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Li S, Silvestri V, Leslie G, Rebbeck TR, Neuhausen SL, Hopper JL, Nielsen HR, Lee A, Yang X, McGuffog L, Parsons MT, Andrulis IL, Arnold N, Belotti M, Borg Å, Buecher B, Buys SS, Caputo SM, Chung WK, Colas C, Colonna SV, Cook J, Daly MB, de la Hoya M, de Pauw A, Delhomelle H, Eason J, Engel C, Evans DG, Faust U, Fehm TN, Fostira F, Fountzilas G, Frone M, Garcia-Barberan V, Garre P, Gauthier-Villars M, Gehrig A, Glendon G, Goldgar DE, Golmard L, Greene MH, Hahnen E, Hamann U, Hanson H, Hassan T, Hentschel J, Horvath J, Izatt L, Janavicius R, Jiao Y, John EM, Karlan BY, Kim SW, Konstantopoulou I, Kwong A, Laugé A, Lee JW, Lesueur F, Mebirouk N, Meindl A, Mouret-Fourme E, Musgrave H, Ngeow Yuen Yie J, Niederacher D, Park SK, Pedersen IS, Ramser J, Ramus SJ, Rantala J, Rashid MU, Reichl F, Ritter J, Rump A, Santamariña M, Saule C, Schmidt G, Schmutzler RK, Senter L, Shariff S, Singer CF, Southey MC, Stoppa-Lyonnet D, Sutter C, Tan Y, Teo SH, Terry MB, Thomassen M, Tischkowitz M, Toland AE, Torres D, Vega A, Wagner SA, Wang-Gohrke S, Wappenschmidt B, Weber BHF, Yannoukakos D, Spurdle AB, Easton DF, Chenevix-Trench G, Ottini L, Antoniou AC. Cancer Risks Associated With BRCA1 and BRCA2 Pathogenic Variants. J Clin Oncol 2022; 40:1529-1541. [PMID: 35077220 PMCID: PMC9084432 DOI: 10.1200/jco.21.02112] [Citation(s) in RCA: 79] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 10/19/2021] [Accepted: 12/20/2021] [Indexed: 12/24/2022] Open
Abstract
PURPOSE To provide precise age-specific risk estimates of cancers other than female breast and ovarian cancers associated with pathogenic variants (PVs) in BRCA1 and BRCA2 for effective cancer risk management. METHODS We used data from 3,184 BRCA1 and 2,157 BRCA2 families in the Consortium of Investigators of Modifiers of BRCA1/2 to estimate age-specific relative (RR) and absolute risks for 22 first primary cancer types adjusting for family ascertainment. RESULTS BRCA1 PVs were associated with risks of male breast (RR = 4.30; 95% CI, 1.09 to 16.96), pancreatic (RR = 2.36; 95% CI, 1.51 to 3.68), and stomach (RR = 2.17; 95% CI, 1.25 to 3.77) cancers. Associations with colorectal and gallbladder cancers were also suggested. BRCA2 PVs were associated with risks of male breast (RR = 44.0; 95% CI, 21.3 to 90.9), stomach (RR = 3.69; 95% CI, 2.40 to 5.67), pancreatic (RR = 3.34; 95% CI, 2.21 to 5.06), and prostate (RR = 2.22; 95% CI, 1.63 to 3.03) cancers. The stomach cancer RR was higher for females than males (6.89 v 2.76; P = .04). The absolute risks to age 80 years ranged from 0.4% for male breast cancer to approximately 2.5% for pancreatic cancer for BRCA1 carriers and from approximately 2.5% for pancreatic cancer to 27% for prostate cancer for BRCA2 carriers. CONCLUSION In addition to female breast and ovarian cancers, BRCA1 and BRCA2 PVs are associated with increased risks of male breast, pancreatic, stomach, and prostate (only BRCA2 PVs) cancers, but not with the risks of other previously suggested cancers. The estimated age-specific risks will refine cancer risk management in men and women with BRCA1/2 PVs.
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Steinberg J, Iles MM, Lee JY, Wang X, Law MH, Smit AK, Nguyen‐Dumont T, Giles GG, Southey MC, Milne RL, Mann GJ, Bishop DT, MacInnis RJ, Cust AE. Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts. Br J Dermatol 2022; 186:823-834. [PMID: 34921685 PMCID: PMC9545863 DOI: 10.1111/bjd.20956] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 11/11/2021] [Accepted: 12/11/2021] [Indexed: 12/05/2022]
Abstract
BACKGROUND Previous studies suggest that polygenic risk scores (PRSs) may improve melanoma risk stratification. However, there has been limited independent validation of PRS-based risk prediction, particularly assessment of calibration (comparing predicted to observed risks). OBJECTIVES To evaluate PRS-based melanoma risk prediction in prospective UK and Australian cohorts with European ancestry. METHODS We analysed invasive melanoma incidence in the UK Biobank (UKB; n = 395 647, 1651 cases) and a case-cohort nested within the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4765, 303 cases). Three PRSs were evaluated: 68 single-nucleotide polymorphisms (SNPs) at 54 loci from a 2020 meta-analysis (PRS68), 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50) and 45 SNPs at 21 loci known in 2018 (PRS45). Ten-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment. RESULTS Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in the UKB [ratio of expected/observed cases: E/O = 0·65, 95% confidence interval (CI) 0·62-0·68] and MCCS (E/O = 0·63, 95% CI 0·56-0·72). For UKB, calibration was improved by PRS adjustment, with PRS50-adjusted risks E/O = 0·91, 95% CI 0·87-0·95. The discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (Δ area under the curve 0·07-0·10, P < 0·0001), and higher than for PRS45-adjusted risks (Δ area under the curve 0·02-0·04, P < 0·001). CONCLUSIONS A PRS derived from a larger, more diverse meta-analysis improves risk prediction compared with an earlier PRS, and might help tailor melanoma prevention and early detection strategies to different risk levels. Recalibration of absolute risks may be necessary for application to specific populations.
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Dareng EO, Tyrer JP, Barnes DR, Jones MR, Yang X, Aben KKH, Adank MA, Agata S, Andrulis IL, Anton-Culver H, Antonenkova NN, Aravantinos G, Arun BK, Augustinsson A, Balmaña J, Bandera EV, Barkardottir RB, Barrowdale D, Beckmann MW, Beeghly-Fadiel A, Benitez J, Bermisheva M, Bernardini MQ, Bjorge L, Black A, Bogdanova NV, Bonanni B, Borg A, Brenton JD, Budzilowska A, Butzow R, Buys SS, Cai H, Caligo MA, Campbell I, Cannioto R, Cassingham H, Chang-Claude J, Chanock SJ, Chen K, Chiew YE, Chung WK, Claes KBM, Colonna S, Cook LS, Couch FJ, Daly MB, Dao F, Davies E, de la Hoya M, de Putter R, Dennis J, DePersia A, Devilee P, Diez O, Ding YC, Doherty JA, Domchek SM, Dörk T, du Bois A, Dürst M, Eccles DM, Eliassen HA, Engel C, Evans GD, Fasching PA, Flanagan JM, Fortner RT, Machackova E, Friedman E, Ganz PA, Garber J, Gensini F, Giles GG, Glendon G, Godwin AK, Goodman MT, Greene MH, Gronwald J, Hahnen E, Haiman CA, Håkansson N, Hamann U, Hansen TVO, Harris HR, Hartman M, Heitz F, Hildebrandt MAT, Høgdall E, Høgdall CK, Hopper JL, Huang RY, Huff C, Hulick PJ, Huntsman DG, Imyanitov EN, Isaacs C, Jakubowska A, James PA, Janavicius R, Jensen A, Johannsson OT, John EM, Jones ME, Kang D, Karlan BY, Karnezis A, Kelemen LE, Khusnutdinova E, Kiemeney LA, Kim BG, Kjaer SK, Komenaka I, Kupryjanczyk J, Kurian AW, Kwong A, Lambrechts D, Larson MC, Lazaro C, Le ND, Leslie G, Lester J, Lesueur F, Levine DA, Li L, Li J, Loud JT, Lu KH, Lubiński J, Mai PL, Manoukian S, Marks JR, Matsuno RK, Matsuo K, May T, McGuffog L, McLaughlin JR, McNeish IA, Mebirouk N, Menon U, Miller A, Milne RL, Minlikeeva A, Modugno F, Montagna M, Moysich KB, Munro E, Nathanson KL, Neuhausen SL, Nevanlinna H, Yie JNY, Nielsen HR, Nielsen FC, Nikitina-Zake L, Odunsi K, Offit K, Olah E, Olbrecht S, Olopade OI, Olson SH, Olsson H, Osorio A, Papi L, Park SK, Parsons MT, Pathak H, Pedersen IS, Peixoto A, Pejovic T, Perez-Segura P, Permuth JB, Peshkin B, Peterlongo P, Piskorz A, Prokofyeva D, Radice P, Rantala J, Riggan MJ, Risch HA, Rodriguez-Antona C, Ross E, Rossing MA, Runnebaum I, Sandler DP, Santamariña M, Soucy P, Schmutzler RK, Setiawan VW, Shan K, Sieh W, Simard J, Singer CF, Sokolenko AP, Song H, Southey MC, Steed H, Stoppa-Lyonnet D, Sutphen R, Swerdlow AJ, Tan YY, Teixeira MR, Teo SH, Terry KL, Terry MB, Thomassen M, Thompson PJ, Thomsen LCV, Thull DL, Tischkowitz M, Titus L, Toland AE, Torres D, Trabert B, Travis R, Tung N, Tworoger SS, Valen E, van Altena AM, van der Hout AH, Van Nieuwenhuysen E, van Rensburg EJ, Vega A, Edwards DV, Vierkant RA, Wang F, Wappenschmidt B, Webb PM, Weinberg CR, Weitzel JN, Wentzensen N, White E, Whittemore AS, Winham SJ, Wolk A, Woo YL, Wu AH, Yan L, Yannoukakos D, Zavaglia KM, Zheng W, Ziogas A, Zorn KK, Kleibl Z, Easton D, Lawrenson K, DeFazio A, Sellers TA, Ramus SJ, Pearce CL, Monteiro AN, Cunningham J, Goode EL, Schildkraut JM, Berchuck A, Chenevix-Trench G, Gayther SA, Antoniou AC, Pharoah PDP. Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk. Eur J Hum Genet 2022; 30:630-631. [PMID: 35314806 PMCID: PMC9090804 DOI: 10.1038/s41431-022-01085-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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Howe LJ, Nivard MG, Morris TT, Hansen AF, Rasheed H, Cho Y, Chittoor G, Ahlskog R, Lind PA, Palviainen T, van der Zee MD, Cheesman R, Mangino M, Wang Y, Li S, Klaric L, Ratliff SM, Bielak LF, Nygaard M, Giannelis A, Willoughby EA, Reynolds CA, Balbona JV, Andreassen OA, Ask H, Baras A, Bauer CR, Boomsma DI, Campbell A, Campbell H, Chen Z, Christofidou P, Corfield E, Dahm CC, Dokuru DR, Evans LM, de Geus EJC, Giddaluru S, Gordon SD, Harden KP, Hill WD, Hughes A, Kerr SM, Kim Y, Kweon H, Latvala A, Lawlor DA, Li L, Lin K, Magnus P, Magnusson PKE, Mallard TT, Martikainen P, Mills MC, Njølstad PR, Overton JD, Pedersen NL, Porteous DJ, Reid J, Silventoinen K, Southey MC, Stoltenberg C, Tucker-Drob EM, Wright MJ, Hewitt JK, Keller MC, Stallings MC, Lee JJ, Christensen K, Kardia SLR, Peyser PA, Smith JA, Wilson JF, Hopper JL, Hägg S, Spector TD, Pingault JB, Plomin R, Havdahl A, Bartels M, Martin NG, Oskarsson S, Justice AE, Millwood IY, Hveem K, Naess Ø, Willer CJ, Åsvold BO, Koellinger PD, Kaprio J, Medland SE, Walters RG, Benjamin DJ, Turley P, Evans DM, Davey Smith G, Hayward C, Brumpton B, Hemani G, Davies NM. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects. Nat Genet 2022; 54:581-592. [PMID: 35534559 PMCID: PMC9110300 DOI: 10.1038/s41588-022-01062-7] [Citation(s) in RCA: 111] [Impact Index Per Article: 55.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 03/25/2022] [Indexed: 02/01/2023]
Abstract
Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.
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Wang X, Kapoor PM, Auer PL, Dennis J, Dunning AM, Wang Q, Lush M, Michailidou K, Bolla MK, Aronson KJ, Murphy RA, Brooks-Wilson A, Lee DG, Cordina-Duverger E, Guénel P, Truong T, Mulot C, Teras LR, Patel AV, Dossus L, Kaaks R, Hoppe R, Lo WY, Brüning T, Hamann U, Czene K, Gabrielson M, Hall P, Eriksson M, Jung A, Becher H, Couch FJ, Larson NL, Olson JE, Ruddy KJ, Giles GG, MacInnis RJ, Southey MC, Le Marchand L, Wilkens LR, Haiman CA, Olsson H, Augustinsson A, Krüger U, Wagner P, Scott C, Winham SJ, Vachon CM, Perou CM, Olshan AF, Troester MA, Hunter DJ, Eliassen HA, Tamimi RM, Brantley K, Andrulis IL, Figueroa J, Chanock SJ, Ahearn TU, García-Closas M, Evans GD, Newman WG, van Veen EM, Howell A, Wolk A, Håkansson N, Anton-Culver H, Ziogas A, Jones ME, Orr N, Schoemaker MJ, Swerdlow AJ, Kitahara CM, Linet M, Prentice RL, Easton DF, Milne RL, Kraft P, Chang-Claude J, Lindström S. Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women. Sci Rep 2022; 12:6199. [PMID: 35418701 PMCID: PMC9007944 DOI: 10.1038/s41598-022-10121-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 03/11/2022] [Indexed: 02/02/2023] Open
Abstract
Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.
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Renault AL, Dowty JG, Steen JA, Li S, Winship IM, Giles GG, Hopper JL, Southey MC, Nguyen-Dumont T. Population-based estimates of age-specific cumulative risk of breast cancer for pathogenic variants in ATM. Breast Cancer Res 2022; 24:24. [PMID: 35365198 PMCID: PMC8973562 DOI: 10.1186/s13058-022-01518-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 03/07/2022] [Indexed: 11/25/2022] Open
Abstract
Background Multigene panel tests for breast cancer predisposition routinely include ATM as it is now a well-established breast cancer predisposition gene. Methods We included ATM in a multigene panel test applied to the Australian Breast Cancer Family Registry (ABCFR), a population-based case–control–family study of breast cancer, with the purpose of estimating the prevalence and penetrance of heterozygous ATM pathogenic variants from the family data, using segregation analysis. Results The estimated breast cancer hazard ratio for carriers of pathogenic ATM variants in the ABCFR was 1.32 (95% confidence interval 0.45–3.87; P = 0.6). The estimated cumulative risk of breast cancer to age 80 years for heterozygous ATM pathogenic variant carriers was estimated to be 13% (95% CI 4.6–30). Conclusions Although ATM has been definitively identified as a breast cancer predisposition gene, further evidence, such as variant-specific penetrance estimates, are needed to inform risk management strategies for carriers of pathogenic variants to increase the clinical utility of population testing of this gene. Supplementary Information The online version contains supplementary material available at 10.1186/s13058-022-01518-y.
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Dugué PA, Hodge AM, Ulvik A, Ueland PM, Midttun Ø, Rinaldi S, MacInnis RJ, Li SX, Meyer K, Navionis AS, Flicker L, Severi G, English DR, Vineis P, Tell GS, Southey MC, Milne RL, Giles GG. Association of Markers of Inflammation, the Kynurenine Pathway and B Vitamins with Age and Mortality, and a Signature of Inflammaging. J Gerontol A Biol Sci Med Sci 2022; 77:826-836. [PMID: 34117761 DOI: 10.1093/gerona/glab163] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Inflammation is a key feature of aging. We aimed to (i) investigate the association of 34 blood markers potentially involved in inflammatory processes with age and mortality and (ii) develop a signature of "inflammaging." METHODS Thirty-four blood markers relating to inflammation, B vitamin status, and the kynurenine pathway were measured in 976 participants in the Melbourne Collaborative Cohort Study at baseline (median age = 59 years) and follow-up (median age = 70 years). Associations with age and mortality were assessed using linear and Cox regression, respectively. A parsimonious signature of inflammaging was developed and its association with mortality was compared with 2 marker scores calculated across all markers associated with age and mortality, respectively. RESULTS The majority of markers (30/34) were associated with age, with stronger associations observed for neopterin, cystatin C, interleukin (IL)-6, tumor necrosis factor alpha (TNF-α), several markers of the kynurenine pathway and derived indices KTR (kynurenine/tryptophan ratio), PAr index (ratio of 4-pyridoxic acid and the sum of pyridoxal 5'-phosphate and pyridoxal), and HK:XA (3-hydroxykynurenine/xanthurenic acid ratio). Many markers (17/34) showed an association with mortality, in particular IL-6, neopterin, C-reactive protein, quinolinic acid, PAr index, and KTR. The inflammaging signature included 10 markers and was strongly associated with mortality (hazard ratio [HR] per SD = 1.40, 95% CI: 1.24-1.57, p = 2 × 10-8), similar to scores based on all age-associated (HR = 1.38, 95% CI: 1.23-1.55, p = 4 × 10-8) and mortality-associated markers (HR = 1.43, 95% CI: 1.28-1.60, p = 1 × 10-10), respectively. Strong evidence of replication of the inflammaging signature association with mortality was found in the Hordaland Health Study. CONCLUSION Our study highlights the key role of the kynurenine pathway and vitamin B6 catabolism in aging, along with other well-established inflammation-related markers. A signature of inflammaging based on 10 markers was strongly associated with mortality.
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Wang X, Chen H, Kapoor PM, Su YR, Bolla MK, Dennis J, Dunning AM, Lush M, Wang Q, Michailidou K, Pharoah PD, Hopper JL, Southey MC, Koutros S, Freeman LEB, Stone J, Rennert G, Shibli R, Murphy RA, Aronson K, Guénel P, Truong T, Teras LR, Hodge JM, Canzian F, Kaaks R, Brenner H, Arndt V, Hoppe R, Lo WY, Behrens S, Mannermaa A, Kosma VM, Jung A, Becher H, Giles GG, Haiman CA, Maskarinec G, Scott C, Winham S, Simard J, Goldberg MS, Zheng W, Long J, Troester MA, Love MI, Peng C, Tamimi R, Eliassen H, García-Closas M, Figueroa J, Ahearn T, Yang R, Evans DG, Howell A, Hall P, Czene K, Wolk A, Sandler DP, Taylor JA, Swerdlow AJ, Orr N, Lacey JV, Wang S, Olsson H, Easton DF, Milne RL, Hsu L, Kraft P, Chang-Claude J, Lindström S. A genome-wide gene-based gene-environment interaction study of breast cancer in more than 90,000 women. CANCER RESEARCH COMMUNICATIONS 2022; 2:211-219. [PMID: 36303815 PMCID: PMC9604427 DOI: 10.1158/2767-9764.crc-21-0119] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 03/21/2022] [Accepted: 03/24/2022] [Indexed: 06/14/2023]
Abstract
Background Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene-environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. Methods We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P<0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. Results After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE=4.44×10-6). Conclusion In this transcriptome-informed genome-wide gene-environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Impact Our study suggests a limited role of gene-environment interactions in breast cancer risk.
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Lesueur F, Easton DF, Renault AL, Tavtigian SV, Bernstein JL, Kote-Jarai Z, Eeles RA, Plaseska-Karanfia D, Feliubadaló L, Arun B, Herold N, Versmold B, Schmutzler RK, Nguyen-Dumont T, Southey MC, Dorling L, Dunning AM, Ghiorzo P, Dalmasso BS, Cavaciuti E, Le Gal D, Roberts NJ, Dominguez-Valentin M, Rookus M, Taylor AMR, Goldstein AM, Goldgar DE, Stoppa-Lyonnet D, Andrieu N. First international workshop of the ATM and cancer risk group (4-5 December 2019). Fam Cancer 2022; 21:211-227. [PMID: 34125377 PMCID: PMC9969796 DOI: 10.1007/s10689-021-00248-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 03/17/2021] [Indexed: 12/17/2022]
Abstract
The first International Workshop of the ATM and Cancer Risk group focusing on the role of Ataxia-Telangiectasia Mutated (ATM) gene in cancer was held on December 4 and 5, 2019 at Institut Curie in Paris, France. It was motivated by the fact that germline ATM pathogenic variants have been found to be associated with different cancer types. However, due to the lack of precise age-, sex-, and site-specific risk estimates, no consensus on management guidelines for variant carriers exists, and the clinical utility of ATM variant testing is uncertain. The meeting brought together epidemiologists, geneticists, biologists and clinicians to review current knowledge and on-going challenges related to ATM and cancer risk. This report summarizes the meeting sessions content that covered the latest results in family-based and population-based studies, the importance of accurate variant classification, the effect of radiation exposures for ATM variant carriers, and the characteristics of ATM-deficient tumors. The report concludes that ATM variant carriers outside of the context of Ataxia-Telangiectasia may benefit from effective cancer risk management and therapeutic strategies and that efforts to set up large-scale studies in the international framework to achieve this goal are necessary.
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Southey MC, Dugué PA. Improving breast cancer risk prediction with epigenetic risk factors. Nat Rev Clin Oncol 2022; 19:363-364. [PMID: 35351995 DOI: 10.1038/s41571-022-00622-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Dareng EO, Tyrer JP, Barnes DR, Jones MR, Yang X, Aben KKH, Adank MA, Agata S, Andrulis IL, Anton-Culver H, Antonenkova NN, Aravantinos G, Arun BK, Augustinsson A, Balmaña J, Bandera EV, Barkardottir RB, Barrowdale D, Beckmann MW, Beeghly-Fadiel A, Benitez J, Bermisheva M, Bernardini MQ, Bjorge L, Black A, Bogdanova NV, Bonanni B, Borg A, Brenton JD, Budzilowska A, Butzow R, Buys SS, Cai H, Caligo MA, Campbell I, Cannioto R, Cassingham H, Chang-Claude J, Chanock SJ, Chen K, Chiew YE, Chung WK, Claes KBM, Colonna S, Cook LS, Couch FJ, Daly MB, Dao F, Davies E, de la Hoya M, de Putter R, Dennis J, DePersia A, Devilee P, Diez O, Ding YC, Doherty JA, Domchek SM, Dörk T, du Bois A, Dürst M, Eccles DM, Eliassen HA, Engel C, Evans GD, Fasching PA, Flanagan JM, Fortner RT, Machackova E, Friedman E, Ganz PA, Garber J, Gensini F, Giles GG, Glendon G, Godwin AK, Goodman MT, Greene MH, Gronwald J, Hahnen E, Haiman CA, Håkansson N, Hamann U, Hansen TVO, Harris HR, Hartman M, Heitz F, Hildebrandt MAT, Høgdall E, Høgdall CK, Hopper JL, Huang RY, Huff C, Hulick PJ, Huntsman DG, Imyanitov EN, Isaacs C, Jakubowska A, James PA, Janavicius R, Jensen A, Johannsson OT, John EM, Jones ME, Kang D, Karlan BY, Karnezis A, Kelemen LE, Khusnutdinova E, Kiemeney LA, Kim BG, Kjaer SK, Komenaka I, Kupryjanczyk J, Kurian AW, Kwong A, Lambrechts D, Larson MC, Lazaro C, Le ND, Leslie G, Lester J, Lesueur F, Levine DA, Li L, Li J, Loud JT, Lu KH, Lubiński J, Mai PL, Manoukian S, Marks JR, Matsuno RK, Matsuo K, May T, McGuffog L, McLaughlin JR, McNeish IA, Mebirouk N, Menon U, Miller A, Milne RL, Minlikeeva A, Modugno F, Montagna M, Moysich KB, Munro E, Nathanson KL, Neuhausen SL, Nevanlinna H, Yie JNY, Nielsen HR, Nielsen FC, Nikitina-Zake L, Odunsi K, Offit K, Olah E, Olbrecht S, Olopade OI, Olson SH, Olsson H, Osorio A, Papi L, Park SK, Parsons MT, Pathak H, Pedersen IS, Peixoto A, Pejovic T, Perez-Segura P, Permuth JB, Peshkin B, Peterlongo P, Piskorz A, Prokofyeva D, Radice P, Rantala J, Riggan MJ, Risch HA, Rodriguez-Antona C, Ross E, Rossing MA, Runnebaum I, Sandler DP, Santamariña M, Soucy P, Schmutzler RK, Setiawan VW, Shan K, Sieh W, Simard J, Singer CF, Sokolenko AP, Song H, Southey MC, Steed H, Stoppa-Lyonnet D, Sutphen R, Swerdlow AJ, Tan YY, Teixeira MR, Teo SH, Terry KL, Terry MB, Thomassen M, Thompson PJ, Thomsen LCV, Thull DL, Tischkowitz M, Titus L, Toland AE, Torres D, Trabert B, Travis R, Tung N, Tworoger SS, Valen E, van Altena AM, van der Hout AH, Van Nieuwenhuysen E, van Rensburg EJ, Vega A, Edwards DV, Vierkant RA, Wang F, Wappenschmidt B, Webb PM, Weinberg CR, Weitzel JN, Wentzensen N, White E, Whittemore AS, Winham SJ, Wolk A, Woo YL, Wu AH, Yan L, Yannoukakos D, Zavaglia KM, Zheng W, Ziogas A, Zorn KK, Kleibl Z, Easton D, Lawrenson K, DeFazio A, Sellers TA, Ramus SJ, Pearce CL, Monteiro AN, Cunningham J, Goode EL, Schildkraut JM, Berchuck A, Chenevix-Trench G, Gayther SA, Antoniou AC, Pharoah PDP. Polygenic risk modeling for prediction of epithelial ovarian cancer risk. Eur J Hum Genet 2022; 30:349-362. [PMID: 35027648 PMCID: PMC8904525 DOI: 10.1038/s41431-021-00987-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 08/09/2021] [Accepted: 09/27/2021] [Indexed: 12/14/2022] Open
Abstract
Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
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Ye Z, Li S, Dite GS, Nguyen TL, MacInnis RJ, Andrulis IL, Buys SS, Daly MB, John EM, Kurian AW, Genkinger JM, Chung WK, Phillips KA, Thorne H, Thorne H, Winship IM, Milne RL, Dugué PA, Southey MC, Giles GG, Terry MB, Hopper JL. Weight is More Informative than Body Mass Index for Predicting Postmenopausal Breast Cancer Risk: Prospective Family Study Cohort (ProF-SC). Cancer Prev Res (Phila) 2022; 15:185-191. [PMID: 34965921 PMCID: PMC8977841 DOI: 10.1158/1940-6207.capr-21-0164] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 05/17/2021] [Accepted: 12/20/2021] [Indexed: 01/07/2023]
Abstract
We considered whether weight is more informative than body mass index (BMI) = weight/height2 when predicting breast cancer risk for postmenopausal women, and if the weight association differs by underlying familial risk. We studied 6,761 women postmenopausal at baseline with a wide range of familial risk from 2,364 families in the Prospective Family Study Cohort. Participants were followed for on average 11.45 years and there were 416 incident breast cancers. We used Cox regression to estimate risk associations with log-transformed weight and BMI after adjusting for underlying familial risk. We compared model fits using the Akaike information criterion (AIC) and nested models using the likelihood ratio test. The AIC for the weight-only model was 6.22 units lower than for the BMI-only model, and the log risk gradient was 23% greater. Adding BMI or height to weight did not improve fit (ΔAIC = 0.90 and 0.83, respectively; both P = 0.3). Conversely, adding weight to BMI or height gave better fits (ΔAIC = 5.32 and 11.64; P = 0.007 and 0.0002, respectively). Adding height improved only the BMI model (ΔAIC = 5.47; P = 0.006). There was no evidence that the BMI or weight associations differed by underlying familial risk (P > 0.2). Weight is more informative than BMI for predicting breast cancer risk, consistent with nonadipose as well as adipose tissue being etiologically relevant. The independent but multiplicative associations of weight and familial risk suggest that, in terms of absolute breast cancer risk, the association with weight is more important the greater a woman's underlying familial risk. PREVENTION RELEVANCE Our results suggest that the relationship between BMI and breast cancer could be due to a relationship between weight and breast cancer, downgraded by inappropriately adjusting for height; potential importance of anthropometric measures other than total body fat; breast cancer risk associations with BMI and weight are across a continuum.
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Li S, Ye Z, Mather KA, Nguyen TL, Dite GS, Armstrong NJ, Wong EM, Thalamuthu A, Giles GG, Craig JM, Saffery R, Southey MC, Tan Q, Sachdev PS, Hopper JL. Early life affects late-life health through determining DNA methylation across the lifespan: A twin study. EBioMedicine 2022; 77:103927. [PMID: 35301182 PMCID: PMC8927831 DOI: 10.1016/j.ebiom.2022.103927] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 02/07/2022] [Accepted: 02/24/2022] [Indexed: 12/22/2022] Open
Abstract
Background Previous findings for the genetic and environmental contributions to DNA methylation variation were for limited age ranges only. We investigated the lifespan contributions and their implications for human health for the first time. Methods 1,720 monozygotic twin (MZ) pairs and 1,107 dizygotic twin (DZ) pairs aged 0-92 years were included. Familial correlations (i.e., correlations between twins) for 353,681 methylation sites were estimated and modelled as a function of twin pair cohabitation history. Findings The methylome average familial correlation was around zero at birth (MZ pair: -0.01; DZ pair: -0.04), increased with the time of twins living together during childhood at rates of 0.16 (95%CI: 0.12-0.20) for MZ pairs and 0.13 (95%CI: 0.07-0.20) for DZ pairs per decade, and decreased with the time of living apart during adulthood at rates of 0.026 (95%CI: 0.019-0.033) for MZ pairs and 0.027 (95%CI: 0.011-0.043) for DZ pairs per decade. Neither the increasing nor decreasing rate differed by zygosity (both P>0.1), consistent with cohabitation environment shared by twins, rather than genetic factors, influencing the methylation familial correlation changes. Familial correlations for 6.6% (23,386/353,681) sites changed with twin pair cohabitation history. These sites were enriched for high heritability, proximal promoters, and epigenetic/genetic associations with various early-life factors and late-life health conditions. Interpretation Early life strongly influences DNA methylation variation across the lifespan, and the effects are stronger for heritable sites and sites biologically relevant to the regulation of gene expression. Early life could affect late-life health through influencing DNA methylation. Funding Victorian Cancer Agency, Cancer Australia, Cure Cancer Foundation.
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Mavaddat N, Dorling L, Carvalho S, Allen J, González-Neira A, Keeman R, Bolla MK, Dennis J, Wang Q, Ahearn TU, Andrulis IL, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Blomqvist C, Bogdanova NV, Bojesen SE, Briceno I, Brüning T, Camp NJ, Campbell A, Castelao JE, Chang-Claude J, Chanock SJ, Chenevix-Trench G, Christiansen H, Czene K, Dörk T, Eriksson M, Evans DG, Fasching PA, Figueroa JD, Flyger H, Gabrielson M, Gago-Dominguez M, Geisler J, Giles GG, Guénel P, Hadjisavvas A, Hahnen E, Hall P, Hamann U, Hartikainen JM, Hartman M, Hoppe R, Howell A, Jakubowska A, Jung A, Khusnutdinova EK, Kristensen VN, Li J, Lim SH, Lindblom A, Loizidou MA, Lophatananon A, Lubinski J, Madsen MJ, Mannermaa A, Manoochehri M, Margolin S, Mavroudis D, Milne RL, Mohd Taib NA, Morra A, Muir K, Obi N, Osorio A, Park-Simon TW, Peterlongo P, Radice P, Saloustros E, Sawyer EJ, Schmutzler RK, Shah M, Sim X, Southey MC, Thorne H, Tomlinson I, Torres D, Truong T, Yip CH, Spurdle AB, Vreeswijk MPG, Dunning AM, García-Closas M, Pharoah PDP, Kvist A, Muranen TA, Nevanlinna H, Teo SH, Devilee P, Schmidt MK, Easton DF. Pathology of Tumors Associated With Pathogenic Germline Variants in 9 Breast Cancer Susceptibility Genes. JAMA Oncol 2022; 8:e216744. [PMID: 35084436 PMCID: PMC8796069 DOI: 10.1001/jamaoncol.2021.6744] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
IMPORTANCE Rare germline genetic variants in several genes are associated with increased breast cancer (BC) risk, but their precise contributions to different disease subtypes are unclear. This information is relevant to guidelines for gene panel testing and risk prediction. OBJECTIVE To characterize tumors associated with BC susceptibility genes in large-scale population- or hospital-based studies. DESIGN, SETTING, AND PARTICIPANTS The multicenter, international case-control analysis of the BRIDGES study included 42 680 patients and 46 387 control participants, comprising women aged 18 to 79 years who were sampled independently of family history from 38 studies. Studies were conducted between 1991 and 2016. Sequencing and analysis took place between 2016 and 2021. EXPOSURES Protein-truncating variants and likely pathogenic missense variants in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53. MAIN OUTCOMES AND MEASURES The intrinsic-like BC subtypes as defined by estrogen receptor, progesterone receptor, and ERBB2 (formerly known as HER2) status, and tumor grade; morphology; size; stage; lymph node involvement; subtype-specific odds ratios (ORs) for carrying protein-truncating variants and pathogenic missense variants in the 9 BC susceptibility genes. RESULTS The mean (SD) ages at interview (control participants) and diagnosis (cases) were 55.1 (11.9) and 55.8 (10.6) years, respectively; all participants were of European or East Asian ethnicity. There was substantial heterogeneity in the distribution of intrinsic subtypes by gene. RAD51C, RAD51D, and BARD1 variants were associated mainly with triple-negative disease (OR, 6.19 [95% CI, 3.17-12.12]; OR, 6.19 [95% CI, 2.99-12.79]; and OR, 10.05 [95% CI, 5.27-19.19], respectively). CHEK2 variants were associated with all subtypes (with ORs ranging from 2.21-3.17) except for triple-negative disease. For ATM variants, the association was strongest for the hormone receptor (HR)+ERBB2- high-grade subtype (OR, 4.99; 95% CI, 3.68-6.76). BRCA1 was associated with increased risk of all subtypes, but the ORs varied widely, being highest for triple-negative disease (OR, 55.32; 95% CI, 40.51-75.55). BRCA2 and PALB2 variants were also associated with triple-negative disease. TP53 variants were most strongly associated with HR+ERBB2+ and HR-ERBB2+ subtypes. Tumors occurring in pathogenic variant carriers were of higher grade. For most genes and subtypes, a decline in ORs was observed with increasing age. Together, the 9 genes were associated with 27.3% of all triple-negative tumors in women 40 years or younger. CONCLUSIONS AND RELEVANCE The results of this case-control study suggest that variants in the 9 BC risk genes differ substantially in their associated pathology but are generally associated with triple-negative and/or high-grade disease. Knowing the age and tumor subtype distributions associated with individual BC genes can potentially aid guidelines for gene panel testing, risk prediction, and variant classification and guide targeted screening strategies.
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Dennis J, Tyrer JP, Walker LC, Michailidou K, Dorling L, Bolla MK, Wang Q, Ahearn TU, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Freeman LEB, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bogdanova NV, Bojesen SE, Brenner H, Castelao JE, Chang-Claude J, Chenevix-Trench G, Clarke CL, Collée JM, Couch FJ, Cox A, Cross SS, Czene K, Devilee P, Dörk T, Dossus L, Eliassen AH, Eriksson M, Evans DG, Fasching PA, Figueroa J, Fletcher O, Flyger H, Fritschi L, Gabrielson M, Gago-Dominguez M, García-Closas M, Giles GG, González-Neira A, Guénel P, Hahnen E, Haiman CA, Hall P, Hollestelle A, Hoppe R, Hopper JL, Howell A, Jager A, Jakubowska A, John EM, Johnson N, Jones ME, Jung A, Kaaks R, Keeman R, Khusnutdinova E, Kitahara CM, Ko YD, Kosma VM, Koutros S, Kraft P, Kristensen VN, Kubelka-Sabit K, Kurian AW, Lacey JV, Lambrechts D, Larson NL, Linet M, Ogrodniczak A, Mannermaa A, Manoukian S, Margolin S, Mavroudis D, Milne RL, Muranen TA, Murphy RA, Nevanlinna H, Olson JE, Olsson H, Park-Simon TW, Perou CM, Peterlongo P, Plaseska-Karanfilska D, Pylkäs K, Rennert G, Saloustros E, Sandler DP, Sawyer EJ, Schmidt MK, Schmutzler RK, Shibli R, Smeets A, Soucy P, Southey MC, Swerdlow AJ, Tamimi RM, Taylor JA, Teras LR, Terry MB, Tomlinson I, Troester MA, Truong T, Vachon CM, Wendt C, Winqvist R, Wolk A, Yang XR, Zheng W, Ziogas A, Simard J, Dunning AM, Pharoah PDP, Easton DF. Rare germline copy number variants (CNVs) and breast cancer risk. Commun Biol 2022; 5:65. [PMID: 35042965 PMCID: PMC8766486 DOI: 10.1038/s42003-021-02990-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 12/01/2021] [Indexed: 12/14/2022] Open
Abstract
Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.
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Ahearn TU, Zhang H, Michailidou K, Milne RL, Bolla MK, Dennis J, Dunning AM, Lush M, Wang Q, Andrulis IL, Anton-Culver H, Arndt V, Aronson KJ, Auer PL, Augustinsson A, Baten A, Becher H, Behrens S, Benitez J, Bermisheva M, Blomqvist C, Bojesen SE, Bonanni B, Børresen-Dale AL, Brauch H, Brenner H, Brooks-Wilson A, Brüning T, Burwinkel B, Buys SS, Canzian F, Castelao JE, Chang-Claude J, Chanock SJ, Chenevix-Trench G, Clarke CL, Collée JM, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dwek M, Eccles DM, Evans DG, Fasching PA, Figueroa J, Floris G, Gago-Dominguez M, Gapstur SM, García-Sáenz JA, Gaudet MM, Giles GG, Goldberg MS, González-Neira A, Alnæs GIG, Grip M, Guénel P, Haiman CA, Hall P, Hamann U, Harkness EF, Heemskerk-Gerritsen BAM, Holleczek B, Hollestelle A, Hooning MJ, Hoover RN, Hopper JL, Howell A, Jakimovska M, Jakubowska A, John EM, Jones ME, Jung A, Kaaks R, Kauppila S, Keeman R, Khusnutdinova E, Kitahara CM, Ko YD, Koutros S, Kristensen VN, Krüger U, Kubelka-Sabit K, Kurian AW, Kyriacou K, Lambrechts D, Lee DG, Lindblom A, Linet M, Lissowska J, Llaneza A, Lo WY, MacInnis RJ, Mannermaa A, Manoochehri M, Margolin S, Martinez ME, McLean C, Meindl A, Menon U, Nevanlinna H, Newman WG, Nodora J, Offit K, Olsson H, Orr N, Park-Simon TW, Patel AV, Peto J, Pita G, Plaseska-Karanfilska D, Prentice R, Punie K, Pylkäs K, Radice P, Rennert G, Romero A, Rüdiger T, Saloustros E, Sampson S, Sandler DP, Sawyer EJ, Schmutzler RK, Schoemaker MJ, Schöttker B, Sherman ME, Shu XO, Smichkoska S, Southey MC, Spinelli JJ, Swerdlow AJ, Tamimi RM, Tapper WJ, Taylor JA, Teras LR, Terry MB, Torres D, Troester MA, Vachon CM, van Deurzen CHM, van Veen EM, Wagner P, Weinberg CR, Wendt C, Wesseling J, Winqvist R, Wolk A, Yang XR, Zheng W, Couch FJ, Simard J, Kraft P, Easton DF, Pharoah PDP, Schmidt MK, García-Closas M, Chatterjee N. Common variants in breast cancer risk loci predispose to distinct tumor subtypes. Breast Cancer Res 2022; 24:2. [PMID: 34983606 PMCID: PMC8725568 DOI: 10.1186/s13058-021-01484-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 11/02/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. METHODS Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. RESULTS Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. CONCLUSION This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.
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Chen H, Fan S, Stone J, Thompson DJ, Douglas J, Li S, Scott C, Bolla MK, Wang Q, Dennis J, Michailidou K, Li C, Peters U, Hopper JL, Southey MC, Nguyen-Dumont T, Nguyen TL, Fasching PA, Behrens A, Cadby G, Murphy RA, Aronson K, Howell A, Astley S, Couch F, Olson J, Milne RL, Giles GG, Haiman CA, Maskarinec G, Winham S, John EM, Kurian A, Eliassen H, Andrulis I, Evans DG, Newman WG, Hall P, Czene K, Swerdlow A, Jones M, Pollan M, Fernandez-Navarro P, McConnell DS, Kristensen VN, Rothstein JH, Wang P, Habel LA, Sieh W, Dunning AM, Pharoah PDP, Easton DF, Gierach GL, Tamimi RM, Vachon CM, Lindström S. Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci. Breast Cancer Res 2022; 24:27. [PMID: 35414113 PMCID: PMC9006574 DOI: 10.1186/s13058-022-01524-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 04/02/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. METHODS We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. RESULTS We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes. CONCLUSIONS Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.
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Giardiello D, Hooning MJ, Hauptmann M, Keeman R, Heemskerk-Gerritsen BAM, Becher H, Blomqvist C, Bojesen SE, Bolla MK, Camp NJ, Czene K, Devilee P, Eccles DM, Fasching PA, Figueroa JD, Flyger H, García-Closas M, Haiman CA, Hamann U, Hopper JL, Jakubowska A, Leeuwen FE, Lindblom A, Lubiński J, Margolin S, Martinez ME, Nevanlinna H, Nevelsteen I, Pelders S, Pharoah PDP, Siesling S, Southey MC, van der Hout AH, van Hest LP, Chang-Claude J, Hall P, Easton DF, Steyerberg EW, Schmidt MK. Correction: PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients. Breast Cancer Res 2022; 24:82. [PMID: 36419099 PMCID: PMC9682632 DOI: 10.1186/s13058-022-01579-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Li H, Engel C, de la Hoya M, Peterlongo P, Yannoukakos D, Livraghi L, Radice P, Thomassen M, Hansen TVO, Gerdes AM, Nielsen HR, Caputo SM, Zambelli A, Borg A, Solano A, Thomas A, Parsons MT, Antoniou AC, Leslie G, Yang X, Chenevix-Trench G, Caldes T, Kwong A, Pedersen IS, Lautrup CK, John EM, Terry MB, Hopper JL, Southey MC, Andrulis IL, Tischkowitz M, Janavicius R, Boonen SE, Kroeldrup L, Varesco L, Hamann U, Vega A, Palmero EI, Garber J, Montagna M, Van Asperen CJ, Foretova L, Greene MH, Selkirk T, Moller P, Toland AE, Domchek SM, James PA, Thorne H, Eccles DM, Nielsen SM, Manoukian S, Pasini B, Caligo MA, Lazaro C, Kirk J, Wappenschmidt B, Spurdle AB, Couch FJ, Schmutzler R, Goldgar DE. Risks of breast and ovarian cancer for women harboring pathogenic missense variants in BRCA1 and BRCA2 compared with those harboring protein truncating variants. Genet Med 2022; 24:119-129. [PMID: 34906479 PMCID: PMC10170303 DOI: 10.1016/j.gim.2021.08.016] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/22/2021] [Accepted: 08/25/2021] [Indexed: 12/20/2022] Open
Abstract
PURPOSE Germline genetic testing for BRCA1 and BRCA2 variants has been a part of clinical practice for >2 decades. However, no studies have compared the cancer risks associated with missense pathogenic variants (PVs) with those associated with protein truncating (PTC) variants. METHODS We collected 582 informative pedigrees segregating 1 of 28 missense PVs in BRCA1 and 153 pedigrees segregating 1 of 12 missense PVs in BRCA2. We analyzed 324 pedigrees with PTC variants in BRCA1 and 214 pedigrees with PTC variants in BRCA2. Cancer risks were estimated using modified segregation analysis. RESULTS Estimated breast cancer risks were markedly lower for women aged >50 years carrying BRCA1 missense PVs than for the women carrying BRCA1 PTC variants (hazard ratio [HR] = 3.9 [2.4-6.2] for PVs vs 12.8 [5.7-28.7] for PTC variants; P = .01), particularly for missense PVs in the BRCA1 C-terminal domain (HR = 2.8 [1.4-5.6]; P = .005). In case of BRCA2, for women aged >50 years, the HR was 3.9 (2.0-7.2) for those heterozygous for missense PVs compared with 7.0 (3.3-14.7) for those harboring PTC variants. BRCA1 p.[Cys64Arg] and BRCA2 p.[Trp2626Cys] were associated with particularly low risks of breast cancer compared with other PVs. CONCLUSION These results have important implications for the counseling of at-risk women who harbor missense PVs in the BRCA1/2 genes.
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Kehm RD, MacInnis RJ, John EM, Liao Y, Kurian AW, Genkinger JM, Knight JA, Colonna SV, Chung WK, Milne R, Zeinomar N, Dite GS, Southey MC, Giles GG, McLachlan SA, Whitaker KD, Friedlander ML, Weideman PC, Glendon G, Nesci S, Phillips KA, Andrulis IL, Buys SS, Daly MB, Hopper JL, Terry MB. Recreational Physical Activity and Outcomes After Breast Cancer in Women at High Familial Risk. JNCI Cancer Spectr 2021; 5:pkab090. [PMID: 34950851 PMCID: PMC8692829 DOI: 10.1093/jncics/pkab090] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 09/08/2021] [Accepted: 10/14/2021] [Indexed: 12/13/2022] Open
Abstract
Background Recreational physical activity (RPA) is associated with improved survival after breast cancer (BC) in average-risk women, but evidence is limited for women who are at increased familial risk because of a BC family history or BRCA1 and BRCA2 pathogenic variants (BRCA1/2 PVs). Methods We estimated associations of RPA (self-reported average hours per week within 3 years of BC diagnosis) with all-cause mortality and second BC events (recurrence or new primary) after first invasive BC in women in the Prospective Family Study Cohort (n = 4610, diagnosed 1993-2011, aged 22-79 years at diagnosis). We fitted Cox proportional hazards regression models adjusted for age at diagnosis, demographics, and lifestyle factors. We tested for multiplicative interactions (Wald test statistic for cross-product terms) and additive interactions (relative excess risk due to interaction) by age at diagnosis, body mass index, estrogen receptor status, stage at diagnosis, BRCA1/2 PVs, and familial risk score estimated from multigenerational pedigree data. Statistical tests were 2-sided. Results We observed 1212 deaths and 473 second BC events over a median follow-up from study enrollment of 11.0 and 10.5 years, respectively. After adjusting for covariates, RPA (any vs none) was associated with lower all-cause mortality of 16.1% (95% confidence interval [CI] = 2.4% to 27.9%) overall, 11.8% (95% CI = -3.6% to 24.9%) in women without BRCA1/2 PVs, and 47.5% (95% CI = 17.4% to 66.6%) in women with BRCA1/2 PVs (RPA*BRCA1/2 multiplicative interaction P = .005; relative excess risk due to interaction = 0.87, 95% CI = 0.01 to 1.74). RPA was not associated with risk of second BC events. Conclusion Findings support that RPA is associated with lower all-cause mortality in women with BC, particularly in women with BRCA1/2 PVs.
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Yu C, Hodge AM, Wong EM, Joo JE, Makalic E, Schmidt D, Buchanan DD, Hopper JL, Giles GG, Southey MC, Dugué PA. Association of FOXO3 Blood DNA Methylation with Cancer Risk, Cancer Survival, and Mortality. Cells 2021; 10:cells10123384. [PMID: 34943892 PMCID: PMC8699522 DOI: 10.3390/cells10123384] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 11/22/2021] [Accepted: 11/26/2021] [Indexed: 12/29/2022] Open
Abstract
Genetic variants in FOXO3 are associated with longevity. Here, we assessed whether blood DNA methylation at FOXO3 was associated with cancer risk, survival, and mortality. We used data from eight prospective case–control studies of breast (n = 409 cases), colorectal (n = 835), gastric (n = 170), kidney (n = 143), lung (n = 332), prostate (n = 869), and urothelial (n = 428) cancer and B-cell lymphoma (n = 438). Case–control pairs were matched on age, sex, country of birth, and smoking (lung cancer study). Conditional logistic regression was used to assess associations between cancer risk and methylation at 45 CpGs of FOXO3 included on the HumanMethylation450 assay. Mixed-effects Cox models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations with cancer survival (total n = 2286 deaths). Additionally, using data from 1088 older participants, we assessed associations of FOXO3 methylation with overall and cause-specific mortality (n = 354 deaths). Methylation at a CpG in the first exon region of FOXO3 (6:108882981) was associated with gastric cancer survival (HR = 2.39, 95% CI: 1.60–3.56, p = 1.9 × 10−5). Methylation at three CpGs in TSS1500 and gene body was associated with lung cancer survival (p < 6.1 × 10−5). We found no evidence of associations of FOXO3 methylation with cancer risk and mortality. Our findings may contribute to understanding the implication of FOXO3 in longevity.
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Bakshi A, Riaz M, Orchard SG, Carr PR, Joshi AD, Cao Y, Rebello R, Nguyen-Dumont T, Southey MC, Millar JL, Gately L, Gibbs P, Ford LG, Parnes HL, Chan AT, McNeil JJ, Lacaze P. A Polygenic Risk Score Predicts Incident Prostate Cancer Risk in Older Men but Does Not Select for Clinically Significant Disease. Cancers (Basel) 2021; 13:5815. [PMID: 34830967 PMCID: PMC8616400 DOI: 10.3390/cancers13225815] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 11/17/2021] [Accepted: 11/18/2021] [Indexed: 12/24/2022] Open
Abstract
Despite the high prevalence of prostate cancer in older men, the predictive value of a polygenic risk score (PRS) remains uncertain in men aged ≥70 years. We used a 6.6 million-variant PRS to predict the risk of incident prostate cancer in a prospective study of 5701 men of European descent aged ≥70 years (mean age 75 years) enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) clinical trial. The study endpoint was prostate cancer, including metastatic or non-metastatic disease, confirmed by an expert panel. After excluding participants with a history of prostate cancer at enrolment, we used a multivariable Cox proportional hazards model to assess the association between the PRS and incident prostate cancer risk, adjusting for covariates. Additionally, we examined the distribution of Gleason grade groups by PRS group to determine if a higher PRS was associated with higher grade disease. We tested for interaction between the PRS and aspirin treatment. Logistic regression was used to independently assess the association of the PRS with prevalent (pre-trial) prostate cancer, reported in medical histories. During a median follow-up time of 4.6 years, 218 of the 5701 participants (3.8%) were diagnosed with prostate cancer. The PRS predicted incident risk with a hazard ratio (HR) of 1.52 per standard deviation (SD) (95% confidence interval (CI) 1.33-1.74, p < 0.001). Men in the top quintile of the PRS distribution had an almost three times higher risk of prostate cancer than men in the lowest quintile (HR = 2.99 (95% CI 1.90-4.27), p < 0.001). However, a higher PRS was not associated with a higher Gleason grade groups. We found no interaction between aspirin treatment and the PRS for prostate cancer risk. The PRS was also associated with prevalent prostate cancer (odds ratio = 1.80 per SD (95% CI 1.65-1.96), p < 0.001).While a PRS for prostate cancer is strongly associated with incident risk in men aged ≥70 years, the clinical utility of the PRS as a biomarker is currently limited by its inability to select for clinically significant disease.
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Yu C, Dugué PA, Dowty JG, Hammet F, Joo JE, Wong EM, Hosseinpour M, Giles GG, Hopper JL, Nguyen-Dumont T, MacInnis RJ, Southey MC. Repeatability of methylation measures using a QIAseq targeted methyl panel and comparison with the Illumina HumanMethylation450 assay. BMC Res Notes 2021; 14:394. [PMID: 34689793 PMCID: PMC8543877 DOI: 10.1186/s13104-021-05809-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 10/11/2021] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVE In previous studies using Illumina Infinium methylation arrays, we have identified DNA methylation marks associated with cancer predisposition and progression. In the present study, we have sought to find appropriate technology to both technically validate our data and expand our understanding of DNA methylation in these genomic regions. Here, we aimed to assess the repeatability of methylation measures made using QIAseq targeted methyl panel and to compare them with those obtained from the Illumina HumanMethylation450 (HM450K) assay. We included in the analysis high molecular weight DNA extracted from whole blood (WB) and DNA extracted from formalin-fixed paraffin-embedded tissues (FFPE). RESULTS The repeatability of QIAseq-methylation measures was assessed at 40 CpGs, using the Intraclass Correlation Coefficient (ICC). The mean ICCs and 95% confidence intervals (CI) were 0.72 (0.62-0.81), 0.59 (0.47-0.71) and 0.80 (0.73-0.88) for WB, FFPE and both sample types combined, respectively. For technical replicates measured using QIAseq and HM450K, the mean ICCs (95% CI) were 0.53 (0.39-0.68), 0.43 (0.31-0.56) and 0.70 (0.59-0.80), respectively. Bland-Altman plots indicated good agreement between QIAseq and HM450K measurements. These results demonstrate that the QIAseq targeted methyl panel produces reliable and reproducible methylation measurements across the 40 CpGs that were examined.
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Li SX, Milne RL, Nguyen-Dumont T, English DR, Giles GG, Southey MC, Antoniou AC, Lee A, Winship I, Hopper JL, Terry MB, MacInnis RJ. Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models. Cancers (Basel) 2021; 13:5194. [PMID: 34680343 PMCID: PMC8534072 DOI: 10.3390/cancers13205194] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 09/30/2021] [Accepted: 10/13/2021] [Indexed: 11/20/2022] Open
Abstract
Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models (IBIS, BOADICEA, BRCAPRO, BRCAPRO-BCRAT, BCRAT, and iCARE-lit). 15-year risk scores were estimated using lifestyle factors and family history measures from 7608 women in the Melbourne Collaborative Cohort Study who were aged 50-65 years and unaffected at commencement of follow-up two (conducted in 2003-2007), of whom 351 subsequently developed breast cancer. Risk discrimination was assessed using the C-statistic and calibration using the expected/observed number of incident cases across the spectrum of risk by age group (50-54, 55-59, 60-65 years) and family history of breast cancer. C-statistics were higher for BOADICEA (0.59, 95% confidence interval (CI) 0.56-0.62) and IBIS (0.57, 95% CI 0.54-0.61) than the other models (p-difference ≤ 0.04). No model except BOADICEA calibrated well across the spectrum of 15-year risk (p-value < 0.03). The performance of BOADICEA and IBIS was similar across age groups and for women with or without a family history. For middle-aged Australian women, BOADICEA and IBIS had the highest discriminatory accuracy of the six risk models, but apart from BOADICEA, no model was well-calibrated across the risk spectrum.
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Escala-Garcia M, Canisius S, Keeman R, Beesley J, Anton-Culver H, Arndt V, Augustinsson A, Becher H, Beckmann MW, Behrens S, Bermisheva M, Bojesen SE, Bolla MK, Brenner H, Canzian F, Castelao JE, Chang-Claude J, Chanock SJ, Couch FJ, Czene K, Daly MB, Dennis J, Devilee P, Dörk T, Dunning AM, Easton DF, Ekici AB, Eliassen AH, Fasching PA, Flyger H, Gago-Dominguez M, García-Closas M, García-Sáenz JA, Geisler J, Giles GG, Grip M, Gündert M, Hahnen E, Haiman CA, Håkansson N, Hall P, Hamann U, Hartikainen JM, Heemskerk-Gerritsen BAM, Hollestelle A, Hoppe R, Hopper JL, Hunter DJ, Jacot W, Jakubowska A, John EM, Jung AY, Kaaks R, Khusnutdinova E, Koppert LB, Kraft P, Kristensen VN, Kurian AW, Lambrechts D, Le Marchand L, Lindblom A, Luben RN, Lubiński J, Mannermaa A, Manoochehri M, Margolin S, Mavroudis D, Muranen TA, Nevanlinna H, Olshan AF, Olsson H, Park-Simon TW, Patel AV, Peterlongo P, Pharoah PDP, Punie K, Radice P, Rennert G, Rennert HS, Romero A, Roylance R, Rüdiger T, Ruebner M, Saloustros E, Sawyer EJ, Schmutzler RK, Schoemaker MJ, Scott C, Southey MC, Surowy H, Swerdlow AJ, Tamimi RM, Teras LR, Thomas E, Tomlinson I, Troester MA, Vachon CM, Wang Q, Winqvist R, Wolk A, Ziogas A, Michailidou K, Chenevix-Trench G, Bachelot T, Schmidt MK. Germline variants and breast cancer survival in patients with distant metastases at primary breast cancer diagnosis. Sci Rep 2021; 11:19787. [PMID: 34611289 PMCID: PMC8492709 DOI: 10.1038/s41598-021-99409-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 09/07/2021] [Indexed: 02/02/2023] Open
Abstract
Breast cancer metastasis accounts for most of the deaths from breast cancer. Identification of germline variants associated with survival in aggressive types of breast cancer may inform understanding of breast cancer progression and assist treatment. In this analysis, we studied the associations between germline variants and breast cancer survival for patients with distant metastases at primary breast cancer diagnosis. We used data from the Breast Cancer Association Consortium (BCAC) including 1062 women of European ancestry with metastatic breast cancer, 606 of whom died of breast cancer. We identified two germline variants on chromosome 1, rs138569520 and rs146023652, significantly associated with breast cancer-specific survival (P = 3.19 × 10-8 and 4.42 × 10-8). In silico analysis suggested a potential regulatory effect of the variants on the nearby target genes SDE2 and H3F3A. However, the variants showed no evidence of association in a smaller replication dataset. The validation dataset was obtained from the SNPs to Risk of Metastasis (StoRM) study and included 293 patients with metastatic primary breast cancer at diagnosis. Ultimately, larger replication studies are needed to confirm the identified associations.
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