Melbourne School of Population and Global Health - Research Publications

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    Breast cancer risks associated with missense variants in breast cancer susceptibility genes.
    Dorling, L ; Carvalho, S ; Allen, J ; Parsons, MT ; Fortuno, C ; González-Neira, A ; Heijl, SM ; Adank, MA ; Ahearn, TU ; Andrulis, IL ; Auvinen, P ; Becher, H ; Beckmann, MW ; Behrens, S ; Bermisheva, M ; Bogdanova, NV ; Bojesen, SE ; Bolla, MK ; Bremer, M ; Briceno, I ; Camp, NJ ; Campbell, A ; Castelao, JE ; Chang-Claude, J ; Chanock, SJ ; Chenevix-Trench, G ; NBCS Collaborators, ; Collée, JM ; Czene, K ; Dennis, J ; Dörk, T ; Eriksson, M ; Evans, DG ; Fasching, PA ; Figueroa, J ; Flyger, H ; Gabrielson, M ; Gago-Dominguez, M ; García-Closas, M ; Giles, GG ; Glendon, G ; Guénel, P ; Gündert, M ; Hadjisavvas, A ; Hahnen, E ; Hall, P ; Hamann, U ; Harkness, EF ; Hartman, M ; Hogervorst, FBL ; Hollestelle, A ; Hoppe, R ; Howell, A ; kConFab Investigators, ; SGBCC Investigators, ; Jakubowska, A ; Jung, A ; Khusnutdinova, E ; Kim, S-W ; Ko, Y-D ; Kristensen, VN ; Lakeman, IMM ; Li, J ; Lindblom, A ; Loizidou, MA ; Lophatananon, A ; Lubiński, J ; Luccarini, C ; Madsen, MJ ; Mannermaa, A ; Manoochehri, M ; Margolin, S ; Mavroudis, D ; Milne, RL ; Mohd Taib, NA ; Muir, K ; Nevanlinna, H ; Newman, WG ; Oosterwijk, JC ; Park, SK ; Peterlongo, P ; Radice, P ; Saloustros, E ; Sawyer, EJ ; Schmutzler, RK ; Shah, M ; Sim, X ; Southey, MC ; Surowy, H ; Suvanto, M ; Tomlinson, I ; Torres, D ; Truong, T ; van Asperen, CJ ; Waltes, R ; Wang, Q ; Yang, XR ; Pharoah, PDP ; Schmidt, MK ; Benitez, J ; Vroling, B ; Dunning, AM ; Teo, SH ; Kvist, A ; de la Hoya, M ; Devilee, P ; Spurdle, AB ; Vreeswijk, MPG ; Easton, DF (Springer Science and Business Media LLC, 2022-05-18)
    BACKGROUND: Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. METHODS: We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. RESULTS: The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. CONCLUSIONS: These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.
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    Genetic insights into biological mechanisms governing human ovarian ageing
    Ruth, KS ; Day, FR ; Hussain, J ; Martinez-Marchal, A ; Aiken, CE ; Azad, A ; Thompson, DJ ; Knoblochova, L ; Abe, H ; Tarry-Adkins, JL ; Gonzalez, JM ; Fontanillas, P ; Claringbould, A ; Bakker, OB ; Sulem, P ; Walters, RG ; Terao, C ; Turon, S ; Horikoshi, M ; Lin, K ; Onland-Moret, NC ; Sankar, A ; Hertz, EPT ; Timshel, PN ; Shukla, V ; Borup, R ; Olsen, KW ; Aguilera, P ; Ferrer-Roda, M ; Huang, Y ; Stankovic, S ; Timmers, PRHJ ; Ahearn, TU ; Alizadeh, BZ ; Naderi, E ; Andrulis, IL ; Arnold, AM ; Aronson, KJ ; Augustinsson, A ; Bandinelli, S ; Barbieri, CM ; Beaumont, RN ; Becher, H ; Beckmann, MW ; Benonisdottir, S ; Bergmann, S ; Bochud, M ; Boerwinkle, E ; Bojesen, SE ; Bolla, MK ; Boomsma, DI ; Bowker, N ; Brody, JA ; Broer, L ; Buring, JE ; Campbell, A ; Campbell, H ; Castelao, JE ; Catamo, E ; Chanock, SJ ; Chenevix-Trench, G ; Ciullo, M ; Corre, T ; Couch, FJ ; Cox, A ; Crisponi, L ; Cross, SS ; Cucca, F ; Czene, K ; Smith, GD ; de Geus, EJCN ; de Mutsert, R ; De Vivo, I ; Demerath, EW ; Dennis, J ; Dunning, AM ; Dwek, M ; Eriksson, M ; Esko, T ; Fasching, PA ; Faul, JD ; Ferrucci, L ; Franceschini, N ; Frayling, TM ; Gago-Dominguez, M ; Mezzavilla, M ; Garcia-Closas, M ; Gieger, C ; Giles, GG ; Grallert, H ; Gudbjartsson, DF ; Gudnason, V ; Guenel, P ; Haiman, CA ; Hakansson, N ; Hall, P ; Hayward, C ; He, C ; He, W ; Heiss, G ; Hoffding, MK ; Hopper, JL ; Hottenga, JJ ; Hu, F ; Hunter, D ; Ikram, MA ; Jackson, RD ; Joaquim, MDR ; John, EM ; Joshi, PK ; Karasik, D ; Kardia, SLR ; Kartsonaki, C ; Karlsson, R ; Kitahara, CM ; Kolcic, I ; Kooperberg, C ; Kraft, P ; Kurian, AW ; Kutalik, Z ; La Bianca, M ; LaChance, G ; Langenberg, C ; Launer, LJ ; Laven, JSE ; Lawlor, DA ; Le Marchand, L ; Li, J ; Lindblom, A ; Lindstrom, S ; Lindstrom, T ; Linet, M ; Liu, Y ; Liu, S ; Luan, J ; Magi, R ; Magnusson, PKE ; Mangino, M ; Mannermaa, A ; Marco, B ; Marten, J ; Martin, NG ; Mbarek, H ; McKnight, B ; Medland, SE ; Meisinger, C ; Meitinger, T ; Menni, C ; Metspalu, A ; Milani, L ; Milne, RL ; Montgomery, GW ; Mook-Kanamori, DO ; Mulas, A ; Mulligan, AM ; Murray, A ; Nalls, MA ; Newman, A ; Noordam, R ; Nutile, T ; Nyholt, DR ; Olshan, AF ; Olsson, H ; Painter, JN ; Patel, AV ; Pedersen, NL ; Perjakova, N ; Peters, A ; Peters, U ; Pharoah, PDP ; Polasek, O ; Porcu, E ; Psaty, BM ; Rahman, I ; Rennert, G ; Rennert, HS ; Ridker, PM ; Ring, SM ; Robino, A ; Rose, LM ; Rosendaal, FR ; Rossouw, J ; Rudan, I ; Rueedi, R ; Ruggiero, D ; Sala, CF ; Saloustros, E ; Sandler, DP ; Sanna, S ; Sawyer, EJ ; Sarnowski, C ; Schlessinger, D ; Schmidt, MK ; Schoemaker, MJ ; Schraut, KE ; Scott, C ; Shekari, S ; Shrikhande, A ; Smith, AV ; Smith, BH ; Smith, JA ; Sorice, R ; Southey, MC ; Spector, TD ; Spinelli, JJ ; Stampfer, M ; Stoeckl, D ; van Meurs, JBJ ; Strauch, K ; Styrkarsdottir, U ; Swerdlow, AJ ; Tanaka, T ; Teras, LR ; Teumer, A ; thorsteinsdottir, U ; Timpson, NJ ; Toniolo, D ; Traglia, M ; Troester, MA ; Truong, T ; Tyrrell, J ; Uitterlinden, AG ; Ulivi, S ; Vachon, CM ; Vitart, V ; Voelker, U ; Vollenweider, P ; Voelzke, H ; Wang, Q ; Wareham, NJ ; Weinberg, CR ; Weir, DR ; Wilcox, AN ; van Dijk, KW ; Willemsen, G ; Wilson, JF ; Wolffenbuttel, BHR ; Wolk, A ; Wood, AR ; Zhao, W ; Zygmunt, M ; Chen, Z ; Li, L ; Franke, L ; Burgess, S ; Deelen, P ; Pers, TH ; Grondahl, ML ; Andersen, CY ; Pujol, A ; Lopez-Contreras, AJ ; Daniel, JA ; Stefansson, K ; Chang-Claude, J ; van der Schouw, YT ; Lunetta, KL ; Chasman, DI ; Easton, DF ; Visser, JA ; Ozanne, SE ; Namekawa, SH ; Solc, P ; Murabito, JM ; Ong, KK ; Hoffmann, ER ; Murray, A ; Roig, I ; Perry, JRB (NATURE PORTFOLIO, 2021-08-04)
    Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.
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    Genetically Predicted Circulating C-Reactive Protein Concentration and Colorectal Cancer Survival: A Mendelian Randomization Consortium Study
    Hua, X ; Dai, JY ; Lindstrom, S ; Harrison, TA ; Lin, Y ; Alberts, SR ; Alwers, E ; Berndt, S ; Brenner, H ; Buchanan, DD ; Campbell, PT ; Casey, G ; Chang-Claude, J ; Gallinger, S ; Giles, GG ; Goldberg, RM ; Gunter, MJ ; Hoffmeister, M ; Jenkins, MA ; Joshi, AD ; Ma, W ; Milne, RL ; Murphy, N ; Pai, RK ; Sakoda, LC ; Schoen, RE ; Shi, Q ; Slattery, ML ; Song, M ; White, E ; Le Marchand, L ; Chan, AT ; Peters, U ; Newcomb, PA (AMER ASSOC CANCER RESEARCH, 2021-07-01)
    BACKGROUND: A positive association between circulating C-reactive protein (CRP) and colorectal cancer survival was reported in observational studies, which are susceptible to unmeasured confounding and reverse causality. We used a Mendelian randomization approach to evaluate the association between genetically predicted CRP concentrations and colorectal cancer-specific survival. METHODS: We used individual-level data for 16,918 eligible colorectal cancer cases of European ancestry from 15 studies within the International Survival Analysis of Colorectal Cancer Consortium. We calculated a genetic-risk score based on 52 CRP-associated genetic variants identified from genome-wide association studies. Because of the non-collapsibility of hazard ratios from Cox proportional hazards models, we used the additive hazards model to calculate hazard differences (HD) and 95% confidence intervals (CI) for the association between genetically predicted CRP concentrations and colorectal cancer-specific survival, overall and by stage at diagnosis and tumor location. Analyses were adjusted for age at diagnosis, sex, body mass index, genotyping platform, study, and principal components. RESULTS: Of the 5,395 (32%) deaths accrued over up to 10 years of follow-up, 3,808 (23%) were due to colorectal cancer. Genetically predicted CRP concentration was not associated with colorectal cancer-specific survival (HD, -1.15; 95% CI, -2.76 to 0.47 per 100,000 person-years; P = 0.16). Similarly, no associations were observed in subgroup analyses by stage at diagnosis or tumor location. CONCLUSIONS: Despite adequate power to detect moderate associations, our results did not support a causal effect of circulating CRP concentrations on colorectal cancer-specific survival. IMPACT: Future research evaluating genetically determined levels of other circulating inflammatory biomarkers (i.e., IL6) with colorectal cancer survival outcomes is needed.
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    Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3
    Mocci, E ; Kundu, P ; Wheeler, W ; Arslan, AA ; Beane-Freeman, LE ; Bracci, PM ; Brennan, P ; Canzian, F ; Du, M ; Gallinger, S ; Giles, GG ; Goodman, PJ ; Kooperberg, C ; Le Marchand, L ; Neale, RE ; Shu, X-O ; Visvanathan, K ; White, E ; Zheng, W ; Albanes, D ; Andreotti, G ; Babic, A ; Bamlet, WR ; Berndt, S ; Blackford, AL ; Bueno-de-Mesquita, B ; Buring, JE ; Campa, D ; Chanock, SJ ; Childs, EJ ; Duell, EJ ; Fuchs, CS ; Gaziano, JM ; Giovannucci, EL ; Goggins, MG ; Hartge, P ; Hassan, MM ; Holly, EA ; Hoover, RN ; Hung, RJ ; Kurtz, RC ; Lee, I-M ; Malats, N ; Milne, RL ; Ng, K ; Oberg, AL ; Panico, S ; Peters, U ; Porta, M ; Rabe, KG ; Riboli, E ; Rothman, N ; Scelo, G ; Sesso, HD ; Silverman, DT ; Stevens, VL ; Strobel, O ; Thompson, IM ; Tjonneland, A ; Trichopoulou, A ; Van den Eeden, SK ; Wactawski-Wende, J ; Wentzensen, N ; Wilkens, LR ; Yu, H ; Yuan, F ; Zeleniuch-Jacquotte, A ; Amundadottir, LT ; Li, D ; Jacobs, EJ ; Petersen, GM ; Wolpin, BM ; Risch, HA ; Kraft, P ; Chatterjee, N ; Klein, AP ; Stolzenberg-Solomon, R (AMER ASSOC CANCER RESEARCH, 2021-06-01)
    Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10-8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82-0.93; former smokers 1.00, 95% CI, 0.91-1.07; current smokers 1.25, 95% CI 1.12-1.40, P interaction = 3.08 × 10-9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r 2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. SIGNIFICANCE: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.
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    Breast Cancer Risk Factors and Survival by Tumor Subtype: Pooled Analyses from the Breast Cancer Association Consortium
    Morra, A ; Jung, AY ; Behrens, S ; Keeman, R ; Ahearn, TU ; Anton-Culver, H ; Arndt, V ; Augustinsson, A ; Auvinen, PK ; Freeman, LEB ; 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, J-Y ; Clarke, CL ; Couch, FJ ; Cox, A ; Cross, SS ; Czene, K ; Dork, T ; Dunning, AM ; Dwek, M ; Easton, DF ; Eccles, DM ; Egan, KM ; Evans, DG ; Fasching, PA ; Flyger, H ; Gago-Dominguez, M ; Gapstur, SM ; Garcia-Saenz, JA ; Gaudet, MM ; Giles, GG ; Grip, M ; Guenel, P ; Haiman, CA ; Hakansson, 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, J ; Lambrechts, D ; Le Marchand, L ; Li, J ; Lindblom, A ; Lush, M ; Mannermaa, A ; Manoochehri, M ; Margolin, S ; Mariapun, S ; Matsuo, K ; Mavroudis, D ; Milne, RL ; Muranen, TA ; Newman, WG ; Noh, D-Y ; Nordestgaard, BG ; Obi, N ; Olshan, AF ; Olsson, H ; Park-Simon, T-W ; 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, C-Y ; Shu, X-O ; 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, K-Y ; Yu, J-C ; Zheng, W ; Ziogas, A ; Yang, XR ; Eliassen, AH ; Holmes, MD ; Garcia-Closas, M ; Teo, SH ; Schmidt, MK ; Chang-Claude, J (AMER ASSOC CANCER RESEARCH, 2021-04-01)
    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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    Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing
    Southey, MC ; Dowty, JG ; Riaz, M ; Steen, JA ; Renault, A-L ; Tucker, K ; Kirk, J ; James, P ; Winship, I ; Pachter, N ; Poplawski, N ; Grist, S ; Park, DJ ; Pope, BJ ; Mahmood, K ; Hammet, F ; Mahmoodi, M ; Tsimiklis, H ; Theys, D ; Rewse, A ; Willis, A ; Morrow, A ; Speechly, C ; Harris, R ; Sebra, R ; Schadt, E ; Lacaze, P ; McNeil, JJ ; Giles, GG ; Milne, RL ; Hopper, JL ; Nguyen-Dumont, T (NATURE PORTFOLIO, 2021-12-09)
    Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing are urgently required. Most prior research has been based on women selected for high-risk features and more data is needed to make inference about breast cancer risk for women unselected for family history, an important consideration of population screening. We tested 1464 women diagnosed with breast cancer and 862 age-matched controls participating in the Australian Breast Cancer Family Study (ABCFS), and 6549 healthy, older Australian women enroled in the ASPirin in Reducing Events in the Elderly (ASPREE) study for rare germline variants using a 24-gene-panel. Odds ratios (ORs) were estimated using unconditional logistic regression adjusted for age and other potential confounders. We identified pathogenic variants in 11.1% of the ABCFS cases, 3.7% of the ABCFS controls and 2.2% of the ASPREE (control) participants. The estimated breast cancer OR [95% confidence interval] was 5.3 [2.1-16.2] for BRCA1, 4.0 [1.9-9.1] for BRCA2, 3.4 [1.4-8.4] for ATM and 4.3 [1.0-17.0] for PALB2. Our findings provide a population-based perspective to gene-panel testing for breast cancer predisposition and opportunities to improve predictors for identifying women who carry pathogenic variants in breast cancer predisposition genes.
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    Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk.
    Dareng, EO ; Tyrer, JP ; Barnes, DR ; Jones, MR ; Yang, X ; Aben, KKH ; Adank, MA ; Agata, S ; Andrulis, IL ; Anton-Culver, H ; Antonenkova, NN ; Aravantinos, G ; Arun, BK ; Augustinsson, A ; Balmaña, J ; Bandera, EV ; Barkardottir, RB ; Barrowdale, D ; Beckmann, MW ; Beeghly-Fadiel, A ; Benitez, J ; Bermisheva, M ; Bernardini, MQ ; Bjorge, L ; Black, A ; Bogdanova, NV ; Bonanni, B ; Borg, A ; Brenton, JD ; Budzilowska, A ; Butzow, R ; Buys, SS ; Cai, H ; Caligo, MA ; Campbell, I ; Cannioto, R ; Cassingham, H ; Chang-Claude, J ; Chanock, SJ ; Chen, K ; Chiew, Y-E ; Chung, WK ; Claes, KBM ; Colonna, S ; GEMO Study Collaborators, ; GC-HBOC Study Collaborators, ; EMBRACE Collaborators, ; Cook, LS ; Couch, FJ ; Daly, MB ; Dao, F ; Davies, E ; de la Hoya, M ; de Putter, R ; Dennis, J ; DePersia, A ; Devilee, P ; Diez, O ; Ding, YC ; Doherty, JA ; Domchek, SM ; Dörk, T ; du Bois, A ; Dürst, M ; Eccles, DM ; Eliassen, HA ; Engel, C ; Evans, GD ; Fasching, PA ; Flanagan, JM ; Fortner, RT ; Machackova, E ; Friedman, E ; Ganz, PA ; Garber, J ; Gensini, F ; Giles, GG ; Glendon, G ; Godwin, AK ; Goodman, MT ; Greene, MH ; Gronwald, J ; OPAL Study Group, ; AOCS Group, ; Hahnen, E ; Haiman, CA ; Håkansson, N ; Hamann, U ; Hansen, TVO ; Harris, HR ; Hartman, M ; Heitz, F ; Hildebrandt, MAT ; Høgdall, E ; Høgdall, CK ; Hopper, JL ; Huang, R-Y ; Huff, C ; Hulick, PJ ; Huntsman, DG ; Imyanitov, EN ; KConFab Investigators, ; HEBON Investigators, ; Isaacs, C ; Jakubowska, A ; James, PA ; Janavicius, R ; Jensen, A ; Johannsson, OT ; John, EM ; Jones, ME ; Kang, D ; Karlan, BY ; Karnezis, A ; Kelemen, LE ; Khusnutdinova, E ; Kiemeney, LA ; Kim, B-G ; Kjaer, SK ; Komenaka, I ; Kupryjanczyk, J ; Kurian, AW ; Kwong, A ; Lambrechts, D ; Larson, MC ; Lazaro, C ; Le, ND ; Leslie, G ; Lester, J ; Lesueur, F ; Levine, DA ; Li, L ; Li, J ; Loud, JT ; Lu, KH ; Lubiński, J ; Mai, PL ; Manoukian, S ; Marks, JR ; Matsuno, RK ; Matsuo, K ; May, T ; McGuffog, L ; McLaughlin, JR ; McNeish, IA ; Mebirouk, N ; Menon, U ; Miller, A ; Milne, RL ; Minlikeeva, A ; Modugno, F ; Montagna, M ; Moysich, KB ; Munro, E ; Nathanson, KL ; Neuhausen, SL ; Nevanlinna, H ; Yie, JNY ; Nielsen, HR ; Nielsen, FC ; Nikitina-Zake, L ; Odunsi, K ; Offit, K ; Olah, E ; Olbrecht, S ; Olopade, OI ; Olson, SH ; Olsson, H ; Osorio, A ; Papi, L ; Park, SK ; Parsons, MT ; Pathak, H ; Pedersen, IS ; Peixoto, A ; Pejovic, T ; Perez-Segura, P ; Permuth, JB ; Peshkin, B ; Peterlongo, P ; Piskorz, A ; Prokofyeva, D ; Radice, P ; Rantala, J ; Riggan, MJ ; Risch, HA ; Rodriguez-Antona, C ; Ross, E ; Rossing, MA ; Runnebaum, I ; Sandler, DP ; Santamariña, M ; Soucy, P ; Schmutzler, RK ; Setiawan, VW ; Shan, K ; Sieh, W ; Simard, J ; Singer, CF ; Sokolenko, AP ; Song, H ; Southey, MC ; Steed, H ; Stoppa-Lyonnet, D ; Sutphen, R ; Swerdlow, AJ ; Tan, YY ; Teixeira, MR ; Teo, SH ; Terry, KL ; Terry, MB ; OCAC Consortium, ; CIMBA Consortium, ; Thomassen, M ; Thompson, PJ ; Thomsen, LCV ; Thull, DL ; Tischkowitz, M ; Titus, L ; Toland, AE ; Torres, D ; Trabert, B ; Travis, R ; Tung, N ; Tworoger, SS ; Valen, E ; van Altena, AM ; van der Hout, AH ; Van Nieuwenhuysen, E ; van Rensburg, EJ ; Vega, A ; Edwards, DV ; Vierkant, RA ; Wang, F ; Wappenschmidt, B ; Webb, PM ; Weinberg, CR ; Weitzel, JN ; Wentzensen, N ; White, E ; Whittemore, AS ; Winham, SJ ; Wolk, A ; Woo, Y-L ; Wu, AH ; Yan, L ; Yannoukakos, D ; Zavaglia, KM ; Zheng, W ; Ziogas, A ; Zorn, KK ; Kleibl, Z ; Easton, D ; Lawrenson, K ; DeFazio, A ; Sellers, TA ; Ramus, SJ ; Pearce, CL ; Monteiro, AN ; Cunningham, J ; Goode, EL ; Schildkraut, JM ; Berchuck, A ; Chenevix-Trench, G ; Gayther, SA ; Antoniou, AC ; Pharoah, PDP (Springer Science and Business Media LLC, 2022-05)
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    Disparities in radiation therapy utilization for cancer patients in Victoria
    Ong, WL ; Finn, N ; Te Marvelde, L ; Hornby, C ; Milne, RL ; Hanna, GG ; Pitson, G ; Elsaleh, H ; Millar, JL ; Foroudi, F (WILEY, 2022-03-31)
    INTRODUCTION: To evaluate the proportion of cancer patients who received radiation therapy (RT) within 12 months of cancer diagnosis (RTU12) and identify factors associated with RTU12. METHODS: This is a population-based cohort of individuals with incident cancer, diagnosed between 2013 and 2017 in Victoria. Data linkages were performed between the Victorian Cancer Registry and Victorian Radiotherapy Minimum Dataset. The primary outcome was the proportion of patients who had RTU12. For the three most common cancers (i.e., prostate, breast and lung cancer), the time trend in RTU12 and factors associated with RTU12 were evaluated. RESULTS: The overall RTU12 in our study cohort was 26-20% radical RT and 6% palliative RT. Of the 21,735 men with prostate cancer, RTU12 was 17%, with no significant change over time (P-trend = 0.53). In multivariate analyses, increasing age and lower socioeconomic status were independently associated with higher RTU12 for prostate cancer. Of the 20,883 women with breast cancer, RTU12 was 64%, which increased from 62% in 2013 to 65% in 2017 (P-trend < 0.05). In multivariate analyses, age, socioeconomic status and area of residency were independently associated with RTU12 for breast cancer. Of the 13,093 patients with lung cancer, RTU12 was 42%, with no significant change over time (P-trend = 0.16). In multivariate analyses, younger age, male and lower socioeconomic status were independently associated with higher RTU12. CONCLUSION: In this large population-based state-wide cohort of cancer patients, only 1 in 4 had RT within 12 months of diagnosis. There were marked sociodemographic disparities in RTU12 for prostate, breast and lung cancer patients.
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    Patterns of the use of advanced radiation therapy techniques for the management of bone metastases and the associated factors in Victoria
    Fogarty, T ; Tacey, M ; McCorkell, G ; Kok, D ; Hornby, C ; Milne, RL ; Millar, J ; Foroudi, F ; Ong, WL (WILEY, 2022-02-01)
    INTRODUCTION: To describe the pattern of the use of advanced radiation therapy (RT) techniques, including intensity-modulated RT (IMRT), volumetric modulated arc therapy (VMAT), and stereotactic body RT (SBRT) for the management of bone metastases (BM), and the associated factors in Victoria. METHODS: We used a population-based cohort of patients from the state-wide Victorian Radiotherapy Minimum Data Set (VRMDS) who received RT for BM between 2012 and 2017. The primary outcome was proportion of RT courses using advanced RT techniques. The Cochran-Armitage test for trend was used to evaluate temporal trend in advanced RT use. Multinomial logistic regression was used to identify factors associated with advanced RT use. RESULTS: A total of 18,158 courses of RT were delivered to 10,956 patients-16,626 (91.6%) courses were 3D conformal RT, 857 (4.7%) IMRT/VMAT and 675 (3.7%) SBRT. There was a sharp increase in IMRT/VMAT use from <1% in 2012-2015, to 10.1% in 2016 and 16.3% in 2017 (P-trend < 0.001). Increase in SBRT use was more gradual, from 1.2% in 2012 to 4.8% in 2016 and 5.5% in 2017 for SBRT (P-trend<0.001). In multivariate analyses, year of RT was the strongest predictor of IMRT/VMAT use (OR = 41; 95%CI = 25-67; P < 0.001, comparing 2012-2013 and 2016-2017). Primary tumour type (prostate cancer) was the strongest predictor of SBRT use (OR = 6.07; 95% CI = 4.19-8.80; P < 0.001). CONCLUSION: Overall, there was increasing trend in the use of advanced RT techniques for BM in Victoria, with a distinct pattern for IMRT/VMAT compared with SBRT - SBRT uptake was more gradual while IMRT/VMAT uptake was abrupt, occurring contemporaneously with Medicare Benefit Scheme funding changes in 2016.
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    A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women
    Wang, X ; Chen, H ; Kapoor, PM ; Su, Y-R ; Bolla, MK ; Dennis, J ; Dunning, AM ; Lush, M ; Wang, Q ; Michailidou, K ; Pharoah, PDP ; Hopper, JL ; Southey, MC ; Koutros, S ; Freeman, LEB ; Stone, J ; Rennert, G ; Shibli, R ; Murphy, RA ; Aronson, K ; Guénel, P ; Truong, T ; Teras, LR ; Hodge, JM ; Canzian, F ; Kaaks, R ; Brenner, H ; Arndt, V ; Hoppe, R ; Lo, W-Y ; Behrens, S ; Mannermaa, A ; Kosma, V-M ; Jung, A ; Becher, H ; Giles, GG ; Haiman, CA ; Maskarinec, G ; Scott, C ; Winham, S ; Simard, J ; Goldberg, MS ; Zheng, W ; Long, J ; Troester, MA ; Love, MI ; Peng, C ; Tamimi, R ; Eliassen, H ; García-Closas, M ; Figueroa, J ; Ahearn, T ; Yang, R ; Evans, DG ; Howell, A ; Hall, P ; Czene, K ; Wolk, A ; Sandler, DP ; Taylor, JA ; Swerdlow, AJ ; Orr, N ; Lacey, JV ; Wang, S ; Olsson, H ; Easton, DF ; Milne, RL ; Hsu, L ; Kraft, P ; Chang-Claude, J ; Lindström, S (American Association for Cancer Research (AACR), 2022-04-08)
    Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P &lt; 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk.