Challenges and approaches to calibrating patient phenotype as evidence for cancer gene variant classification under ACMG/AMP guidelines.

Cristina Fortuno¹, Kyriaki Michailidou², Michael Parsons¹, Jill S Dolinsky³, Tina Pesaran³, Amal Yussuf³, Jessica L Mester⁴, Kathleen S Hruska⁴, Susan Hiraki⁴, Robert O'Connor⁵, Raymond C Chan⁵, Serra Kim⁵, Sean V Tavtigian⁶, David Goldgar⁶, Paul A James^7,8, Amanda B Spurdle^1,9

¹Population Health Program, QIMR Berghofer Medical Research Institute, Herston, QLD 4006, Australia.

²Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus.

³Ambry Genetics, Aliso Viejo, CA 92656, United States.

⁴GeneDx, Gaithersburg, MD 20877, United States.

⁵Color Genomics, Inc., Burlingame, CA 94010, United States.

⁶Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, United States.

⁷Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre and Royal Melbourne Hospital, Melbourne, VIC 3052, Australia.

⁸Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC 3010, Australia.

⁹Faculty of Medicine, The University of Queensland, Herston, QLD 4006, Australia.

PubMed PMC DOI PDF

Abstract

Since first publication of the American College of Medical Genetics and Genomics/Association for Medical Pathology (ACMG/AMP) variant classification guidelines, additional recommendations for application of certain criteria have been released (https://clinicalgenome.org/docs/), to improve their application in the diagnostic setting. However, none have addressed use of the PS4 and PP4 criteria, cap…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free Account Sign In

Want unlimited research access? See Pro plans

Mentioned Companies

NIH Funding

Grant #11266199
Upgrading rigor and efficiency of germline cancer gene variant classification for the 2020s
UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
$521,002 (FY2026)

Other Funding

NCI NIH HHS(R01 CA264971)
United States
NIH HHS(R01 CA264971)
United States

MeSH Terms

Humans0Genetic Variation*Genetic Testing0Genome, Human0Phenotype0Genes, Neoplasm0Neoplasms*

Keywords

ACMG PS4cancer genegermline variant classificationlogistic regressionproband counting

Article Info

PMID: 38271184
PMCID: PMC11000651
DOI: 10.1093/hmg/ddae009
Received: November 13, 2023
Accepted: January 10, 2024

How to Cite

Fortuno C et al. Challenges and approaches to calibrating patient phenotype as evidence for cancer gene variant classification under ACMG/AMP guidelines. Hum Mol Genet2024;33(8):724-732. doi:10.1093/hmg/ddae009

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.