Evaluation of ACMG-Guideline-Based Variant Classification of Cancer Susceptibility and Non-Cancer-Associated Genes in Families Affected by Breast Cancer

Am J Hum Genet. 2016 May 5;98(5):801-817. doi: 10.1016/j.ajhg.2016.02.024.


Sequencing tests assaying panels of genes or whole exomes are widely available for cancer risk evaluation. However, methods for classification of variants resulting from this testing are not well studied. We evaluated the ability of a variant-classification methodology based on American College of Medical Genetics and Genomics (ACMG) guidelines to define the rate of mutations and variants of uncertain significance (VUS) in 180 medically relevant genes, including all ACMG-designated reportable cancer and non-cancer-associated genes, in individuals who met guidelines for hereditary cancer risk evaluation. We performed whole-exome sequencing in 404 individuals in 253 families and classified 1,640 variants. Potentially clinically actionable (likely pathogenic [LP] or pathogenic [P]) versus nonactionable (VUS, likely benign, or benign) calls were 95% concordant with locus-specific databases and Clinvar. LP or P mutations were identified in 12 of 25 breast cancer susceptibility genes in 26 families without identified BRCA1/2 mutations (11%). Evaluation of 84 additional genes associated with autosomal-dominant cancer susceptibility identified LP or P mutations in only two additional families (0.8%). However, individuals from 10 of 253 families (3.9%) had incidental LP or P mutations in 32 non-cancer-associated genes, and 9% of individuals were monoallelic carriers of a rare LP or P mutation in 39 genes associated with autosomal-recessive cancer susceptibility. Furthermore, 95% of individuals had at least one VUS. In summary, these data support the clinical utility of ACMG variant-classification guidelines. Additionally, evaluation of extended panels of cancer-associated genes in breast/ovarian cancer families leads to only an incremental clinical benefit but substantially increases the complexity of the results.

Publication types

  • Evaluation Study

MeSH terms

  • Adult
  • Aged
  • Biomarkers, Tumor / genetics
  • Breast Neoplasms / genetics*
  • Computational Biology / methods
  • Exome
  • Female
  • Genetic Predisposition to Disease*
  • Genetic Testing / standards*
  • Genetic Variation
  • Genomics / standards*
  • Guidelines as Topic*
  • High-Throughput Nucleotide Sequencing / standards
  • Humans
  • Middle Aged
  • Mutation / genetics*
  • Sequence Analysis, DNA / standards*
  • Young Adult


  • Biomarkers, Tumor