Abstract
PURPOSE: Variants of uncertain significance (VUS) are considered one of the most significant impediments to the translation of genetic test results into precise clinical recommendations. The 2015 American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) classification guidelines established a general framework for the assessment and classification of genetic variants; yet, gene-specific specifications are needed to enable better variant classification to reduce the number of VUS. The process of gene-specific adaptations of the ACMG/AMP codes is led and accompanied by ClinGen and implemented by Variant Curation Expert Panels (VCEP). The Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) VCEP recently published its specifications for the BRCA1 (HGNC:1100) and BRCA2 (HGNC:1101) genes. We investigated the differences in reclassification between the ENIGMA specifications and the standard ACMG/AMP classification system in a clinical setting. METHODS: We reclassified 121 VUS identified in these genes with the latest annotation data using the standard ACMG/AMP classification system and recommendations from the Sequence Variant Interpretation and the ENIGMA specifications. To simplify the reevaluation process, we have created a University of California Santa Cruz Genome Browser track hub that displays the exact data points required for variant classification using the ENIGMA VCEP specifications at the exon and variant level (https://genome.ucsc.edu/s/abenet/BRCA.ENIGMA.hg19). RESULTS: By comparing the codes used and their different weighting in the 2 approaches, we were able to demonstrate the superiority of the application of ENIGMA VCEP specifications, which resulted in a dramatic reduction of VUS (83.5% ENIGMA VCEP vs 20% ACMG/AMP + Sequence Variant Interpretation). CONCLUSION: For the diagnostic analysis of the BRCA1 and BRCA2 genes, the use of the ENIGMA VCEP specifications gives the best possible result in the clinical translation of genetic variants. The University of California Santa Cruz Genome Browser BRCA1/BRCA2 ENIGMA track set significantly simplified the interpretation process.