gene are warranted in Spanish BC patients to know its implication in BC predisposition

Work, family and daily mobility: a new approach to the problem through a mobility survey

AbstractObjectivesTo analyze gender inequalities in socioeconomic factors affecting the amount of time spent travelling for work-related and home-related reasons among working individuals aged between 30 and 44 years old during a weekday in Catalonia (Spain).MethodsA cross-sectional study was conducted. Data were obtained from employed individuals aged between 30 and 44 years of age who reported travelling on the day prior to the interview in the Catalan Mobility Survey 2006 (N = 23,424). Multivariate logistic regression models were adjusted to determine the factors associated with longer time spent travelling according to the reason for travelling (work- or home-related journeys). Odds ratios and 95% confidence intervals are presented.ResultsA higher proportion of men travelled and spent more time travelling for work-related reasons, while a higher proportion of women travelled and spend more time travelling for home-related reasons. A higher educational level was associated with greater time spent travelling for work-related reasons in both men and women but was related to an increase in travelling time for home-related reasons only in men. In women, a larger household was associated with greater travel time for home-related reasons and with less travel time for work-related reasons.ConclusionThis study confirms the different mobility patterns in men and women, related to their distinct positions in the occupational, family and domestic spheres. Gender inequalities in mobility within the working population are largely determined by the greater responsibility of women in the domestic and family sphere. This finding should be taken into account in the design of future transport policies

Head-on crashes on two-way interurban roads: a public health concern in road safety

AbstractObjectiveTo describe the magnitude and characteristics of crashes and drivers involved in head-on crashes on two-way interurban roads in Spain between 2007 and 2012, and to identify the factors associated with the likelihood of head-on crashes on these roads compared with other types of crash.MethodsA cross-sectional study was conducted using the National Crash Register. The dependent variables were head-on crashes with injury (yes/no) and drivers involved in head-on crashes (yes/no). Factors associated with head-on crashes and with being a driver involved in a head-on crash versus other types of crash were studied using a multivariate robust Poisson regression model to estimate proportion ratios (PR) and confidence intervals (95% CI).ResultsThere were 9,192 head-on crashes on two-way Spanish interurban roads. A total of 15,412 men and 3,862 women drivers were involved. Compared with other types of crash, head-on collisions were more likely on roads 7 m or more wide, on road sections with curves, narrowings or drop changes, on wet or snowy surfaces, and in twilight conditions. Transgressions committed by drivers involved in head-on crashes were driving in the opposite direction and incorrectly overtaking another vehicle. Factors associated with a lower probability of head-on crashes were the existence of medians (PR=0.57; 95%CI: 0.48-0.68) and a paved shoulder of less than 1.5 meters (PR=0.81; 95%CI: 0.77-0.86) or from 1.5 to 2.45 meters (PR=0.90; 95%CI: 0.84-0.96).ConclusionsThis study allowed the characterization of crashes and drivers involved in head-on crashes on two-way interurban roads. The lower probability observed on roads with median strips point to these measures as an effective way to reduce these collision

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 pre-diction 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. (J Mol Diagn 2024, 26: 17-28; https://doi.org/10.1016/j.jmoldx.2023.09.009

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.FEDER funds-a way to build Europe PI19/00553 PI16/00563 PI16/01898 SAF2015-68016-RGeneralitat de Catalunya 2017SGR1282 2017SGR496CERCA Program: Government of CataloniaXunta de GaliciaInstituto de Salud Carlos III. AES PI19/00340Spanish Government SAF2016-80255-REuropean Commission EFA086/15Instituto de Salud Carlos III European Commissio

Thorough in silico and in vitro cDNA analysis of 21 putative BRCA1 and BRCA2 splice variants and a complex tandem duplication in BRCA2 allowing the identification of activated cryptic splice donor sites in BRCA2 exon 11

For 21 putative BRCA1 and BRCA2 splice site variants, the concordance between mRNA analysis and predictions by in silico programs was evaluated. Aberrant splicing was confirmed for 12 alterations. In silico prediction tools were helpful to determine for which variants cDNA analysis is warranted, however, predictions for variants in the Cartegni consensus region but outside the canonical sites, were less reliable. Learning algorithms like Adaboost and Random Forest outperformed the classical tools. Further validations are warranted prior to implementation of these novel tools in clinical settings. Additionally, we report here for the first time activated cryptic donor sites in the large exon 11 of BRCA2 by evaluating the effect at the cDNA level of a novel tandem duplication (5 breakpoint in intron 4; 3 breakpoint in exon 11) and of a variant disrupting the splice donor site of exon 11 (c.6841+1G>C). Additional sites were predicted, but not activated. These sites warrant further research to increase our knowledge on cis and trans acting factors involved in the conservation of correct transcription of this large exon. This may contribute to adequate design of ASOs (antisense oligonucleotides), an emerging therapy to render cancer cells sensitive to PARP inhibitor and platinum therapies

About 1% of the breast and ovarian Spanish families testing negative for BRCA1 and BRCA2 are carriers of RAD51D pathogenic variants

RAD51D mutations have been recently identified in breast (BC) and ovarian cancer (OC) families. Although an etiological role in OC appears to be present, the association of RAD51D mutations and BC risk is more unclear. We aimed to determine the prevalence of germline RAD51D mutations in Spanish BC/OC families negative for BRCA1/BRCA2 mutations. We analyzed 842 index patients: 491 from BC/OC families, 171 BC families, 51 OC families and 129 patients without family history but with early-onset BC or OC or metachronous BC and OC. Mutation detection was performed with high-resolution melting, denaturing high-performance liquid chromatography or Sanger sequencing. Three mutations were found in four families with BC and OC cases (0.82%). Two were novel: c.1A>T (p.Met1?) and c.667+2_667+23del, leading to the exon 7 skipping and one previously described: c.674C>T (p.Arg232*). All were present in BC/OC families with only one OC. The c.667+2_667+23del cosegregated in the family with one early-onset BC and two bilateral BC cases. We also identified the c.629C>T (p.Ala210Val) variant, which was predicted in silico to be potentially pathogenic. About 1% of the BC and OC Spanish families negative for BRCA1/BRCA2 are carriers of RAD51D mutations. The presence of several BC mutation carriers, albeit in the context of familial OC, suggests an increased risk for BC, which should be taken into account in the follow-up and early detection measures. RAD51D testing should be considered in clinical setting for families with BC and OC, irrespective of the number of OC cases in the family

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

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