Lee K, Seifert BA, Shimelis H, Ghosh R, Crowley SB, Carter NJ, Doonanco K, Foreman AK, Ritter DI, Jimenez S, Trapp M, Offit K, Plon SE, Couch FJ. Clinical validity assessment of genes frequently tested on hereditary breast and ovarian cancer susceptibility sequencing panels.
Genet Med 2019;
21:1497-1506. [PMID:
30504931 PMCID:
PMC6579711 DOI:
10.1038/s41436-018-0361-5]
[Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Accepted: 11/01/2018] [Indexed: 12/13/2022] Open
Abstract
PURPOSE
Several genes on hereditary breast and ovarian cancer susceptibility test panels have not been systematically examined for strength of association with disease. We employed the Clinical Genome Resource (ClinGen) clinical validity framework to assess the strength of evidence between selected genes and breast or ovarian cancer.
METHODS
Thirty-one genes offered on cancer panel testing were selected for evaluation. The strength of gene-disease relationship was systematically evaluated and a clinical validity classification of either Definitive, Strong, Moderate, Limited, Refuted, Disputed, or No Reported Evidence was assigned.
RESULTS
Definitive clinical validity classifications were made for 10/31 and 10/32 gene-disease pairs for breast and ovarian cancer respectively. Two genes had a Moderate classification whereas, 6/31 and 6/32 genes had Limited classifications for breast and ovarian cancer respectively. Contradictory evidence resulted in Disputed or Refuted assertions for 9/31 genes for breast and 4/32 genes for ovarian cancer. No Reported Evidence of disease association was asserted for 5/31 genes for breast and 11/32 for ovarian cancer.
CONCLUSION
Evaluation of gene-disease association using the ClinGen clinical validity framework revealed a wide range of classifications. This information should aid laboratories in tailoring appropriate gene panels and assist health-care providers in interpreting results from panel testing.
Collapse