Evidence-based recommendations for gene-specific ACMG/AMP variant classification from the ClinGen ENIGMA BRCA1 and BRCA2 Variant Curation Expert Panel.

The ENIGMA research consortium develops and applies methods to determine clinical significance of variants in hereditary breast and ovarian cancer genes. An ENIGMA BRCA1/2 classification sub-group, formed in 2015 as a ClinGen external expert panel, evolved into a ClinGen internal Variant Curation Expert Panel (VCEP) to align with Food and Drug Administration recognized processes for ClinVar contributions. The VCEP reviewed American College of Medical Genetics and Genomics/Association of Molecular Pathology (ACMG/AMP) classification criteria for relevance to interpreting BRCA1 and BRCA2 variants. Statistical methods were used to calibrate evidence strength for different data types. Pilot specifications were tested on 40 variants and documentation revised for clarity and ease of use. The original criterion descriptions for 13 evidence codes were considered non-applicable or overlapping with other criteria. Scenario of use was extended or re-purposed for eight codes. Extensive analysis and/or data review informed specification descriptions and weights for all codes. Specifications were applied to pilot variants with pre-existing ClinVar classification as follows: 13 uncertain significance or conflicting, 14 pathogenic and/or likely pathogenic, and 13 benign and/or likely benign. Review resolved classification for 11/13 uncertain significance or conflicting variants and retained or improved confidence in classification for the remaining variants. Alignment of pre-existing ENIGMA research classification processes with ACMG/AMP classification guidelines highlighted several gaps in the research processes and the baseline ACMG/AMP criteria. Calibration of evidence strength was key to justify utility and strength of different data types for gene-specific application. The gene-specific criteria demonstrated value for improving ACMG/AMP-aligned classification of BRCA1 and BRCA2 variants.

Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria.

Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational predictors as "supporting" level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (supporting, moderate, strong, very strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tool's scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score intervals) corresponding to each strength of evidence for pathogenicity and benignity for thirteen missense variant interpretation tools, using carefully assembled independent data sets. Most tools achieved supporting evidence level for both pathogenic and benign classification using newly established thresholds. Multiple tools reached score thresholds justifying moderate and several reached strong evidence levels. One tool reached very strong evidence level for benign classification on some variants. Based on these findings, we provide recommendations for evidence-based revisions of the PP3 and BP4 ACMG/AMP criteria using individual tools and future assessment of computational methods for clinical interpretation.

Alkoxycarbonyl Groups in Metalloesters Showing Oxocarbenium-like Structure and Alkylating Reactivity.

In contrast to the well-documented acylating reactivity, the alkylating reactivity of the alkoxycarbonyl group, as signified by its oxocarbenium-like resonance structure, remains almost unexplored. Herein, the first series of Co/Ni dinuclear metalloesters exhibiting the novel oxocarbenium-like alkoxycarbonyl groups were synthesized and characterized. In these deformed alkoxycarbonyl groups, the Ccarbonyl-Oalkoxyl bonds were contracted to 1.177(11)~1.191(9) Šwith the elongations of the Ccarbonyl=Ocarbonyl bonds to 1.368(13)~1.441(9) Å. Meanwhile, the O-Calkyl bonds were also elongated to 1.522(11) ~1.607(15) Å, and were by far the longest O-Calkyl bonds reported for alkoxycarbonyl groups. As triggered by the long O-Calkyl distances, the alkylating reactivity of the oxocarbenium-like methoxycarbonyl group towards a series of C/N/O-nucleophiles via the rare BAL2 mechanism at ambient conditions was examined. Furthermore, the homo-etherifications of alcohols mediated by the Co/Ni dinuclear metalloesters were investigated. The yields followed the trend ethanol≫n-propanol≫n-butanol ≈n-pentanol, that closely related to the structure features of the alkoxycarbonyl groups in corresponding metalloesters: while the ethoxycarbonyl group showed the reactive oxocarbenium-like framework, the n-propoxycarbonyl group displayed the dioxocarbenium-like skeleton with a shorter O-Calkyl bond; In comparison, the classical frameworks with unactivated alkyl moieties were observed for n-butoxycarbonyl and n-pentoxycarbonyl groups.

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.

Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants.

Germline pathogenic variants in TP53 are associated with Li-Fraumeni syndrome, a cancer predisposition disorder inherited in an autosomal dominant pattern associated with a high risk of malignancy, including early-onset breast cancers, sarcomas, adrenocortical carcinomas, and brain tumors. Intense cancer surveillance for individuals with TP53 germline pathogenic variants is associated with reduced cancer-related mortality. Accurate and consistent classification of germline variants across clinical and research laboratories is important to ensure appropriate cancer surveillance recommendations. Here, we describe the work performed by the Clinical Genome Resource TP53 Variant Curation Expert Panel (ClinGen TP53 VCEP) focused on specifying the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines for germline variant classification to the TP53 gene. Specifications were developed for 20 ACMG/AMP criteria, while nine were deemed not applicable. The original strength level for the 10 criteria was also adjusted due to current evidence. Use of TP53-specific guidelines and sharing of clinical data among experts and clinical laboratories led to a decrease in variants of uncertain significance from 28% to 12% compared with the original guidelines. The ClinGen TP53 VCEP recommends the use of these TP53-specific ACMG/AMP guidelines as the standard strategy for TP53 germline variant classification.

Considerations in assessing germline variant pathogenicity using cosegregation analysis.

PURPOSE: The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have developed guidelines for classifying germline variants as pathogenic or benign to interpret genetic testing results. Cosegregation analysis is an important component of the guidelines. There are two main approaches for cosegregation analysis: meiosis counting and Bayes factor-based quantitative methods. Of these, the ACMG/AMP guidelines employ only meiosis counting. The accuracy of either approach has not been sufficiently addressed in previous works. METHODS: We analyzed hypothetical, simulated, and real-life data to evaluate the accuracy of each approach for cancer-associated genes. RESULTS: We demonstrate that meiosis counting can provide incorrect classifications when the underlying genetic basis of the disease departs from simple Mendelian situations. Some Bayes factor approaches are currently implemented with inappropriate penetrance. We propose an improved penetrance model and describe several critical considerations, including the accuracy of cosegregation for moderate-risk genes and the impact of pleiotropy, population, and birth year. We highlight a webserver, COOL (Co-segregation Online, http://BJFengLab.org/ ), that implements an accurate Bayes factor cosegregation analysis. CONCLUSION: An appropriate penetrance model improves the accuracy of Bayes factor cosegregation analysis for high-penetrant variants, and is a better choice than meiosis counting whenever feasible.

Comprehensive annotation of BRCA1 and BRCA2 missense variants by functionally validated sequence-based computational prediction models.

PURPOSE: To improve methods for predicting the impact of missense variants of uncertain significance (VUS) in BRCA1 and BRCA2 on protein function. METHODS: Functional data for 248 BRCA1 and 207 BRCA2 variants from assays with established high sensitivity and specificity for damaging variants were used to recalibrate 40 in silico algorithms predicting the impact of variants on protein activity. Additional random forest (RF) and naïve voting method (NVM) metapredictors for both BRCA1 and BRCA2 were developed to increase predictive accuracy. RESULTS: Optimized thresholds for in silico prediction models significantly improved the accuracy of predicted functional effects for BRCA1 and BRCA2 variants. In addition, new BRCA1-RF and BRCA2-RF metapredictors showed area under the curve (AUC) values of 0.92 (95% confidence interval [CI]: 0.88-0.96) and 0.90 (95% CI: 0.84-0.95), respectively. Similarly, the BRCA1-NVM and BRCA2-NVM models had AUCs of 0.93 and 0.90. The RF and NVM models were used to predict the pathogenicity of all possible missense variants in BRCA1 and BRCA2. CONCLUSION: The recalibrated algorithms and new metapredictors significantly improved upon current models for predicting the impact of variants in cancer risk-associated domains of BRCA1 and BRCA2. Prediction of the functional impact of all possible variants in BRCA1 and BRCA2 provides important information about the clinical relevance of variants in these genes.

Germline mutations in PPFIBP2 are associated with lethal prostate cancer.

BACKGROUND: Few genes have germline mutations which predispose men to more aggressive prostate cancer (PCa). This study evaluated the contribution of germline loss of function (LOF) variants in PPFIBP2 to risk of lethal PCa. METHODS: A case-case study of 1414 PCa patients with lethal PCa and low-risk localized PCa was performed. Germline DNA samples from these patients were sequenced for PPFIBP2. Mutation carrier rates and association with lethal PCa were analyzed using the Fisher exact test, logistic regression, and Kaplan-Meier survival analysis. RESULTS: In the entire study population, eight patients, all of European ancestry, were identified as carrying PPFIBP2 pathogenic or likely pathogenic mutations. Seven (1.52%) of 462 lethal PCa patients were carriers compared with only one (0.12%) carrier in 810 low-risk PCa patients, P = 0.0029. The estimated Odds Ratio (OR) of carrying PPFIBP2 mutation for lethal PCa was 13.8 in European American population. The PPFIBP2 loss-of-function mutation carrier rate in lethal PCa cases was also higher than in 33 370 non-Finnish European individuals from the Exome Aggregation Consortium (ExAC) (carrier rate of 0.17%, P = 1.92 × 10-5 ) and in 498 men with localized PCa from The Cancer Genome Atlas cohort (TCGA) cohort (carrier rate of 0%, P = 0.0058). Survival analysis in European American lethal cases revealed PPFIBP2 mutation status as an independent predictor of shorter survival after adjusting for age at diagnosis, PSA at diagnosis, and genetic background (hazard ratio = 2.62, P = 0.034). CONCLUSIONS: While larger studies are needed, germline mutations in a novel gene, PPFIBP2, differentiated risk for lethal PCa from low-risk cases and were associated with shorter survival times after diagnosis.

PERCH: A Unified Framework for Disease Gene Prioritization.

To interpret genetic variants discovered from next-generation sequencing, integration of heterogeneous information is vital for success. This article describes a framework named PERCH (Polymorphism Evaluation, Ranking, and Classification for a Heritable trait), available at http://BJFengLab.org/. It can prioritize disease genes by quantitatively unifying a new deleteriousness measure called BayesDel, an improved assessment of the biological relevance of genes to the disease, a modified linkage analysis, a novel rare-variant association test, and a converted variant call quality score. It supports data that contain various combinations of extended pedigrees, trios, and case-controls, and allows for a reduced penetrance, an elevated phenocopy rate, liability classes, and covariates. BayesDel is more accurate than PolyPhen2, SIFT, FATHMM, LRT, Mutation Taster, Mutation Assessor, PhyloP, GERP++, SiPhy, CADD, MetaLR, and MetaSVM. The overall approach is faster and more powerful than the existing quantitative method pVAAST, as shown by the simulations of challenging situations in finding the missing heritability of a complex disease. This framework can also classify variants of unknown significance (variants of uncertain significance) by quantitatively integrating allele frequencies, deleteriousness, association, and co-segregation. PERCH is a versatile tool for gene prioritization in gene discovery research and variant classification in clinical genetic testing.

Breast cancer risk prediction using a polygenic risk score in the familial setting: a prospective study from the Breast Cancer Family Registry and kConFab.

PURPOSE: This study examined the utility of sets of single-nucleotide polymorphisms (SNPs) in familial but non-BRCA-associated breast cancer (BC). METHODS: We derived a polygenic risk score (PRS) based on 24 known BC risk SNPs for 4,365 women from the Breast Cancer Family Registry and Kathleen Cuningham Consortium Foundation for Research into Familial Breast Cancer familial BC cohorts. We compared scores for women based on cancer status at baseline; 2,599 women unaffected at enrollment were followed-up for an average of 7.4 years. Cox proportional hazards regression was used to analyze the association of PRS with BC risk. The BOADICEA risk prediction algorithm was used to measure risk based on family history alone. RESULTS: The mean PRS at baseline was 2.25 (SD, 0.35) for affected women and was 2.17 (SD, 0.35) for unaffected women from combined cohorts (P < 10-6). During follow-up, 205 BC cases occurred. The hazard ratios for continuous PRS (per SD) and upper versus lower quintiles were 1.38 (95% confidence interval: 1.22-1.56) and 3.18 (95% confidence interval: 1.84-5.23) respectively. Based on their PRS-based predicted risk, management for up to 23% of women could be altered. CONCLUSION: Including BC-associated SNPs in risk assessment can provide more accurate risk prediction than family history alone and can influence recommendations for cancer screening and prevention modalities for high-risk women.Genet Med 19 1, 30-35.

Targeted massively parallel sequencing of a panel of putative breast cancer susceptibility genes in a large cohort of multiple-case breast and ovarian cancer families.

INTRODUCTION: Gene panel testing for breast cancer susceptibility has become relatively cheap and accessible. However, the breast cancer risks associated with mutations in many genes included in these panels are unknown. METHODS: We performed custom-designed targeted sequencing covering the coding exons of 17 known and putative breast cancer susceptibility genes in 660 non-BRCA1/2 women with familial breast cancer. Putative deleterious mutations were genotyped in relevant family members to assess co-segregation of each variant with disease. We used maximum likelihood models to estimate the breast cancer risks associated with mutations in each of the genes. RESULTS: We found 31 putative deleterious mutations in 7 known breast cancer susceptibility genes (TP53, PALB2, ATM, CHEK2, CDH1, PTEN and STK11) in 45 cases, and 22 potential deleterious mutations in 31 cases in 8 other genes (BARD1, BRIP1, MRE11, NBN, RAD50, RAD51C, RAD51D and CDK4). The relevant variants were then genotyped in 558 family members. Assuming a constant relative risk of breast cancer across age groups, only variants in CDH1, CHEK2, PALB2 and TP53 showed evidence of a significantly increased risk of breast cancer, with some supportive evidence that mutations in ATM confer moderate risk. CONCLUSIONS: Panel testing for these breast cancer families provided additional relevant clinical information for <2% of families. We demonstrated that segregation analysis has some potential to help estimate the breast cancer risks associated with mutations in breast cancer susceptibility genes, but very large case-control sequencing studies and/or larger family-based studies will be needed to define the risks more accurately.

A homozygous PMS2 founder mutation with an attenuated constitutional mismatch repair deficiency phenotype.

BACKGROUND: Inherited mutations in DNA mismatch repair genes predispose to different cancer syndromes depending on whether they are mono-allelic or bi-allelic. This supports a causal relationship between expression level in the germline and phenotype variation. As a model to study this relationship, our study aimed to define the pathogenic characteristics of a recurrent homozygous coding variant in PMS2 displaying an attenuated phenotype identified by clinical genetic testing in seven Inuit families from Northern Quebec. METHODS: Pathogenic characteristics of the PMS2 mutation NM_000535.5:c.2002A>G were studied using genotype-phenotype correlation, single-molecule expression detection and single genome microsatellite instability analysis. RESULTS: This PMS2 mutation generates a de novo splice site that competes with the authentic site. In homozygotes, expression of the full-length protein is reduced to a level barely detectable by conventional diagnostics. Median age at primary cancer diagnosis is 22 years among 13 NM_000535.5:c.2002A>G homozygotes, versus 8 years in individuals carrying bi-allelic truncating mutations. Residual expression of full-length PMS2 transcript was detected in normal tissues from homozygotes with cancers in their 20s. CONCLUSIONS: Our genotype-phenotype study of c.2002A>G illustrates that an extremely low level of PMS2 expression likely delays cancer onset, a feature that could be exploited in cancer preventive intervention.

Estimation of the RNU2 macrosatellite mutation rate by BRCA1 mutation tracing.

Large tandem repeat sequences have been poorly investigated as severe technical limitations and their frequent absence from the genome reference hinder their analysis. Extensive allelotyping of this class of variation has not been possible until now and their mutational dynamics are still poorly known. In order to estimate the mutation rate of a macrosatellite, we analysed in detail the RNU2 locus, which displays at least 50 different alleles containing 5-82 copies of a 6.1 kb repeat unit. Mining data from the 1000 Genomes Project allowed us to precisely estimate copy numbers of the RNU2 repeat unit using read depth of coverage. This further revealed significantly different mean values in various recent modern human populations, favoring a scenario of fast evolution of this locus. Its proximity to a disease gene with numerous founder mutations, BRCA1, within the same linkage disequilibrium block, offered the unique opportunity to trace RNU2 arrays over a large timescale. Analysis of the transmission of RNU2 arrays associated with one 'private' mutation in an extended kindred and four founder mutations in multiple kindreds gave an estimation by maximum likelihood of 5 × 10(-3) mutations per generation, which is close to that of microsatellites.

Rare and common variants in CARD14, encoding an epidermal regulator of NF-kappaB, in psoriasis.

Psoriasis is a common inflammatory disorder of the skin and other organs. We have determined that mutations in CARD14, encoding a nuclear factor of kappa light chain enhancer in B cells (NF-kB) activator within skin epidermis, account for PSORS2. Here, we describe fifteen additional rare missense variants in CARD14, their distribution in seven psoriasis cohorts (>6,000 cases and >4,000 controls), and their effects on NF-kB activation and the transcriptome of keratinocytes. There were more CARD14 rare variants in cases than in controls (burden test p value = 0.0015). Some variants were only seen in a single case, and these included putative pathogenic mutations (c.424G>A [p.Glu142Lys] and c.425A>G [p.Glu142Gly]) and the generalized-pustular-psoriasis mutation, c.413A>C (p.Glu138Ala); these three mutations lie within the coiled-coil domain of CARD14. The c.349G>A (p.Gly117Ser) familial-psoriasis mutation was present at a frequency of 0.0005 in cases of European ancestry. CARD14 variants led to a range of NF-kB activities; in particular, putative pathogenic variants led to levels >2.5× higher than did wild-type CARD14. Two variants (c.511C>A [p.His171Asn] and c.536G>A [p.Arg179His]) required stimulation with tumor necrosis factor alpha (TNF-α) to achieve significant increases in NF-kB levels. Transcriptome profiling of wild-type and variant CARD14 transfectants in keratinocytes differentiated probably pathogenic mutations from neutral variants such as polymorphisms. Over 20 CARD14 polymorphisms were also genotyped, and meta-analysis revealed an association between psoriasis and rs11652075 (c.2458C>T [p.Arg820Trp]; p value = 2.1 × 10(-6)). In the two largest psoriasis cohorts, evidence for association increased when rs11652075 was conditioned on HLA-Cw*0602 (PSORS1). These studies contribute to our understanding of the genetic basis of psoriasis and illustrate the challenges faced in identifying pathogenic variants in common disease.

PAPRIKA: A Question Bank for Assessing Psoriatic Arthritis Risk in Individuals of Diverse Ancestries.

OBJECTIVE: We aimed to create a question bank about clinical factors for predicting the diagnoses of psoriatic arthritis in patients with psoriasis of various ancestries and skin tones, which can be completed entirely by patients. METHODS: Utah Psoriasis Initiative participants without a psoriatic arthritis diagnosis at enrollment were observed for diagnosis during the study period. We inferred ancestry from exome sequencing data and performed Cox proportional hazards regression to identify clinical predictors of psoriatic arthritis in different ancestry groups. Based on results and literature review, we developed a question bank for assessing psoriatic arthritis risk among patients with psoriasis in various ancestries. RESULTS: Patient-reported untreated psoriasis induration and history of fingernail psoriasis were associated with psoriatic arthritis in participants of European and non-European ancestry. We developed the Psoriatic Arthritis Prediction and Identification Question Bank for Diverse Ancestries (PAPRIKA) version 1.0, which included questions regarding psoriasis characteristics, arthritis symptoms, comorbidities, family history, and demographics. PAPRIKA is accessible at http://bjfenglab.org/. CONCLUSION: The clinical features (untreated psoriasis induration and history of fingernail psoriasis) that can predict psoriatic arthritis in European individuals also work for non-European individuals. PAPRIKA can be used to gather psoriatic arthritis predictive data from patients with psoriasis without provider assistance and is relevant for patients across ancestries.

Measuring Psoriasis Severity at Home.

Psoriasis plaque severity metrics, such as induration (thickness), erythema (redness), and desquamation (scaliness), are associated with the subsequent development of psoriatic arthritis (PsA) among cutaneous-only psoriasis patients (patients with skin or nail psoriasis but no psoriatic arthritis). These metrics can be used for PsA screening. However, a key challenge in PsA screening is to optimize accessibility and minimize costs for patients, while also reducing the burden on healthcare systems. Therefore, an ideal screening tool consists of questions that patients can answer without a physician's assistance. Although reference images can be used to help a patient self-assess erythema and desquamation severity, a patient would need a tactile induration reference card to self-assess induration severity. This protocol describes how to create an induration reference card, the Psoriasis Thickness Reference Card, as well as how to use it to assess lesion induration severity. Administration of reference images for erythema and desquamation and a Psoriasis Thickness Reference Card for induration to 27 psoriasis patients showed that patients were moderately successful at self-assessing the severity of these three metrics. These findings support the feasibility of a future PsA screening test that patients can complete without the need for physician assistance.

Using gene and gene-set association tests to identify lethal prostate cancer genes.

BACKGROUND: Recent advances in the detection and treatment of prostate cancer (PCa) have reduced morbidity and mortality from this common cancer. Despite these improvements, PCa remains the second leading cause of cancer death in men in the United States. Further understanding of the genetic underpinnings of lethal PCa is required to drive risk detection and prevention and ultimately reduce mortality. We therefore set out to identify germline variants associated with cases of lethal prostate cancer (LPCa). METHODS: Using a two-stage study design, we compared whole-exome sequencing data of 550 LPCa patients to 488 healthy male controls. Men were classified as having LPCa based on medical record review. Candidate genes were identified using gene- and gene-set-based rare truncating variant association tests. Case-control burden testing through Firth's penalized logistic regression and case-gnomAD allelic burden testing through a one-sided mid-p Fisher's exact test were conducted. Each gene's p-values from these tests were combined into an omnibus p-value for candidate gene selection. In the subsequent validation stage, genes were assessed using the UK Biobank and Firth's penalized logistic regression for each ancestry, combined through meta-analysis. RESULTS: Gene-based rare variant association tests identified 12 genes nominally associated with LPCa. Rare-variant association tests identified a gene set with a significantly higher burden of truncating germline mutations in LPCa patients than controls. Combining gene- and gene-set test results, four nominally significant genes (PPP1R3A, TG, PPFIBP2, and BTN3A3) were selected as candidates. Subsequent validation using the UK Biobank found that PPP1R3A was significantly associated with LPCa risk (odds ratio 2.34, CI 1.20-4.59). Specifically, pGln662ArgfsTer7 was identified as the predominant variant in PPP1R3A among LPCa patients in our dataset. CONCLUSIONS: Both individual gene and gene-set analyses identified candidates associated with LPCa. The novel association of PPP1R3A and LPCa risk merits further investigation.

Inherited Germline Variants in Urinary Tract Cancer: A Multicenter Whole-Exome Sequencing Analysis and Correlation With Clinical Features and Tumor Genomics.

PURPOSE: This study investigates a real-world multicenter cohort of patients with urinary tract cancer (UTC), with primary disease sites including the bladder, urethra, and upper tract, who enrolled for research molecular testing of their germline and tumor. The purpose of this study was to evaluate factors that could affect the likelihood of identifying a clinically actionable germline pathogenic variant (PV). METHODS: Patients with UTC were identified from 10 cancer institutes of the Oncology Research Information Exchange Network consortium. The data set comprised abstracted clinical data with germline and tumor genomic data, and comparative analyses were conducted. RESULTS: Clinically actionable germline PVs in cancer predisposition genes were identified in 16 (4.5%) of 354 patients. A higher proportion of patients with the urethra and the upper tract as the primary sites of disease had PVs with a prevalence of 11% (5/45), compared with only 3.6% (11/308) in those with the bladder as the primary site of disease (P = .04). There were no significant differences in markers of genomic instability (such as tumor mutational burden, microsatellite instability [MSI], and loss of heterozygosity, copy number, and chromosomal instability) between those with PVs and those without (P > .05). Of the PVs identified, 10 (62%) were in homologous recombination repair (HRR) genes, three (19%) in mismatch repair (MMR) genes, and three (19%) in genes associated with other pathways. CONCLUSION: Tissue-based assessment of genomic instability, such as MSI, does not reliably indicate germline PV. A comprehensive clinical germline testing approach that includes HRR genes in addition to MMR genes is likely to yield PVs in approximately one of 10 patients with nonbladder primary disease sites such as the upper tract and the urethra.

Atypical cancer risk profile in carriers of Italian founder BRCA1 variant p.His1673del: Implications for classification and clinical management.

BACKGROUND: BRCA1:c.5017_5019del (p.His1673del) is a founder variant relatively frequent in Northern Italy. Despite previous suggestion of pathogenicity, variant classification in public databases is still conflicting, needing additional evidence. METHODS: Maximum likelihood penetrance of breast/ovarian and other cancer types was estimated using full pedigree data from 53 informative Italian families. The effect of the variant on BRCA1-ABRAXAS1 interaction was assessed using a GFP-fragment reassembly-based PPI assay. Results were combined with additional data from multiple sources to classify the variant according to ACMG/AMP classification rules specified for BRCA1/2. RESULTS: Variant-carriers displayed increased risk for ovarian cancer (HR = 33.0, 95% CI = 7.0-155.0; cumulative risk at age 70 = 27.6%, 95% CI = 12.6-40.0%) but not for breast cancer (HR = 0.7, 95% CI = 0.2-2.2). An increased risk of uterine cancer (HR = 8.0, 95% CI = 1.03-61.6) emerged, warranting further evaluation. Likelihood-ratio in favor of pathogenicity was 98898642.82 under assumption of standard BRCA1 breast and ovarian penetrance, and 104240832.84 after excluding breast cancer diagnoses (based on penetrance results). Functional analysis demonstrated that the variant abrogates the BRCA1-ABRAXAS1 binding, supporting the PS3 code assignment within the ACMG/AMP rule-based model. Collectively, these findings allowed to classify the variant as pathogenic. CONCLUSION: Pathogenicity of BRCA1:c.5017_5019del(p.His1673del) has been confirmed; however, breast cancer risk in Italian families is not increased, unlike in families from other countries and in carriers of most BRCA1 pathogenic variants. The knowledge of atypical risk profiles for this and other variants will pave the way for personalized management based on specific genotype.