A Hematogenous Route for Medulloblastoma Leptomeningeal Metastases.

While the preponderance of morbidity and mortality in medulloblastoma patients are due to metastatic disease, most research focuses on the primary tumor due to a dearth of metastatic tissue samples and model systems. Medulloblastoma metastases are found almost exclusively on the leptomeningeal surface of the brain and spinal cord; dissemination is therefore thought to occur through shedding of primary tumor cells into the cerebrospinal fluid followed by distal re-implantation on the leptomeninges. We present evidence for medulloblastoma circulating tumor cells (CTCs) in therapy-naive patients and demonstrate in vivo, through flank xenografting and parabiosis, that medulloblastoma CTCs can spread through the blood to the leptomeningeal space to form leptomeningeal metastases. Medulloblastoma leptomeningeal metastases express high levels of the chemokine CCL2, and expression of CCL2 in medulloblastoma in vivo is sufficient to drive leptomeningeal dissemination. Hematogenous dissemination of medulloblastoma offers a new opportunity to diagnose and treat lethal disseminated medulloblastoma.

The Regulatory Factor ZFHX3 Modifies Circadian Function in SCN via an AT Motif-Driven Axis.

We identified a dominant missense mutation in the SCN transcription factor Zfhx3, termed short circuit (Zfhx3(Sci)), which accelerates circadian locomotor rhythms in mice. ZFHX3 regulates transcription via direct interaction with predicted AT motifs in target genes. The mutant protein has a decreased ability to activate consensus AT motifs in vitro. Using RNA sequencing, we found minimal effects on core clock genes in Zfhx3(Sci/+) SCN, whereas the expression of neuropeptides critical for SCN intercellular signaling was significantly disturbed. Moreover, mutant ZFHX3 had a decreased ability to activate AT motifs in the promoters of these neuropeptide genes. Lentiviral transduction of SCN slices showed that the ZFHX3-mediated activation of AT motifs is circadian, with decreased amplitude and robustness of these oscillations in Zfhx3(Sci/+) SCN slices. In conclusion, by cloning Zfhx3(Sci), we have uncovered a circadian transcriptional axis that determines the period and robustness of behavioral and SCN molecular rhythms.

Challenges and approaches to calibrating patient phenotype as evidence for cancer gene variant classification under ACMG/AMP guidelines.

Since first publication of the American College of Medical Genetics and Genomics/Association for Medical Pathology (ACMG/AMP) variant classification guidelines, additional recommendations for application of certain criteria have been released (https://clinicalgenome.org/docs/), to improve their application in the diagnostic setting. However, none have addressed use of the PS4 and PP4 criteria, capturing patient presentation as evidence towards pathogenicity. Application of PS4 can be done through traditional case-control studies, or "proband counting" within or across clinical testing cohorts. Review of the existing PS4 and PP4 specifications for Hereditary Cancer Gene Variant Curation Expert Panels revealed substantial differences in the approach to defining specifications. Using BRCA1, BRCA2 and TP53 as exemplar genes, we calibrated different methods proposed for applying the "PS4 proband counting" criterion. For each approach, we considered limitations, non-independence with other ACMG/AMP criteria, broader applicability, and variability in results for different datasets. Our findings highlight inherent overlap of proband-counting methods with ACMG/AMP frequency codes, and the importance of calibration to derive dataset-specific code weights that can account for potential between-dataset differences in ascertainment and other factors. Our work emphasizes the advantages and generalizability of logistic regression analysis over simple proband-counting approaches to empirically determine the relative predictive capacity and weight of various personal clinical features in the context of multigene panel testing, for improved variant interpretation. We also provide a general protocol, including instructions for data formatting and a web-server for analysis of personal history parameters, to facilitate dataset-specific calibration analyses required to use such data for germline variant classification.

Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup.

The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.

Clinical implications of VUS reclassification in a single-centre series from application of ACMG/AMP classification rules specified for BRCA1/2.

BACKGROUND: BRCA1/2 testing is crucial to guide clinical decisions in patients with hereditary breast/ovarian cancer, but detection of variants of uncertain significance (VUSs) prevents proper management of carriers. The ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles) BRCA1/2 Variant Curation Expert Panel (VCEP) has recently developed BRCA1/2 variant classification guidelines consistent with ClinGen processes, specified against the ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular-Pathology) classification framework. METHODS: The ClinGen-approved BRCA1/2-specified ACMG/AMP classification guidelines were applied to BRCA1/2 VUSs identified from 2011 to 2022 in a series of patients, retrieving information from the VCEP documentation, public databases, literature and ENIGMA unpublished data. Then, we critically re-evaluated carrier families based on new results and checked consistency of updated classification with main sources for clinical interpretation of BRCA1/2 variants. RESULTS: Among 166 VUSs detected in 231 index cases, 135 (81.3%) found in 197 index cases were classified by applying BRCA1/2-specified ACMG/AMP criteria: 128 (94.8%) as Benign/Likely Benign and 7 (5.2%) as Pathogenic/Likely Pathogenic. The average time from the first report as 'VUS' to classification using this approach was 49.4 months. Considering that 15 of these variants found in 64 families had already been internally reclassified prior to this work, this study provided 121 new reclassifications among the 151 (80.1%) remaining VUSs, relevant to 133/167 (79.6%) families. CONCLUSIONS: These results demonstrated the effectiveness of new BRCA1/2 ACMG/AMP classification guidelines for VUS classification within a clinical cohort, and their important clinical impact. Furthermore, they suggested a cadence of no more than 3 years for regular review of VUSs, which however requires time, expertise and resources.

Male with an apparently normal phenotype carrying a BRCA1 exon 20 duplication in trans to a BRCA1 frameshift variant.

BACKGROUND: Reports of dual carriers of pathogenic BRCA1 variants in trans are extremely rare, and so far, most individuals have been associated with a Fanconi Anemia-like phenotype. METHODS: We identified two families with a BRCA1 in-frame exon 20 duplication (Ex20dup). In one male individual, the variant was in trans with the BRCA1 frameshift variant c.2475delC p.(Asp825Glufs*21). We performed splicing analysis and used a transcription activation domain (TAD) assay to assess the functional impact of Ex20dup. We collected pedigrees and mapped the breakpoints of the duplication by long- and short-read genome sequencing. In addition, we performed a mitomycin C (MMC) assay from the dual carrier using cultured lymphoblastoid cells. RESULTS: Genome sequencing and RNA analysis revealed the BRCA1 exon 20 duplication to be in tandem. The duplication was expressed without skipping any one of the two exon 20 copies, resulting in a lack of wild-type transcripts from this allele. TAD assay indicated that the Ex20dup variant has a functional level similar to the well-known moderate penetrant pathogenic BRCA1 variant c.5096G > A p.(Arg1699Gln). MMC assay of the dual carrier indicated a slightly impaired chromosomal repair ability. CONCLUSIONS: This is the first reported case where two BRCA1 variants with demonstrated functional impact are identified in trans in a male patient with an apparently normal clinical phenotype and no BRCA1-associated cancer. The results pinpoint a minimum necessary BRCA1 protein activity to avoid a Fanconi Anemia-like phenotype in compound heterozygous status and yet still predispose carriers to hormone-related cancers. These findings urge caution when counseling families regarding potential Fanconi Anemia risk. Furthermore, prudence should be taken when classifying individual variants as benign based on co-occurrence in trans with well-established pathogenic variants.

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

BACKGROUND: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking. METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity. RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants. CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

SpliceAI-10k calculator for the prediction of pseudoexonization, intron retention, and exon deletion.

SUMMARY: SpliceAI is a widely used splicing prediction tool and its most common application relies on the maximum delta score to assign variant impact on splicing. We developed the SpliceAI-10k calculator (SAI-10k-calc) to extend use of this tool to predict: the splicing aberration type including pseudoexonization, intron retention, partial exon deletion, and (multi)exon skipping using a 10 kb analysis window; the size of inserted or deleted sequence; the effect on reading frame; and the altered amino acid sequence. SAI-10k-calc has 95% sensitivity and 96% specificity for predicting variants that impact splicing, computed from a control dataset of 1212 single-nucleotide variants (SNVs) with curated splicing assay results. Notably, it has high performance (≥84% accuracy) for predicting pseudoexon and partial intron retention. The automated amino acid sequence prediction allows for efficient identification of variants that are expected to result in mRNA nonsense-mediated decay or translation of truncated proteins. AVAILABILITY AND IMPLEMENTATION: SAI-10k-calc is implemented in R (https://github.com/adavi4/SAI-10k-calc) and also available as a Microsoft Excel spreadsheet. Users can adjust the default thresholds to suit their target performance values.

Same day discharge colon surgery: is it financially worth it?

AIM: Same day discharge (SDD) for colorectal surgery shows increasing promise in the era of enhanced recovery after surgery protocols and minimally invasive surgery. It has become increasingly relevant due to the constraints posed by the COVID-19 pandemic. The aim of this study was to compare SDD and postoperative day 1 (POD1) discharge to understand the clinical outcomes and financial impact on factors such as cost, charge, revenue, contribution margin and readmission. METHOD: A retrospective review of colectomies was performed at a single institution over a 2-year period (n = 143). Two populations were identified: SDD (n = 51) and POD1 (n = 92). Patients were selected by International Statistical Classification of Diseases and Related Health Problems-10 (ICD-10) and Diagnosis Related Grouper (DRG) codes. RESULTS: There was a statistically significant difference favouring SDD in total hospital cost (p < 0.0001), average direct costs (p < 0.0001) and average charges (p < 0.0016). SDD average hospital costs were $8699 (values in USD throughout) compared with $11 652 for POD 1 (p < 0.0001), and average SDD hospital charges were $85 506 compared with $97 008 for POD1 (p < 0.0016). The net revenue for SDD was $22 319 while for POD1 it was $26 173 (p = 0.14). Upon comparison of contribution margins (SDD $13 620 vs. POD1 $14 522), the difference was not statistically significant (p = 0.73). There were no identified statistically significant differences in operating room time, robotic console time, readmission rates or surgical complications. CONCLUSIONS: Amidst the pandemic-related constraints, we found that SDD was associated with lower hospital costs and comparable contribution margins compared with POD1. Additionally, the study was unable to identify any significant difference between operating time, readmissions, and surgical complications when performing SDD.

A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants: application to BRCA1 and BRCA2.

A large number of variants identified through clinical genetic testing in disease susceptibility genes, are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion), can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analyses of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC), and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity - findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in BRCA1, BRCA2 and other high-risk genes with known penetrance.

SOX9 modulates cancer biomarker and cilia genes in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive form of cancer with high mortality. The cellular origins of PDAC are largely unknown; however, ductal cells, especially centroacinar cells (CACs), have several characteristics in common with PDAC, such as expression of SOX9 and components of the Notch-signaling pathway. Mutations in KRAS and alterations to Notch signaling are common in PDAC, and both these pathways regulate the transcription factor SOX9. To identify genes regulated by SOX9, we performed siRNA knockdown of SOX9 followed by RNA-seq in PANC-1s, a human PDAC cell line. We report 93 differentially expressed (DE) genes, with convergence on alterations to Notch-signaling pathways and ciliogenesis. These results point to SOX9 and Notch activity being in a positive feedback loop and SOX9 regulating cilia production in PDAC. We additionally performed ChIP-seq in PANC-1s to identify direct targets of SOX9 binding and integrated these results with our DE gene list. Nine of the top 10 downregulated genes have evidence of direct SOX9 binding at their promoter regions. One of these targets was the cancer stem cell marker EpCAM. Using whole-mount in situ hybridization to detect epcam transcript in zebrafish larvae, we demonstrated that epcam is a CAC marker and that Sox9 regulation of epcam expression is conserved in zebrafish. Additionally, we generated an epcam null mutant and observed pronounced defects in ciliogenesis during development. Our results provide a link between SOX9, EpCAM and ciliary repression that can be exploited in improving our understanding of the cellular origins and mechanisms of PDAC.

Cognitive issues in patients with IDH mutant gliomas: from neuroscience to clinical neuropsychology.

PURPOSE: The understanding of cognitive symptoms in patients with IDH-Mutant gliomas (IDH-Mut) is rapidly developing. In this article, we summarize the neuroscientific knowledge base regarding the influence of IDH-Mut tumors and their treatment on cognition and provide guidance regarding the management of these symptoms in patients. METHODS: We performed a review of peer reviewed publications relevant to IDH-Mut glioma and cognitive outcomes and provide an overview of the literature as well as a case example to clarify management strategies. RESULTS: At the time of presentation, patients with IDH-Mut gliomas have a favorable cognitive profile as compared with those with IDH-wild type (WT) tumors. The relatively low cognitive burden may reflect the slower growth rate of IDH-Mut tumors, which is less disruptive to both local and widespread neural networks. Human connectomic research using a variety of modalities has demonstrated relatively preserved network efficiency in patients with IDH-Mut gliomas as compared with IDH-WT tumors. Risk of cognitive decline from surgery can potentially be mitigated by careful integration of intra-operative mapping. Longer term cognitive risks of tumor treatment, including chemotherapy and radiation, are best managed by instituting neuropsychological assessment as part of the long-term care of patients with IDH-Mutant glioma. A specific timeline for such integrative care is provided. CONCLUSIONS: Given the relative recency of the IDH-mutation based classification of gliomas, as well as the long time course of this disease, a thoughtful and comprehensive strategy to studying patient outcomes and devising methods of cognitive risk reduction is required.

Mitigating Radiotoxicity in the Central Nervous System: Role of Proton Therapy.

OPINION STATEMENT: Central nervous system (CNS) radiotoxicity remains a challenge in neuro-oncology. Dose distribution advantages of protons over photons have prompted increased use of brain-directed proton therapy. While well-recognized among pediatric populations, the benefit of proton therapy among adults with CNS malignancies remains controversial. We herein discuss the role of protons in mitigating late CNS radiotoxicities in adult patients. Despite limited clinical trials, evidence suggests toxicity profile advantages of protons over conventional radiotherapy, including retention of neurocognitive function and brain volume. Modelling studies predict superior dose conformality of protons versus state-of-the-art photon techniques reduces late radiogenic vasculopathies, endocrinopathies, and malignancies. Conversely, potentially higher brain tissue necrosis rates following proton therapy highlight a need to resolve uncertainties surrounding the impact of variable biological effectiveness of protons on dose distribution. Clinical trials comparing best photon and particle-based therapy are underway to establish whether protons substantially improve long-term treatment-related outcomes in adults with CNS malignancies.

Dissociable effects of visual crowding on the perception of color and motion.

Our ability to recognize objects in peripheral vision is fundamentally limited by crowding, the deleterious effect of clutter that disrupts the recognition of features ranging from orientation and color to motion and depth. Previous research is equivocal on whether this reflects a singular process that disrupts all features simultaneously or multiple processes that affect each independently. We examined crowding for motion and color, two features that allow a strong test of feature independence. "Cowhide" stimuli were presented 15° in peripheral vision, either in isolation or surrounded by flankers to give crowding. Observers reported either the target direction (clockwise/counterclockwise from upward) or its hue (blue/purple). We first established that both features show systematic crowded errors (biased predominantly toward the flanker identities) and selectivity for target-flanker similarity (with reduced crowding for dissimilar target/flanker elements). The multiplicity of crowding was then tested with observers identifying both features. Here, a singular object-selective mechanism predicts that when crowding is weak for one feature and strong for the other that crowding should be all-or-none for both. In contrast, when crowding was weak for color and strong for motion, errors were reduced for color but remained for motion, and vice versa with weak motion and strong color crowding. This double dissociation reveals that crowding disrupts certain combinations of visual features in a feature-specific manner, ruling out a singular object-selective mechanism. Thus, the ability to recognize one aspect of a cluttered scene, like color, offers no guarantees for the correct recognition of other aspects, like motion.

Objective assessment of stored blood quality by deep learning.

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often assessed by microscopic examination or biochemical and biophysical assays, which are complex, time-consuming, and destructive to fragile cells. Here we demonstrate the use of label-free imaging flow cytometry and deep learning to characterize RBC lesions. Using brightfield images, a trained neural network achieved 76.7% agreement with experts in classifying seven clinically relevant RBC morphologies associated with storage lesions, comparable to 82.5% agreement between different experts. Given that human observation and classification may not optimally discern RBC quality, we went further and eliminated subjective human annotation in the training step by training a weakly supervised neural network using only storage duration times. The feature space extracted by this network revealed a chronological progression of morphological changes that better predicted blood quality, as measured by physiological hemolytic assay readouts, than the conventional expert-assessed morphology classification system. With further training and clinical testing across multiple sites, protocols, and instruments, deep learning and label-free imaging flow cytometry might be used to routinely and objectively assess RBC storage lesions. This would automate a complex protocol, minimize laboratory sample handling and preparation, and reduce the impact of procedural errors and discrepancies between facilities and blood donors. The chronology-based machine-learning approach may also improve upon humans' assessment of morphological changes in other biomedically important progressions, such as differentiation and metastasis.

SPiP: Splicing Prediction Pipeline, a machine learning tool for massive detection of exonic and intronic variant effects on mRNA splicing.

Modeling splicing is essential for tackling the challenge of variant interpretation as each nucleotide variation can be pathogenic by affecting pre-mRNA splicing via disruption/creation of splicing motifs such as 5'/3' splice sites, branch sites, or splicing regulatory elements. Unfortunately, most in silico tools focus on a specific type of splicing motif, which is why we developed the Splicing Prediction Pipeline (SPiP) to perform, in one single bioinformatic analysis based on a machine learning approach, a comprehensive assessment of the variant effect on different splicing motifs. We gathered a curated set of 4616 variants scattered all along the sequence of 227 genes, with their corresponding splicing studies. The Bayesian analysis provided us with the number of control variants, that is, variants without impact on splicing, to mimic the deluge of variants from high-throughput sequencing data. Results show that SPiP can deal with the diversity of splicing alterations, with 83.13% sensitivity and 99% specificity to detect spliceogenic variants. Overall performance as measured by area under the receiving operator curve was 0.986, better than SpliceAI and SQUIRLS (0.965 and 0.766) for the same data set. SPiP lends itself to a unique suite for comprehensive prediction of spliceogenicity in the genomic medicine era. SPiP is available at: https://sourceforge.net/projects/splicing-prediction-pipeline/.

Clinical, splicing, and functional analysis to classify BRCA2 exon 3 variants: Application of a points-based ACMG/AMP approach.

Skipping of BRCA2 exon 3 (∆E3) is a naturally occurring splicing event, complicating clinical classification of variants that may alter ∆E3 expression. This study used multiple evidence types to assess pathogenicity of 85 variants in/near BRCA2 exon 3. Bioinformatically predicted spliceogenic variants underwent mRNA splicing analysis using minigenes and/or patient samples. ∆E3 was measured using quantitative analysis. A mouse embryonic stem cell (mESC) based assay was used to determine the impact of 18 variants on mRNA splicing and protein function. For each variant, population frequency, bioinformatic predictions, clinical data, and existing mRNA splicing and functional results were collated. Variant class was assigned using a gene-specific adaptation of ACMG/AMP guidelines, following a recently proposed points-based system. mRNA and mESC analysis combined identified six variants with transcript and/or functional profiles interpreted as loss of function. Cryptic splice site use for acceptor site variants generated a transcript encoding a shorter protein that retains activity. Overall, 69/85 (81%) variants were classified using the points-based approach. Our analysis shows the value of applying gene-specific ACMG/AMP guidelines using a points-based approach and highlights the consideration of cryptic splice site usage to appropriately assign PVS1 code strength.

The splicing effect of variants at branchpoint elements in cancer genes.

PURPOSE: Branchpoint elements are required for intron removal, and variants at these elements can result in aberrant splicing. We aimed to assess the value of branchpoint annotations generated from recent large-scale studies to select branchpoint-abrogating variants, using hereditary cancer genes as model. METHODS: We identified branchpoint elements in 119 genes associated with hereditary cancer from 3 genome-wide experimentally-inferred and 2 predicted branchpoint data sets. We then identified variants that occur within branchpoint elements from public databases. We compared conservation, unique variant observations, and population frequencies at different nucleotides within branchpoint motifs. Finally, selected minigene assays were performed to assess the splicing effect of variants at branchpoint elements within mismatch repair genes. RESULTS: There was poor overlap between predicted and experimentally-inferred branchpoints. Our analysis of cancer genes suggested that variants at -2 nucleotide, -1 nucleotide, and branchpoint positions in experimentally-inferred canonical motifs are more likely to be clinically relevant. Minigene assay data showed the -2 nucleotide to be more important to branchpoint motif integrity but also showed fluidity in branchpoint usage. CONCLUSION: Data from cancer gene analysis suggest that there are few high-risk alleles that severely impact function via branchpoint abrogation. Results of this study inform a general scheme to prioritize branchpoint motif variants for further study.

Risks of breast and ovarian cancer for women harboring pathogenic missense variants in BRCA1 and BRCA2 compared with those harboring protein truncating variants.

PURPOSE: Germline genetic testing for BRCA1 and BRCA2 variants has been a part of clinical practice for >2 decades. However, no studies have compared the cancer risks associated with missense pathogenic variants (PVs) with those associated with protein truncating (PTC) variants. METHODS: We collected 582 informative pedigrees segregating 1 of 28 missense PVs in BRCA1 and 153 pedigrees segregating 1 of 12 missense PVs in BRCA2. We analyzed 324 pedigrees with PTC variants in BRCA1 and 214 pedigrees with PTC variants in BRCA2. Cancer risks were estimated using modified segregation analysis. RESULTS: Estimated breast cancer risks were markedly lower for women aged >50 years carrying BRCA1 missense PVs than for the women carrying BRCA1 PTC variants (hazard ratio [HR] = 3.9 [2.4-6.2] for PVs vs 12.8 [5.7-28.7] for PTC variants; P = .01), particularly for missense PVs in the BRCA1 C-terminal domain (HR = 2.8 [1.4-5.6]; P = .005). In case of BRCA2, for women aged >50 years, the HR was 3.9 (2.0-7.2) for those heterozygous for missense PVs compared with 7.0 (3.3-14.7) for those harboring PTC variants. BRCA1 p.[Cys64Arg] and BRCA2 p.[Trp2626Cys] were associated with particularly low risks of breast cancer compared with other PVs. CONCLUSION: These results have important implications for the counseling of at-risk women who harbor missense PVs in the BRCA1/2 genes.