Clinical Pathology - Research Publications

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    Lifetime alcohol intake and risk of non-Hodgkin lymphoma: Findings from the Melbourne Collaborative Cohort Study
    Jayasekara, H ; Juneja, S ; Hodge, AM ; Room, R ; Milne, RL ; Hopper, JL ; English, DR ; Giles, GG ; MacInnis, RJ (WILEY, 2018-03-01)
    Cohort studies have reported inconsistent evidence regarding alcohol intake and risk of non-Hodgkin lymphoma (NHL), mostly based on alcohol intake assessed close to study enrolment. We examined this association using alcohol intake measured from age 20 onwards. We calculated usual alcohol intake for 10-year periods from age 20 using recalled frequency and quantity of beverage-specific consumption for 37,990 participants aged 40-69 years from the Melbourne Collaborative Cohort Study. Cox regression was performed to derive hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between alcohol intake (g/day) and NHL risk. After a mean follow-up of 19.3 years, 538 NHL cases were diagnosed. Approximately 80% of participants were either lifetime abstainers or consumed below 20 g of ethanol/day. All categories of lifetime alcohol intake were associated with about 20% lower incidence of NHL compared with lifetime abstention, but there was no evidence of a trend by amount consumed (HR = 0.97 per 10 g/day increment in intake, 95% CI: 0.92-1.03; p value = 0.3). HRs for beer, wine and spirits were 0.91 (95% CI: 0.83-1.00; p value = 0.05), 1.03 (95% CI: 0.94-1.12; p value = 0.6), and 1.06 (95% CI: 0.83-1.37; p value = 0.6), respectively, per 10 g/day increment in lifetime intake. There were no significant differences in associations between NHL subtypes. In this low-drinking cohort, we did not detect a dose-dependent association between lifetime alcohol intake and NHL risk.
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    Associations of alcohol intake, smoking, physical activity and obesity with survival following colorectal cancer diagnosis by stage, anatomic site and tumor molecular subtype
    Jayasekara, H ; English, DR ; Haydon, A ; Hodge, AM ; Lynch, BM ; Rosty, C ; Williamson, EJ ; Clendenning, M ; Southey, MC ; Jenkins, MA ; Room, R ; Hopper, JL ; Milne, RL ; Buchanan, DD ; Giles, GG ; MacInnis, RJ (WILEY, 2018-01-15)
    The influence of lifestyle factors on survival following a diagnosis of colorectal cancer (CRC) is not well established. We examined associations between lifestyle factors measured before diagnosis and CRC survival. The Melbourne Collaborative Cohort Study collected data on alcohol intake, cigarette smoking and physical activity, and body measurements at baseline (1990-1994) and wave 2 (2003-2007). We included participants diagnosed to 31 August 2015 with incident stages I-III CRC within 10-years post exposure assessment. Information on tumor characteristics and vital status was obtained. Tumor DNA was tested for microsatellite instability (MSI) and somatic mutations in oncogenes BRAF (V600E) and KRAS. We estimated hazard ratios (HRs) for associations between lifestyle factors and overall and CRC-specific mortality using Cox regression. Of 724 eligible CRC cases, 339 died (170 from CRC) during follow-up (average 9.0 years). Exercise (non-occupational/leisure-time) was associated with higher CRC-specific survival for stage II (HR = 0.25, 95% CI: 0.10-0.60) but not stages I/III disease (p for interaction = 0.01), and possibly for colon and KRAS wild-type tumors. Waist circumference was inversely associated with CRC-specific survival (HR = 1.25 per 10 cm increment, 95% CI: 1.08-1.44), independent of stage, anatomic site and tumor molecular status. Cigarette smoking was associated with lower overall survival, with suggestive evidence of worse survival for BRAF mutated CRC, but not with CRC-specific survival. Alcohol intake was not associated with survival. Survival did not differ by MSI status. We have identified pre-diagnostic predictors of survival following CRC that may have clinical and public health relevance.
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    Lifetime alcohol intake is associated with an increased risk of KRAS plus and BRAF-/KRAS- but not BRAF plus colorectal cancer
    Jayasekara, H ; MacInnis, RJ ; Williamson, EJ ; Hodge, AM ; Clendenning, M ; Rosty, C ; Walters, R ; Room, R ; Southey, MC ; Jenkins, MA ; Milne, RL ; Hopper, JL ; Giles, GG ; Buchanan, DD ; English, DR (WILEY, 2017-04)
    Ethanol in alcoholic beverages is a causative agent for colorectal cancer. Colorectal cancer is a biologically heterogeneous disease, and molecular subtypes defined by the presence of somatic mutations in BRAF and KRAS are known to exist. We examined associations between lifetime alcohol intake and molecular and anatomic subtypes of colorectal cancer. We calculated usual alcohol intake for 10-year periods from age 20 using recalled frequency and quantity of beverage-specific consumption for 38,149 participants aged 40-69 years from the Melbourne Collaborative Cohort Study. Cox regression was performed to derive hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between lifetime alcohol intake and colorectal cancer risk. Heterogeneity in the HRs across subtypes of colorectal cancer was assessed. A positive dose-dependent association between lifetime alcohol intake and overall colorectal cancer risk (mean follow-up = 14.6 years; n = 596 colon and n = 326 rectal cancer) was observed (HR = 1.08, 95% CI: 1.04-1.12 per 10 g/day increment). The risk was greater for rectal than colon cancer (phomogeneity  = 0.02). Alcohol intake was associated with increased risks of KRAS+ (HR = 1.07, 95% CI: 1.00-1.15) and BRAF-/KRAS- (HR = 1.05, 95% CI: 1.00-1.11) but not BRAF+ tumors (HR = 0.89, 95% CI: 0.78-1.01; phomogeneity  = 0.01). Alcohol intake is associated with an increased risk of KRAS+ and BRAF-/KRAS- tumors originating via specific molecular pathways including the traditional adenoma-carcinoma pathway but not with BRAF+ tumors originating via the serrated pathway. Therefore, limiting alcohol intake from a young age might reduce colorectal cancer originating via the traditional adenoma-carcinoma pathway.
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    Benign breast disease increases breast cancer risk independent of underlying familial risk profile: Findings from a Prospective Family Study Cohort
    Zeinomar, N ; Phillips, K-A ; Daly, MB ; Milne, RL ; Dite, GS ; MacInnis, RJ ; Liao, Y ; Kehm, RD ; Knight, JA ; Southey, MC ; Chung, WK ; Giles, GG ; McLachlan, S-A ; Friedlander, ML ; Weideman, PC ; Glendon, G ; Nesci, S ; Andrulis, IL ; Buys, SS ; John, EM ; Hopper, JL ; Terry, MB (WILEY, 2019-07-15)
    Benign breast disease (BBD) is an established breast cancer (BC) risk factor, but it is unclear whether the magnitude of the association applies to women at familial or genetic risk. This information is needed to improve BC risk assessment in clinical settings. Using the Prospective Family Study Cohort, we used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of BBD with BC risk. We also examined whether the association with BBD differed by underlying familial risk profile (FRP), calculated using absolute risk estimates from the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) model. During 176,756 person-years of follow-up (median: 10.9 years, maximum: 23.7) of 17,154 women unaffected with BC at baseline, we observed 968 incident cases of BC. A total of 4,704 (27%) women reported a history of BBD diagnosis at baseline. A history of BBD was associated with a greater risk of BC: HR = 1.31 (95% CI: 1.14-1.50), and did not differ by underlying FRP, with HRs of 1.35 (95% CI: 1.11-1.65), 1.26 (95% CI: 1.00-1.60), and 1.40 (95% CI: 1.01-1.93), for categories of full-lifetime BOADICEA score <20%, 20 to <35%, ≥35%, respectively. There was no difference in the association for women with BRCA1 mutations (HR: 1.64; 95% CI: 1.04-2.58), women with BRCA2 mutations (HR: 1.34; 95% CI: 0.78-2.3) or for women without a known BRCA1 or BRCA2 mutation (HR: 1.31; 95% CI: 1.13-1.53) (pinteraction  = 0.95). Women with a history of BBD have an increased risk of BC that is independent of, and multiplies, their underlying familial and genetic risk.
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    Heritable methylation marks associated with breast and prostate cancer risk
    Dugue, P-A ; Dowty, JG ; Joo, JE ; Wong, EM ; Makalic, E ; Schmidt, DF ; English, DR ; Hopper, JL ; Pedersen, J ; Severi, G ; MacInnis, RJ ; Milne, RL ; Giles, GG ; Southey, MC (WILEY, 2018-09-15)
    BACKGROUND: DNA methylation can mimic the effects of germline mutations in cancer predisposition genes. Recently, we identified twenty-four heritable methylation marks associated with breast cancer risk. As breast and prostate cancer share genetic risk factors, including rare, high-risk mutations (eg, in BRCA2), we hypothesized that some of these heritable methylation marks might also be associated with the risk of prostate cancer. METHODS: We studied 869 incident prostate cancers (430 aggressive and 439 non-aggressive) and 869 matched controls nested within a prospective cohort study. DNA methylation was measured in pre-diagnostic blood samples using the Illumina Infinium HM450K BeadChip. Conditional logistic regression models, adjusted for prostate cancer risk factors and blood cell composition, were used to estimate odds ratios and 95% confidence intervals for the association between the 24 methylation marks and the risk of prostate cancer. RESULTS: Five methylation marks within the VTRNA2-1 promoter region (cg06536614, cg00124993, cg26328633, cg25340688, and cg26896946), and one in the body of CLGN (cg22901919) were associated with the risk of prostate cancer. In stratified analyses, the five VTRNA2-1 marks were associated with the risk of aggressive prostate cancer. CONCLUSIONS: This work highlights a potentially important new area of investigation for prostate cancer susceptibility and adds to our knowledge about shared risk factors for breast and prostate cancer.
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    Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants
    Dadaev, T ; Saunders, EJ ; Newcombe, PJ ; Anokian, E ; Leongamornlert, DA ; Brook, MN ; Cieza-Borrella, C ; Mijuskovic, M ; Wakerell, S ; Al Olama, AA ; Schumacher, FR ; Berndt, SI ; Benlloch, S ; Ahmed, M ; Goh, C ; Sheng, X ; Zhang, Z ; Muir, K ; Govindasami, K ; Lophatananon, A ; Stevens, VL ; Gapstur, SM ; Carter, BD ; Tangen, CM ; Goodman, P ; Thompson, IM ; Batra, J ; Chambers, S ; Moya, L ; Clements, J ; Horvath, L ; Tilley, W ; Risbridger, G ; Gronberg, H ; Aly, M ; Nordstrom, T ; Pharoah, P ; Pashayan, N ; Schleutker, J ; Tammela, TLJ ; Sipeky, C ; Auvinen, A ; Albanes, D ; Weinstein, S ; Wolk, A ; Hakansson, N ; West, C ; Dunning, AM ; Burnet, N ; Mucci, L ; Giovannucci, E ; Andriole, G ; Cussenot, O ; Cancel-Tassin, G ; Koutros, S ; Freeman, LEB ; Sorensen, KD ; Orntoft, TF ; Borre, M ; Maehle, L ; Grindedal, EM ; Neal, DE ; Donovan, JL ; Hamdy, FC ; Martin, RM ; Travis, RC ; Key, TJ ; Hamilton, RJ ; Fleshner, NE ; Finelli, A ; Ingles, SA ; Stern, MC ; Rosenstein, B ; Kerns, S ; Ostrer, H ; Lu, Y-J ; Zhang, H-W ; Feng, N ; Mao, X ; Guo, X ; Wang, G ; Sun, Z ; Giles, GG ; Southey, MC ; MacInnis, RJ ; FitzGerald, LM ; Kibel, AS ; Drake, BF ; Vega, A ; Gomez-Caamano, A ; Fachal, L ; Szulkin, R ; Eklund, M ; Kogevinas, M ; Llorca, J ; Castano-Vinyals, G ; Penney, KL ; Stampfer, M ; Park, JY ; Sellers, TA ; Lin, H-Y ; Stanford, JL ; Cybulski, C ; Wokolorczyk, D ; Lubinski, J ; Ostrander, EA ; Geybels, MS ; Nordestgaard, BG ; Nielsen, SF ; Weisher, M ; Bisbjerg, R ; Roder, MA ; Iversen, P ; Brenner, H ; Cuk, K ; Holleczek, B ; Maier, C ; Luedeke, M ; Schnoeller, T ; Kim, J ; Logothetis, CJ ; John, EM ; Teixeira, MR ; Paulo, P ; Cardoso, M ; Neuhausen, SL ; Steele, L ; Ding, YC ; De Ruyck, K ; De Meerleer, G ; Ost, P ; Razack, A ; Lim, J ; Teo, S-H ; Lin, DW ; Newcomb, LF ; Lessel, D ; Gamulin, M ; Kulis, T ; Kaneva, R ; Usmani, N ; Slavov, C ; Mitev, V ; Parliament, M ; Singhal, S ; Claessens, F ; Joniau, S ; Van den Broeck, T ; Larkin, S ; Townsend, PA ; Aukim-Hastie, C ; Gago-Dominguez, M ; Castelao, JE ; Martinez, ME ; Roobol, MJ ; Jenster, G ; van Schaik, RHN ; Menegaux, F ; Truong, T ; Koudou, YA ; Xu, J ; Khaw, K-T ; Cannon-Albright, L ; Pandha, H ; Michael, A ; Kierzek, A ; Thibodeau, SN ; McDonnell, SK ; Schaid, DJ ; Lindstrom, S ; Turman, C ; Ma, J ; Hunter, DJ ; Riboli, E ; Siddiq, A ; Canzian, F ; Kolonel, LN ; Le Marchand, L ; Hoover, RN ; Machiela, MJ ; Kraft, P ; Freedman, M ; Wiklund, F ; Chanock, S ; Henderson, BE ; Easton, DF ; Haiman, CA ; Eeles, RA ; Conti, DV ; Kote-Jarai, Z (NATURE PORTFOLIO, 2018-06-11)
    Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
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    Germline variation at 8q24 and prostate cancer risk in men of European ancestry
    Matejcic, M ; Saunders, EJ ; Dadaev, T ; Brook, MN ; Wang, K ; Sheng, X ; Al Olama, AA ; Schumacher, FR ; Ingles, SA ; Govindasami, K ; Benlloch, S ; Berndt, S ; Albanes, D ; Koutros, S ; Muir, K ; Stevens, VL ; Gapstur, SM ; Tangen, CM ; Batra, J ; Clements, J ; Gronberg, H ; Pashayan, N ; Schleutker, J ; Wolk, A ; West, C ; Mucci, L ; Kraft, P ; Cancel-Tassin, G ; Sorensen, KD ; Maehle, L ; Grindedal, EM ; Strom, SS ; Neal, DE ; Hamdy, FC ; Donovan, JL ; Travis, RC ; Hamilton, RJ ; Rosenstein, B ; Lu, Y-J ; Giles, GG ; Kibel, AS ; Vega, A ; Bensen, JT ; Kogevinas, M ; Penney, KL ; Park, JY ; Stanford, JL ; Cybulski, C ; Nordestgaard, BG ; Brenner, H ; Maier, C ; Kim, J ; Teixeira, MR ; Neuhausen, SL ; De Ruyck, K ; Razack, A ; Newcomb, LF ; Lessel, D ; Kaneva, R ; Usmani, N ; Claessens, F ; Townsend, PA ; Dominguez, MG ; Roobol, MJ ; Menegaux, F ; Khaw, K-T ; Cannon-Albright, LA ; Pandha, H ; Thibodeau, SN ; Schaid, DJ ; Wiklund, F ; Chanock, SJ ; Easton, DF ; Eeles, RA ; Kote-Jarai, Z ; Conti, D ; Haiman, CA (NATURE PORTFOLIO, 2018-11-05)
    Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10-15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62-4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.
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    Age-specific breast cancer risk by body mass index and familial risk: prospective family study cohort (ProF-SC)
    Hopper, JL ; Dite, GS ; MacInnis, RJ ; Liao, Y ; Zeinomar, N ; Knight, JA ; Southey, MC ; Milne, RL ; Chung, WK ; Giles, GG ; Genkinger, JM ; McLachlan, S-A ; Friedlander, ML ; Antoniou, AC ; Weideman, PC ; Glendon, G ; Nesci, S ; Andrulis, IL ; Buys, SS ; Daly, MB ; John, EM ; Phillips, KA ; Terry, MB (BMC, 2018-11-03)
    BACKGROUND: The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman's familial risk. METHODS: We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline. RESULTS: The strength and direction of the BMI risk association depended on baseline menopausal status (P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk. CONCLUSIONS: The greater a woman's familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer.
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    Genome-wide association study of germline variants and breast cancer-specific mortality
    Escala-Garcia, M ; Guo, Q ; Doerk, T ; Canisius, S ; Keeman, R ; Dennis, J ; Beesley, J ; Lecarpentier, J ; Bolla, MK ; Wang, Q ; Abraham, J ; Andrulis, IL ; Anton-Culver, H ; Arndt, V ; Auer, PL ; Beckmann, MW ; Behrens, S ; Benitez, J ; Bermisheva, M ; Bernstein, L ; Blomqvist, C ; Boeckx, B ; Bojesen, SE ; Bonanni, B ; Borresen-Dale, A-L ; Brauch, H ; Brenner, H ; Brentnall, A ; Brinton, L ; Broberg, P ; Brock, IW ; Brucker, SY ; Burwinkel, B ; Caldas, C ; Caldes, T ; Campa, D ; Canzian, F ; Carracedo, A ; Carter, BD ; Castelao, JE ; Chang-Claude, J ; Chanock, SJ ; Chenevix-Trench, G ; Cheng, T-YD ; Chin, S-F ; Clarke, CL ; Cordina-Duverger, E ; Couch, FJ ; Cox, DG ; Cox, A ; Cross, SS ; Czene, K ; Daly, MB ; Devilee, P ; Dunn, JA ; Dunning, AM ; Durcan, L ; Dwek, M ; Earl, HM ; Ekici, AB ; Eliassen, AH ; Ellberg, C ; Engel, C ; Eriksson, M ; Evans, DG ; Figueroa, J ; Flesch-Janys, D ; Flyger, H ; Gabrielson, M ; Gago-Dominguez, M ; Galle, E ; Gapstur, SM ; Garcia-Closas, M ; Garcia-Saenz, JA ; Gaudet, MM ; George, A ; Georgoulias, V ; Giles, GG ; Glendon, G ; Goldgar, DE ; Gonzalez-Neira, A ; Alnaes, GIG ; Grip, M ; Guenel, P ; Haeberle, L ; Hahnen, E ; Haiman, CA ; Hakansson, N ; Hall, P ; Hamann, U ; Hankinson, S ; Harkness, EF ; Harrington, PA ; Hart, SN ; Hartikainen, JM ; Hein, A ; Hillemanns, P ; Hiller, L ; Holleczek, B ; Hollestelle, A ; Hooning, MJ ; Hoover, RN ; Hopper, JL ; Howell, A ; Huang, G ; Humphreys, K ; Hunter, DJ ; Janni, W ; John, EM ; Jones, ME ; Jukkola-Vuorinen, A ; Jung, A ; Kaaks, R ; Kabisch, M ; Kaczmarek, K ; Kerin, MJ ; Khan, S ; Khusnutdinova, E ; Kiiski, J ; Kitahara, CM ; Knight, JA ; Ko, Y-D ; Koppert, LB ; Kosma, V-M ; Kraft, P ; Kristensen, VN ; Kruger, U ; Kuehl, T ; Lambrechts, D ; Le Marchand, L ; Lee, E ; Lejbkowicz, F ; Li, L ; Lindblom, A ; Lindstrom, S ; Linet, M ; Lissowska, J ; Lo, W-Y ; Loibl, S ; Lubinski, J ; Lux, MP ; MacInnis, RJ ; Maierthaler, M ; Maishman, T ; Makalic, E ; Mannermaa, A ; Manoochehri, M ; Manoukian, S ; Margolin, S ; Martinez, ME ; Mavroudis, D ; McLean, C ; Meindl, A ; Middha, P ; Miller, N ; Milne, RL ; Moreno, F ; Mulligan, AM ; Mulot, C ; Nassir, R ; Neuhausen, SL ; Newman, WT ; Nielsen, SF ; Nordestgaard, BG ; Norman, A ; Olsson, H ; Orr, N ; Pankratz, VS ; Park-Simon, T-W ; Perez, JIA ; Perez-Barrios, C ; Peterlongo, P ; Petridis, C ; Pinchev, M ; Prajzendanc, K ; Prentice, R ; Presneau, N ; Prokofieva, D ; Pylkas, K ; Rack, B ; Radice, P ; Ramachandran, D ; Rennert, G ; Rennert, HS ; Rhenius, V ; Romero, A ; Roylance, R ; Saloustros, E ; Sawyer, EJ ; Schmidt, DF ; Schmutzler, RK ; Schneeweiss, A ; Schoemaker, MJ ; Schumacher, F ; Schwentner, L ; Scott, RJ ; Scott, C ; Seynaeve, C ; Shah, M ; Simard, J ; Smeets, A ; Sohn, C ; Southey, MC ; Swerdlow, AJ ; Talhouk, A ; Tamimi, RM ; Tapper, WJ ; Teixeira, MR ; Tengstrom, M ; Terry, MB ; Thoene, K ; Tollenaar, RAEM ; Tomlinson, I ; Torres, D ; Truong, T ; Turman, C ; Turnbull, C ; Ulmer, H-U ; Untch, M ; Vachon, C ; van Asperen, CJ ; van den Ouweland, AMW ; van Veen, EM ; Wendt, C ; Whittemore, AS ; Willett, W ; Winqvist, R ; Wolk, A ; Yang, XR ; Zhang, Y ; Easton, DF ; Fasching, PA ; Nevanlinna, H ; Eccles, DM ; Pharoah, PDP ; Schmidt, MK (NATURE PUBLISHING GROUP, 2019-03-19)
    BACKGROUND: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. METHODS: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP). RESULTS: We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10-8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10-7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10-7, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster. CONCLUSIONS: We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.
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    Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes
    Mavaddat, N ; Michailidou, K ; Dennis, J ; Lush, M ; Fachal, L ; Lee, A ; Tyrer, JP ; Chen, T-H ; Wang, Q ; Bolla, MK ; Yang, X ; Adank, MA ; Ahearn, T ; Aittomaki, K ; Allen, J ; Andrulis, IL ; Anton-Culver, H ; Antonenkova, NN ; Arndt, V ; Aronson, KJ ; Auer, PL ; Auvinen, P ; Barrdahl, M ; Freeman, LEB ; Beckmann, MW ; Behrens, S ; Benitez, J ; Bermisheva, M ; Bernstein, L ; Blomqvist, C ; Bogdanova, N ; Bojesen, SE ; Bonanni, B ; Borresen-Dale, A-L ; Brauch, H ; Bremer, M ; Brenner, H ; Brentnall, A ; Brock, IW ; Brooks-Wilson, A ; Brucker, SY ; Bruening, T ; Burwinkel, B ; Campa, D ; Carter, BD ; Castelao, JE ; Chanock, SJ ; Chlebowski, R ; Christiansen, H ; Clarke, CL ; Collee, JM ; Cordina-Duverger, E ; Cornelissen, S ; Couch, FJ ; Cox, A ; Cross, SS ; Czene, K ; Daly, MB ; Devilee, P ; Doerk, T ; dos-Santos-Silva, I ; Dumont, M ; Durcan, L ; Dwek, M ; Eccles, DM ; Ekici, AB ; Eliassen, AH ; Ellberg, C ; Engel, C ; Eriksson, M ; Evans, DG ; Fasching, PA ; Figueroa, J ; Fletcher, O ; Flyger, H ; Foersti, A ; Fritschi, L ; Gabrielson, M ; Gago-Dominguez, M ; Gapstur, SM ; Garcia-Saenz, JA ; Gaudet, MM ; Georgoulias, V ; Giles, GG ; Gilyazova, IR ; Glendon, G ; Goldberg, MS ; Goldgar, DE ; Gonzalez-Neira, A ; Alnaes, GIG ; Grip, M ; Gronwald, J ; Grundy, A ; Guenel, P ; Haeberle, L ; Hahnen, E ; Haiman, CA ; Hakansson, N ; Hamann, U ; Hankinson, SE ; Harkness, EF ; Hart, SN ; He, W ; Hein, A ; Heyworth, J ; Hillemanns, P ; Hollestelle, A ; Hooning, MJ ; Hoover, RN ; Hopper, JL ; Howell, A ; Huang, G ; Humphreys, K ; Hunter, DJ ; Jakimovska, M ; Jakubowska, A ; Janni, W ; John, EM ; Johnson, N ; Jones, ME ; Jukkola-Vuorinen, A ; Jung, A ; Kaaks, R ; Kaczmarek, K ; Kataja, V ; Keeman, R ; Kerin, MJ ; Khusnutdinova, E ; Kiiski, J ; Knight, JA ; Ko, Y-D ; Kosma, V-M ; Koutros, S ; Kristensen, VN ; Kruger, U ; Kuehl, T ; Lambrechts, D ; Le Marchand, L ; Lee, E ; Lejbkowicz, F ; Lilyquist, J ; Lindblom, A ; Lindstrom, S ; Lissowska, J ; Lo, W-Y ; Loibl, S ; Long, J ; Lubinski, J ; Lux, MP ; MacInnis, RJ ; Maishman, T ; Makalic, E ; Kostovska, IM ; Mannermaa, A ; Manoukian, S ; Margolin, S ; Martens, JWM ; Martinez, ME ; Mavroudis, D ; McLean, C ; Meindl, A ; Menon, U ; Middha, P ; Miller, N ; Moreno, F ; Mulligan, AM ; Mulot, C ; Munoz-Garzon, VM ; Neuhausen, SL ; Nevanlinna, H ; Neven, P ; Newman, WG ; Nielsen, SF ; Nordestgaard, BG ; Norman, A ; Offit, K ; Olson, JE ; Olsson, H ; Orr, N ; Pankratz, VS ; Park-Simon, T-W ; Perez, JIA ; Perez-Barrios, C ; Peterlongo, P ; Peto, J ; Pinchev, M ; Plaseska-Karanfilska, D ; Polley, EC ; Prentice, R ; Presneau, N ; Prokofyeva, D ; Purrington, K ; Pylkas, K ; Rack, B ; Radice, P ; Rau-Murthy, R ; Rennert, G ; Rennert, HS ; Rhenius, V ; Robson, M ; Romero, A ; Ruddy, KJ ; Ruebner, M ; Saloustros, E ; Sandler, DP ; Sawyer, EJ ; Schmidt, DF ; Schmutzler, RK ; Schneeweiss, A ; Schoemaker, MJ ; Schumacher, F ; Schuermann, P ; Schwentner, L ; Scott, C ; Scott, RJ ; Seynaeve, C ; Shah, M ; Sherman, ME ; Shrubsole, MJ ; Shu, X-O ; 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Gill, G ; Thorne, H ; Campbell, I ; Hickie, I ; Caldon, L ; Winship, I ; Cui, J ; Flanagan, J ; Kollias, J ; Visvader, J ; Taylor, J ; Burke, J ; Saunus, J ; Forbs, J ; Hopper, J ; Beesley, J ; Kirk, J ; French, J ; Tucker, K ; Wu, K ; Phillips, K ; Forrest, L ; Lipton, L ; Andrews, L ; Lobb, L ; Walker, L ; Kentwell, M ; Spurdle, M ; Cummings, M ; Gleeson, M ; Harris, M ; Jenkins, M ; Young, MA ; Delatycki, M ; Wallis, M ; Burgess, M ; Brown, M ; Southey, M ; Bogwitz, M ; Field, M ; Friedlander, M ; Gattas, M ; Saleh, M ; Aghmesheh, M ; Hayward, N ; Pachter, N ; Cohen, P ; Duijf, P ; James, P ; Simpson, P ; Fong, P ; Butow, P ; Williams, R ; Kefford, R ; Simard, J ; Balleine, R-M ; Dawson, S-J ; Lok, S ; O'connell, S ; Greening, S ; Nightingale, S ; Edwards, S ; Fox, S ; McLachlan, S-A ; Lakhani, S ; Dudding, T ; Antill, Y ; Sahlberg, KK ; Ottestad, L ; Karesen, R ; Schlichting, E ; Holmen, MM ; Sauer, T ; Haakensen, V ; Engebraten, O ; Naume, B ; Fossa, A ; Kiserud, CE ; Reinertsen, K ; Helland, A ; Riis, M ; Geisler, J ; Dunning, AM ; Thompson, DJ ; Chenevix-Trench, G ; Chang-Claude, J ; Schmidt, MK ; Hall, P ; Milne, RL ; Pharoah, PDP ; Antoniou, AC ; Chatterjee, N ; Kraft, P ; Garcia-Closas, M ; Easton, DF (CELL PRESS, 2019-01-03)
    Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.