학술논문

Breast Cancer Risk Genes — Association Analysis in More than 113,000 Women
Document Type
article
Author
Dorling, LeilaCarvalho, SaraAllen, JamieGonzález-Neira, AnnaLuccarini, CraigWahlström, CeciliaPooley, Karen AParsons, Michael TFortuno, CristinaWang, QinBolla, Manjeet KDennis, JoeKeeman, RenskeAlonso, M RosarioÁlvarez, NuriaHerraez, BelenFernandez, VictoriaNúñez-Torres, RocioOsorio, AnaValcich, JeanetteLi, MinervaTörngren, ThereseHarrington, Patricia ABaynes, CarolineConroy, Don MDecker, BrennanFachal, LauraMavaddat, NasimAhearn, ThomasAittomäki, KristiinaAntonenkova, Natalia NArnold, NorbertArveux, PatrickAusems, Margreet GEMAuvinen, PäiviBecher, HeikoBeckmann, Matthias WBehrens, SabineBermisheva, MarinaBiałkowska, KatarzynaBlomqvist, CarlBogdanova, Natalia VBogdanova-Markov, NadjaBojesen, Stig EBonanni, BernardoBørresen-Dale, Anne-LiseBrauch, HiltrudBremer, MichaelBriceno, IgnacioBrüning, ThomasBurwinkel, BarbaraCameron, David ACamp, Nicola JCampbell, ArchieCarracedo, AngelCastelao, Jose ECessna, Melissa HChanock, Stephen JChristiansen, HansCollée, J MargrietCordina-Duverger, EmilieCornelissen, StenCzene, KamilaDörk, ThiloEkici, Arif BEngel, ChristophEriksson, MikaelFasching, Peter AFigueroa, JonineFlyger, HenrikFörsti, AstaGabrielson, MarikeGago-Dominguez, ManuelaGeorgoulias, VassiliosGil, FabianGiles, Graham GGlendon, GordGarcia, Encarna B GómezAlnæs, Grethe I GrenakerGuénel, PascalHadjisavvas, AndreasHaeberle, LotharHahnen, EricHall, PerHamann, UteHarkness, Elaine FHartikainen, Jaana MHartman, MikaelHe, WeiHeemskerk-Gerritsen, Bernadette AMHillemanns, PeterHogervorst, Frans BLHollestelle, AntoinetteHo, Weang KeeHooning, Maartje JHowell, AnthonyHumphreys, KeithIdris, FaizaJakubowska, AnnaJung, Audrey
Source
New England Journal of Medicine. 384(5)
Subject
Breast Cancer
Cancer
Genetics
Aetiology
2.1 Biological and endogenous factors
Adolescent
Adult
Age Factors
Aged
Aged
80 and over
Breast Neoplasms
Female
Genetic Predisposition to Disease
Genetic Variation
Humans
Logistic Models
Middle Aged
Mutation
Missense
Odds Ratio
Risk
Sequence Analysis
DNA
Young Adult
Breast Cancer Association Consortium
Medical and Health Sciences
General & Internal Medicine
Language
Abstract
BackgroundGenetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.MethodsWe used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.ResultsProtein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.ConclusionsThe results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).