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

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 S...

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Main Authors: 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
Format: Article
Language:English
Published: BMC 2018-12-01
Series:Genome Medicine
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13073-018-0607-5
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language English
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author 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
spellingShingle 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
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
Genome Medicine
ACMG secondary findings
Familial cancer exome
Population study
Variant classification
author_facet 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
author_sort Jung Kim
title 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
title_short 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_sort 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
publisher BMC
series Genome Medicine
issn 1756-994X
publishDate 2018-12-01
description 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.
topic ACMG secondary findings
Familial cancer exome
Population study
Variant classification
url http://link.springer.com/article/10.1186/s13073-018-0607-5
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spelling doaj-f8d664b0a6b34bb18931cda5ffb1397c2020-11-25T00:45:35ZengBMCGenome Medicine1756-994X2018-12-011011910.1186/s13073-018-0607-5Prevalence 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 controlsJung Kim0Wen Luo1Mingyi Wang2Talia Wegman-Ostrosky3Megan N. Frone4Jennifer J. Johnston5Michael L. Nickerson6Melissa Rotunno7Shengchao A. Li8Maria I. Achatz9Seth A. Brodie10Michael Dean11Kelvin C. de Andrade12Fernanda P. Fortes13Matthew Gianferante14Payal Khincha15Mary L. McMaster16Lisa J. McReynolds17Alexander Pemov18Maisa Pinheiro19Karina M. Santiago20Blanche P. Alter21Neil E. Caporaso22Shahinaz M. Gadalla23Lynn R. Goldin24Mark H. Greene25Jennifer Loud26Xiaohong R. Yang27Neal D. Freedman28Susan M. Gapstur29Mia M. Gaudet30Donato Calista31Paola Ghiorzo32Maria Concetta Fargnoli33Eduardo Nagore34Ketty Peris35Susana Puig36Maria Teresa Landi37Belynda Hicks38Bin Zhu39Jia Liu40Joshua N. Sampson41Stephen J. Chanock42Lisa J. Mirabello43Lindsay M. Morton44Leslie G. Biesecker45Margaret A. Tucker46Sharon A. Savage47Alisa M. Goldstein48Douglas R. Stewart49Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHCancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIHLaboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHEpidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIHCancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHCancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHIntegrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHIntegrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHMetabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHBehavioral and Epidemiology Research Group, American Cancer SocietyBehavioral and Epidemiology Research Group, American Cancer SocietyDepartment of Dermatology, Maurizio Bufalini HospitalDepartment of Internal Medicine and Medical Specialties, University of Genoa and Genetics of Rare Cancers, IRCCS Ospedale Policinico San MartinoDepartment of Dermatology, University of L’AquilaDepartment of Dermatology, Instituto Valenciano de OncologiaInstitute of Dermatology, Catholic University - Fondazione Policlinico Universitario A. Gemelli, IRCCSDermatology Department, Melanoma Unit, Hospital Clinic de Barcelona, IDIBAPS, Universitat de Barcelona, Barcelona, Spain & Centro de Investigacion Biomedica en Red en Enfermedades Raras (CIBERER)Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHCancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Leidos Biomedical Research, Inc.Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHOffice of the Director, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIHDivision of Cancer Epidemiology and Genetics, Human Genetics Program National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHClinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHAbstract 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.http://link.springer.com/article/10.1186/s13073-018-0607-5ACMG secondary findingsFamilial cancer exomePopulation studyVariant classification