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Morra A, Jung AY, Behrens S, Keeman R, Ahearn TU, Anton-Culver H, Arndt V, Augustinsson A, Auvinen PK, Beane Freeman LE, Becher H, Beckmann MW, Blomqvist C, Bojesen SE, Bolla MK, Brenner H, Briceno I, Brucker SY, Camp NJ, Campa D, Canzian F, Castelao JE, Chanock SJ, Choi JY, Clarke CL, Couch FJ, Cox A, Cross SS, Czene K, Dörk T, Dunning AM, Dwek M, Easton DF, Eccles DM, Egan KM, Evans DG, Fasching PA, Flyger H, Gago-Dominguez M, Gapstur SM, García-Sáenz JA, Gaudet MM, Giles GG, Grip M, Guénel P, Haiman CA, Håkansson N, Hall P, Hamann U, Han SN, Hart SN, Hartman M, Heyworth JS, Hoppe R, Hopper JL, Hunter DJ, Ito H, Jager A, Jakimovska M, Jakubowska A, Janni W, Kaaks R, Kang D, Kapoor PM, Kitahara CM, Koutros S, Kraft P, Kristensen VN, Lacey JV, Lambrechts D, Le Marchand L, Li J, Lindblom A, Lubiński J, Lush M, Mannermaa A, Manoochehri M, Margolin S, Mariapun S, Matsuo K, Mavroudis D, Milne RL, Muranen TA, Newman WG, Noh DY, Nordestgaard BG, Obi N, Olshan AF, Olsson H, Park-Simon TW, Petridis C, Pharoah PDP, Plaseska-Karanfilska D, Presneau N, Rashid MU, Rennert G, Rennert HS, Rhenius V, Romero A, Saloustros E, Sawyer EJ, Schneeweiss A, Schwentner L, Scott C, Shah M, Shen CY, Shu XO, Southey MC, Stram DO, Tamimi RM, Tapper W, Tollenaar RAEM, Tomlinson I, Torres D, Troester MA, Truong T, Vachon CM, Wang Q, Wang SS, Williams JA, Winqvist R, Wolk A, Wu AH, Yoo KY, Yu JC, Zheng W, Ziogas A, Yang XR, Eliassen AH, Holmes MD, García-Closas M, Teo SH, Schmidt MK, Chang-Claude J. Breast Cancer Risk Factors and Survival by Tumor Subtype: Pooled Analyses from the Breast Cancer Association Consortium. Cancer Epidemiol Biomarkers Prev 2021; 30:623-642. [PMID: 33500318 PMCID: PMC8026532 DOI: 10.1158/1055-9965.epi-20-0924] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 08/31/2020] [Accepted: 01/08/2021] [Indexed: 12/09/2022] Open
Abstract
BACKGROUND It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype. METHODS We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype. RESULTS There was no evidence of heterogeneous associations between risk factors and mortality by subtype (P adj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0-<5 years versus ≥10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking. CONCLUSIONS We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype. IMPACT Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.
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Russell H, Kedzierska K, Buchanan DD, Thomas R, Tham E, Mints M, Keränen A, Giles GG, Southey MC, Milne RL, Tomlinson I, Church D, Spurdle AB, O'Mara TA, Lewis A. Correction to: The MLH1 polymorphism rs1800734 and risk of endometrial cancer with microsatellite instability. Clin Epigenetics 2021; 13:69. [PMID: 33794988 PMCID: PMC8015168 DOI: 10.1186/s13148-021-01058-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
An amendment to this paper has been published and can be accessed via the original article.
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Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, Schumacher FR, Olama AAA, Benlloch S, Dadaev T, Brook MN, Sahimi A, Hoffmann TJ, Takahashi A, Matsuda K, Momozawa Y, Fujita M, Muir K, Lophatananon A, Wan P, Le Marchand L, Wilkens LR, Stevens VL, Gapstur SM, Carter BD, Schleutker J, Tammela TLJ, Sipeky C, Auvinen A, Giles GG, Southey MC, MacInnis RJ, Cybulski C, Wokołorczyk D, Lubiński J, Neal DE, Donovan JL, Hamdy FC, Martin RM, Nordestgaard BG, Nielsen SF, Weischer M, Bojesen SE, Røder MA, Iversen P, Batra J, Chambers S, Moya L, Horvath L, Clements JA, Tilley W, Risbridger GP, Gronberg H, Aly M, Szulkin R, Eklund M, Nordström T, Pashayan N, Dunning AM, Ghoussaini M, Travis RC, Key TJ, Riboli E, Park JY, Sellers TA, Lin HY, Albanes D, Weinstein SJ, Mucci LA, Giovannucci E, Lindstrom S, Kraft P, Hunter DJ, Penney KL, Turman C, Tangen CM, Goodman PJ, Thompson IM, Hamilton RJ, Fleshner NE, Finelli A, Parent MÉ, Stanford JL, Ostrander EA, Geybels MS, Koutros S, Freeman LEB, Stampfer M, Wolk A, Håkansson N, Andriole GL, Hoover RN, Machiela MJ, Sørensen KD, Borre M, Blot WJ, Zheng W, Yeboah ED, Mensah JE, Lu YJ, Zhang HW, Feng N, Mao X, Wu Y, Zhao SC, Sun Z, Thibodeau SN, McDonnell SK, Schaid DJ, West CML, Burnet N, Barnett G, Maier C, Schnoeller T, Luedeke M, Kibel AS, Drake BF, Cussenot O, Cancel-Tassin G, Menegaux F, Truong T, Koudou YA, John EM, Grindedal EM, Maehle L, Khaw KT, Ingles SA, Stern MC, Vega A, Gómez-Caamaño A, Fachal L, Rosenstein BS, Kerns SL, Ostrer H, Teixeira MR, Paulo P, Brandão A, Watya S, Lubwama A, Bensen JT, Fontham ETH, Mohler J, Taylor JA, Kogevinas M, Llorca J, Castaño-Vinyals G, Cannon-Albright L, Teerlink CC, Huff CD, Strom SS, Multigner L, Blanchet P, Brureau L, Kaneva R, Slavov C, Mitev V, Leach RJ, Weaver B, Brenner H, Cuk K, Holleczek B, Saum KU, Klein EA, Hsing AW, Kittles RA, Murphy AB, Logothetis CJ, Kim J, Neuhausen SL, Steele L, Ding YC, Isaacs WB, Nemesure B, Hennis AJM, Carpten J, Pandha H, Michael A, De Ruyck K, De Meerleer G, Ost P, Xu J, Razack A, Lim J, Teo SH, Newcomb LF, Lin DW, Fowke JH, Neslund-Dudas C, Rybicki BA, Gamulin M, Lessel D, Kulis T, Usmani N, Singhal S, Parliament M, Claessens F, Joniau S, Van den Broeck T, Gago-Dominguez M, Castelao JE, Martinez ME, Larkin S, Townsend PA, Aukim-Hastie C, Bush WS, Aldrich MC, Crawford DC, Srivastava S, Cullen JC, Petrovics G, Casey G, Roobol MJ, Jenster G, van Schaik RHN, Hu JJ, Sanderson M, Varma R, McKean-Cowdin R, Torres M, Mancuso N, Berndt SI, Van Den Eeden SK, Easton DF, Chanock SJ, Cook MB, Wiklund F, Nakagawa H, Witte JS, Eeles RA, Kote-Jarai Z, Haiman CA. Publisher Correction: Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction. Nat Genet 2021; 53:413. [PMID: 33473200 DOI: 10.1038/s41588-021-00786-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Kapoor PM, Mavaddat N, Choudhury PP, Wilcox AN, Lindström S, Behrens S, Michailidou K, Dennis J, Bolla MK, Wang Q, Jung A, Abu-Ful Z, Ahearn T, Andrulis IL, Anton-Culver H, Arndt V, Aronson KJ, Auer PL, Freeman LEB, Becher H, Beckmann MW, Beeghly-Fadiel A, Benitez J, Bernstein L, Bojesen SE, Brauch H, Brenner H, Brüning T, Cai Q, Campa D, Canzian F, Carracedo A, Carter BD, Castelao JE, Chanock SJ, Chatterjee N, Chenevix-Trench G, Clarke CL, Couch FJ, Cox A, Cross SS, Czene K, Dai JY, Earp HS, Ekici AB, Eliassen AH, Eriksson M, Evans DG, Fasching PA, Figueroa J, Fritschi L, Gabrielson M, Gago-Dominguez M, Gao C, Gapstur SM, Gaudet MM, Giles GG, González-Neira A, Guénel P, Haeberle L, Haiman CA, Håkansson N, Hall P, Hamann U, Hatse S, Heyworth J, Holleczek B, Hoover RN, Hopper JL, Howell A, Hunter DJ, John EM, Jones ME, Kaaks R, Keeman R, Kitahara CM, Ko YD, Koutros S, Kurian AW, Lambrechts D, Le Marchand L, Lee E, Lejbkowicz F, Linet M, Lissowska J, Llaneza A, MacInnis RJ, Martinez ME, Maurer T, McLean C, Neuhausen SL, Newman WG, Norman A, O’Brien KM, Olshan AF, Olson JE, Olsson H, Orr N, Perou CM, Pita G, Polley EC, Prentice RL, Rennert G, Rennert HS, Ruddy KJ, Sandler DP, Saunders C, Schoemaker MJ, Schöttker B, Schumacher F, Scott C, Scott RJ, Shu XO, Smeets A, Southey MC, Spinelli JJ, Stone J, Swerdlow AJ, Tamimi RM, Taylor JA, Troester MA, Vachon CM, van Veen EM, Wang X, Weinberg CR, Weltens C, Willett W, Winham SJ, Wolk A, Yang XR, Zheng W, Ziogas A, Dunning AM, Pharoah PDP, Schmidt MK, Kraft P, Easton DF, Milne RL, García-Closas M, Chang-Claude J. Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk. J Natl Cancer Inst 2021; 113:329-337. [PMID: 32359158 PMCID: PMC7936056 DOI: 10.1093/jnci/djaa056] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 03/30/2020] [Accepted: 04/23/2020] [Indexed: 01/01/2023] Open
Abstract
We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.
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Coignard J, Lush M, Beesley J, O'Mara TA, Dennis J, Tyrer JP, Barnes DR, McGuffog L, Leslie G, Bolla MK, Adank MA, Agata S, Ahearn T, Aittomäki K, Andrulis IL, Anton-Culver H, Arndt V, Arnold N, Aronson KJ, Arun BK, Augustinsson A, Azzollini J, Barrowdale D, Baynes C, Becher H, Bermisheva M, Bernstein L, Białkowska K, Blomqvist C, Bojesen SE, Bonanni B, Borg A, Brauch H, Brenner H, Burwinkel B, Buys SS, Caldés T, Caligo MA, Campa D, Carter BD, Castelao JE, Chang-Claude J, Chanock SJ, Chung WK, Claes KBM, Clarke CL, Collée JM, Conroy DM, Czene K, Daly MB, Devilee P, Diez O, Ding YC, Domchek SM, Dörk T, Dos-Santos-Silva I, Dunning AM, Dwek M, Eccles DM, Eliassen AH, Engel C, Eriksson M, Evans DG, Fasching PA, Flyger H, Fostira F, Friedman E, Fritschi L, Frost D, Gago-Dominguez M, Gapstur SM, Garber J, Garcia-Barberan V, García-Closas M, García-Sáenz JA, Gaudet MM, Gayther SA, Gehrig A, Georgoulias V, Giles GG, Godwin AK, Goldberg MS, Goldgar DE, González-Neira A, Greene MH, Guénel P, Haeberle L, Hahnen E, Haiman CA, Håkansson N, Hall P, Hamann U, Harrington PA, Hart SN, He W, Hogervorst FBL, Hollestelle A, Hopper JL, Horcasitas DJ, Hulick PJ, Hunter DJ, Imyanitov EN, Jager A, Jakubowska A, James PA, Jensen UB, John EM, Jones ME, Kaaks R, Kapoor PM, Karlan BY, Keeman R, Khusnutdinova E, Kiiski JI, Ko YD, Kosma VM, Kraft P, Kurian AW, Laitman Y, Lambrechts D, Le Marchand L, Lester J, Lesueur F, Lindstrom T, Lopez-Fernández A, Loud JT, Luccarini C, Mannermaa A, Manoukian S, Margolin S, Martens JWM, Mebirouk N, Meindl A, Miller A, Milne RL, Montagna M, Nathanson KL, Neuhausen SL, Nevanlinna H, Nielsen FC, O'Brien KM, Olopade OI, Olson JE, Olsson H, Osorio A, Ottini L, Park-Simon TW, Parsons MT, Pedersen IS, Peshkin B, Peterlongo P, Peto J, Pharoah PDP, Phillips KA, Polley EC, Poppe B, Presneau N, Pujana MA, Punie K, Radice P, Rantala J, Rashid MU, Rennert G, Rennert HS, Robson M, Romero A, Rossing M, Saloustros E, Sandler DP, Santella R, Scheuner MT, Schmidt MK, Schmidt G, Scott C, Sharma P, Soucy P, Southey MC, Spinelli JJ, Steinsnyder Z, Stone J, Stoppa-Lyonnet D, Swerdlow A, Tamimi RM, Tapper WJ, Taylor JA, Terry MB, Teulé A, Thull DL, Tischkowitz M, Toland AE, Torres D, Trainer AH, Truong T, Tung N, Vachon CM, Vega A, Vijai J, Wang Q, Wappenschmidt B, Weinberg CR, Weitzel JN, Wendt C, Wolk A, Yadav S, Yang XR, Yannoukakos D, Zheng W, Ziogas A, Zorn KK, Park SK, Thomassen M, Offit K, Schmutzler RK, Couch FJ, Simard J, Chenevix-Trench G, Easton DF, Andrieu N, Antoniou AC. A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers. Nat Commun 2021; 12:1078. [PMID: 33597508 PMCID: PMC7890067 DOI: 10.1038/s41467-020-20496-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Accepted: 11/19/2020] [Indexed: 02/02/2023] Open
Abstract
Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10-8, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers.
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Nguyen-Dumont T, Dowty J, Tucker K, Kirk J, James P, Trainer A, Winship I, Pachter N, Poplawski N, Grist S, Park DJ, Renault AL, Hammet F, Mahmoodi M, Tsimiklis H, Steen JA, Theys D, Rewse A, Willis A, Morrow A, Speechly C, Harris R, Riaz M, Sebra R, Schadt E, Lacaze P, McNeil J, Hopper JL, Southey MC. Abstract PS7-04: Population-based estimates of breast cancer risk for germline pathogenic variants identified by gene-panel testing: An Australian perspective. Cancer Res 2021. [DOI: 10.1158/1538-7445.sabcs20-ps7-04] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
BRA-STRAP is an Australia-wide study of breast cancer predisposition that brings together gene-panel data from 30,000 adult Australian women of all ages, across the breast cancer risk spectrum, with and without a diagnosis of breast cancer. The “BRA-STRAP panel” includes 24 genes* that are involved in, or putatively associated with, predisposition to breast and/or ovarian cancer. Despite insufficient evidence for clinical translation for some of these genes, all 24 are commonly included on panel tests for breast cancer predisposition.
We present findings from the population-based case-control sub-study of BRA-STRAP, which involved 1451 women diagnosed with breast cancer and 857 age-matched controls participating in the Australian Breast Cancer Family Registry (ABCFR), and 6101 healthy, elderly Australian women enrolled in the ASPREE study. These analyses focus on rare genetic variants predicted to lead to loss of function and/or classified as pathogenic/likely pathogenic (P/LP) in ClinVar. Odds ratios (ORs) for their associations with breast cancer were estimated by aggregating genetic variants for each gene.
For the women diagnosed with breast cancer, the median age at diagnosis (inter-quartile range, IQR) was 40.0 (14.0) years and the overall frequency of P/LP variant carriers across all genes was 156/1451 (10.8%). The median age (IQR) of the ABCFR and ASPREE controls were 39.4 (14.9) and 73.9 (5.8) years, respectively. The frequencies of P/LP variant carriers were 33/857 (3.9%) and 268/6101 (4.4%) in the ABCFR and ASPREE controls, respectively. We combined both control datasets and, after adjusting for age and other potential confounders, the ORs associated with P/LP variants in BRCA1 and BRCA2 were 4.1 [95% confidence interval (CI): 1.8-10.2] and 2.9 [95% CI: 1.5-6], respectively. We also found that the OR for P/LP variants in ATM was 4.0 [95% CI: 1.5-10.4] and the OR for P/LP variants in PALB2 was 2.2 [95% CI: 0.75-5.7] although this did not reach statistical significance.
These results contribute to international efforts to refine the breast cancer risk estimates for genetic variants identified from population-based screening of unselected women using genes that are included on panel tests and thought to be potentially breast cancer predisposition genes.The case-control-family design of the ABCFR will also allow us to estimate the age specific cumulative risk (penetrance) of these genetic variants, which is important for genetic counselling and the clinical management of carrier families.
*ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, FANCM, MLH1, MRE11A, MSH2, MSH6, MUTYH, NBN, NF1, PALB2, PMS2, PTEN, RAD50, RAD51C, RAD51D, RECQL, STK11 and TP53
Citation Format: Tu Nguyen-Dumont, James Dowty, Katherine Tucker, Judy Kirk, Paul James, Alison Trainer, Ingrid Winship, Nicholas Pachter, Nicola Poplawski, Scott Grist, Daniel J Park, Anne-Laure Renault, Fleur Hammet, Maryam Mahmoodi, Helen Tsimiklis, Jason A Steen, Derrick Theys, Amanda Rewse, Amanda Willis, April Morrow, Catherine Speechly, Rebecca Harris, Moeen Riaz, Robert Sebra, Eric Schadt, Paul Lacaze, John McNeil, John L Hopper, Melissa C Southey. Population-based estimates of breast cancer risk for germline pathogenic variants identified by gene-panel testing: An Australian perspective [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-04.
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Dorling L, Carvalho S, Allen J, González-Neira A, Luccarini C, Wahlström C, Pooley KA, Parsons MT, Fortuno C, Wang Q, Bolla MK, Dennis J, Keeman R, Alonso MR, Álvarez N, Herraez B, Fernandez V, Núñez-Torres R, Osorio A, Valcich J, Li M, Törngren T, Harrington PA, Baynes C, Conroy DM, Decker B, Fachal L, Mavaddat N, Ahearn T, Aittomäki K, Antonenkova NN, Arnold N, Arveux P, Ausems MGEM, Auvinen P, Becher H, Beckmann MW, Behrens S, Bermisheva M, Białkowska K, Blomqvist C, Bogdanova NV, Bogdanova-Markov N, Bojesen SE, Bonanni B, Børresen-Dale AL, Brauch H, Bremer M, Briceno I, Brüning T, Burwinkel B, Cameron DA, Camp NJ, Campbell A, Carracedo A, Castelao JE, Cessna MH, Chanock SJ, Christiansen H, Collée JM, Cordina-Duverger E, Cornelissen S, Czene K, Dörk T, Ekici AB, Engel C, Eriksson M, Fasching PA, Figueroa J, Flyger H, Försti A, Gabrielson M, Gago-Dominguez M, Georgoulias V, Gil F, Giles GG, Glendon G, Garcia EBG, Alnæs GIG, Guénel P, Hadjisavvas A, Haeberle L, Hahnen E, Hall P, Hamann U, Harkness EF, Hartikainen JM, Hartman M, He W, Heemskerk-Gerritsen BAM, Hillemanns P, Hogervorst FBL, Hollestelle A, Ho WK, Hooning MJ, Howell A, Humphreys K, Idris F, Jakubowska A, Jung A, Kapoor PM, Kerin MJ, Khusnutdinova E, Kim SW, Ko YD, Kosma VM, Kristensen VN, Kyriacou K, Lakeman IMM, Lee JW, Lee MH, Li J, Lindblom A, Lo WY, Loizidou MA, Lophatananon A, Lubiński J, MacInnis RJ, Madsen MJ, Mannermaa A, Manoochehri M, Manoukian S, Margolin S, Martinez ME, Maurer T, Mavroudis D, McLean C, Meindl A, Mensenkamp AR, Michailidou K, Miller N, Mohd Taib NA, Muir K, Mulligan AM, Nevanlinna H, Newman WG, Nordestgaard BG, Ng PS, Oosterwijk JC, Park SK, Park-Simon TW, Perez JIA, Peterlongo P, Porteous DJ, Prajzendanc K, Prokofyeva D, Radice P, Rashid MU, Rhenius V, Rookus MA, Rüdiger T, Saloustros E, Sawyer EJ, Schmutzler RK, Schneeweiss A, Schürmann P, Shah M, Sohn C, Southey MC, Surowy H, Suvanto M, Thanasitthichai S, Tomlinson I, Torres D, Truong T, Tzardi M, Valova Y, van Asperen CJ, Van Dam RM, van den Ouweland AMW, van der Kolk LE, van Veen EM, Wendt C, Williams JA, Yang XR, Yoon SY, Zamora MP, Evans DG, de la Hoya M, Simard J, Antoniou AC, Borg Å, Andrulis IL, Chang-Claude J, García-Closas M, Chenevix-Trench G, Milne RL, Pharoah PDP, Schmidt MK, Spurdle AB, Vreeswijk MPG, Benitez J, Dunning AM, Kvist A, Teo SH, Devilee P, Easton DF. Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women. N Engl J Med 2021; 384:428-439. [PMID: 33471991 PMCID: PMC7611105 DOI: 10.1056/nejmoa1913948] [Citation(s) in RCA: 432] [Impact Index Per Article: 144.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Genetic 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. METHODS We 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. RESULTS Protein-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. CONCLUSIONS The 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.).
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Johnson N, Maguire S, Morra A, Kapoor PM, Tomczyk K, Jones ME, Schoemaker MJ, Gilham C, Bolla MK, Wang Q, Dennis J, Ahearn TU, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Augustinsson A, Baynes C, Freeman LEB, Beckmann MW, Benitez J, Bermisheva M, Blomqvist C, Boeckx B, Bogdanova NV, Bojesen SE, Brauch H, Brenner H, Burwinkel B, Campa D, Canzian F, Castelao JE, Chanock SJ, Chenevix-Trench G, Clarke CL, Conroy DM, Couch FJ, Cox A, Cross SS, Czene K, Dörk T, Eliassen AH, Engel C, Evans DG, Fasching PA, Figueroa J, Floris G, Flyger H, Gago-Dominguez M, Gapstur SM, García-Closas M, Gaudet MM, Giles GG, Goldberg MS, González-Neira A, Guénel P, Hahnen E, Haiman CA, Håkansson N, Hall P, Hamann U, Harrington PA, Hart SN, Hooning MJ, Hopper JL, Howell A, Hunter DJ, Jager A, Jakubowska A, John EM, Kaaks R, Keeman R, Khusnutdinova E, Kitahara CM, Kosma VM, Koutros S, Kraft P, Kristensen VN, Kurian AW, Lambrechts D, Le Marchand L, Linet M, Lubiński J, Mannermaa A, Manoukian S, Margolin S, Martens JWM, Mavroudis D, Mayes R, Meindl A, Milne RL, Neuhausen SL, Nevanlinna H, Newman WG, Nielsen SF, Nordestgaard BG, Obi N, Olshan AF, Olson JE, Olsson H, Orban E, Park-Simon TW, Peterlongo P, Plaseska-Karanfilska D, Pylkäs K, Rennert G, Rennert HS, Ruddy KJ, Saloustros E, Sandler DP, Sawyer EJ, Schmutzler RK, Scott C, Shu XO, Simard J, Smichkoska S, Sohn C, Southey MC, Spinelli JJ, Stone J, Tamimi RM, Taylor JA, Tollenaar RAEM, Tomlinson I, Troester MA, Truong T, Vachon CM, van Veen EM, Wang SS, Weinberg CR, Wendt C, Wildiers H, Winqvist R, Wolk A, Zheng W, Ziogas A, Dunning AM, Pharoah PDP, Easton DF, Howie AF, Peto J, Dos-Santos-Silva I, Swerdlow AJ, Chang-Claude J, Schmidt MK, Orr N, Fletcher O. CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers. Br J Cancer 2021; 124:842-854. [PMID: 33495599 PMCID: PMC7884683 DOI: 10.1038/s41416-020-01185-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 10/21/2020] [Accepted: 11/05/2020] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk. METHODS We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry. RESULTS For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10-18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10-8). CONCLUSIONS The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.
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Suman M, Dugué PA, Wong EM, Joo JE, Hopper JL, Nguyen-Dumont T, Giles GG, Milne RL, McLean C, Southey MC. Association of variably methylated tumour DNA regions with overall survival for invasive lobular breast cancer. Clin Epigenetics 2021; 13:11. [PMID: 33461604 PMCID: PMC7814464 DOI: 10.1186/s13148-020-00975-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 11/10/2020] [Indexed: 12/12/2022] Open
Abstract
Background Tumour DNA methylation profiling has shown potential to refine disease subtyping and improve the diagnosis and prognosis prediction of breast cancer. However, limited data exist regarding invasive lobular breast cancer (ILBC). Here, we investigated the genome-wide variability of DNA methylation levels across ILBC tumours and assessed the association between methylation levels at the variably methylated regions and overall survival in women with ILBC. Methods Tumour-enriched DNA was prepared by macrodissecting formalin-fixed paraffin embedded (FFPE) tumour tissue from 130 ILBCs diagnosed in the participants of the Melbourne Collaborative Cohort Study (MCCS). Genome-wide tumour DNA methylation was measured using the HumanMethylation 450K (HM450K) BeadChip array. Variably methylated regions (VMRs) were identified using the DMRcate package in R. Cox proportional hazards regression models were used to assess the association between methylation levels at the ten most significant VMRs and overall survival. Gene set enrichment analyses were undertaken using the web-based tool Metaspace. Replication of the VMR and survival analysis findings was examined using data retrieved from The Cancer Genome Atlas (TCGA) for 168 ILBC cases. We also examined the correlation between methylation and gene expression for the ten VMRs of interest using TCGA data. Results We identified 2771 VMRs (P < 10−8) in ILBC tumours. The ten most variably methylated clusters were predominantly located in the promoter region of the genes: ISM1, APC, TMEM101, ASCL2, NKX6, HIST3H2A/HIST3H2BB, HCG4P3, HES5, CELF2 and EFCAB4B. Higher methylation level at several of these VMRs showed an association with reduced overall survival in the MCCS. In TCGA, all associations were in the same direction, however stronger than in the MCCS. The pooled analysis of the MCCS and TCGA data showed that methylation at four of the ten genes was associated with reduced overall survival, independently of age and tumour stage; APC: Hazard Ratio (95% Confidence interval) per one-unit M-value increase: 1.18 (1.02–1.36), TMEM101: 1.23 (1.02–1.48), HCG4P3: 1.37 (1.05–1.79) and CELF2: 1.21 (1.02–1.43). A negative correlation was observed between methylation and gene expression for CELF2 (R = − 0.25, P = 0.001), but not for TMEM101 and APC. Conclusions Our study identified regions showing greatest variability across the ILBC tumour genome and found methylation at several genes to potentially serve as a biomarker of survival for women with ILBC.
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Kho PF, Amant F, Annibali D, Ashton K, Attia J, Auer PL, Beckmann MW, Black A, Brinton L, Buchanan DD, Chanock SJ, Chen C, Chen MM, Cheng THT, Cook LS, Crous-Bous M, Czene K, De Vivo I, Dennis J, Dörk T, Dowdy SC, Dunning AM, Dürst M, Easton DF, Ekici AB, Fasching PA, Fridley BL, Friedenreich CM, García-Closas M, Gaudet MM, Giles GG, Goode EL, Gorman M, Haiman CA, Hall P, Hankinson SE, Hein A, Hillemanns P, Hodgson S, Hoivik EA, Holliday EG, Hunter DJ, Jones A, Kraft P, Krakstad C, Lambrechts D, Le Marchand L, Liang X, Lindblom A, Lissowska J, Long J, Lu L, Magliocco AM, Martin L, McEvoy M, Milne RL, Mints M, Nassir R, Otton G, Palles C, Pooler L, Proietto T, Rebbeck TR, Renner SP, Risch HA, Rübner M, Runnebaum I, Sacerdote C, Sarto GE, Schumacher F, Scott RJ, Setiawan VW, Shah M, Sheng X, Shu XO, Southey MC, Tham E, Tomlinson I, Trovik J, Turman C, Tyrer JP, Van Den Berg D, Wang Z, Wentzensen N, Xia L, Xiang YB, Yang HP, Yu H, Zheng W, Webb PM, Thompson DJ, Spurdle AB, Glubb DM, O'Mara TA. Mendelian randomization analyses suggest a role for cholesterol in the development of endometrial cancer. Int J Cancer 2021; 148:307-319. [PMID: 32851660 PMCID: PMC7757859 DOI: 10.1002/ijc.33206] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 05/08/2020] [Accepted: 05/26/2020] [Indexed: 01/14/2023]
Abstract
Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P < 5 × 10-8 ) were identified as instrumental variables, and assessed using genome-wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non-endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non-endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non-endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non-endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.
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Karlsson Q, Brook MN, Dadaev T, Wakerell S, Saunders EJ, Muir K, Neal DE, Giles GG, MacInnis RJ, Thibodeau SN, McDonnell SK, Cannon-Albright L, Teixeira MR, Paulo P, Cardoso M, Huff C, Li D, Yao Y, Scheet P, Permuth JB, Stanford JL, Dai JY, Ostrander EA, Cussenot O, Cancel-Tassin G, Hoegel J, Herkommer K, Schleutker J, Tammela TLJ, Rathinakannan V, Sipeky C, Wiklund F, Grönberg H, Aly M, Isaacs WB, Dickinson JL, FitzGerald LM, Chua MLK, Nguyen-Dumont T, Schaid DJ, Southey MC, Eeles RA, Kote-Jarai Z. Rare Germline Variants in ATM Predispose to Prostate Cancer: A PRACTICAL Consortium Study. Eur Urol Oncol 2021; 4:570-579. [PMID: 33436325 PMCID: PMC8381233 DOI: 10.1016/j.euo.2020.12.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 11/23/2020] [Accepted: 12/01/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND Germline ATM mutations are suggested to contribute to predisposition to prostate cancer (PrCa). Previous studies have had inadequate power to estimate variant effect sizes. OBJECTIVE To precisely estimate the contribution of germline ATM mutations to PrCa risk. DESIGN, SETTING, AND PARTICIPANTS We analysed next-generation sequencing data from 13 PRACTICAL study groups comprising 5560 cases and 3353 controls of European ancestry. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Variant Call Format files were harmonised, annotated for rare ATM variants, and classified as tier 1 (likely pathogenic) or tier 2 (potentially deleterious). Associations with overall PrCa risk and clinical subtypes were estimated. RESULTS AND LIMITATIONS PrCa risk was higher in carriers of a tier 1 germline ATM variant, with an overall odds ratio (OR) of 4.4 (95% confidence interval [CI]: 2.0-9.5). There was also evidence that PrCa cases with younger age at diagnosis (<65 yr) had elevated tier 1 variant frequencies (pdifference = 0.04). Tier 2 variants were also associated with PrCa risk, with an OR of 1.4 (95% CI: 1.1-1.7). CONCLUSIONS Carriers of pathogenic ATM variants have an elevated risk of developing PrCa and are at an increased risk for earlier-onset disease presentation. These results provide information for counselling of men and their families. PATIENT SUMMARY In this study, we estimated that men who inherit a likely pathogenic mutation in the ATM gene had an approximately a fourfold risk of developing prostate cancer. In addition, they are likely to develop the disease earlier.
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Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, Schumacher FR, Olama AAA, Benlloch S, Dadaev T, Brook MN, Sahimi A, Hoffmann TJ, Takahashi A, Matsuda K, Momozawa Y, Fujita M, Muir K, Lophatananon A, Wan P, Le Marchand L, Wilkens LR, Stevens VL, Gapstur SM, Carter BD, Schleutker J, Tammela TLJ, Sipeky C, Auvinen A, Giles GG, Southey MC, MacInnis RJ, Cybulski C, Wokołorczyk D, Lubiński J, Neal DE, Donovan JL, Hamdy FC, Martin RM, Nordestgaard BG, Nielsen SF, Weischer M, Bojesen SE, Røder MA, Iversen P, Batra J, Chambers S, Moya L, Horvath L, Clements JA, Tilley W, Risbridger GP, Gronberg H, Aly M, Szulkin R, Eklund M, Nordström T, Pashayan N, Dunning AM, Ghoussaini M, Travis RC, Key TJ, Riboli E, Park JY, Sellers TA, Lin HY, Albanes D, Weinstein SJ, Mucci LA, Giovannucci E, Lindstrom S, Kraft P, Hunter DJ, Penney KL, Turman C, Tangen CM, Goodman PJ, Thompson IM, Hamilton RJ, Fleshner NE, Finelli A, Parent MÉ, Stanford JL, Ostrander EA, Geybels MS, Koutros S, Freeman LEB, Stampfer M, Wolk A, Håkansson N, Andriole GL, Hoover RN, Machiela MJ, Sørensen KD, Borre M, Blot WJ, Zheng W, Yeboah ED, Mensah JE, Lu YJ, Zhang HW, Feng N, Mao X, Wu Y, Zhao SC, Sun Z, Thibodeau SN, McDonnell SK, Schaid DJ, West CML, Burnet N, Barnett G, Maier C, Schnoeller T, Luedeke M, Kibel AS, Drake BF, Cussenot O, Cancel-Tassin G, Menegaux F, Truong T, Koudou YA, John EM, Grindedal EM, Maehle L, Khaw KT, Ingles SA, Stern MC, Vega A, Gómez-Caamaño A, Fachal L, Rosenstein BS, Kerns SL, Ostrer H, Teixeira MR, Paulo P, Brandão A, Watya S, Lubwama A, Bensen JT, Fontham ETH, Mohler J, Taylor JA, Kogevinas M, Llorca J, Castaño-Vinyals G, Cannon-Albright L, Teerlink CC, Huff CD, Strom SS, Multigner L, Blanchet P, Brureau L, Kaneva R, Slavov C, Mitev V, Leach RJ, Weaver B, Brenner H, Cuk K, Holleczek B, Saum KU, Klein EA, Hsing AW, Kittles RA, Murphy AB, Logothetis CJ, Kim J, Neuhausen SL, Steele L, Ding YC, Isaacs WB, Nemesure B, Hennis AJM, Carpten J, Pandha H, Michael A, De Ruyck K, De Meerleer G, Ost P, Xu J, Razack A, Lim J, Teo SH, Newcomb LF, Lin DW, Fowke JH, Neslund-Dudas C, Rybicki BA, Gamulin M, Lessel D, Kulis T, Usmani N, Singhal S, Parliament M, Claessens F, Joniau S, Van den Broeck T, Gago-Dominguez M, Castelao JE, Martinez ME, Larkin S, Townsend PA, Aukim-Hastie C, Bush WS, Aldrich MC, Crawford DC, Srivastava S, Cullen JC, Petrovics G, Casey G, Roobol MJ, Jenster G, van Schaik RHN, Hu JJ, Sanderson M, Varma R, McKean-Cowdin R, Torres M, Mancuso N, Berndt SI, Van Den Eeden SK, Easton DF, Chanock SJ, Cook MB, Wiklund F, Nakagawa H, Witte JS, Eeles RA, Kote-Jarai Z, Haiman CA. Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction. Nat Genet 2021; 53:65-75. [PMID: 33398198 PMCID: PMC8148035 DOI: 10.1038/s41588-020-00748-0] [Citation(s) in RCA: 205] [Impact Index Per Article: 68.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 11/05/2020] [Indexed: 01/28/2023]
Abstract
Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.
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Dugué PA, Wilson R, Lehne B, Jayasekara H, Wang X, Jung CH, Joo JE, Makalic E, Schmidt DF, Baglietto L, Severi G, Gieger C, Ladwig KH, Peters A, Kooner JS, Southey MC, English DR, Waldenberger M, Chambers JC, Giles GG, Milne RL. Alcohol consumption is associated with widespread changes in blood DNA methylation: Analysis of cross-sectional and longitudinal data. Addict Biol 2021; 26:e12855. [PMID: 31789449 DOI: 10.1111/adb.12855] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 09/29/2019] [Accepted: 11/04/2019] [Indexed: 12/26/2022]
Abstract
DNA methylation may be one of the mechanisms by which alcohol consumption is associated with the risk of disease. We conducted a large-scale, cross-sectional, genome-wide DNA methylation association study of alcohol consumption and a longitudinal analysis of repeated measurements taken several years apart. Using the Illumina HumanMethylation450 BeadChip, DNA methylation was measured in blood samples from 5606 Melbourne Collaborative Cohort Study (MCCS) participants. For 1088 of them, these measures were repeated using blood samples collected a median of 11 years later. Associations between alcohol intake and blood DNA methylation were assessed using linear mixed-effects regression models. Independent data from the London Life Sciences Prospective Population (LOLIPOP) (N = 4042) and Cooperative Health Research in the Augsburg Region (KORA) (N = 1662) cohorts were used to replicate associations discovered in the MCCS. Cross-sectional analyses identified 1414 CpGs associated with alcohol intake at P < 10-7 , 1243 of which had not been reported previously. Of these novel associations, 1078 were replicated (P < .05) using LOLIPOP and KORA data. Using the MCCS data, we also replicated 403 of 518 previously reported associations. Interaction analyses suggested that associations were stronger for women, non-smokers, and participants genetically predisposed to consume less alcohol. Of the 1414 CpGs, 530 were differentially methylated (P < .05) in former compared with current drinkers. Longitudinal associations between the change in alcohol intake and the change in methylation were observed for 513 of the 1414 cross-sectional associations. Our study indicates that alcohol intake is associated with widespread changes in DNA methylation across the genome. Longitudinal analyses showed that the methylation status of alcohol-associated CpGs may change with alcohol consumption changes in adulthood.
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MacInnis RJ, Knight JA, Chung WK, Milne RL, Whittemore AS, Buchsbaum R, Liao Y, Zeinomar N, Dite GS, Southey MC, Goldgar D, Giles GG, Kurian AW, Andrulis IL, John EM, Daly MB, Buys SS, Phillips KA, Hopper JL, Terry MB. Comparing 5-Year and Lifetime Risks of Breast Cancer using the Prospective Family Study Cohort. J Natl Cancer Inst 2020; 113:785-791. [PMID: 33301022 DOI: 10.1093/jnci/djaa178] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 08/06/2020] [Accepted: 10/13/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Clinical guidelines often use predicted lifetime risk from birth to define criteria for making decisions regarding breast cancer screening rather than thresholds based on absolute 5-year risk from current age. METHODS We used the Prospective Family Cohort Study of 14 657 women without breast cancer at baseline in which, during a median follow-up of 10 years, 482 women were diagnosed with invasive breast cancer. We examined the performances of the International Breast Cancer Intervention Study (IBIS) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk models when using the alternative thresholds by comparing predictions based on 5-year risk with those based on lifetime risk from birth and remaining lifetime risk. All statistical tests were 2-sided. RESULTS Using IBIS, the areas under the receiver-operating characteristic curves were 0.66 (95% confidence interval = 0.63 to 0.68) and 0.56 (95% confidence interval = 0.54 to 0.59) for 5-year and lifetime risks, respectively (Pdiff < .001). For equivalent sensitivities, the 5-year incidence almost always had higher specificities than lifetime risk from birth. For women aged 20-39 years, 5-year risk performed better than lifetime risk from birth. For women aged 40 years or older, receiver-operating characteristic curves were similar for 5-year and lifetime IBIS risk from birth. Classifications based on remaining lifetime risk were inferior to 5-year risk estimates. Results were similar using BOADICEA. CONCLUSIONS Our analysis shows that risk stratification using clinical models will likely be more accurate when based on predicted 5-year risk compared with risks based on predicted lifetime and remaining lifetime, particularly for women aged 20-39 years.
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Nguyen TL, Schmidt DF, Makalic E, Maskarinec G, Li S, Dite GS, Aung YK, Evans CF, Trinh HN, Baglietto L, Stone J, Song YM, Sung J, MacInnis RJ, Dugué PA, Dowty JG, Jenkins MA, Milne RL, Southey MC, Giles GG, Hopper JL. Novel mammogram-based measures improve breast cancer risk prediction beyond an established mammographic density measure. Int J Cancer 2020; 148:2193-2202. [PMID: 33197272 DOI: 10.1002/ijc.33396] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 10/28/2020] [Accepted: 11/02/2020] [Indexed: 12/11/2022]
Abstract
Mammograms contain information that predicts breast cancer risk. We developed two novel mammogram-based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). Their risk prediction when fitted together, and with an established measure of conventional mammographic density (Cumulus), is not known. We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen-detected cases and 1197 matched controls; and 354 younger-diagnosis cases and 944 controls frequency-matched for age at mammogram. We conducted conditional and unconditional logistic regression analyses of individually- and frequency-matched studies, respectively. We estimated measure-specific risk gradients as the change in odds per standard deviation of controls after adjusting for age and body mass index (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). For interval, screen-detected and younger-diagnosis cancer risks, the best fitting models (OPERAs [95% confidence intervals]) involved: Cumulus (1.81 [1.41-2.31]) and Cirrus (1.72 [1.38-2.14]); Cirrus (1.49 [1.32-1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27-1.68]), respectively. The AUCs were: 0.73 [0.68-0.77], 0.63 [0.60-0.66], and 0.72 [0.69-0.75], respectively. Combined, our new mammogram-based measures have twice the risk gradient for screen-detected and younger-diagnosis breast cancer (P ≤ 10-12 ), have at least the same discriminatory power as the current polygenic risk score, and are more correlated with causal factors than conventional mammographic density. Discovering more information about breast cancer risk from mammograms could help enable risk-based personalised breast screening.
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Dugué PA, Bassett JK, Wong EM, Joo JE, Li S, Yu C, Schmidt DF, Makalic E, Doo NW, Buchanan DD, Hodge AM, English DR, Hopper JL, Giles GG, Southey MC, Milne RL. Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study. JNCI Cancer Spectr 2020; 5:pkaa109. [PMID: 33442664 PMCID: PMC7791618 DOI: 10.1093/jncics/pkaa109] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 09/16/2020] [Accepted: 10/29/2020] [Indexed: 02/07/2023] Open
Abstract
Background We previously investigated the association between 5 "first-generation" measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length. Methods We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity. Results We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively). Conclusions The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.
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Kramer I, Hooning MJ, Mavaddat N, Hauptmann M, Keeman R, Steyerberg EW, Giardiello D, Antoniou AC, Pharoah PDP, Canisius S, Abu-Ful Z, Andrulis IL, Anton-Culver H, Aronson KJ, Augustinsson A, Becher H, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bogdanova NV, Bojesen SE, Bolla MK, Bonanni B, Brauch H, Bremer M, Brucker SY, Burwinkel B, Castelao JE, Chan TL, Chang-Claude J, Chanock SJ, Chenevix-Trench G, Choi JY, Clarke CL, Collée JM, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dos-Santos-Silva I, Dunning AM, Dwek M, Eccles DM, Evans DG, Fasching PA, Flyger H, Gago-Dominguez M, García-Closas M, García-Sáenz JA, Giles GG, Goldgar DE, González-Neira A, Haiman CA, Håkansson N, Hamann U, Hartman M, Heemskerk-Gerritsen BAM, Hollestelle A, Hopper JL, Hou MF, Howell A, Ito H, Jakimovska M, Jakubowska A, Janni W, John EM, Jung A, Kang D, Kets CM, Khusnutdinova E, Ko YD, Kristensen VN, Kurian AW, Kwong A, Lambrechts D, Le Marchand L, Li J, Lindblom A, Lubiński J, Mannermaa A, Manoochehri M, Margolin S, Matsuo K, Mavroudis D, Meindl A, Milne RL, Mulligan AM, Muranen TA, Neuhausen SL, Nevanlinna H, Newman WG, Olshan AF, Olson JE, Olsson H, Park-Simon TW, Peto J, Petridis C, Plaseska-Karanfilska D, Presneau N, Pylkäs K, Radice P, Rennert G, Romero A, Roylance R, Saloustros E, Sawyer EJ, Schmutzler RK, Schwentner L, Scott C, See MH, Shah M, Shen CY, Shu XO, Siesling S, Slager S, Sohn C, Southey MC, Spinelli JJ, Stone J, Tapper WJ, Tengström M, Teo SH, Terry MB, Tollenaar RAEM, Tomlinson I, Troester MA, Vachon CM, van Ongeval C, van Veen EM, Winqvist R, Wolk A, Zheng W, Ziogas A, Easton DF, Hall P, Schmidt MK. Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk. Am J Hum Genet 2020; 107:837-848. [PMID: 33022221 PMCID: PMC7675034 DOI: 10.1016/j.ajhg.2020.09.001] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 09/02/2020] [Indexed: 12/18/2022] Open
Abstract
Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS313) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS313 was quantified using Cox regression analyses. We assessed PRS313 interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS313 was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS313 was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10th percentile and 20.5% at the 90th percentile of PRS313. We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS313 alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS313 is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies.
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Brandão A, Paulo P, Maia S, Pinheiro M, Peixoto A, Cardoso M, Silva MP, Santos C, Eeles RA, Kote-Jarai Z, Muir K, Schleutker J, Wang Y, Pashayan N, Batra J, Grönberg H, Neal DE, Nordestgaard BG, Tangen CM, Southey MC, Wolk A, Albanes D, Haiman CA, Travis RC, Stanford JL, Mucci LA, West CML, Nielsen SF, Kibel AS, Cussenot O, Berndt SI, Koutros S, Sørensen KD, Cybulski C, Grindedal EM, Park JY, Ingles SA, Maier C, Hamilton RJ, Rosenstein BS, Vega A, Kogevinas M, Wiklund F, Penney KL, Brenner H, John EM, Kaneva R, Logothetis CJ, Neuhausen SL, Ruyck KD, Razack A, Newcomb LF, Lessel D, Usmani N, Claessens F, Gago-Dominguez M, Townsend PA, Roobol MJ, Teixeira MR. The CHEK2 Variant C.349A>G Is Associated with Prostate Cancer Risk and Carriers Share a Common Ancestor. Cancers (Basel) 2020; 12:E3254. [PMID: 33158149 PMCID: PMC7694218 DOI: 10.3390/cancers12113254] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/19/2020] [Accepted: 10/20/2020] [Indexed: 02/07/2023] Open
Abstract
The identification of recurrent founder variants in cancer predisposing genes may have important implications for implementing cost-effective targeted genetic screening strategies. In this study, we evaluated the prevalence and relative risk of the CHEK2 recurrent variant c.349A>G in a series of 462 Portuguese patients with early-onset and/or familial/hereditary prostate cancer (PrCa), as well as in the large multicentre PRACTICAL case-control study comprising 55,162 prostate cancer cases and 36,147 controls. Additionally, we investigated the potential shared ancestry of the carriers by performing identity-by-descent, haplotype and age estimation analyses using high-density SNP data from 70 variant carriers belonging to 11 different populations included in the PRACTICAL consortium. The CHEK2 missense variant c.349A>G was found significantly associated with an increased risk for PrCa (OR 1.9; 95% CI: 1.1-3.2). A shared haplotype flanking the variant in all carriers was identified, strongly suggesting a common founder of European origin. Additionally, using two independent statistical algorithms, implemented by DMLE+2.3 and ESTIAGE, we were able to estimate the age of the variant between 2300 and 3125 years. By extending the haplotype analysis to 14 additional carrier families, a shared core haplotype was revealed among all carriers matching the conserved region previously identified in the high-density SNP analysis. These findings are consistent with CHEK2 c.349A>G being a founder variant associated with increased PrCa risk, suggesting its potential usefulness for cost-effective targeted genetic screening in PrCa families.
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Li S, Nguyen TL, Wong EM, Dugué PA, Dite GS, Armstrong NJ, Craig JM, Mather KA, Sachdev PS, Saffery R, Sung J, Tan Q, Thalamuthu A, Milne RL, Giles GG, Southey MC, Hopper JL. Genetic and environmental causes of variation in epigenetic aging across the lifespan. Clin Epigenetics 2020; 12:158. [PMID: 33092643 PMCID: PMC7583207 DOI: 10.1186/s13148-020-00950-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 10/13/2020] [Indexed: 12/14/2022] Open
Abstract
Background DNA methylation-based biological age (DNAm age) is an important biomarker for adult health. Studies in specific age ranges have found widely varying results about its genetic and environmental causes of variation. However, these studies are not able to provide a comprehensive view of the causes of variation over the lifespan.
Results In order to investigate the genetic and environmental causes of DNAm age variation across the lifespan, we pooled genome-wide DNA methylation data for 4217 people aged 0–92 years from 1871 families. DNAm age was calculated using the Horvath epigenetic clock. We estimated familial correlations in DNAm age for monozygotic (MZ) twin, dizygotic (DZ) twin, sibling, parent–offspring, and spouse pairs by cohabitation status. Genetic and environmental variance components models were fitted and compared. We found that twin pair correlations were − 0.12 to 0.18 around birth, not different from zero (all P > 0.29). For all pairs of relatives, their correlations increased with time spent living together (all P < 0.02) at different rates (MZ > DZ and siblings > parent–offspring; P < 0.001) and decreased with time spent living apart (P = 0.02) at similar rates. These correlation patterns were best explained by cohabitation-dependent shared environmental factors, the effects of which were 1.41 (95% confidence interval [CI] 1.16 to 1.66) times greater for MZ pairs than for DZ and sibling pairs, and the latter were 2.03 (95% CI 1.13 to 9.47) times greater than for parent–offspring pairs. Genetic factors explained 13% (95% CI − 10 to 35%) of variation (P = 0.27). Similar results were found for another two epigenetic clocks, suggesting that our observations are robust to how DNAm age is measured. In addition, results for the other clocks were consistent with there also being a role for prenatal environmental factors in determining their variation. Conclusions Variation in DNAm age is mostly caused by environmental factors, including those shared to different extents by relatives while living together and whose effects persist into old age. The equal environment assumption of the classic twin study might not hold for epigenetic aging.
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Barnes DR, Rookus MA, McGuffog L, Leslie G, Mooij TM, Dennis J, Mavaddat N, Adlard J, Ahmed M, Aittomäki K, Andrieu N, Andrulis IL, Arnold N, Arun BK, Azzollini J, Balmaña J, Barkardottir RB, Barrowdale D, Benitez J, Berthet P, Białkowska K, Blanco AM, Blok MJ, Bonanni B, Boonen SE, Borg Å, Bozsik A, Bradbury AR, Brennan P, Brewer C, Brunet J, Buys SS, Caldés T, Caligo MA, Campbell I, Christensen LL, Chung WK, Claes KBM, Colas C, Collonge-Rame MA, Cook J, Daly MB, Davidson R, de la Hoya M, de Putter R, Delnatte C, Devilee P, Diez O, Ding YC, Domchek SM, Dorfling CM, Dumont M, Eeles R, Ejlertsen B, Engel C, Evans DG, Faivre L, Foretova L, Fostira F, Friedlander M, Friedman E, Frost D, Ganz PA, Garber J, Gehrig A, Gerdes AM, Gesta P, Giraud S, Glendon G, Godwin AK, Goldgar DE, González-Neira A, Greene MH, Gschwantler-Kaulich D, Hahnen E, Hamann U, Hanson H, Hentschel J, Hogervorst FBL, Hooning MJ, Horvath J, Hu C, Hulick PJ, Imyanitov EN, Isaacs C, Izatt L, Izquierdo A, Jakubowska A, James PA, Janavicius R, John EM, Joseph V, Karlan BY, Kast K, Koudijs M, Kruse TA, Kwong A, Laitman Y, Lasset C, Lazaro C, Lester J, Lesueur F, Liljegren A, Loud JT, Lubiński J, Mai PL, Manoukian S, Mari V, Mebirouk N, Meijers-Heijboer HEJ, Meindl A, Mensenkamp AR, Miller A, Montagna M, Mouret-Fourme E, Mukherjee S, Mulligan AM, Nathanson KL, Neuhausen SL, Nevanlinna H, Niederacher D, Nielsen FC, Nikitina-Zake L, Noguès C, Olah E, Olopade OI, Ong KR, O'Shaughnessy-Kirwan A, Osorio A, Ott CE, Papi L, Park SK, Parsons MT, Pedersen IS, Peissel B, Peixoto A, Peterlongo P, Pfeiler G, Phillips KA, Prajzendanc K, Pujana MA, Radice P, Ramser J, Ramus SJ, Rantala J, Rennert G, Risch HA, Robson M, Rønlund K, Salani R, Schuster H, Senter L, Shah PD, Sharma P, Side LE, Singer CF, Slavin TP, Soucy P, Southey MC, Spurdle AB, Steinemann D, Steinsnyder Z, Stoppa-Lyonnet D, Sutter C, Tan YY, Teixeira MR, Teo SH, Thull DL, Tischkowitz M, Tognazzo S, Toland AE, Trainer AH, Tung N, van Engelen K, van Rensburg EJ, Vega A, Vierstraete J, Wagner G, Walker L, Wang-Gohrke S, Wappenschmidt B, Weitzel JN, Yadav S, Yang X, Yannoukakos D, Zimbalatti D, Offit K, Thomassen M, Couch FJ, Schmutzler RK, Simard J, Easton DF, Chenevix-Trench G, Antoniou AC. Polygenic risk scores and breast and epithelial ovarian cancer risks for carriers of BRCA1 and BRCA2 pathogenic variants. Genet Med 2020; 22:1653-1666. [PMID: 32665703 PMCID: PMC7521995 DOI: 10.1038/s41436-020-0862-x] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 05/28/2020] [Accepted: 05/29/2020] [Indexed: 11/21/2022] Open
Abstract
PURPOSE We assessed the associations between population-based polygenic risk scores (PRS) for breast (BC) or epithelial ovarian cancer (EOC) with cancer risks for BRCA1 and BRCA2 pathogenic variant carriers. METHODS Retrospective cohort data on 18,935 BRCA1 and 12,339 BRCA2 female pathogenic variant carriers of European ancestry were available. Three versions of a 313 single-nucleotide polymorphism (SNP) BC PRS were evaluated based on whether they predict overall, estrogen receptor (ER)-negative, or ER-positive BC, and two PRS for overall or high-grade serous EOC. Associations were validated in a prospective cohort. RESULTS The ER-negative PRS showed the strongest association with BC risk for BRCA1 carriers (hazard ratio [HR] per standard deviation = 1.29 [95% CI 1.25-1.33], P = 3×10-72). For BRCA2, the strongest association was with overall BC PRS (HR = 1.31 [95% CI 1.27-1.36], P = 7×10-50). HR estimates decreased significantly with age and there was evidence for differences in associations by predicted variant effects on protein expression. The HR estimates were smaller than general population estimates. The high-grade serous PRS yielded the strongest associations with EOC risk for BRCA1 (HR = 1.32 [95% CI 1.25-1.40], P = 3×10-22) and BRCA2 (HR = 1.44 [95% CI 1.30-1.60], P = 4×10-12) carriers. The associations in the prospective cohort were similar. CONCLUSION Population-based PRS are strongly associated with BC and EOC risks for BRCA1/2 carriers and predict substantial absolute risk differences for women at PRS distribution extremes.
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MacInnis RJ, Liao Y, Knight JA, Milne RL, Whittemore AS, Chung WK, Leoce N, Buchsbaum R, Zeinomar N, Dite GS, Southey MC, Goldgar D, Giles GG, McLachlan SA, Weideman PC, Nesci S, Friedlander ML, Glendon G, Andrulis IL, John EM, Daly MB, Buys SS, Phillips KA, Hopper JL, Terry MB. Considerations When Using Breast Cancer Risk Models for Women with Negative BRCA1/BRCA2 Mutation Results. J Natl Cancer Inst 2020; 112:418-422. [PMID: 31584660 DOI: 10.1093/jnci/djz194] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 09/06/2019] [Accepted: 09/17/2019] [Indexed: 01/20/2023] Open
Abstract
The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study). During follow-up, 482 women were diagnosed with invasive breast cancer. Mutation testing was conducted independent of incident cancers. All models underpredicted risk by 26.3%-56.7% for women who tested negative but whose relatives had not been tested (n = 1363; 63 breast cancers). Although replication studies with larger sample sizes are needed, until these models are recalibrated for women who test negative and have no relatives tested, caution should be used when considering changing the breast cancer risk management intensity of such women based on risk estimates from these models.
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Chamberlain JA, Dugué PA, Bassett JK, Milne RL, Joo JE, Wong EM, Brinkman MT, Stuart GW, Boussioutas A, Southey MC, Giles GG, Mitchell H, English DR, Hodge AM. DNA Methylation in Peripheral Blood and Risk of Gastric Cancer: A Prospective Nested Case-control Study. Cancer Prev Res (Phila) 2020; 14:233-240. [PMID: 32958588 DOI: 10.1158/1940-6207.capr-20-0003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Revised: 06/04/2020] [Accepted: 09/15/2020] [Indexed: 12/24/2022]
Abstract
DNA methylation in peripheral blood is a potential biomarker of gastric cancer risk which could be used for early detection. We conducted a prospective case-control study nested within the Melbourne Collaborative Cohort Study. Genomic DNA was prepared from blood samples collected a median of 12 years before diagnosis for cases (N = 168). Controls (N = 163) were matched to cases on sex, year of birth, country of birth, and blood sample type using incidence density sampling. Genome-wide DNA methylation was measured using the Infinium HumanMethylation450K Beadchip. Global measures of DNA methylation were defined as the median methylation M value, calculated for each of 13 CpG subsets representing genomic function, mean methylation and location, and reliability of measurement. Conditional logistic regression was conducted to assess associations between these global measures of methylation and gastric cancer risk, adjusting for Helicobacter pylori and other potential confounders. We tested nonlinear associations using quintiles of the global measure distribution. A genome-wide association study of DNA methylation and gastric cancer risk was also conducted (N = 484,989 CpGs) using conditional logistic regression, adjusting for potential confounders. Differentially methylated regions (DMR) were investigated using the R package DMRcate We found no evidence of associations with gastric cancer risk for individual CpGs or DMRs (P > 7.6 × 10-6). No evidence of association was observed with global measures of methylation (OR 1.07 per SD of overall median methylation; 95% confidence interval, 0.80-1.44; P = 0.65). We found no evidence that blood DNA methylation is prospectively associated with gastric cancer risk.Prevention Relevance: We studied DNA methylation in blood to try and predict who was at risk of gastric cancer before symptoms developed, by which stage survival is poor. We did not find any such markers, but the importance of early diagnosis in gastric cancer remains, and the search for markers continues.
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Muranen TA, Khan S, Fagerholm R, Aittomäki K, Cunningham JM, Dennis J, Leslie G, McGuffog L, Parsons MT, Simard J, Slager S, Soucy P, Easton DF, Tischkowitz M, Spurdle AB, Schmutzler RK, Wappenschmidt B, Hahnen E, Hooning MJ, Singer CF, Wagner G, Thomassen M, Pedersen IS, Domchek SM, Nathanson KL, Lazaro C, Rossing CM, Andrulis IL, Teixeira MR, James P, Garber J, Weitzel JN, Jakubowska A, Yannoukakos D, John EM, Southey MC, Schmidt MK, Antoniou AC, Chenevix-Trench G, Blomqvist C, Nevanlinna H. Association of germline variation with the survival of women with BRCA1/2 pathogenic variants and breast cancer. NPJ Breast Cancer 2020; 6:44. [PMID: 32964118 PMCID: PMC7483417 DOI: 10.1038/s41523-020-00185-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 08/11/2020] [Indexed: 02/02/2023] Open
Abstract
Germline genetic variation has been suggested to influence the survival of breast cancer patients independently of tumor pathology. We have studied survival associations of genetic variants in two etiologically unique groups of breast cancer patients, the carriers of germline pathogenic variants in BRCA1 or BRCA2 genes. We found that rs57025206 was significantly associated with the overall survival, predicting higher mortality of BRCA1 carrier patients with estrogen receptor-negative breast cancer, with a hazard ratio 4.37 (95% confidence interval 3.03-6.30, P = 3.1 × 10-9). Multivariable analysis adjusted for tumor characteristics suggested that rs57025206 was an independent survival marker. In addition, our exploratory analyses suggest that the associations between genetic variants and breast cancer patient survival may depend on tumor biological subgroup and clinical patient characteristics.
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Darst BF, Dadaev T, Saunders E, Sheng X, Wan P, Pooler L, Xia LY, Chanock S, Berndt SI, Gapstur SM, Stevens V, Albanes D, Weinstein SJ, Gnanapragasam V, Giles GG, Nguyen-Dumont T, Milne RL, Pomerantz M, Schmidt JA, Mucci L, Catalona WJ, Hetrick KN, Doheny KF, MacInnis RJ, Southey MC, Eeles RA, Wiklund F, Kote-Jarai Z, Conti DV, Haiman CA. Germline Sequencing DNA Repair Genes in 5545 Men With Aggressive and Nonaggressive Prostate Cancer. J Natl Cancer Inst 2020; 113:616-625. [PMID: 32853339 DOI: 10.1093/jnci/djaa132] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 07/27/2020] [Accepted: 08/20/2020] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND There is an urgent need to identify factors specifically associated with aggressive prostate cancer (PCa) risk. We investigated whether rare pathogenic, likely pathogenic, or deleterious (P/LP/D) germline variants in DNA repair genes are associated with aggressive PCa risk in a case-case study of aggressive vs nonaggressive disease. METHODS Participants were 5545 European-ancestry men, including 2775 nonaggressive and 2770 aggressive PCa cases, which included 467 metastatic cases (16.9%). Samples were assembled from 12 international studies and germline sequenced together. Rare (minor allele frequency < 0.01) P/LP/D variants were analyzed for 155 DNA repair genes. We compared single variant, gene-based, and DNA repair pathway-based burdens by disease aggressiveness. All statistical tests are 2-sided. RESULTS BRCA2 and PALB2 had the most statistically significant gene-based associations, with 2.5% of aggressive and 0.8% of nonaggressive cases carrying P/LP/D BRCA2 alleles (odds ratio [OR] = 3.19, 95% confidence interval [CI] = 1.94 to 5.25, P = 8.58 × 10-7) and 0.65% of aggressive and 0.11% of nonaggressive cases carrying P/LP/D PALB2 alleles (OR = 6.31, 95% CI = 1.83 to 21.68, P = 4.79 × 10-4). ATM had a nominal association, with 1.6% of aggressive and 0.8% of nonaggressive cases carrying P/LP/D ATM alleles (OR = 1.88, 95% CI = 1.10 to 3.22, P = .02). In aggregate, P/LP/D alleles within 24 literature-curated candidate PCa DNA repair genes were more common in aggressive than nonaggressive cases (carrier frequencies = 14.2% vs 10.6%, respectively; P = 5.56 × 10-5). However, this difference was non-statistically significant (P = .18) on excluding BRCA2, PALB2, and ATM. Among these 24 genes, P/LP/D carriers had a 1.06-year younger diagnosis age (95% CI = -1.65 to 0.48, P = 3.71 × 10-4). CONCLUSIONS Risk conveyed by DNA repair genes is largely driven by rare P/LP/D alleles within BRCA2, PALB2, and ATM. These findings support the importance of these genes in both screening and disease management considerations.
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Schaid DJ, McDonnell SK, FitzGerald LM, DeRycke L, Fogarty Z, Giles GG, MacInnis RJ, Southey MC, Nguyen-Dumont T, Cancel-Tassin G, Cussenot O, Whittemore AS, Sieh W, Ioannidis NM, Hsieh CL, Stanford JL, Schleutker J, Cropp CD, Carpten J, Hoegel J, Eeles R, Kote-Jarai Z, Ackerman MJ, Klein CJ, Mandal D, Cooney KA, Bailey-Wilson JE, Helfand B, Catalona WJ, Wiklund F, Riska S, Bahetti S, Larson MC, Cannon Albright L, Teerlink C, Xu J, Isaacs W, Ostrander EA, Thibodeau SN. Two-stage Study of Familial Prostate Cancer by Whole-exome Sequencing and Custom Capture Identifies 10 Novel Genes Associated with the Risk of Prostate Cancer. Eur Urol 2020; 79:353-361. [PMID: 32800727 PMCID: PMC7881048 DOI: 10.1016/j.eururo.2020.07.038] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Accepted: 07/31/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Family history of prostate cancer (PCa) is a well-known risk factor, and both common and rare genetic variants are associated with the disease. OBJECTIVE To detect new genetic variants associated with PCa, capitalizing on the role of family history and more aggressive PCa. DESIGN, SETTING, AND PARTICIPANTS A two-stage design was used. In stage one, whole-exome sequencing was used to identify potential risk alleles among affected men with a strong family history of disease or with more aggressive disease (491 cases and 429 controls). Aggressive disease was based on a sum of scores for Gleason score, node status, metastasis, tumor stage, prostate-specific antigen at diagnosis, systemic recurrence, and time to PCa death. Genes identified in stage one were screened in stage two using a custom-capture design in an independent set of 2917 cases and 1899 controls. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Frequencies of genetic variants (singly or jointly in a gene) were compared between cases and controls. RESULTS AND LIMITATIONS Eleven genes previously reported to be associated with PCa were detected (ATM, BRCA2, HOXB13, FAM111A, EMSY, HNF1B, KLK3, MSMB, PCAT1, PRSS3, and TERT), as well as an additional 10 novel genes (PABPC1, QK1, FAM114A1, MUC6, MYCBP2, RAPGEF4, RNASEH2B, ULK4, XPO7, and THAP3). Of these 10 novel genes, all but PABPC1 and ULK4 were primarily associated with the risk of aggressive PCa. CONCLUSIONS Our approach demonstrates the advantage of gene sequencing in the search for genetic variants associated with PCa and the benefits of sampling patients with a strong family history of disease or an aggressive form of disease. PATIENT SUMMARY Multiple genes are associated with prostate cancer (PCa) among men with a strong family history of this disease or among men with an aggressive form of PCa.
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