TP53 variants of uncertain significance: increasing challenges in variant interpretation and genetic counseling

2019 ◽  
Vol 18 (4) ◽  
pp. 451-456
Author(s):  
Camila Matzenbacher Bittar ◽  
Igor Araujo Vieira ◽  
Cristina Silva Sabato ◽  
Tiago Finger Andreis ◽  
Bárbara Alemar ◽  
...  
2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Hannah Gelman ◽  
◽  
Jennifer N. Dines ◽  
Jonathan Berg ◽  
Alice H. Berger ◽  
...  

AbstractVariants of uncertain significance represent a massive challenge to medical genetics. Multiplexed functional assays, in which the functional effects of thousands of genomic variants are assessed simultaneously, are increasingly generating data that can be used as additional evidence for or against variant pathogenicity. Such assays have the potential to resolve variants of uncertain significance, thereby increasing the clinical utility of genomic testing. Existing standards from the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) and new guidelines from the Clinical Genome Resource (ClinGen) establish the role of functional data in variant interpretation, but do not address the specific challenges or advantages of using functional data derived from multiplexed assays. Here, we build on these existing guidelines to provide recommendations to experimentalists for the production and reporting of multiplexed functional data and to clinicians for the evaluation and use of such data. By following these recommendations, experimentalists can produce transparent, complete, and well-validated datasets that are primed for clinical uptake. Our recommendations to clinicians and diagnostic labs on how to evaluate the quality of multiplexed functional datasets, and how different datasets could be incorporated into the ACMG/AMP variant-interpretation framework, will hopefully clarify whether and how such data should be used. The recommendations that we provide are designed to enhance the quality and utility of multiplexed functional data, and to promote their judicious use.


2021 ◽  
Author(s):  
Kathryn McCormick ◽  
Trisha Brock ◽  
Matthew Wood ◽  
Lan Guo ◽  
Kolt McBride ◽  
...  

Purpose: Functional evidence is a pillar of variant interpretation according to ACMG guidelines. Functional evidence can be obtained in a variety of models and assay systems, including patient-derived tissues and iPSCs, in vitro cellular assays, and in vivo assays. Here we evaluate the reliability and practicality of variant interpretation in the small animal model, C. elegans, through a series of experiments evaluating the function of syntaxin binding protein, STXBP1, a well-known causative gene for Early infantile epileptic encephalopathy 1 (EIEE1). Methods: Using CRISPR, we replaced the coding sequence for unc-18 with the coding sequence for the human ortholog STXBP1. Next, we used CRISPR to introduce precise point mutations in the human STXBP1 coding sequence, reflecting three clinical categories (benign, pathogenic, and variants of uncertain significance (VUS)). We quantified 26 features of the resulting worms movement to train Random Forest (RF) and Support Vector Machines (SVM) machine learning classifiers on known pathogenic and benign variants. We characterized the classifiers, and then used the behavioral data from the VUS-expressing animals to predict the categorization of the VUS. Results: Whereas knock-out worms without unc-18 are severely impaired in motor function, worms expressing STXBP1 in its place have restored motor function. We produced worms with STXBP1 variants previously classified by ACMG criteria, including 25 benign variants, 32 pathogenic, and 24 variants of uncertain significance (VUS). Using either SVM or RF classifiers, we were able to obtain a sensitivity of 0.84-0.97 on known benign and pathogenic strains. By comparing multiple ML classification methods, we were able to classify 9 of the VUS as functionally abnormal, suggesting that these VUS are likely to be pathogenic. Conclusions: We demonstrate that automated analysis of a small animal system is an effective, scalable, and fast way to understand functional consequences of variants in STXBP1, one of the most common causes of genetic epilepsies and neurodevelopmental disorders. Keywords: STXBP1, C. elegans, CRISPR, Unc-18


2019 ◽  
Vol 49 ◽  
pp. S61-S71 ◽  
Author(s):  
Allison Werner-Lin ◽  
Judith L. M. Mccoyd ◽  
Barbara A. Bernhardt

2017 ◽  
Vol 26 (4) ◽  
pp. 866-877 ◽  
Author(s):  
Ilana Solomon ◽  
Elizabeth Harrington ◽  
Gillian Hooker ◽  
Lori Erby ◽  
Jennifer Axilbund ◽  
...  

Circulation ◽  
2018 ◽  
Vol 138 (24) ◽  
pp. 2852-2854 ◽  
Author(s):  
Wenjian Lv ◽  
Lyon Qiao ◽  
Nataliya Petrenko ◽  
Wenjun Li ◽  
Anjali T. Owens ◽  
...  

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260852
Author(s):  
Meryem Ozgencil ◽  
Julian Barwell ◽  
Marc Tischkowitz ◽  
Louise Izatt ◽  
Ian Kesterton ◽  
...  

Establishing a universally applicable protocol to assess the impact of BRCA1 variants of uncertain significance (VUS) expression is a problem which has yet to be resolved despite major progresses have been made. The numerous difficulties which must be overcome include the choices of cellular models and functional assays. We hypothesised that the use of induced pluripotent stem (iPS) cells might facilitate the standardisation of protocols for classification, and could better model the disease process. We generated eight iPS cell lines from patient samples expressing either BRCA1 pathogenic variants, non-pathogenic variants, or BRCA1 VUSs. The impact of these variants on DNA damage repair was examined using a ɣH2AX foci formation assay, a Homologous Repair (HR) reporter assay, and a chromosome abnormality assay. Finally, all lines were tested for their ability to differentiate into mammary lineages in vitro. While the results obtained from the two BRCA1 pathogenic variants were consistent with published data, some other variants exhibited differences. The most striking of these was the BRCA1 variant Y856H (classified as benign), which was unexpectedly found to present a faulty HR repair pathway, a finding linked to the presence of an additional variant in the ATM gene. Finally, all lines were able to differentiate first into mammospheres, and then into more advanced mammary lineages expressing luminal- or basal-specific markers. This study stresses that BRCA1 genetic analysis alone is insufficient to establish a reliable and functional classification for assessment of clinical risk, and that it cannot be performed without considering the other genetic aberrations which may be present in patients. The study also provides promising opportunities for elucidating the physiopathology and clinical evolution of breast cancer, by using iPS cells.


Author(s):  
Andreea Catana ◽  
Adina Patricia Apostu ◽  
Razvan-Geo Antemie

Breast cancer is one of the most common malignancies and the leading cause of death among women worldwide. About 20% of breast cancers are hereditary. Approximately 30% of the mutations have remained negative after testing BRCA1/2 even in families with a Mendelian inheritance pattern for breast cancer. Additional non-BRCA genes have been identified as predisposing for breast cancer. Multi gene panel testing tries to cover and explain the BRCA negative inherited breast cancer, improving efficiency, speed and costs of the breast cancer screening. We identified 23 studies reporting results from individuals who have undergone multi gene panel testing for hereditary breast cancer and noticed a prevalence of 1-12% of non-BRCA genes, but also a high level of variants of uncertain significance. A result with a high level of variants of uncertain significance is likely to be more costly than bring benefits, as well as increase the anxiety for patients. Regarding further development of multi gene panel testing, more research is required to establish both the optimal care of patients with cancer (specific treatments like PARP inhibitors) and the management of unaffected individuals (chemoprevention and/or prophylactic surgeries). Early detection in these patients as well as prophylactic measures will significantly increase the chance of survival. Therefore, multi gene panel testing is not yet ready to be used outside clear guidelines. In conclusion, studies on additional cohorts will be needed to better define the real prevalence, penetrance and the variants of these genes, as well as to describe clear evidence-based guidelines for these patients. 


2021 ◽  
Author(s):  
Mayumi Kamada ◽  
Atsuko Takagi ◽  
Ryosuke Kojima ◽  
Yoshihisa Tanaka ◽  
Masahiko Nakatsui ◽  
...  

While the number of genome sequences continues to increase, the functions of many detected gene variants remain to be identified. These variants of uncertain significance constitute a major barrier to precision medicine. Although many computational methods have been developed to predict the function of these variants, they all rely on individual gene features and do not consider complex molecular relationships. Here we develop PathoGN, a molecular network-based approach for predicting variant pathogenicity. PathoGN significantly outperforms existing methods using benchmark datasets. Moreover, PathoGN successfully predicts the pathogenicity of 3,994 variants of uncertain significance in the real-world database ClinVar and designates potential pathogenicity. This is the first computational method for the clinical interpretation of variants using biomolecular networks, and we anticipate our method to be broadly useful for the clinical interpretation of variants and for assigning biological function to unknown variants at the genomic scale.


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