Search

Pathogenic germline variants in the TP53 gene predispose to a wide range of cancers, known collectively as Li-Fraumeni syndrome (LFS). There has been much research aimed to identify genotype-phenotype correlations, that is, differences between variant location and/or effect and cancer spectrum. These correlations, should they exist, have potential to impact clinical management of carriers. Review of previously published studies showed a variety of study designs and inconsistency in reported findings. Here, we used pooled data from 427 TP53 carriers who had undergone multigene panel testing and 154 TP53 carriers identified by single-gene testing to investigate correlations between TP53 genotype (truncating variants, hotspot variants, other missense variants with dominant-negative effect, missense variants without dominant-negative effect) and a number of LFS-selected malignancies. Our results suggest that carriers of truncating and hotspot variants might be more likely to present with LFS cancers and have shorter time to first cancer diagnosis compared to carriers of other variant types. However, the differences observed were minor, and we conclude that there is currently insufficient evidence to consider location and/or molecular effect of pathogenic variants to assist with clinical management of TP53 carriers. Larger studies are necessary to confirm the correlations suggested by our analysis. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Background: A variant can be pathogenic or benign with relation to a human disease. Current classification categories from benign to pathogenic reflect a probabilistic summary of the current understanding. A primary metric of clinical utility for multiplexed assays of variant effect (MAVE) is the number of variants that can be reclassified from uncertain significance (VUS). However, a gap in this measure of utility is that it underrepresents the information gained from MAVEs. The aim of this study was to develop an improved quantification metric for MAVE utility. We propose adopting an information content approach that includes data that does not reclassify variants will better reflect true information gain. We adopted an information content approach to evaluate the information gain, in bits, for MAVEs of BRCA1, PTEN, and TP53. Here, one bit represents the amount of information required to completely classify a single variant starting from no information. Results: BRCA1 MAVEs produced a total of 831.2 bits of information, 6.58% of the total missense information in BRCA1 and a 22-fold increase over the information that only contributed to VUS reclassification. PTEN MAVEs produced 2059.6 bits of information which represents 32.8% of the total missense information in PTEN and an 85-fold increase over the information that contributed to VUS reclassification. TP53 MAVEs produced 277.8 bits of information which represents 6.22% of the total missense information in TP53 and a 3.5-fold increase over the information that contributed to VUS reclassification. Conclusions: An information content approach will more accurately portray information gained through MAVE mapping efforts than by counting the number of variants reclassified. This information content approach may also help define the impact of guideline changes that modify the information definitions used to classify groups of variants. [ABSTRACT FROM AUTHOR]

TP53 pathogenic germline variation is associated with the multi-cancer predisposition Li–Fraumeni syndrome (LFS). Next-generation sequencing and multigene panel testing are highlighting variability in the clinical presentation of patients with TP53 positive results. We aimed to investigate if the p53 variants considered as major hotspots at both germline and somatic levels (p.Arg175His, p.Gly245Asp, p.Gly245Ser, p.Arg248Gln, p.Arg248Trp, p.Arg273Cys, p.Arg273His, and p.Arg282Trp) were associated with poorer prognostic features compared to other pathogenic missense variants in the DNA-binding domain. To do so, we assessed clinical features from 1025 carriers of germline TP53 pathogenic variants (749 probands and 276 relatives) from three independent datasets (IARC TP53 Database, Ambry Single Gene Testing, and Ambry Multigene Panel Testing). We observed that, compared to carriers of non-hotspot germline variants, individuals that carried a hotspot germline variant were more likely to present with a Classic LFS phenotype, earlier age of first breast cancer onset, and shorter time to diagnosis to any cancer. Further studies with larger datasets addressing differences in cancer phenotypes by genotype are thus needed to replicate our findings and consider variant effect and position, towards future personalized clinical management of pathogenic variant carriers. Image, graphical abstract [ABSTRACT FROM AUTHOR]

The ClinGen Hereditary Breast, Ovarian, and Pancreatic Cancer (HBOP) Variant Curation Expert Panel (VCEP) is composed of internationally recognized experts in clinical genetics, molecular biology, and variant interpretation. This VCEP made specifications for the American College of Medical Genetics and Association for Molecular Pathology (ACMG/AMP) guidelines for the ataxia telangiectasia mutated (ATM) gene according to the ClinGen protocol. These gene-specific rules for ATM were modified from the ACMG/AMP guidelines and were tested against 33 ATM variants of various types and classifications in a pilot curation phase. The pilot revealed a majority agreement between the HBOP VCEP classifications and the ClinVar-deposited classifications. Six pilot variants had conflicting interpretations in ClinVar, and re-evaluation with the VCEP's ATM -specific rules resulted in four that were classified as benign, one as likely pathogenic, and one as a variant of uncertain significance (VUS) by the VCEP, improving the certainty of interpretations in the public domain. Overall, 28 of the 33 pilot variants were not VUS, leading to an 85% classification rate. The ClinGen-approved, modified rules demonstrated value for improved interpretation of variants in ATM. This paper details ACMG/AMP-style guidelines for ataxia telangiectasia mutated (ATM) variant interpretation and shows the results of pilot classifications. Several phenotype-driven rules were omitted or modified due to low-penetrance and commonness of breast cancer. This work aims to harmonize the classification of ATM variants and avoid misinterpretation by using standard rules. [ABSTRACT FROM AUTHOR]

Many in silico predictors of genetic variant pathogenicity have been previously developed, but there is currently no standard application of these algorithms for variant assessment. Using 4,094 ClinVar-curated missense variants in clinically actionable genes, we evaluated the accuracy and yield of benign and deleterious evidence in 5 in silico meta-predictors, as well as agreement of SIFT and PolyPhen2, and report the derived thresholds for the best performing predictor(s). REVEL and BayesDel outperformed all other meta-predictors (CADD, MetaSVM, Eigen), with higher positive predictive value, comparable negative predictive value, higher yield, and greater overall prediction performance. Agreement of SIFT and PolyPhen2 resulted in slightly higher yield but lower overall prediction performance than REVEL or BayesDel. Our results support the use of gene-level rather than generalized thresholds, when gene-level thresholds can be estimated. Our results also support the use of 2-sided thresholds, which allow for uncertainty, rather than a single, binary cut-point for assigning benign and deleterious evidence. The gene-level 2-sided thresholds we derived for REVEL or BayesDel can be used to assess in silico evidence for missense variants in accordance with current classification guidelines. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the articles "Gene-Panel Sequencing and the Prediction of Breast-Cancer Risk," by D. F. Easton and colleagues and "ClinGen--The Clinical Genome Resource," by H. L. Rehm and colleagues, both published in the June 4, 2015 issue.

Variants of uncertain significance (VUSs) in BRCA2 are a common result of hereditary cancer genetic testing. While more than 4,000 unique VUSs, comprised of missense or intronic variants, have been identified in BRCA2 , the few missense variants now classified clinically as pathogenic or likely pathogenic are predominantly located in the region encoding the C-terminal DNA binding domain (DBD). We report on functional evaluation of the influence of 462 BRCA2 missense variants affecting the DBD on DNA repair activity of BRCA2 using a homology-directed DNA double-strand break repair assay. Of these, 137 were functionally abnormal, 313 were functionally normal, and 12 demonstrated intermediate function. Comparisons with other functional studies of BRCA2 missense variants yielded strong correlations. Sequence-based in silico prediction models had high sensitivity, but limited specificity, relative to the homology-directed repair assay. Combining the functional results with clinical and genetic data in an American College of Medical Genetics (ACMG)/Association for Molecular Pathology (AMP)-like variant classification framework from a clinical testing laboratory, after excluding known splicing variants and functionally intermediate variants, classified 431 of 442 (97.5%) missense variants (129 as pathogenic/likely pathogenic and 302 as benign/likely benign). Functionally abnormal variants classified as pathogenic by ACMG/AMP rules were associated with a slightly lower risk of breast cancer (odds ratio [OR] 5.15, 95% confidence interval [CI] 3.43–7.83) than BRCA2 DBD protein truncating variants (OR 8.56, 95% CI 6.03–12.36). Overall, functional studies of BRCA2 variants using validated assays substantially improved the variant classification yield from ACMG/AMP models and are expected to improve clinical management of many individuals found to harbor germline BRCA2 missense VUS. Combining results from a homology-directed repair functional assay with clinical and genetic data in an American College of Medical Genetics (ACMG)/AMP-like variant classification framework classified 97.5% of the evaluated BRCA2 non-splicing missense variants as pathogenic/likely pathogenic or benign/likely benign. The results should prove useful for clinical management of individuals with germline BRCA2 missense variants. [ABSTRACT FROM AUTHOR]

The 2015 American College of Medical Genetics and Genomics and the Association for Molecular Pathology variant classification publication established a standard employed internationally to guide laboratories in variant assessment. Those recommendations included both pathogenic (PP1) and benign (BS4) criteria for evaluating the inheritance patterns of variants, but details of how to apply those criteria at appropriate evidence levels were sparse. Several publications have since attempted to provide additional guidance, but anecdotally, this issue is still challenging. Additionally, it is not clear that those prior efforts fully distinguished disease-gene identification considerations from variant pathogenicity considerations nor did they address autosomal-recessive and X-linked inheritance. Here, we have taken a mixed inductive and deductive approach to this problem using real diseases as examples. We have developed a practical heuristic for genetic co-segregation evidence and have also determined that the specific phenotype criterion (PP4) is inseparably coupled to the co-segregation criterion. We have also determined that negative evidence at one locus constitutes positive evidence for other loci for disorders with locus heterogeneity. Finally, we provide a points-based system for evaluating phenotype and co-segregation as evidence types to support or refute a locus and show how that can be integrated into the Bayesian framework now used for variant classification and consistent with the 2015 guidelines. The 2015 ACMG/AMP variant classification recommendations included pathogenic (PP1) and benign (BS4) criteria for co-segregation, but details for using them were sparse. We developed a points-based co-segregation heuristic and integrated the specific phenotype criterion (PP4). We also show that negative evidence at one locus constitutes positive evidence for other loci. [ABSTRACT FROM AUTHOR]

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. [Display omitted] The ClinGen SVI Splicing Subgroup provides recommendations for the application of existing splicing-related ACMG/AMP codes and re-purposing of other codes to capture splicing-related evidence. This study outlines a process for developing a gene-specific PVS1 decision tree and provides methodology to calibrate bioinformatic splice prediction tools. [ABSTRACT FROM AUTHOR]

Purpose PTEN mutations are associated with breast, colon, endometrial, kidney, and thyroid cancers. Most PTEN promoter alterations, however, are characterized as variants of unknown significance, and their contribution to cancer risk is unclear. Materials and Methods Personal and family histories of 88,333 patients undergoing PTEN analysis as part of multigene panel testing (MGPT) were retrospectively reviewed. Cases (n=59,784)were individuals with personal history of PTEN-related cancer. Controls (n=28,549) had no personal history of cancer. Individuals were categorized as positive for one or more mutations(PATHO), without mutations but carrying one or morepromoter variant(PROM), or negative for alterations (WT). Multivariable logistic regression was used to assess PTEN associations with phenotypes, adjusted for race/ethnicity, age, sex, and MGPT. Results Overall, 79 (0.09%) patients were PATHO and 791 (0.9%) were PROM carriers. Compared with WT, PATHOs were 2.30 (95% CI, 1.19 to 4.72) times as likely to have breast, 7.23 (95% CI, 2.74 to 19.14) times as likely to have bilateral/multiple primary breast, and 7.56 (95% CI, 1.97 to 23.98) times as likely to have uterine/endometrial cancer. PROMs were not significantly more likely than WT to have cancer (all 0.84 < odds ratio < 1.15; P > .05). Conclusion PTEN promoter variants were not associated with cancer. These results do not support the inclusion of PTEN promoter sequencing in MGPT. [ABSTRACT FROM AUTHOR]

Purpose: PTEN mutations are associated with breast, colon, endometrial, kidney, and thyroid cancers. Most PTEN promoter alterations, however, are characterized as variants of unknown significance, and their contribution to cancer risk is unclear. Materials and Methods: Personal and family histories of 88,333 patients undergoing PTEN analysis as part of multigene panel testing (MGPT) were retrospectively reviewed. Cases (n = 59,784) were individuals with personal history of PTEN -related cancer. Controls (n = 28,549) had no personal history of cancer. Individuals were categorized as positive for one or more mutations (PATHO), without mutations but carrying one or more promoter variant (PROM), or negative for alterations (WT). Multivariable logistic regression was used to assess PTEN associations with phenotypes, adjusted for race/ethnicity, age, sex, and MGPT. Results: Overall, 79 (0.09%) patients were PATHO and 791 (0.9%) were PROM carriers. Compared with WT, PATHOs were 2.30 (95% CI, 1.19 to 4.72) times as likely to have breast, 7.23 (95% CI, 2.74 to 19.14) times as likely to have bilateral/multiple primary breast, and 7.56 (95% CI, 1.97 to 23.98) times as likely to have uterine/endometrial cancer. PROMs were not significantly more likely than WT to have cancer (all 0.84 < odds ratio < 1.15; P >.05). Conclusion: PTEN promoter variants were not associated with cancer. These results do not support the inclusion of PTEN promoter sequencing in MGPT. [ABSTRACT FROM AUTHOR]

Clinical interpretation of missense variants is challenging because the majority identified by genetic testing are rare and their functional effects are unknown. Consequently, most variants are of uncertain significance and cannot be used for clinical diagnosis or management. Although not much can be done to ameliorate variant rarity, multiplexed assays of variant effect (MAVEs), where thousands of single-nucleotide variant effects are simultaneously measured experimentally, provide functional evidence that can help resolve variants of unknown significance (VUSs). However, a rigorous assessment of the clinical value of multiplexed functional data for variant interpretation is lacking. Thus, we systematically combined previously published BRCA1 , TP53 , and PTEN multiplexed functional data with phenotype and family history data for 324 VUSs identified by a single diagnostic testing laboratory. We curated 49,281 variant functional scores from MAVEs for these three genes and integrated four different TP53 multiplexed functional datasets into a single functional prediction for each variant by using machine learning. We then determined the strength of evidence provided by each multiplexed functional dataset and reevaluated 324 VUSs. Multiplexed functional data were effective in driving variant reclassification when combined with clinical data, eliminating 49% of VUSs for BRCA1 , 69% for TP53 , and 15% for PTEN. Thus, multiplexed functional data, which are being generated for numerous genes, are poised to have a major impact on clinical variant interpretation. [ABSTRACT FROM AUTHOR]

To evaluate the racial and ethnic differences in prevalence of germline pathogenic variants (PVs) and the effect of race and ethnicity on breast cancer (BC) risk among carriers, results of multigene testing of 77 900 women with BC (non-Hispanic White [NHW] = 57 003; Ashkenazi-Jewish = 4798; Black = 6722; Hispanic = 5194; and Asian = 4183) were analyzed, and the frequency of PVs in each gene were compared between BC patients (cases) and race- and ethnicity-matched gnomAD reference controls. Compared with NHWs, BRCA1 PVs were enriched in Ashkenazi-Jews and Hispanics, whereas CHEK2 PVs were statistically significantly lower in Blacks, Hispanics, and Asians (all 2-sided P < .05). In case-control studies, BARD1 PVs were associated with high risks (odds ratio > 4.00) of BC in Blacks, Hispanics, and Asians; ATM PVs were associated with increased risk of BC among all races and ethnicities except Asians, whereas CHEK2 and BRIP1 PVs were associated with increased risk of BC among NHWs and Hispanics only. These findings suggest a need for personalized management of BC risk in PV carriers based on race and ethnicity. [ABSTRACT FROM AUTHOR]

Determination of the clinical relevance of rare germline variants of uncertain significance (VUSs) in the BRCA2 cancer predisposition gene remains a challenge as a result of limited availability of data for use in classification models. However, laboratory-based functional data derived from validated functional assays of known sensitivity and specificity may influence the interpretation of VUSs. We evaluated 252 missense VUSs from the BRCA2 DNA-binding domain by using a homology-directed DNA repair (HDR) assay and identified 90 as non-functional and 162 as functional. The functional assay results were integrated with other available data sources into an ACMG/AMP rules-based classification framework used by a hereditary cancer testing laboratory. Of the 186 missense variants observed by the testing laboratory, 154 were classified as VUSs without functional data. However, after applying protein functional data, 86% (132/154) of the VUSs were reclassified as either likely pathogenic/pathogenic (39/132) or likely benign/benign (93/132), which impacted testing results for 1,900 individuals. These results indicate that validated functional assay data can have a substantial impact on VUS classification and associated clinical management for many individuals with inherited alterations in BRCA2. [ABSTRACT FROM AUTHOR]

Background: The germline cancer predisposition genes associated with increased risk of each clinical subtype of breast cancer, defined by estrogen receptor (ER), progesterone receptor (PR), and HER2, are not well defined.Methods: A total of 54 555 invasive breast cancer patients with 56 480 breast tumors were subjected to clinical hereditary cancer multigene panel testing. Heterogeneity for predisposition genes across clinical breast cancer subtypes was assessed by comparing mutation frequencies by gene among tumor subtypes and by association studies between each tumor subtype and reference controls.Results: Mutations in 15 cancer predisposition genes were detected in 8.6% of patients with ER+/HER2-; 8.9% with ER+/HER2+; 7.7% with ER-/HER2+; and 14.4% of ER-/PR-/HER2- tumors. BRCA1, BRCA2, BARD1, and PALB2 mutations were enriched in ER- and HER2- tumors; RAD51C and RAD51D mutations were enriched in ER- tumors only; TP53 mutations were enriched in HER2+ tumors, and ATM and CHEK2 mutations were enriched in both ER+ and/or HER2+ tumors. All genes were associated with moderate (odds ratio > 2.00) or strong (odds ratio > 5.00) risks of at least one subtype of breast cancer in case-control analyses. Mutations in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53 had predicted lifetime absolute risks of at least 20.0% for breast cancer.Conclusions: Germline mutations in hereditary cancer panel genes confer subtype-specific risks of breast cancer. Combined tumor subtype, age at breast cancer diagnosis, and family history of breast and/or ovarian cancer information provides refined categorical estimates of mutation prevalence for women considering genetic testing. [ABSTRACT FROM AUTHOR]

Computational algorithms are often used to assess pathogenicity of Variants of Uncertain Significance (VUS) that are found in disease-associated genes. Most computational methods include analysis of protein multiple sequence alignments (PMSA), assessing interspecies variation. Careful validation of PMSA-based methods has been done for relatively few genes, partially because creation of curated PMSAs is labor-intensive. We assessed how PMSA-based computational tools predict the effects of the missense changes in the APC gene, in which pathogenic variants cause Familial Adenomatous Polyposis. Most Pathogenic or Likely Pathogenic APC variants are protein-truncating changes. However, public databases now contain thousands of variants reported as missense. We created a curated APC PMSA that contained >3 substitutions/site, which is large enough for statistically robust in silico analysis. The creation of the PMSA was not easily automated, requiring significant querying and computational analysis of protein and genome sequences. Of 1924 missense APC variants in the NCBI ClinVar database, 1800 (93.5%) are reported as VUS. All but two missense variants listed as P/LP occur at canonical splice or Exonic Splice Enhancer sites. Pathogenicity predictions by five computational tools (Align-GVGD, SIFT, PolyPhen2, MAPP, REVEL) differed widely in their predictions of Pathogenic/Likely Pathogenic (range 17.5–75.0%) and Benign/Likely Benign (range 25.0–82.5%) for APC missense variants in ClinVar. When applied to 21 missense variants reported in ClinVar and securely classified as Benign, the five methods ranged in accuracy from 76.2–100%. Computational PMSA-based methods can be an excellent classifier for variants of some hereditary cancer genes. However, there may be characteristics of the APC gene and protein that confound the results of in silico algorithms. A systematic study of these features could greatly improve the automation of alignment-based techniques and the use of predictive algorithms in hereditary cancer genes. [ABSTRACT FROM AUTHOR]

There is a growing need to develop variant prediction tools capable of assessing a wide spectrum of evidence. We present a Bayesian framework that involves aggregating pathogenicity data across multiple in silico scores on a gene-by-gene basis and multiple evidence statistics in both quantitative and qualitative forms, and performs 5-tiered variant classification based on the resulting probability credible interval. When evaluated in 1,161 missense variants, our gene-specific in silico model-based meta-predictor yielded an area under the curve (AUC) of 96.0% and outperformed all other in silico predictors. Multifactorial model analysis incorporating all available evidence yielded 99.7% AUC, with 22.8% predicted as variants of uncertain significance (VUS). Use of only 3 auto-computed evidence statistics yielded 98.6% AUC with 56.0% predicted as VUS, which represented sufficient accuracy to rapidly assign a significant portion of VUS to clinically meaningful classifications. Collectively, our findings support the use of this framework to conduct large-scale variant prioritization using in silico predictors followed by variant prediction and classification with a high degree of predictive accuracy. [ABSTRACT FROM AUTHOR]

Purpose: The relevance of inherited pathogenic mutations in cancer predisposition genes in pancreatic cancer is not well understood. We aimed to assess the characteristics of patients with pancreatic cancer referred for hereditary cancer genetic testing and to estimate the risk of pancreatic cancer associated with mutations in panel-based cancer predisposition genes in this high-risk population. Methods: Patients with pancreatic cancer (N = 1,652) were identified from a 140,000-patient cohort undergoing multigene panel testing of predisposition genes between March 2012 and June 2016. Gene-level mutation frequencies relative to Exome Aggregation Consortium and Genome Aggregation Database reference controls were assessed. Results: The frequency of germline cancer predisposition gene mutations among patients with pancreatic cancer was 20.73%. Mutations in ATM , BRCA2 , CDKN2A , MSH2 , MSH6 , PALB2 , and TP53 were associated with high pancreatic cancer risk (odds ratio, > 5), and mutations in BRCA1 were associated with moderate risk (odds ratio, > 2). In a logistic regression model adjusted for age at diagnosis and family history of cancer, ATM and BRCA2 mutations were associated with personal history of breast or pancreatic cancer, whereas PALB2 mutations were associated with family history of breast or pancreatic cancer. Conclusion: These findings provide insight into the spectrum of mutations expected in patients with pancreatic cancer referred for cancer predisposition testing. Mutations in eight genes confer high or moderate risk of pancreatic cancer and may prove useful for risk assessment for pancreatic and other cancers. Family and personal histories of breast cancer are strong predictors of germline mutations. [ABSTRACT FROM AUTHOR]