Abstract
Missense variants represent a significant proportion of variants identified in clinical genetic testing. In the absence of strong clinical or functional evidence, the American College of Medical Genetics recommends that these findings be classified as variants of uncertain significance (VUS). VUSs may be reclassified to better inform patient care when new evidence is available. It is critical that the methods used for reclassification are robust in order to prevent inappropriate medical management strategies and unnecessary, life-altering surgeries. In an effort to provide evidence for classification, several in silico algorithms have been developed that attempt to predict the functional impact of missense variants through amino acid sequence conservation analysis. We report an analysis comparing internally derived, evidence-based classifications with the results obtained from six commonly used algorithms. We compiled a dataset of 1118 variants in BRCA1, BRCA2, MLH1, and MSH2 previously classified by our laboratory’s evidence-based variant classification program. We compared internally derived classifications with those obtained from the following in silico tools: Align-GVGD, CONDEL, Grantham Analysis, MAPP-MMR, PolyPhen-2, and SIFT. Despite being based on similar underlying principles, all algorithms displayed marked divergence in accuracy, specificity, and sensitivity. Overall, accuracy ranged from 58.7 to 90.8% while the Matthews Correlation Coefficient ranged from 0.26–0.65. CONDEL, a weighted average of multiple algorithms, did not perform significantly better than its individual components evaluated here. These results suggest that the in silico algorithms evaluated here do not provide reliable evidence regarding the clinical significance of missense variants in genes associated with hereditary cancer.
Highlights
Accurate variant classification is of significant importance to patient care
In order to provide a comprehensive evaluation of their clinical use, we evaluated the predictive functionality of several in silico tools in a large cohort of individuals who underwent clinical genetic testing
All missense variants identified in BRCA1, BRCA2, MLH1, and MSH2 by a commercial testing laboratory (Myriad Genetic Laboratories, Inc., Salt Lake City, UT) as of August 2013 were evaluated here
Summary
Clinically actionable variants have the potential to help guide medical management decisions. In such cases, these decisions are guided by the National Comprehensive Cancer Network (NCCN) guidelines (https://www.nccn.org/professionals/physician_gls/f_ guidelines.asp). Due to the high risk of developing breast and/or ovarian cancer women with pathogenic variants in BRCA1 and BRCA2 are recommended to receive increased screening, chemoprevention, and prophylactic surgeries (Daly et al 2016). Individuals with pathogenic variants in MLH1 and MSH2 are recommended to receive more frequent colonoscopies starting at an earlier age due to the risk of developing colorectal cancer (Provenzale et al 2016). Given the importance of accurate clinical variant classification, the American College of Medical Genetics (ACMG) have published guidelines for the interpretation of sequence variants that often require multiple lines of evidence (Richards et al 2015).
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