IARC Unclassified Genetic Variants Working Group: Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results

Department of Pediatrics, Baylor Cancer Genetics Clinic, Baylor College of Medicine, Houston, Texas, USA.
Human Mutation (Impact Factor: 5.14). 11/2008; 29(11):1282-91. DOI: 10.1002/humu.20880
Source: PubMed


Genetic testing of cancer susceptibility genes is now widely applied in clinical practice to predict risk of developing cancer. In general, sequence-based testing of germline DNA is used to determine whether an individual carries a change that is clearly likely to disrupt normal gene function. Genetic testing may detect changes that are clearly pathogenic, clearly neutral, or variants of unclear clinical significance. Such variants present a considerable challenge to the diagnostic laboratory and the receiving clinician in terms of interpretation and clear presentation of the implications of the result to the patient. There does not appear to be a consistent approach to interpreting and reporting the clinical significance of variants either among genes or among laboratories. The potential for confusion among clinicians and patients is considerable and misinterpretation may lead to inappropriate clinical consequences. In this article we review the current state of sequence-based genetic testing, describe other standardized reporting systems used in oncology, and propose a standardized classification system for application to sequence-based results for cancer predisposition genes. We suggest a system of five classes of variants based on the degree of likelihood of pathogenicity. Each class is associated with specific recommendations for clinical management of at-risk relatives that will depend on the syndrome. We propose that panels of experts on each cancer predisposition syndrome facilitate the classification scheme and designate appropriate surveillance and cancer management guidelines. The international adoption of a standardized reporting system should improve the clinical utility of sequence-based genetic tests to predict cancer risk.

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Available from: Sharon E Plon, Oct 09, 2015
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    • "In their work, the authors benchmarked the reliability of in silico predictions comparing their results with experimental assays and demonstrating that bioinformatics tools can be used for pathogenicity prediction of uncertain variants. For each VUS, the posterior odds ratio (OR) for pathogenicity was calculated as detailed in Methods and a final classification following the rules suggested by Plon et al. [52] compiled. For the PHD family, 42 VUS were classified as pathogenic (Class 5; Table 1), 36 VUS as likely pathogenic (Class 4; Table 2) and 30 VUS remain uncertain (Class 3; Table 3 "
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    ABSTRACT: PHDs (proline hydroxylases) are a small protein family found in all organisms, considered the central regulator of the molecular hypoxia response due to PHDs being completely inactivated under low oxygen concentration. At physiological oxygen concentration, PHDs drive the degradation of the HIF-1α (hypoxia-inducible factor 1-α), which is responsible for upregulating the expression of genes involved in the cellular response to hypoxia. Hypoxia is a common feature of most tumors, in particular during metastasis development. Indeed, cancer reacts by activating pathways promoting new blood vessel formation and activating strategies aimed to improve survival. In this scenario, the PHD family regulates the activation of HIF-1α and cell-cycle regulation. Several PHD mutations were found in cancer patients, underlining their importance for human health. Here, we propose a Bayesian model able to predict the pathological effect of human PHD mutations and their correlation with cancer outcome. The model was developed through an integrative in silico approach, where data collected from the literature has been coupled with sequence evolution and structural analysis. The model was used to assess 135 human PHD variants. Finally, bioinformatics characterization was used to demonstrate how few amino acid changes are able to explain the functional specialization of PHD family members and their physiological role in human health. Copyright © 2015 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.
    Biochimie 07/2015; 116. DOI:10.1016/j.biochi.2015.07.009 · 2.96 Impact Factor
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    • "Relevant to this topic, the International Society for Gastrointestinal Hereditary Tumours (InSIGHT) has recently described the procedure undertaken to validate integrated methods for classifying mismatch repair gene variants in order to use them in a clinical context for Lynch syndrome (Thompson et al., 2013). The authors underlined the need of an international support to standardize also the development of databases in which the final VUS classification should be provided (Plon et al., 2008; Thompson et al., 2013). "
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    ABSTRACT: CDKN2A codes for two oncosuppressors by alternative splicing of two first exons: p16INK4a and p14ARF. Germline mutations are found in about 40% of melanoma-prone families, and most of them are missense mutations mainly affecting p16INK4a. A growing number of p16INK4a Variants of Uncertain Significance (VUS) are being identified but, unless their pathogenic role can be demonstrated, they cannot be used for identification of carriers at risk. Predicting the effect of these VUS by either a “standard” in silico approach, or functional tests alone, is rather difficult. Here we report a protocol for the assessment of any p16INK4a VUS, which combines experimental and computational tools in an integrated approach. We analyzed p16INK4a VUS from melanoma patients as well as variants derived through permutation of conserved p16INK4a amino acids. Variants were expressed in a p16INK4a-null cell line (U2-OS) and tested for their ability to block proliferation. In parallel, these VUS underwent in silico prediction analysis and molecular dynamics simulations. Evaluation of in silico and functional data disclosed a high agreement for 15/16 missense mutations, suggesting that this approach could represent a pilot study for the definition of a protocol applicable to VUS in general, involved in other diseases, as well.This article is protected by copyright. All rights reserved
    Human Mutation 07/2014; 35(7). DOI:10.1002/humu.22550 · 5.14 Impact Factor
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    • "Only determination of pathogenicity by a multifactorial likelihood model using independent data sources (e.g. segregation analysis, allele frequency, tumor pathology markers, co-occurrence, and co-observation with BRCA2 pathogenic variants) should be considered clinically [35], [36], [37]. "
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    ABSTRACT: Germline inactivating variants in BRCA1 lead to a significantly increased risk of breast and ovarian cancers in carriers. While the functional effect of many variants can be inferred from the DNA sequence, determining the effect of missense variants present a significant challenge. A series of biochemical and cell biological assays have been successfully used to explore the impact of these variants on the function of BRCA1, which contribute to assessing their likelihood of pathogenicity. It has been determined that variants that co-localize with structural or functional motifs are more likely to disrupt the stability and function of BRCA1. Here we assess the functional impact of 37 variants chosen to probe the functional impact of variants in phosphorylation sites and in the BRCT domains. In addition, we perform a meta-analysis of 170 unique variants tested by the transcription activation assays in the carboxy-terminal domain of BRCA1 using a recently developed computation model to provide assessment for functional impact and their likelihood of pathogenicity.
    PLoS ONE 05/2014; 9(5):e97766. DOI:10.1371/journal.pone.0097766 · 3.23 Impact Factor
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