Genome Medicine (Dec 2018)
Prevalence of pathogenic/likely pathogenic variants in the 24 cancer genes of the ACMG Secondary Findings v2.0 list in a large cancer cohort and ethnicity-matched controls
- Jung Kim,
- Wen Luo,
- Mingyi Wang,
- Talia Wegman-Ostrosky,
- Megan N. Frone,
- Jennifer J. Johnston,
- Michael L. Nickerson,
- Melissa Rotunno,
- Shengchao A. Li,
- Maria I. Achatz,
- Seth A. Brodie,
- Michael Dean,
- Kelvin C. de Andrade,
- Fernanda P. Fortes,
- Matthew Gianferante,
- Payal Khincha,
- Mary L. McMaster,
- Lisa J. McReynolds,
- Alexander Pemov,
- Maisa Pinheiro,
- Karina M. Santiago,
- Blanche P. Alter,
- Neil E. Caporaso,
- Shahinaz M. Gadalla,
- Lynn R. Goldin,
- Mark H. Greene,
- Jennifer Loud,
- Xiaohong R. Yang,
- Neal D. Freedman,
- Susan M. Gapstur,
- Mia M. Gaudet,
- Donato Calista,
- Paola Ghiorzo,
- Maria Concetta Fargnoli,
- Eduardo Nagore,
- Ketty Peris,
- Susana Puig,
- Maria Teresa Landi,
- Belynda Hicks,
- Bin Zhu,
- Jia Liu,
- Joshua N. Sampson,
- Stephen J. Chanock,
- Lisa J. Mirabello,
- Lindsay M. Morton,
- Leslie G. Biesecker,
- Margaret A. Tucker,
- Sharon A. Savage,
- Alisa M. Goldstein,
- Douglas R. Stewart
Affiliations
- Jung Kim
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Wen Luo
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.
- Mingyi Wang
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.
- Talia Wegman-Ostrosky
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Megan N. Frone
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Jennifer J. Johnston
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH
- Michael L. Nickerson
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Melissa Rotunno
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH
- Shengchao A. Li
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.
- Maria I. Achatz
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Seth A. Brodie
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.
- Michael Dean
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Kelvin C. de Andrade
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Fernanda P. Fortes
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Matthew Gianferante
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Payal Khincha
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Mary L. McMaster
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Lisa J. McReynolds
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Alexander Pemov
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Maisa Pinheiro
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Karina M. Santiago
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Blanche P. Alter
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Neil E. Caporaso
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Shahinaz M. Gadalla
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Lynn R. Goldin
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Mark H. Greene
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Jennifer Loud
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Xiaohong R. Yang
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Neal D. Freedman
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Susan M. Gapstur
- Behavioral and Epidemiology Research Group, American Cancer Society
- Mia M. Gaudet
- Behavioral and Epidemiology Research Group, American Cancer Society
- Donato Calista
- Department of Dermatology, Maurizio Bufalini Hospital
- Paola Ghiorzo
- Department of Internal Medicine and Medical Specialties, University of Genoa and Genetics of Rare Cancers, IRCCS Ospedale Policinico San Martino
- Maria Concetta Fargnoli
- Department of Dermatology, University of L’Aquila
- Eduardo Nagore
- Department of Dermatology, Instituto Valenciano de Oncologia
- Ketty Peris
- Institute of Dermatology, Catholic University - Fondazione Policlinico Universitario A. Gemelli, IRCCS
- Susana Puig
- Dermatology Department, Melanoma Unit, Hospital Clinic de Barcelona, IDIBAPS, Universitat de Barcelona, Barcelona, Spain & Centro de Investigacion Biomedica en Red en Enfermedades Raras (CIBERER)
- Maria Teresa Landi
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Belynda Hicks
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.
- Bin Zhu
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.
- Jia Liu
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.
- Joshua N. Sampson
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Stephen J. Chanock
- Office of the Director, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Lisa J. Mirabello
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Lindsay M. Morton
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Leslie G. Biesecker
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH
- Margaret A. Tucker
- Division of Cancer Epidemiology and Genetics, Human Genetics Program National Cancer Institute, NIH
- Sharon A. Savage
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Alisa M. Goldstein
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- Douglas R. Stewart
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
- DOI
- https://doi.org/10.1186/s13073-018-0607-5
- Journal volume & issue
-
Vol. 10,
no. 1
pp. 1 – 9
Abstract
Abstract Background Prior research has established that the prevalence of pathogenic/likely pathogenic (P/LP) variants across all of the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes is approximately 0.8–5%. We investigated the prevalence of P/LP variants in the 24 ACMG SF v2.0 cancer genes in a family-based cancer research cohort (n = 1173) and in cancer-free ethnicity-matched controls (n = 982). Methods We used InterVar to classify variants and subsequently conducted a manual review to further examine variants of unknown significance (VUS). Results In the 24 genes on the ACMG SF v2.0 list associated with a cancer phenotype, we observed 8 P/LP unique variants (8 individuals; 0.8%) in controls and 11 P/LP unique variants (14 individuals; 1.2%) in cases, a non-significant difference. We reviewed 115 VUS. The median estimated per-variant review time required was 30 min; the first variant within a gene took significantly (p = 0.0009) longer to review (median = 60 min) compared with subsequent variants (median = 30 min). The concordance rate was 83.3% for the variants examined by two reviewers. Conclusion The 115 VUS required database and literature review, a time- and labor-intensive process hampered by the difficulty in interpreting conflicting P/LP determinations. By rigorously investigating the 24 ACMG SF v2.0 cancer genes, our work establishes a benchmark P/LP variant prevalence rate in a familial cancer cohort and controls.
Keywords