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1. Pre-diagnosis tea and coffee consumption and survival after a diagnosis of ovarian cancer: results from the Ovarian Cancer Association Consortium.

Author

Nagle, CM, Ibiebele, TI, Bandera, EV, Cramer, D, Doherty, JA, Giles, GG, Goodman, MT, Hanley, GE, Harris, HR, Jensen, A, Kjaer, SK, Lee, AW, Milne, RL, Qin, B, Richardson, J, Sasamoto, N, Sieh, W, Terry, KL, Titus, L, Trabert, B, Wentzensen, N, Wu, AH, Berchuck, A, Pike, M, Pearce, CL, Webb, PM, Nagle, CM, Ibiebele, TI, Bandera, EV, Cramer, D, Doherty, JA, Giles, GG, Goodman, MT, Hanley, GE, Harris, HR, Jensen, A, Kjaer, SK, Lee, AW, Milne, RL, Qin, B, Richardson, J, Sasamoto, N, Sieh, W, Terry, KL, Titus, L, Trabert, B, Wentzensen, N, Wu, AH, Berchuck, A, Pike, M, Pearce, CL, and Webb, PM

Abstract

BACKGROUND: Tea and coffee are the most frequently consumed beverages in the world. Green tea in particular contains compounds with potential anti-cancer effects, but its association with survival after ovarian cancer is uncertain. METHODS: We investigated the associations between tea and coffee consumption before diagnosis and survival using data from 10 studies in the Ovarian Cancer Association Consortium. Data on tea (green, black, herbal), coffee and caffeine intake were available for up to 5724 women. We used Cox proportional hazards regression to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CI). RESULTS: Compared with women who did not drink any green tea, consumption of one or more cups/day was associated with better overall survival (aHR = 0.84, 95% CI 0.71-1.00, p-trend = 0.04). A similar association was seen for ovarian cancer-specific survival in five studies with this information (aHR = 0.81, 0.66-0.99, p-trend = 0.045). There was no consistent variation between subgroups defined by clinical or lifestyle characteristics and adjustment for other aspects of lifestyle did not appreciably alter the estimates. We found no evidence of an association between coffee, black or herbal tea, or caffeine intake and survival. CONCLUSION: The observed association with green tea consumption before diagnosis raises the possibility that consumption after diagnosis might improve patient outcomes.

Published
2024

2. Epithelial-Mesenchymal Transition (EMT) Gene Variants and Epithelial Ovarian Cancer (EOC) Risk

Author

Amankwah, EK, Lin, HY, Tyrer, JP, Lawrenson, K, Dennis, J, Chornokur, G, Aben, KKH, Anton-Culver, H, Antonenkova, N, Bruinsma, F, Bandera, EV, Bean, YT, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bunker, CH, Butzow, R, Campbell, IG, Carty, K, Chen, Z, Chen, YA, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, du Bois, A, Despierre, E, Dicks, E, Doherty, JA, Dörk, T, Dürst, M, Easton, DF, Eccles, DM, Edwards, RP, Ekici, AB, Fasching, PA, Fridley, BL, Gao, YT, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goodman, MT, Gronwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, CK, Hogdall, E, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, BT, Karlan, BY, Jim, H, Kellar, M, Kiemeney, LA, Krakstad, C, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lim, BK, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, Mcguire, V, Mclaughlin, JR, Mcneish, I, Menon, U, Milne, RL, Modugno, F, Moysich, KB, Ness, RB, Nevanlinna, H, Eilber, U, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, and Weber, RP

Subjects
Epidemiology, Public Health and Health Services, Genetics
Abstract

Epithelial-mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single-nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome-wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT-related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive-cancer patients and 23,447 controls. A P-value

Published
2015

3. Obesity and survival among women with ovarian cancer: results from the Ovarian Cancer Association Consortium

Author

Nagle, CM, Dixon, SC, Jensen, A, Kjaer, SK, Modugno, F, deFazio, A, Fereday, S, Hung, J, Johnatty, SE, Fasching, PA, Beckmann, MW, Lambrechts, D, Vergote, I, Van Nieuwenhuysen, E, Lambrechts, S, Risch, HA, Rossing, MA, Doherty, JA, Wicklund, KG, Chang-Claude, J, Goodman, MT, Ness, RB, Moysich, K, Heitz, F, du Bois, A, Harter, P, Schwaab, I, Matsuo, K, Hosono, S, Goode, EL, Vierkant, RA, Larson, MC, Fridley, BL, Høgdall, C, Schildkraut, JM, Weber, RP, Cramer, DW, Terry, KL, Bandera, EV, Paddock, L, Rodriguez-Rodriguez, L, Wentzensen, N, Yang, HP, Brinton, LA, Lissowska, J, Høgdall, E, Lundvall, L, Whittemore, A, McGuire, V, Sieh, W, Rothstein, J, Sutphen, R, Anton-Culver, H, Ziogas, A, Pearce, CL, Wu, AH, and Webb, PM

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Rare Diseases, Ovarian Cancer, Women's Health, Prevention, Cancer, Obesity, 2.1 Biological and endogenous factors, Body Mass Index, Carcinoma, Ovarian Epithelial, Disease-Free Survival, Female, Humans, Kaplan-Meier Estimate, Neoplasms, Glandular and Epithelial, Ovarian Neoplasms, ovarian cancer, obesity, overall survival, progression-free survival, ovarian cancer-specific survival, Australian Ovarian Cancer Study Group, Ovarian Cancer Association Consortium, Public Health and Health Services, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundObservational studies have reported a modest association between obesity and risk of ovarian cancer; however, whether it is also associated with survival and whether this association varies for the different histologic subtypes are not clear. We undertook an international collaborative analysis to assess the association between body mass index (BMI), assessed shortly before diagnosis, progression-free survival (PFS), ovarian cancer-specific survival and overall survival (OS) among women with invasive ovarian cancer.MethodsWe used original data from 21 studies, which included 12 390 women with ovarian carcinoma. We combined study-specific adjusted hazard ratios (HRs) using random-effects models to estimate pooled HRs (pHR). We further explored associations by histologic subtype.ResultsOverall, 6715 (54%) deaths occurred during follow-up. A significant OS disadvantage was observed for women who were obese (BMI: 30-34.9, pHR: 1.10 (95% confidence intervals (CIs): 0.99-1.23); BMI: ⩾35, pHR: 1.12 (95% CI: 1.01-1.25)). Results were similar for PFS and ovarian cancer-specific survival. In analyses stratified by histologic subtype, associations were strongest for women with low-grade serous (pHR: 1.12 per 5 kg m(-2)) and endometrioid subtypes (pHR: 1.08 per 5 kg m(-2)), and more modest for the high-grade serous (pHR: 1.04 per 5 kg m(-2)) subtype, but only the association with high-grade serous cancers was significant.ConclusionsHigher BMI is associated with adverse survival among the majority of women with ovarian cancer.

Published
2015

4. Methodological considerations in estimation of phenotype heritability using genome-wide SNP data, illustrated by an analysis of the heritability of height in a large sample of African ancestry adults

Author

Witte, John, Chen, F, He, J, Zhang, J, Chen, GK, Thomas, V, Ambrosone, CB, Bandera, EV, Berndt, SI, Bernstein, L, and Blot, WJ

Abstract

© This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public doma

Published
2015

5. Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Author

Dareng, EO, Tyrer, JP, Barnes, DR, Jones, MR, Yang, X, Aben, KKH, Adank, MA, Agata, S, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Aravantinos, G, Arun, BK, Augustinsson, A, Balmaña, J, Bandera, EV, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bermisheva, M, Bernardini, MQ, Bjorge, L, Black, A, Bogdanova, NV, Bonanni, B, Borg, A, Brenton, JD, Budzilowska, A, Butzow, R, Buys, SS, Cai, H, Caligo, MA, Campbell, I, Cannioto, R, Cassingham, H, Chang-Claude, J, Chanock, SJ, Chen, K, Chiew, YE, Chung, WK, Claes, KBM, Colonna, S, Cook, LS, Couch, FJ, Daly, MB, Dao, F, Davies, E, De La Hoya, M, De Putter, R, Dennis, J, DePersia, A, Devilee, P, Diez, O, Ding, YC, Doherty, JA, Domchek, SM, Dörk, T, Du Bois, A, Dürst, M, Eccles, DM, Eliassen, HA, Engel, C, Evans, GD, Fasching, PA, Flanagan, JM, Fortner, RT, Machackova, E, Friedman, E, Ganz, PA, Garber, J, Gensini, F, Giles, GG, Glendon, G, Godwin, AK, Goodman, MT, Greene, MH, Gronwald, J, Hahnen, E, Haiman, CA, Håkansson, N, Hamann, U, Hansen, TVO, Harris, HR, Hartman, M, Heitz, F, Hildebrandt, MAT, Høgdall, E, Høgdall, CK, Hopper, JL, Huang, RY, Huff, C, Hulick, PJ, Huntsman, DG, Imyanitov, EN, Van Der Hout, AH, Isaacs, C, Jakubowska, A, James, PA, Dareng, EO [0000-0003-0802-419X], Tyrer, JP [0000-0003-3724-4757], Barnes, DR [0000-0002-3781-7570], Yang, X [0000-0003-0037-3790], Andrulis, IL [0000-0002-4226-6435], Augustinsson, A [0000-0003-3415-0536], Barrowdale, D [0000-0003-1661-3939], Bonanni, B [0000-0003-3589-2128], Brenton, JD [0000-0002-5738-6683], Butzow, R [0000-0003-4366-5099], Chanock, SJ [0000-0002-2324-3393], Claes, KBM [0000-0003-0841-7372], de la Hoya, M [0000-0002-8113-1410], de Putter, R [0000-0001-9410-8941], Dennis, J [0000-0003-4591-1214], Devilee, P [0000-0002-8023-2009], du Bois, A [0000-0002-8477-506X], Machackova, E [0000-0002-0246-1471], Giles, GG [0000-0003-4946-9099], Godwin, AK [0000-0002-3987-9580], Greene, MH [0000-0003-1852-9239], Heitz, F [0000-0002-2412-0352], Hulick, PJ [0000-0001-8397-4078], Jakubowska, A [0000-0002-5650-0501], James, PA [0000-0002-4361-4657], and Apollo - University of Cambridge Repository

Subjects
Rare Diseases, FOS: Biological sciences, Prevention, Genetics, 32 Biomedical and Clinical Sciences, 3211 Oncology and Carcinogenesis, 3105 Genetics, 31 Biological Sciences, Ovarian Cancer, Cancer
Abstract

Funder: Funding details are provided in the Supplementary Material, Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally-efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestry; 7,669 women of East Asian ancestry; 1,072 women of African ancestry, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestry. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38(95%CI:1.28–1.48,AUC:0.588) per unit standard deviation, in women of European ancestry; 1.14(95%CI:1.08–1.19,AUC:0.538) in women of East Asian ancestry; 1.38(95%CI:1.21-1.58,AUC:0.593) in women of African ancestry; hazard ratios of 1.37(95%CI:1.30–1.44,AUC:0.592) in BRCA1 pathogenic variant carriers and 1.51(95%CI:1.36-1.67,AUC:0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

Published
2022
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6. Polygenic risk modeling for prediction of epithelial ovarian cancer risk (vol 30, pg 349, 2021)

Author

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, Balmana, 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, 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, Dork, T, du Bois, A, Durst, M, Eccles, DM, Eliassen, HA, Engel, C, Evans, GD, Fasching, PA, Flanagan, JM, Fortner, RT, Machackova, E, Friedman, E, Ganz, PA, Garber, J, Gensini, F, Giles, GG, Glendon, G, Godwin, AK, Goodman, MT, Greene, MH, Gronwald, J, Hahnen, E, Haiman, CA, Hakansson, N, Hamann, U, Hansen, TVO, Harris, HR, Hartman, M, Heitz, F, Hildebrandt, MAT, Hogdall, E, Hogdall, CK, Hopper, JL, Huang, R-Y, Huff, C, Hulick, PJ, Huntsman, DG, Imyanitov, EN, Isaacs, C, Jakubowska, A, James, PA, Janavicius, R, Jensen, A, Johannsson, OT, John, EM, Jones, ME, Kang, D, Karlan, BY, Karnezis, A, Kelemen, LE, Khusnutdinova, E, Kiemeney, LA, Kim, 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, Lubinski, 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, Santamarina, M, Soucy, P, Schmutzler, RK, Setiawan, VW, Shan, K, Sieh, W, Simard, J, Singer, CF, Sokolenko, AP, Song, H, Southey, MC, Steed, H, Stoppa-Lyonnet, D, Sutphen, R, Swerdlow, AJ, Tan, YY, Teixeira, MR, Teo, SH, Terry, KL, Terry, MB, Thomassen, M, Thompson, PJ, Thomsen, LCV, Thull, DL, Tischkowitz, M, Titus, L, Toland, AE, Torres, D, Trabert, B, Travis, R, Tung, N, Tworoger, SS, Valen, E, van Altena, AM, van der Hout, AH, Van Nieuwenhuysen, E, van Rensburg, EJ, Vega, A, Edwards, DV, Vierkant, RA, Wang, F, Wappenschmidt, B, Webb, PM, Weinberg, CR, Weitzel, JN, Wentzensen, N, White, E, Whittemore, AS, Winham, SJ, Wolk, A, Woo, 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, JM, Goode, EL, Schildkraut, JM, Berchuck, A, Chenevix-Trench, G, Gayther, SA, Antoniou, AC, Pharoah, PDP, 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, Balmana, 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, 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, Dork, T, du Bois, A, Durst, M, Eccles, DM, Eliassen, HA, Engel, C, Evans, GD, Fasching, PA, Flanagan, JM, Fortner, RT, Machackova, E, Friedman, E, Ganz, PA, Garber, J, Gensini, F, Giles, GG, Glendon, G, Godwin, AK, Goodman, MT, Greene, MH, Gronwald, J, Hahnen, E, Haiman, CA, Hakansson, N, Hamann, U, Hansen, TVO, Harris, HR, Hartman, M, Heitz, F, Hildebrandt, MAT, Hogdall, E, Hogdall, CK, Hopper, JL, Huang, R-Y, Huff, C, Hulick, PJ, Huntsman, DG, Imyanitov, EN, Isaacs, C, Jakubowska, A, James, PA, Janavicius, R, Jensen, A, Johannsson, OT, John, EM, Jones, ME, Kang, D, Karlan, BY, Karnezis, A, Kelemen, LE, Khusnutdinova, E, Kiemeney, LA, Kim, 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, Lubinski, 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, Santamarina, M, Soucy, P, Schmutzler, RK, Setiawan, VW, Shan, K, Sieh, W, Simard, J, Singer, CF, Sokolenko, AP, Song, H, Southey, MC, Steed, H, Stoppa-Lyonnet, D, Sutphen, R, Swerdlow, AJ, Tan, YY, Teixeira, MR, Teo, SH, Terry, KL, Terry, MB, Thomassen, M, Thompson, PJ, Thomsen, LCV, Thull, DL, Tischkowitz, M, Titus, L, Toland, AE, Torres, D, Trabert, B, Travis, R, Tung, N, Tworoger, SS, Valen, E, van Altena, AM, van der Hout, AH, Van Nieuwenhuysen, E, van Rensburg, EJ, Vega, A, Edwards, DV, Vierkant, RA, Wang, F, Wappenschmidt, B, Webb, PM, Weinberg, CR, Weitzel, JN, Wentzensen, N, White, E, Whittemore, AS, Winham, SJ, Wolk, A, Woo, 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, JM, Goode, EL, Schildkraut, JM, Berchuck, A, Chenevix-Trench, G, Gayther, SA, Antoniou, AC, and Pharoah, PDP

Published
2022

8. A transcriptome-wide association study among 97,898 women to identify candidate susceptibility genes for epithelial ovarian cancer risk

Author

Lu, Y, Beeghly-Fadiel, A, Wu, L, Guo, X, Li, B, Schildkraut, JM, Im, HK, Chen, YA, Permuth, JB, Reid, BM, Teer, JK, Moysich, KB, Andrulis, IL, Anton-Culver, H, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Benitez, J, Bjorge, L, Brenton, J, Butzow, R, Caldes, T, Caligo, MA, Campbell, I, Chang-Claude, J, Claes, KBM, Couch, FJ, Cramer, DW, Daly, MB, DeFazio, A, Dennis, J, Diez, O, Domchek, SM, D rk, T, Easton, DF, Eccles, DM, Fasching, PA, Fortner, RET, Fountzilas, G, Friedman, E, Ganz, PA, Garber, J, Giles, GG, Godwin, AK, Goldgar, DE, Goodman, MT, Greene, MH, Gronwald, J, Hamann, U, Heitz, F, Hildebrandt, MAT, Høgdall, CK, Hollestelle, A, Hulick, PJ, Huntsman, DG, Imyanitov, EN, Isaacs, C, Jakubowska, A, James, P, Karlan, BY, Kelemen, LE, Kiemeney, LA, Kjaer, SK, Kwong, A, Le, ND, Leslie, G, Lesueur, F, Levine, DA, Mattiello, A, May, T, McGuffog, L, and McNeish, IA

Subjects
endocrine system diseases, female genital diseases and pregnancy complications
Abstract

© 2018 American Association for Cancer Research. Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 106, we identified 35 genes, including FZD4 at 11q14.2 (Z ¼ 5.08, P ¼ 3.83 107, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 103). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.

Published
2018
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9. Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility

Author

Earp, M, Tyrer, JP, Winham, SJ, Lin, HY, Chornokur, G, Dennis, J, Aben, KKH, Anton-Culver, H, Antonenkova, N, Bandera, EV, Bean, YT, Beckmann, MW, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Bunker, CH, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Despierre, E, Doherty, JA, Dörk, T, Du Bois, A, Dürst, M, Easton, DF, Eccles, DM, Edwards, RP, Ekici, AB, Fasching, PA, Fridley, BL, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goodman, MT, Gronwald, J, Harter, P, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, CK, Høgdall, E, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, BT, Jung, AY, Karlan, BY, Kellar, M, Kiemeney, LA, Lim, BK, Kjaer, SK, Krakstad, C, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lele, S, Lester, J, Levine, DA, Li, Z, Liang, D, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, and McGuire, V

Subjects
endocrine system diseases, female genital diseases and pregnancy complications
Abstract

© This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify bio-features and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR = 1.33, p = 4.46 x 10−6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR = 1.07, p = 0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR = 0.90, p = 0.00033; rs927062, OR = 0.94, p = 0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations.

Published
2018
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10. Adult height is associated with increased risk of ovarian cancer: A Mendelian randomisation study

Author

Dixon-Suen, SC, Nagle, CM, Thrift, AP, Pharoah, PDP, Ewing, A, Pearce, CL, Zheng, W, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Lambrechts, D, Vergote, I, Lambrechts, S, Van Nieuwenhuysen, E, Rossing, MA, Doherty, JA, Wicklund, KG, Chang-Claude, J, Jung, AY, Moysich, KB, Odunsi, K, Goodman, MT, Wilkens, LR, Thompson, PJ, Shvetsov, YB, Dörk, T, Park-Simon, TW, Hillemanns, P, Bogdanova, N, Butzow, R, Nevanlinna, H, Pelttari, LM, Leminen, A, Modugno, F, Ness, RB, Edwards, RP, Kelley, JL, Heitz, F, Du Bois, A, Harter, P, Schwaab, I, Karlan, BY, Lester, J, Orsulic, S, Rimel, BJ, Kjær, SK, Høgdall, E, Jensen, A, Goode, EL, Fridley, BL, Cunningham, JM, Winham, SJ, Giles, GG, Bruinsma, F, Milne, RL, Southey, MC, Hildebrandt, MAT, Wu, X, Lu, KH, Liang, D, Levine, DA, Bisogna, M, Schildkraut, JM, Berchuck, A, Cramer, DW, Terry, KL, Bandera, EV, Olson, SH, Salvesen, HB, Thomsen, LCV, Kopperud, RK, Bjorge, L, Kiemeney, LA, Massuger, LFAG, and Pejovic, T

Subjects
Australian Ovarian Cancer Study Group, Ovarian Cancer Association Consortium
Abstract

© 2018 Cancer Research UK. Background: Observational studies suggest greater height is associated with increased ovarian cancer risk, but cannot exclude bias and/or confounding as explanations for this. Mendelian randomisation (MR) can provide evidence which may be less prone to bias. Methods: We pooled data from 39 Ovarian Cancer Association Consortium studies (16,395 cases; 23,003 controls). We applied two-stage predictor-substitution MR, using a weighted genetic risk score combining 609 single-nucleotide polymorphisms. Study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted height and risk were pooled using random-effects meta-analysis. Results: Greater genetically predicted height was associated with increased ovarian cancer risk overall (pooled-OR (pOR) = 1.06; 95% CI: 1.01-1.11 per 5 cm increase in height), and separately for invasive (pOR = 1.06; 95% CI: 1.01-1.11) and borderline (pOR = 1.15; 95% CI: 1.02-1.29) tumours. Conclusions: Women with a genetic propensity to being taller have increased risk of ovarian cancer. This suggests genes influencing height are involved in pathways promoting ovarian carcinogenesis.

Published
2018
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11. Shared heritability and functional enrichment across six solid cancers

Author

Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboeller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, defazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Doerk, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuhl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Aguado-Barrera, ME, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, Mckay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, Lindstrom, S, Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboeller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, defazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Doerk, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuhl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Aguado-Barrera, ME, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, Mckay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, and Lindstrom, S

Abstract

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10-8), breast and ovarian cancer (rg = 0.24, p = 7 × 10-5), breast and lung cancer (rg = 0.18, p =1.5 × 10-6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10-4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.

Published
2019

12. Shared heritability and functional enrichment across six solid cancers (vol 10, 431, 2019)

Author

Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, deFazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Dork, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuehl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Elias Aguado-Barrera, M, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, McKay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, Lindstrom, S, Jiang, X, Finucane, HK, Schumacher, FR, Schmit, SL, Tyrer, JP, Han, Y, Michailidou, K, Lesseur, C, Kuchenbaecker, KB, Dennis, J, Conti, DV, Casey, G, Gaudet, MM, Huyghe, JR, Albanes, D, Aldrich, MC, Andrew, AS, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Antonenkova, NN, Arnold, SM, Aronson, KJ, Arun, BK, Bandera, EV, Barkardottir, RB, Barnes, DR, Batra, J, Beckmann, MW, Benitez, J, Benlloch, S, Berchuck, A, Berndt, SI, Bickeboller, H, Bien, SA, Blomqvist, C, Boccia, S, Bogdanova, NV, Bojesen, SE, Bolla, MK, Brauch, H, Brenner, H, Brenton, JD, Brook, MN, Brunet, J, Brunnstrom, H, Buchanan, DD, Burwinkel, B, Butzow, R, Cadoni, G, Caldes, T, Caligo, MA, Campbell, I, Campbell, PT, Cancel-Tassin, G, Cannon-Albright, L, Campa, D, Caporaso, N, Carvalho, AL, Chan, AT, Chang-Claude, J, Chanock, SJ, Chen, C, Christiani, DC, Claes, KBM, Claessens, F, Clements, J, Collee, JM, Correa, MC, Couch, FJ, Cox, A, Cunningham, JM, Cybulski, C, Czene, K, Daly, MB, deFazio, A, Devilee, P, Diez, O, Gago-Dominguez, M, Donovan, JL, Dork, T, Duell, EJ, Dunning, AM, Dwek, M, Eccles, DM, Edlund, CK, Edwards, DRV, Ellberg, C, Evans, DG, Fasching, PA, Ferris, RL, Liloglou, T, Figueiredo, JC, Fletcher, O, Fortner, RT, Fostira, F, Franceschi, S, Friedman, E, Gallinger, SJ, Ganz, PA, Garber, J, Garcia-Saenz, JA, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, Goode, EL, Goodman, MT, Goodman, G, Grankvist, K, Greene, MH, Gronberg, H, Gronwald, J, Guenel, P, Hakansson, N, Hall, P, Hamann, U, Hamdy, FC, Hamilton, RJ, Hampe, J, Haugen, A, Heitz, F, Herrero, R, Hillemanns, P, Hoffmeister, M, Hogdall, E, Hong, Y-C, Hopper, JL, Houlston, R, Hulick, PJ, Hunter, DJ, Huntsman, DG, Idos, G, Imyanitov, EN, Ingles, SA, Isaacs, C, Jakubowska, A, James, P, Jenkins, MA, Johansson, M, John, EM, Joshi, AD, Kaneva, R, Karlan, BY, Kelemen, LE, Kuehl, T, Khaw, K-T, Khusnutdinova, E, Kibel, AS, Kiemeney, LA, Kim, J, Kjaer, SK, Knight, JA, Kogevinas, M, Kote-Jarai, Z, Koutros, S, Kristensen, VN, Kupryjanczyk, J, Lacko, M, Lam, S, Lambrechts, D, Landi, MT, Lazarus, P, Le, ND, Lee, E, Lejbkowicz, F, Lenz, H-J, Leslie, G, Lessel, D, Lester, J, Levine, DA, Li, L, Li, CI, Lindblom, A, Lindor, NM, Liu, G, Loupakis, F, Lubinski, J, Maehle, L, Maier, C, Mannermaa, A, Le Marchand, L, Margolin, S, May, T, McGuffog, L, Meindl, A, Middha, P, Miller, A, Milne, RL, MacInnis, RJ, Modugno, F, Montagna, M, Moreno, V, Moysich, KB, Mucci, L, Muir, K, Mulligan, AM, Nathanson, KL, Neal, DE, Ness, AR, Neuhausen, SL, Nevanlinna, H, Newcomb, PA, Newcomb, LF, Nielsen, FC, Nikitina-Zake, L, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Al Olama, AA, Olopade, OI, Olshan, AF, Olsson, H, Osorio, A, Pandha, H, Park, JY, Pashayan, N, Parsons, MT, Pejovic, T, Penney, KL, Peters, WHM, Phelan, CM, Phipps, AI, Plaseska-Karanfilska, D, Pring, M, Prokofyeva, D, Radice, P, Stefansson, K, Ramus, SJ, Raskin, L, Rennert, G, Rennert, HS, van Rensburg, EJ, Riggan, MJ, Risch, HA, Risch, A, Roobol, MJ, Rosenstein, BS, Rossing, MA, De Ruyck, K, Saloustros, E, Sandler, DP, Sawyer, EJ, Schabath, MB, Schleutker, J, Schmidt, MK, Setiawan, VW, Shen, H, Siegel, EM, Sieh, W, Singer, CF, Slattery, ML, Sorensen, KD, Southey, MC, Spurdle, AB, Stanford, JL, Stevens, VL, Stintzing, S, Stone, J, Sundfeldt, K, Sutphen, R, Swerdlow, AJ, Tajara, EH, Tangen, CM, Tardon, A, Taylor, JA, Teare, MD, Teixeira, MR, Terry, MB, Terry, KL, Thibodeau, SN, Thomassen, M, Bjorge, L, Tischkowitz, M, Toland, AE, Torres, D, Townsend, PA, Travis, RC, Tung, N, Tworoger, SS, Ulrich, CM, Usmani, N, Vachon, CM, Van Nieuwenhuysen, E, Vega, A, Elias Aguado-Barrera, M, Wang, Q, Webb, PM, Weinberg, CR, Weinstein, S, Weissler, MC, Weitzel, JN, West, CML, White, E, Whittemore, AS, Wichmann, H-E, Wiklund, F, Winqvist, R, Wolk, A, Woll, P, Woods, M, Wu, AH, Wu, X, Yannoukakos, D, Zheng, W, Zienolddiny, S, Ziogas, A, Zorn, KK, Lane, JM, Saxena, R, Thomas, D, Hung, RJ, Diergaarde, B, McKay, J, Peters, U, Hsu, L, Garcia-Closas, M, Eeles, RA, Chenevix-Trench, G, Brennan, PJ, Haiman, CA, Simard, J, Easton, DF, Gruber, SB, Pharoah, PDP, Price, AL, Pasaniuc, B, Amos, CI, Kraft, P, and Lindstrom, S

Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019

13. History of hypertension, heart disease, and diabetes and ovarian cancer patient survival: evidence from the ovarian cancer association consortium

Author

Minlikeeva, AN, Freudenheim, JL, Cannioto, RA, Szender, JB, Eng, KH, Modugno, F, Ness, RB, LaMonte, MJ, Friel, G, Segal, BH, Odunsi, K, Mayor, P, Zsiros, E, Schmalfeldt, B, Klapdor, R, Doerk, T, Hillemanns, P, Kelemen, LE, Kobel, M, Steed, H, de Fazio, A, Jordan, SJ, Nagle, CM, Risch, HA, Rossing, MA, Doherty, JA, Goodman, MT, Edwards, R, Matsuo, K, Mizuno, M, Karlan, BY, Kjaer, SK, Hogdall, E, Jensen, A, Schildkraut, JM, Terry, KL, Cramer, DW, Bandera, EV, Paddock, LE, Kiemeney, LA, Massuger, LF, Kupryjanczyk, J, Berchuck, A, Chang-Claude, J, Diergaarde, B, Webb, PM, Moysich, KB, Grp, AOCS, and Consortium, OCA

Subjects
Australian Ovarian Cancer Study Group, Risk, Adult, Heart Diseases, Epidemiology, Ovarian Cancer Association Consortium, Adrenergic beta-Antagonists, Oncology and Carcinogenesis, Medications, Cardiovascular, Disease-Free Survival, Rare Diseases, Clinical Research, Diabetes Mellitus, Genetics, Humans, Insulin, Hypoglycemic Agents, Mortality, Aged, Cancer, Ovarian Neoplasms, screening and diagnosis, Beta blockers, Ovarian cancer prognosis, Diabetes, Middle Aged, Ovarian Cancer, 4.1 Discovery and preclinical testing of markers and technologies, Survival Rate, Detection, Good Health and Well Being, Hypertension, Public Health and Health Services, Female
Abstract

PurposeSurvival following ovarian cancer diagnosis is generally low; understanding factors related to prognosis could be important to optimize treatment. The role of previously diagnosed comorbidities and use of medications for those conditions in relation to prognosis for ovarian cancer patients has not been studied extensively, particularly according to histological subtype.MethodsUsing pooled data from fifteen studies participating in the Ovarian Cancer Association Consortium, we examined the associations between history of hypertension, heart disease, diabetes, and medications taken for these conditions and overall survival (OS) and progression-free survival (PFS) among patients diagnosed with invasive epithelial ovarian carcinoma. We used Cox proportional hazards regression models adjusted for age and stage to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) overall and within strata of histological subtypes.ResultsHistory of diabetes was associated with increased risk of mortality (n = 7,674; HR = 1.12; 95% CI = 1.01-1.25). No significant mortality associations were observed for hypertension (n = 6,482; HR = 0.95; 95% CI = 0.88-1.02) or heart disease (n = 4,252; HR = 1.05; 95% CI = 0.87-1.27). No association of these comorbidities was found with PFS in the overall study population. However, among patients with endometrioid tumors, hypertension was associated with lower risk of progression (n = 339, HR = 0.54; 95% CI = 0.35-0.84). Comorbidity was not associated with OS or PFS for any of the other histological subtypes. Ever use of beta blockers, oral antidiabetic medications, and insulin was associated with increased mortality, HR = 1.20; 95% CI = 1.03-1.40, HR = 1.28; 95% CI = 1.05-1.55, and HR = 1.63; 95% CI = 1.20-2.20, respectively. Ever use of diuretics was inversely associated with mortality, HR = 0.71; 95% CI = 0.53-0.94.ConclusionsHistories of hypertension, diabetes, and use of diuretics, beta blockers, insulin, and oral antidiabetic medications may influence the survival of ovarian cancer patients. Understanding mechanisms for these observations could provide insight regarding treatment.

Published
2017
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14. Use of common analgesic medications and ovarian cancer survival: results from a pooled analysis in the Ovarian Cancer Association Consortium

Author

Dixon, SC, Nagle, CM, Wentzensen, N, Trabert, B, Beeghly-Fadiel, A, Schildkraut, JM, Moysich, KB, deFazio, A, Risch, HA, Rossing, MA, Doherty, JA, Wicklund, KG, Goodman, MT, Modugno, F, Ness, RB, Edwards, RP, Jensen, A, Kjaer, SK, Hogdall, E, Berchuck, A, Cramer, DW, Terry, KL, Poole, EM, Bandera, EV, Paddock, LE, Anton-Culver, H, Ziogas, A, Menon, U, Gayther, SA, Ramus, SJ, Gentry-Maharaj, A, Pearce, CL, Wu, AH, Pike, MC, Webb, PM, Grp, AOCS, and Consortium, OCA

Subjects
nonsteroidal anti-inflammatory drugs, ovarian cancer, aspirin, paracetamol, pooled analysis, survival, NSAID, acetaminophen
Published
2017
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15. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African ancestry anthropometry genetics consortium

Author

Ng, MCY, Graff, M, Lu, Y, Justice, AE, Mudgal, P, Liu, CT, Young, K, Yanek, LR, Feitosa, MF, Wojczynski, MK, Rand, K, Brody, JA, Cade, BE, Dimitrov, L, Duan, Q, Guo, X, Lange, LA, Nalls, MA, Okut, H, Tajuddin, SM, Tayo, BO, Vedantam, S, Bradfield, JP, Chen, G, Chen, WM, Chesi, A, Irvin, MR, Padhukasahasram, B, Smith, JA, Zheng, W, Allison, MA, Ambrosone, CB, Bandera, EV, Bartz, TM, Berndt, SI, Bernstein, L, Blot, WJ, Bottinger, EP, Carpten, J, Chanock, SJ, Chen, YDI, Conti, DV, Cooper, RS, Fornage, M, Freedman, BI, Garcia, M, Goodman, PJ, Hsu, YHH, Hu, J, Huff, CD, Ingles, SA, John, EM, Kittles, R, Klein, E, Li, J, McKnight, B, Nayak, U, Nemesure, B, Ogunniyi, A, Olshan, A, Press, MF, Rohde, R, Rybicki, BA, Salako, B, Sanderson, M, Shao, Y, Siscovick, DS, Stanford, JL, Stevens, VL, Stram, A, Strom, SS, Vaidya, D, Witte, JS, Yao, J, Zhu, X, Ziegler, RG, Zonderman, AB, Adeyemo, A, Ambs, S, Cushman, M, Faul, JD, Hakonarson, H, Levin, AM, Nathanson, KL, and Ware, EB

Abstract

© 2017 Public Library of Science. All rights reserved. Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMIfrom the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMIand eight previously established loci at P < 5×10−8: seven for BMI, and one for WHRadjBMIin African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMIwhen combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI(SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (

Published
2017
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16. No evidence that genetic variation in the myeloid-derived suppressor cell pathway influences ovarian cancer survival

Author

Sucheston-Campbell, LE, Cannioto, R, Clay, AI, Etter, JL, Eng, KH, Liu, S, Battaglia, S, Hu, Q, Brian Szender, J, Minlikeeva, A, Joseph, JM, Mayor, P, Abrams, SI, Segal, BH, Wallace, PK, Soh, KT, Zsiros, E, Anton-Culver, H, Bandera, EV, Beckmann, MW, Berchuck, A, Bjorge, L, Bruegl, A, Campbell, IG, Campbell, SP, Chenevix-Trench, G, Cramer, DW, Mieszkowska, AD, Dao, F, Diergaarde, B, Doerk, T, Doherty, JA, Du Bois, A, Eccles, D, Engelholm, SA, Fasching, PA, Gayther, SA, Gentry-Maharaj, A, Glasspool, RM, Goodman, MT, Gronwald, J, Harter, P, Hein, A, Heitz, F, Hillemmanns, P, Høgdall, C, Høgdall, EVS, Huzarski, T, Jensen, A, Johnatty, SE, Jung, A, Karlan, BY, Klapdor, R, Kluz, T, Konopka, B, Kjer, SK, Kupryjanczyk, J, Lambrechts, D, Lester, J, Lubinski, J, Levine, DA, Lundvall, L, McGuire, V, McNeish, IA, Menon, U, Modugno, F, Ness, RB, Orsulic, S, Paul, J, Pearce, CL, Pejovic, T, Pharoah, P, Ramus, SJ, Rothstein, J, Rossing, MA, Rubner, M, Schildkraut, JM, Schmalfeldt, B, Schwaab, I, Siddiqui, N, and Sieh, W

Subjects
endocrine system diseases, female genital diseases and pregnancy complications
Abstract

© 2016 American Association for Cancer Research. Background: The precise mechanism by which the immune system is adversely affected in cancer patients remains poorly understood, but the accumulation of immunosuppressive/protumorigenic myeloid-derived suppressor cells (MDSCs) is thought to be a prominent mechanism contributing to immunologic tolerance of malignant cells in epithelial ovarian cancer (EOC). To this end, we hypothesized genetic variation in MDSC pathway genes would be associated with survival after EOC diagnoses. Methods: We measured the hazard of death due to EOC within 10 years of diagnosis, overall and by invasive subtype, attributable to SNPs in 24 genes relevant in the MDSC pathway in 10,751 women diagnosed with invasive EOC. Versatile Gene-based Association Study and the admixture likelihood method were used to test gene and pathway associations with survival. Results: We did not identify individual SNPs that were significantly associated with survival after correction for multiple testing (P < 3.5 × 10-5), nor did we identify significant associations between the MDSC pathway overall, or the 24 individual genes and EOC survival. Conclusions: In this well-powered analysis, we observed no evidence that inherited variations in MDSC-associated SNPs, individual genes, or the collective genetic pathway contributed to EOC survival outcomes. Impact: Common inherited variation in genes relevant to MDSCs was not associated with survival in women diagnosed with invasive EOC.

Published
2017
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17. Adult height is associated with increased risk of ovarian cancer: A Mendelian randomisation study

Author

Dixon-Suen, Suzanne, Nagle, CM, Thrift, AP, Pharoah, PDP, Ewing, A, Pearce, CL, Zheng, W, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Lambrechts, D, Vergote, I, Lambrechts, S, Van Nieuwenhuysen, E, Rossing, MA, Doherty, JA, Wicklund, KG, Chang-Claude, J, Jung, AY, Moysich, KB, Odunsi, K, Goodman, MT, Wilkens, LR, Thompson, PJ, Shvetsov, YB, Dörk, T, Park-Simon, TW, Hillemanns, P, Bogdanova, N, Butzow, R, Nevanlinna, H, Pelttari, LM, Leminen, A, Modugno, F, Ness, RB, Edwards, RP, Kelley, JL, Heitz, F, Du Bois, A, Harter, P, Schwaab, I, Karlan, BY, Lester, J, Orsulic, S, Rimel, BJ, Kjær, SK, Høgdall, E, Jensen, A, Goode, EL, Fridley, BL, Cunningham, JM, Winham, SJ, Giles, GG, Bruinsma, F, Milne, RL, Southey, MC, Hildebrandt, MAT, Wu, X, Lu, KH, Liang, D, Levine, DA, Bisogna, M, Schildkraut, JM, Berchuck, A, Cramer, DW, Terry, KL, Bandera, EV, Olson, SH, Salvesen, HB, Thomsen, LCV, Kopperud, RK, Bjorge, L, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bruegl, A, Cook, LS, Le, ND, Swenerton, KD, Brooks-Wilson, A, Kelemen, LE, Lubiński, J, Huzarski, T, Gronwald, J, Menkiszak, J, Wentzensen, N, Brinton, L, Yang, H, Lissowska, J, Høgdall, CK, Lundvall, L, Song, H, Tyrer, JP, Campbell, I, Eccles, D, Paul, J, Glasspool, R, Siddiqui, N, Whittemore, AS, Sieh, W, Dixon-Suen, Suzanne, Nagle, CM, Thrift, AP, Pharoah, PDP, Ewing, A, Pearce, CL, Zheng, W, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Lambrechts, D, Vergote, I, Lambrechts, S, Van Nieuwenhuysen, E, Rossing, MA, Doherty, JA, Wicklund, KG, Chang-Claude, J, Jung, AY, Moysich, KB, Odunsi, K, Goodman, MT, Wilkens, LR, Thompson, PJ, Shvetsov, YB, Dörk, T, Park-Simon, TW, Hillemanns, P, Bogdanova, N, Butzow, R, Nevanlinna, H, Pelttari, LM, Leminen, A, Modugno, F, Ness, RB, Edwards, RP, Kelley, JL, Heitz, F, Du Bois, A, Harter, P, Schwaab, I, Karlan, BY, Lester, J, Orsulic, S, Rimel, BJ, Kjær, SK, Høgdall, E, Jensen, A, Goode, EL, Fridley, BL, Cunningham, JM, Winham, SJ, Giles, GG, Bruinsma, F, Milne, RL, Southey, MC, Hildebrandt, MAT, Wu, X, Lu, KH, Liang, D, Levine, DA, Bisogna, M, Schildkraut, JM, Berchuck, A, Cramer, DW, Terry, KL, Bandera, EV, Olson, SH, Salvesen, HB, Thomsen, LCV, Kopperud, RK, Bjorge, L, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bruegl, A, Cook, LS, Le, ND, Swenerton, KD, Brooks-Wilson, A, Kelemen, LE, Lubiński, J, Huzarski, T, Gronwald, J, Menkiszak, J, Wentzensen, N, Brinton, L, Yang, H, Lissowska, J, Høgdall, CK, Lundvall, L, Song, H, Tyrer, JP, Campbell, I, Eccles, D, Paul, J, Glasspool, R, Siddiqui, N, Whittemore, AS, and Sieh, W

Published
2018

19. A survey of microRNA single nucleotide polymorphisms identifies novel breast cancer susceptibility loci in a case-control, population-based study of African-American women.

Author

Bensen, JT, Graff, M, Young, KL, Sethupathy, P, Parker, J, Pecot, CV, Currin, K, Haddad, SA, Ruiz-Narváez, EA, Haiman, CA, Hong, C-C, Sucheston-Campbell, LE, Zhu, Q, Liu, S, Yao, S, Bandera, EV, Rosenberg, L, Lunetta, KL, Ambrosone, CB, Palmer, JR, Troester, MA, Olshan, AF, Bensen, JT, Graff, M, Young, KL, Sethupathy, P, Parker, J, Pecot, CV, Currin, K, Haddad, SA, Ruiz-Narváez, EA, Haiman, CA, Hong, C-C, Sucheston-Campbell, LE, Zhu, Q, Liu, S, Yao, S, Bandera, EV, Rosenberg, L, Lunetta, KL, Ambrosone, CB, Palmer, JR, Troester, MA, and Olshan, AF

Abstract

BACKGROUND: MicroRNAs (miRNAs) regulate gene expression and influence cancer. Primary transcripts of miRNAs (pri-miRNAs) are poorly annotated and little is known about the role of germline variation in miRNA genes and breast cancer (BC). We sought to identify germline miRNA variants associated with BC risk and tumor subtype among African-American (AA) women. METHODS: Under the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium, genotyping and imputed data from four studies on BC in AA women were combined into a final dataset containing 224,188 miRNA gene single nucleotide polymorphisms (SNPs) for 8350 women: 3663 cases and 4687 controls. The primary miRNA sequence was identified for 566 miRNA genes expressed in Encyclopedia of DNA Elements (ENCODE) Tier 1 cell types and human pancreatic islets. Association analysis was conducted using logistic regression for BC status overall and by tumor subtype. RESULTS: A novel BC signal was localized to an 8.6-kb region of 17q25.3 by four SNPs (rs9913477, rs1428882938, rs28585511, and rs7502931) and remained statistically significant after multiple test correction (odds ratio (OR) = 1.44, 95% confidence interval (CI) = 1.26-1.65; p = 3.15 × 10-7; false discovery rate (FDR) = 0.03). These SNPs reside in a genomic location that includes both the predicted primary transcript of the noncoding miRNA gene MIR3065 and the first intron of the gene for brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2). Furthermore, miRNA-associated SNPs on chromosomes 1p32.3, 5q32, and 3p25.1 were the strongest signals for hormone receptor, luminal versus basal-like, and HER2 enrichment status, respectively. A second phase of genotyping (1397 BC cases, 2418 controls) that included two SNPs in the 8.6-kb region was used for validation and meta-analysis. While neither rs4969239 nor rs9913477 was validated, when meta-analyzed with the original dataset their association with BC remained directionally consistent (OR =

Published
2018

20. rs495139 in the TYMS-ENOSF1 Region and Risk of Ovarian Carcinoma of Mucinous Histology

Author

Kelemen, LE, Earp, M, Fridley, BL, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Ekici, AB, Hein, A, Lambrechts, D, Lambrechts, S, Van Nieuwenhuysen, E, Vergote, I, Rossing, MA, Doherty, JA, Chang-Claude, J, Behrens, S, Moysich, KB, Cannioto, R, Lele, S, Odunsi, K, Goodman, MT, Shvetsov, YB, Thompson, PJ, Wilkens, LR, Doerk, T, Antonenkova, N, Bogdanova, N, Hillemanns, P, Runnebaum, IB, du Bois, A, Harter, P, Heitz, F, Schwaab, I, Butzow, R, Pelttari, LM, Nevanlinna, H, Modugno, F, Edwards, RP, Kelley, JL, Ness, RB, Karlan, BY, Lester, J, Orsulic, S, Walsh, C, Kjaer, SK, Jensen, A, Cunningham, JM, Vierkant, RA, Giles, GG, Bruinsma, F, Southey, MC, Hildebrandt, MAT, Liang, D, Lu, K, Wu, X, Sellers, TA, Levine, DA, Schildkraut, JM, Iversen, ES, Terry, KL, Cramer, DW, Tworoger, SS, Poole, EM, Bandera, EV, Olson, SH, Orlow, I, Thomsen, LCV, Bjorge, L, Krakstad, C, Tangen, IL, Kiemeney, LA, Aben, KKH, Massuger, LFAG, van Altena, AM, Pejovic, T, Bean, Y, Kellar, M, Cook, LS, Le, ND, Brooks-Wilson, A, Gronwald, J, Cybulski, C, Jakubowska, A, Lubinski, J, Wentzensen, N, Brinton, LA, Lissowska, J, Hogdall, E, Engelholm, SA, Hogdall, C, Lundvall, L, Nedergaard, L, Pharoah, PDP, Dicks, E, Song, H, Tyrer, JP, McNeish, I, Siddiqui, N, Carty, K, Glasspool, R, Paul, J, Campbell, IG, Eccles, D, Whittemore, AS, McGuire, V, Rothstein, JH, Sieh, W, Narod, SA, Phelan, CM, McLaughlin, JR, Risch, HA, Anton-Culver, H, Ziogas, A, Menon, U, Gayther, SA, Gentry-Maharaj, A, Ramus, SJ, Wu, AH, Pearce, CL, Lee, AW, Pike, MC, Kupryjanczyk, J, Podgorska, A, Plisiecka-Halasa, J, Sawicki, W, Goode, EL, Berchuck, A, Kelemen, LE, Earp, M, Fridley, BL, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Ekici, AB, Hein, A, Lambrechts, D, Lambrechts, S, Van Nieuwenhuysen, E, Vergote, I, Rossing, MA, Doherty, JA, Chang-Claude, J, Behrens, S, Moysich, KB, Cannioto, R, Lele, S, Odunsi, K, Goodman, MT, Shvetsov, YB, Thompson, PJ, Wilkens, LR, Doerk, T, Antonenkova, N, Bogdanova, N, Hillemanns, P, Runnebaum, IB, du Bois, A, Harter, P, Heitz, F, Schwaab, I, Butzow, R, Pelttari, LM, Nevanlinna, H, Modugno, F, Edwards, RP, Kelley, JL, Ness, RB, Karlan, BY, Lester, J, Orsulic, S, Walsh, C, Kjaer, SK, Jensen, A, Cunningham, JM, Vierkant, RA, Giles, GG, Bruinsma, F, Southey, MC, Hildebrandt, MAT, Liang, D, Lu, K, Wu, X, Sellers, TA, Levine, DA, Schildkraut, JM, Iversen, ES, Terry, KL, Cramer, DW, Tworoger, SS, Poole, EM, Bandera, EV, Olson, SH, Orlow, I, Thomsen, LCV, Bjorge, L, Krakstad, C, Tangen, IL, Kiemeney, LA, Aben, KKH, Massuger, LFAG, van Altena, AM, Pejovic, T, Bean, Y, Kellar, M, Cook, LS, Le, ND, Brooks-Wilson, A, Gronwald, J, Cybulski, C, Jakubowska, A, Lubinski, J, Wentzensen, N, Brinton, LA, Lissowska, J, Hogdall, E, Engelholm, SA, Hogdall, C, Lundvall, L, Nedergaard, L, Pharoah, PDP, Dicks, E, Song, H, Tyrer, JP, McNeish, I, Siddiqui, N, Carty, K, Glasspool, R, Paul, J, Campbell, IG, Eccles, D, Whittemore, AS, McGuire, V, Rothstein, JH, Sieh, W, Narod, SA, Phelan, CM, McLaughlin, JR, Risch, HA, Anton-Culver, H, Ziogas, A, Menon, U, Gayther, SA, Gentry-Maharaj, A, Ramus, SJ, Wu, AH, Pearce, CL, Lee, AW, Pike, MC, Kupryjanczyk, J, Podgorska, A, Plisiecka-Halasa, J, Sawicki, W, Goode, EL, and Berchuck, A

Abstract

Thymidylate synthase (TYMS) is a crucial enzyme for DNA synthesis. TYMS expression is regulated by its antisense mRNA, ENOSF1. Disrupted regulation may promote uncontrolled DNA synthesis and tumor growth. We sought to replicate our previously reported association between rs495139 in the TYMS-ENOSF1 3' gene region and increased risk of mucinous ovarian carcinoma (MOC) in an independent sample. Genotypes from 24,351 controls to 15,000 women with invasive OC, including 665 MOC, were available. We estimated per-allele odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression, and meta-analysis when combining these data with our previous report. The association between rs495139 and MOC was not significant in the independent sample (OR = 1.09; 95% CI = 0.97⁻1.22; p = 0.15; N = 665 cases). Meta-analysis suggested a weak association (OR = 1.13; 95% CI = 1.03⁻1.24; p = 0.01; N = 1019 cases). No significant association with risk of other OC histologic types was observed (p = 0.05 for tumor heterogeneity). In expression quantitative trait locus (eQTL) analysis, the rs495139 allele was positively associated with ENOSF1 mRNA expression in normal tissues of the gastrointestinal system, particularly esophageal mucosa (r = 0.51, p = 1.7 × 10-28), and nonsignificantly in five MOC tumors. The association results, along with inconclusive tumor eQTL findings, suggest that a true effect of rs495139 might be small.

Published
2018

21. Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

Author

Lawrenson, K, Kar, S, McCue, K, Kuchenbaeker, K, Michailidou, K, Tyrer, J, Beesley, J, Ramus, SJ, Li, Q, Delgado, MK, Lee, JM, Aittomäki, K, Andrulis, IL, Anton-Culver, H, Arndt, V, Arun, BK, Arver, B, Bandera, EV, Barile, M, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Benitez, J, Berchuck, A, Bisogna, M, Bjorge, L, Blomqvist, C, Blot, W, Bogdanova, N, Bojesen, A, Bojesen, SE, Bolla, MK, Bonanni, B, Børresen-Dale, AL, Brauch, H, Brennan, P, Brenner, H, Bruinsma, F, Brunet, J, Buhari, SA, Burwinkel, B, Butzow, R, Buys, SS, Cai, Q, Caldes, T, Campbell, I, Canniotto, R, Chang-Claude, J, Chiquette, J, Choi, JY, Claes, KBM, Cook, LS, Cox, A, Cramer, DW, Cross, SS, Cybulski, C, Czene, K, Daly, MB, Damiola, F, Dansonka-Mieszkowska, A, Darabi, H, Dennis, J, Devilee, P, Diez, O, Doherty, JA, Domchek, SM, Dorfling, CM, Dörk, T, Dumont, M, Ehrencrona, H, Ejlertsen, B, Ellis, S, Engel, C, Lee, E, Evans, DG, Fasching, PA, Feliubadalo, L, Figueroa, J, and Flesch-Janys, D

Abstract

© 2016 The Author(s). A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P

Published
2016
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22. Genome-wide meta-analyses of breast, ovarian, and prostate cancer association studies identify multiple new susceptibility loci shared by at least two cancer types

Author

Kar, SP, Beesley, J, Al Olama, AA, Michailidou, K, Tyrer, J, Kote-Jarai, ZA, Lawrenson, K, Lindstrom, S, Ramus, SJ, Thompson, DJ, Kibel, AS, Dansonka-Mieszkowska, A, Michael, A, Dieffenbach, AK, Gentry-Maharaj, A, Whittemore, AS, Wolk, A, Monteiro, A, Peixoto, A, Kierzek, A, Cox, A, Rudolph, A, Gonzalez-Neira, A, Wu, AH, Lindblom, A, Swerdlow, A, Ziogas, A, Ekici, AB, Burwinkel, B, Karlan, BY, Nordestgaard, BG, Blomqvist, C, Phelan, C, McLean, C, Pearce, CL, Vachon, C, Cybulski, C, Slavov, C, Stegmaier, C, Maier, C, Ambrosone, CB, Hogdall, CK, Teerlink, CC, Kang, D, Tessier, DC, Schaid, DJ, Stram, DO, Cramer, DW, Neal, DE, Eccles, D, Flesch-Janys, D, Velez Edwards, DR, Wokozorczyk, D, Levine, DA, Yannoukakos, D, Sawyer, EJ, Bandera, EV, Poole, EM, Goode, EL, Khusnutdinova, E, Hogdall, E, Song, F, Bruinsma, F, Heitz, F, Modugno, F, Hamdy, FC, Wiklund, F, Giles, GG, Olsson, H, Wildiers, H, and Ulmer, HU

Abstract

© 2016 American Association for Cancer Research. Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/ BCL2L11; rs7937840/11q12/ INCENP; rs1469713/19p13/ GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/ SMC2; rs8037137/15q26/ RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/ NSUN4; rs9375701/6q23/ L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10−5 in the three-cancer meta-analysis. SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers.

Published
2016
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23. No clinical utility of KRAS variant rs61764370 for ovarian or breast cancer

Author

Hollestelle, A, Van Der Baan, FH, Berchuck, A, Johnatty, SE, Aben, KK, Agnarsson, BA, Aittomäki, K, Alducci, E, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Antoniou, AC, Apicella, C, Arndt, V, Arnold, N, Arun, BK, Arver, B, Ashworth, A, Baglietto, L, Balleine, R, Bandera, EV, Barrowdale, D, Bean, YT, Beckmann, L, Beckmann, MW, Benitez, J, Berger, A, Berger, R, Beuselinck, B, Bisogna, M, Bjorge, L, Blomqvist, C, Bogdanova, NV, Bojesen, A, Bojesen, SE, Bolla, MK, Bonanni, B, Brand, JS, Brauch, H, Brenner, H, Brinton, L, Brooks-Wilson, A, Bruinsma, F, Brunet, J, Brüning, T, Budzilowska, A, Bunker, CH, Burwinkel, B, Butzow, R, Buys, SS, Caligo, MA, Campbell, I, Carter, J, Chang-Claude, J, Chanock, SJ, Claes, KBM, Collée, JM, Cook, LS, Couch, FJ, Cox, A, Cramer, D, Cross, SS, Cunningham, JM, Cybulski, C, Czene, K, Damiola, F, Dansonka-Mieszkowska, A, Darabi, H, De La Hoya, M, Defazio, A, Dennis, J, Devilee, P, and Dicks, EM

Abstract

© 2015 Elsevier Inc. All rights reserved. Objective Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3′ UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370. Methods Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers). Results We found no association with risk of ovarian cancer (OR = 0.99, 95% CI 0.94-1.04, p = 0.74) or breast cancer (OR = 0.98, 95% CI 0.94-1.01, p = 0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR = 1.09, 95% CI 0.97-1.23, p = 0.14, breast cancer HR = 1.04, 95% CI 0.97-1.12, p = 0.27; BRCA2, ovarian cancer HR = 0.89, 95% CI 0.71-1.13, p = 0.34, breast cancer HR = 1.06, 95% CI 0.94-1.19, p = 0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR = 0.94, 95% CI 0.83-1.07, p = 0.38), breast cancer (HR = 0.96, 95% CI 0.87-1.06, p = 0.38), and all other previously-reported associations. Conclusions rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.

Published
2016
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24. Inherited variants affecting RNA editing may contribute to ovarian cancer susceptibility: Results from a large-scale collaboration

Author

Permuth, JB, Reid, B, Earp, M, Chen, YA, Monteiro, ANA, Chen, Z, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Lambrechts, D, Vanderstichele, A, Van Niewenhuyse, E, Vergote, I, Rossing, MA, Doherty, JA, Chang-Claude, J, Moysich, K, Odunsi, K, Goodman, MT, Shvetsov, YB, Wilkens, LR, Thompson, PJ, Dörk, T, Bogdanova, N, Butzow, R, Nevanlinna, H, Pelttari, L, Leminen, A, Modugno, F, Edwards, RP, Ness, RB, Kelley, J, Heitz, F, Karlan, B, Lester, J, Kjaer, SK, Jensen, A, Giles, G, Hildebrandt, M, Liang, D, Lu, KH, Wu, X, Levine, DA, Bisogna, M, Berchuck, A, Cramer, DW, Terry, KL, Tworoger, SS, Poole, EM, Bandera, EV, Fridley, B, Cunningham, J, Winham, SJ, Olson, SH, Orlow, I, Bjorge, L, Kiemeney, LA, Massuger, L, Pejovic, T, Moffitt, M, Le, N, Cook, LS, Brooks-Wilson, A, Kelemen, LE, Gronwald, J, Lubinski, J, Wentzensen, N, Brinton, LA, Lissowska, J, Yang, H, Hogdall, E, Hogdall, C, Lundvall, L, Pharoah, PDP, Song, H, Campbell, I, Eccles, D, and McNeish, I

Abstract

RNA editing in mammals is a form of post-transcriptional modification in which adenosine is converted to inosine by the adenosine deaminases acting on RNA (ADAR) family of enzymes. Based on evidence of altered ADAR expression in epithelial ovarian cancers (EOC), we hypothesized that single nucleotide polymorphisms (SNPs) in ADAR genes modify EOC susceptibility, potentially by altering ovarian tissue gene expression. Using directly genotyped and imputed data from 10,891 invasive EOC cases and 21,693 controls, we evaluated the associations of 5,303 SNPs in ADAD1, ADAR, ADAR2, ADAR3, and SND1. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI), with adjustment for European ancestry. We conducted gene-level analyses using the Admixture Maximum Likelihood (AML) test and the Sequence-Kernel Association test for common and rare variants (SKAT-CR). Association analysis revealed top risk-associated SNP rs77027562 (OR (95% CI)= 1.39 (1.17-1.64), P=1.0x10-4) in ADAR3 and rs185455523 in SND1 (OR (95% CI)= 0.68 (0.56-0.83), P=2.0x10-4). When restricting to serous histology (n=6,500), the magnitude of association strengthened for rs185455523 (OR=0.60, P=1.0x10-4). Gene-level analyses revealed that variation in ADAR was associated (P

Published
2016
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25. Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer

Author

Hampras, SS, Sucheston-Campbell, LE, Cannioto, R, Chang-Claude, J, Modugno, F, Dörk, T, Hillemanns, P, Preus, L, Knutson, KL, Wallace, PK, Hong, CC, Friel, G, Davis, W, Nesline, M, Pearce, CL, Kelemen, LE, Goodman, MT, Bandera, EV, Terry, KL, Schoof, N, Eng, KH, Clay, A, Singh, PK, Joseph, JM, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bean, Y, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Cook, LS, Cramer, DW, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Despierre, E, Dicks, E, Doherty, JA, du Bois, A, Dürst, M, Easton, D, Eccles, D, Edwards, RP, Ekici, AB, Fasching, PA, Fridley, BL, Gao, YT, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Gronwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hogdall, C, Hogdall, E, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, BT, Karlan, BY, Kellar, M, Kelley, JL, Kiemeney, LA, Klapdor, R, Kolomeyevskaya, N, Krakstad, C, Kjaer, SK, Kruszka, B, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Liu, S, and Lu, K

Subjects
endocrine system diseases, female genital diseases and pregnancy complications
Abstract

Background: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer. Methods: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients. Results: The most significant global associations for all genes in the pathway were seen in endometrioid (p = 0.082) and clear cell (p = 0.083), with the most significant gene level association seen with TGFBR2 (p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 (p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA (p = 0.035, endometrioid and mucinous), LGALS1 (p = 0.03, mucinous), STAT5B (p = 0.022, clear cell), TGFBR1 (p = 0.021 endometrioid) and TGFBR2 (p = 0.017 and p = 0.025, endometrioid and mucinous, respectively). Conclusions: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients.

Published
2016
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26. Circulating C-reactive protein and breast cancer risk – systematic literature review and meta-analysis of prospective cohort studies

Author

Chan, DSM, Bandera, EV, Greenwood, DC, and Norat, T

Abstract

We conducted a systematic literature review to explore the association between circulating C-reactive protein (CRP), a low-grade inflammation biomarker, and breast cancer risk. Relevant prospective studies in women were identified in PubMed and Web of Science until February 2015. Random-effects dose-response metaanalysis was conducted, overall and in post-menopausal women. Twelve out of 15 studies identified were included in the meta-analysis on any breast cancers (3,522 cases, 69,610 women) and nine on postmenopausal breast cancer (2,516 cases, 36,847 women). For each doubling of CRP concentration, a 7% (95% CI: 2%–12%) and 6% (95% CI: 1%–11%) increased risk was observed (I2=47% and 32%; P heterogeneity=0.04 and 0.17), respectively. The association was linear over most of the range of CRP concentrations. Positive associations remained in the studies that examined the exclusion of early years of follow-up. Associations were attenuated in studies adjusted for lifestyle factors, which partly explained the significant heterogeneity between studies in the overall analysis. On average, the associations in studies adjusted or not adjusted for body mass index were similar. Low-grade inflammation may have a role in breast cancer development. Additional prospective studies are needed to better understand confounding and effect modification from lifestyle factors.

Published
2015

27. Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer

Author

Lawrenson, K, Li, Q, Kar, S, Seo, JH, Tyrer, J, Spindler, TJ, Lee, J, Chen, Y, Karst, A, Drapkin, R, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Berchuck, A, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chenevix-Trench, G, Chen, A, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Dörk, T, Du Bois, A, Dürst, M, Eccles, D, Easton, DT, Edwards, RP, Eilber, U, Ekici, AB, Fasching, PA, Fridley, BL, Gao, YT, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, James, P, Jensen, A, Ji, BT, Karlan, BY, Kjaer, SK, Kelemen, LE, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kupryjanczyk, J, and Lambrechts, D

Abstract

© 2015 Macmillan Publishers Limited. All rights reserved. Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10-5). For three cis-eQTL associations (P

Published
2015
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28. Cell-type-specific enrichment of risk-associated regulatory elements at ovarian cancer susceptibility loci

Author

Coetzee, SG, Shen, HC, Hazelett, DJ, Lawrenson, K, Kuchenbaecker, K, Tyrer, J, Rhie, SK, Levanon, K, Karst, A, Drapkin, R, Ramus, SJ, Couch, FJ, Offit, K, Chenevix-Trench, G, Monteiro, ANA, Antoniou, A, Freedman, M, Coetzee, GA, Pharoah, PDP, Noushmehr, H, Gayther, SA, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Berchuck, A, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chen, A, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Dörk, T, Bois, AD, Dürst, M, Eccles, D, Easton, DF, Edwards, RP, Eilber, U, Ekici, AB, Fasching, PA, Fridley, BL, Gao, YT, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, James, P, Jensen, A, Ji, BT, Karlan, BY, Kjaer, SK, Kelemen, LE, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lele, S, Leminen, A, and Lester, J

Abstract

© The Author 2015. Published by Oxford University Press. All rights reserved. Understanding the regulatory landscape of the human genome is a central question in complex trait genetics. Most singlenucleotide polymorphisms (SNPs) associated with cancer risk lie in non-protein-coding regions, implicating regulatory DNA elements as functional targets of susceptibility variants. Here, we describe genome-wide annotation of regions of open chromatin and histone modification in fallopian tube and ovarian surface epithelial cells (FTSECs, OSECs), the debated cellular origins of high-grade serous ovarian cancers (HGSOCs) and in endometriosis epithelial cells (EECs), the likely precursor of clear cell ovarian carcinomas (CCOCs). The regulatory architecture of these cell types was compared with normal human mammary epithelial cells and LNCaP prostate cancer cells. We observed similar positional patterns of global enhancer signatures across the three different ovarian cancer precursor cell types, and evidence of tissue-specific regulatory signatures compared to nongynecological cell types. We found significant enrichment for risk-associated SNPs intersecting regulatory biofeatures at 17 known HGSOC susceptibility loci in FTSECs (P = 3.8 × 10-30), OSECs (P = 2.4 × 10-23) and HMECs (P = 6.7 × 10-15) but not for EECs (P = 0.45) or LNCaP cells (P = 0.88). Hierarchical clustering of risk SNPs conditioned on the six different cell types indicates FTSECs and OSECs are highly related (96% of samples using multi-scale bootstrapping) suggesting both cell types may be precursors of HGSOC. These data represent the first description of regulatory catalogues of normal precursor cells for different ovarian cancer subtypes, and provide unique insights into the tissue specific regulatory variation with respect to the likely functional targets of germline genetic susceptibility variants for ovarian cancer.

Published
2015
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29. Common genetic variation in cellular transport genes and epithelial ovarian cancer (EOC) risk

Author

Chornokur, G, Lin, HY, Tyrer, JP, Lawrenson, K, Dennis, J, Amankwah, EK, Qu, X, Tsai, YY, Jim, HSL, Chen, Z, Chen, AY, Permuth-Wey, J, Aben, KKH, Anton-Culver, H, Antonenkova, N, Bruinsma, F, Bandera, EV, Bean, YT, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bunker, CH, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Du Bois, A, Despierre, E, Dicks, E, Doherty, JA, Dörk, T, Dürst, M, Easton, DF, Eccles, DM, Edwards, RP, Ekici, AB, Fasching, PA, Fridley, BL, Gao, YT, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goodman, MT, Gronwald, J, Harrington, P, Harter, P, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, CK, Hogdall, E, Hosono, S, Jakubowska, A, Jensen, A, Ji, BT, Karlan, BY, Kelemen, LE, Kellar, M, Kiemeney, LA, Krakstad, C, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, and Lester, J

Abstract

© 2015 Chornokur et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background: Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk. Methods: In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q-4). Conclusion: These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes.

Published
2015
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30. Use of common analgesic medications and ovarian cancer survival: Results from a pooled analysis in the Ovarian Cancer Association Consortium

Author

Dixon-Suen, Suzanne, Nagle, CM, Wentzensen, N, Trabert, B, Beeghly-Fadiel, A, Schildkraut, JM, Moysich, KB, DeFazio, A, Risch, HA, Rossing, MA, Doherty, JA, Wicklund, KG, Goodman, MT, Modugno, F, Ness, RB, Edwards, RP, Jensen, A, Kjær, SK, Høgdall, E, Berchuck, A, Cramer, DW, Terry, KL, Poole, EM, Bandera, EV, Paddock, LE, Anton-Culver, H, Ziogas, A, Menon, U, Gayther, SA, Ramus, SJ, Gentry-Maharaj, A, Pearce, CL, Wu, AH, Pike, MC, Webb, PM, Dixon-Suen, Suzanne, Nagle, CM, Wentzensen, N, Trabert, B, Beeghly-Fadiel, A, Schildkraut, JM, Moysich, KB, DeFazio, A, Risch, HA, Rossing, MA, Doherty, JA, Wicklund, KG, Goodman, MT, Modugno, F, Ness, RB, Edwards, RP, Jensen, A, Kjær, SK, Høgdall, E, Berchuck, A, Cramer, DW, Terry, KL, Poole, EM, Bandera, EV, Paddock, LE, Anton-Culver, H, Ziogas, A, Menon, U, Gayther, SA, Ramus, SJ, Gentry-Maharaj, A, Pearce, CL, Wu, AH, Pike, MC, and Webb, PM

Published
2017

31. History of thyroid disease and survival of ovarian cancer patients: results from the Ovarian Cancer Association Consortium, a brief report.

Author

Minlikeeva, AN, Freudenheim, JL, Cannioto, RA, Eng, KH, Szender, JB, Mayor, P, Etter, JL, Cramer, DW, Diergaarde, B, Doherty, JA, Dörk, T, Edwards, R, deFazio, A, Friel, G, Goodman, MT, Hillemanns, P, Høgdall, E, Jensen, A, Jordan, SJ, Karlan, BY, Kjær, SK, Klapdor, R, Matsuo, K, Mizuno, M, Nagle, CM, Odunsi, K, Paddock, L, Rossing, MA, Schildkraut, JM, Schmalfeldt, B, Segal, BH, Starbuck, K, Terry, KL, Webb, PM, Zsiros, E, Ness, RB, Modugno, F, Bandera, EV, Chang-Claude, J, Moysich, KB, Minlikeeva, AN, Freudenheim, JL, Cannioto, RA, Eng, KH, Szender, JB, Mayor, P, Etter, JL, Cramer, DW, Diergaarde, B, Doherty, JA, Dörk, T, Edwards, R, deFazio, A, Friel, G, Goodman, MT, Hillemanns, P, Høgdall, E, Jensen, A, Jordan, SJ, Karlan, BY, Kjær, SK, Klapdor, R, Matsuo, K, Mizuno, M, Nagle, CM, Odunsi, K, Paddock, L, Rossing, MA, Schildkraut, JM, Schmalfeldt, B, Segal, BH, Starbuck, K, Terry, KL, Webb, PM, Zsiros, E, Ness, RB, Modugno, F, Bandera, EV, Chang-Claude, J, and Moysich, KB

Abstract

BACKGROUND: Findings from in vitro studies suggest that increased exposure to thyroid hormones can influence progression of ovarian tumours. However, epidemiologic evidence on this topic is limited. METHODS: We pooled data from 11 studies from the Ovarian Cancer Association Consortium. Using multivariate Cox proportional hazards models, we estimated associations between hyper- and hypothyroidism and medications prescribed for these conditions with 5-year all-cause survival among women diagnosed with invasive ovarian cancer. RESULTS: Overall, there was a nonsignificant association with history of hyperthyroidism (n=160 cases) and mortality (HR=1.22; 95% CI=0.97-1.53). Furthermore, diagnosis of hyperthyroidism within the 5 years before ovarian cancer diagnosis was associated with an increased risk of death (HR=1.94; 95% CI=1.19-3.18). A more modest association was observed with history of hypothyroidism (n=624 cases) and mortality (HR=1.16; 95% CI=1.03-1.31). Neither duration of hypothyroidism nor use of thyroid medications was associated with survival. CONCLUSIONS: In this large study of women with ovarian cancer, we found that recent history of hyperthyroidism and overall history of hypothyroidism were associated with worse 5-year survival.

Published
2017

32. Enrichment of putative PAX8 target genes at serous epithelial ovarian cancer susceptibility loci

Author

Kar, SP, Adler, E, Tyrer, J, Hazelett, D, Anton-Culver, H, Bandera, EV, Beckmann, MW, Berchuck, A, Bogdanova, N, Brinton, L, Butzow, R, Campbell, I, Carty, K, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Dansonka-Mieszkowska, A, Doherty, JA, Doerk, T, Duerst, M, Eccles, D, Fasching, PA, Flanagan, J, Gentry-Maharaj, A, Glasspool, R, Goode, EL, Goodman, MT, Gronwald, J, Heitz, F, Hildebrandt, MAT, Hogdall, E, Hogdall, CK, Huntsman, DG, Jensen, A, Karlan, BY, Kelemen, LE, Kiemeney, LA, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Levine, DA, Li, Q, Lissowska, J, Lu, KH, Lubinski, J, Massuger, LFAG, McGuire, V, McNeish, I, Menon, U, Modugno, F, Monteiro, AN, Moysich, KB, Ness, RB, Nevanlinna, H, Paul, J, Pearce, CL, Pejovic, T, Permuth, JB, Phelan, C, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rossing, MA, Salvesen, HB, Schildkraut, JM, Sellers, TA, Sherman, M, Siddiqui, N, Sieh, W, Song, H, Southey, M, Terry, KL, Tworoger, SS, Walsh, C, Wentzensen, N, Whittemore, AS, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Freedman, ML, Gayther, SA, Pharoah, PDP, Lawrenson, K, Kar, SP, Adler, E, Tyrer, J, Hazelett, D, Anton-Culver, H, Bandera, EV, Beckmann, MW, Berchuck, A, Bogdanova, N, Brinton, L, Butzow, R, Campbell, I, Carty, K, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Dansonka-Mieszkowska, A, Doherty, JA, Doerk, T, Duerst, M, Eccles, D, Fasching, PA, Flanagan, J, Gentry-Maharaj, A, Glasspool, R, Goode, EL, Goodman, MT, Gronwald, J, Heitz, F, Hildebrandt, MAT, Hogdall, E, Hogdall, CK, Huntsman, DG, Jensen, A, Karlan, BY, Kelemen, LE, Kiemeney, LA, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Levine, DA, Li, Q, Lissowska, J, Lu, KH, Lubinski, J, Massuger, LFAG, McGuire, V, McNeish, I, Menon, U, Modugno, F, Monteiro, AN, Moysich, KB, Ness, RB, Nevanlinna, H, Paul, J, Pearce, CL, Pejovic, T, Permuth, JB, Phelan, C, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rossing, MA, Salvesen, HB, Schildkraut, JM, Sellers, TA, Sherman, M, Siddiqui, N, Sieh, W, Song, H, Southey, M, Terry, KL, Tworoger, SS, Walsh, C, Wentzensen, N, Whittemore, AS, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Freedman, ML, Gayther, SA, Pharoah, PDP, and Lawrenson, K

Abstract

BACKGROUND: Genome-wide association studies (GWAS) have identified 18 loci associated with serous ovarian cancer (SOC) susceptibility but the biological mechanisms driving these findings remain poorly characterised. Germline cancer risk loci may be enriched for target genes of transcription factors (TFs) critical to somatic tumorigenesis. METHODS: All 615 TF-target sets from the Molecular Signatures Database were evaluated using gene set enrichment analysis (GSEA) and three GWAS for SOC risk: discovery (2196 cases/4396 controls), replication (7035 cases/21 693 controls; independent from discovery), and combined (9627 cases/30 845 controls; including additional individuals). RESULTS: The PAX8-target gene set was ranked 1/615 in the discovery (PGSEA<0.001; FDR=0.21), 7/615 in the replication (PGSEA=0.004; FDR=0.37), and 1/615 in the combined (PGSEA<0.001; FDR=0.21) studies. Adding other genes reported to interact with PAX8 in the literature to the PAX8-target set and applying an alternative to GSEA, interval enrichment, further confirmed this association (P=0.006). Fifteen of the 157 genes from this expanded PAX8 pathway were near eight loci associated with SOC risk at P<10-5 (including six with P<5 × 10-8). The pathway was also associated with differential gene expression after shRNA-mediated silencing of PAX8 in HeyA8 (PGSEA=0.025) and IGROV1 (PGSEA=0.004) SOC cells and several PAX8 targets near SOC risk loci demonstrated in vitro transcriptomic perturbation. CONCLUSIONS: Putative PAX8 target genes are enriched for common SOC risk variants. This finding from our agnostic evaluation is of particular interest given that PAX8 is well-established as a specific marker for the cell of origin of SOC.

Published
2017

33. Adult body mass index and risk of ovarian cancer by subtype: A Mendelian randomization study

Author

Dixon-Suen, Suzanne, Nagle, CM, Thrift, AP, Pharoah, PDP, Pearce, CL, Zheng, W, Painter, JN, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Lambrechts, D, Vergote, I, Lambrechts, S, Van Nieuwenhuysen, E, Rossing, MA, Doherty, JA, GWicklund, K, Chang-Claude, J, Rudolph, A, Moysich, KB, Odunsi, K, Goodman, MT, Wilkens, LR, Thompson, PJ, Shvetsov, YB, Dörk, T, Park-Simon, TW, Hillemanns, P, Bogdanova, N, Butzow, R, Nevanlinna, H, Pelttari, LM, Leminen, A, Modugno, F, Ness, RB, Edwards, RP, Kelley, JL, Heitz, F, Karlan, BY, Kjær, SK, Høgdall, E, Jensen, A, Goode, EL, Fridley, BL, Cunningham, JM, Winham, SJ, Giles, GG, Bruinsma, F, Milne, RL, Southey, MC, Hildebrandt, MAT, Wu, X, Lu, KH, Liang, D, Levine, DA, Bisogna, M, Schildkraut, JM, Berchuck, A, Cramer, DW, Terry, KL, Bandera, EV, Olson, SH, Salvesen, HB, Thomsen, LC, Kopperud, RK, Bjorge, L, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Cook, LS, Le, ND, Swenerton, KD, Brooks-Wilson, A, Kelemen, LE, Lubiński, J, Huzarski, T, Gronwald, J, Menkiszak, J, Wentzensen, N, Brinton, L, Yang, H, Lissowska, J, Høgdall, CK, Lundvall, L, Song, H, Tyrer, JP, Campbell, I, Eccles, D, Paul, J, Glasspool, R, Siddiqui, N, Whittemore, AS, Sieh, W, McGuire, V, Rothstein, JH, Narod, SA, Phelan, C, Risch, HA, McLaughlin, JR, Anton-Culver, H, Dixon-Suen, Suzanne, Nagle, CM, Thrift, AP, Pharoah, PDP, Pearce, CL, Zheng, W, Painter, JN, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Lambrechts, D, Vergote, I, Lambrechts, S, Van Nieuwenhuysen, E, Rossing, MA, Doherty, JA, GWicklund, K, Chang-Claude, J, Rudolph, A, Moysich, KB, Odunsi, K, Goodman, MT, Wilkens, LR, Thompson, PJ, Shvetsov, YB, Dörk, T, Park-Simon, TW, Hillemanns, P, Bogdanova, N, Butzow, R, Nevanlinna, H, Pelttari, LM, Leminen, A, Modugno, F, Ness, RB, Edwards, RP, Kelley, JL, Heitz, F, Karlan, BY, Kjær, SK, Høgdall, E, Jensen, A, Goode, EL, Fridley, BL, Cunningham, JM, Winham, SJ, Giles, GG, Bruinsma, F, Milne, RL, Southey, MC, Hildebrandt, MAT, Wu, X, Lu, KH, Liang, D, Levine, DA, Bisogna, M, Schildkraut, JM, Berchuck, A, Cramer, DW, Terry, KL, Bandera, EV, Olson, SH, Salvesen, HB, Thomsen, LC, Kopperud, RK, Bjorge, L, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Cook, LS, Le, ND, Swenerton, KD, Brooks-Wilson, A, Kelemen, LE, Lubiński, J, Huzarski, T, Gronwald, J, Menkiszak, J, Wentzensen, N, Brinton, L, Yang, H, Lissowska, J, Høgdall, CK, Lundvall, L, Song, H, Tyrer, JP, Campbell, I, Eccles, D, Paul, J, Glasspool, R, Siddiqui, N, Whittemore, AS, Sieh, W, McGuire, V, Rothstein, JH, Narod, SA, Phelan, C, Risch, HA, McLaughlin, JR, and Anton-Culver, H

Published
2016

34. The use and interpretation of anthropometric measures in cancer epidemiology: A perspective from the world cancer research fund international continuous update project.

Author

Bandera, EV, Fay, SH, Giovannucci, E, Leitzmann, MF, Marklew, R, McTiernan, A, Mullee, A, Romieu, I, Thune, I, Uauy, R, Wiseman, MJ, World Cancer Research Fund International Continuous Update Project Panel, Bandera, EV, Fay, SH, Giovannucci, E, Leitzmann, MF, Marklew, R, McTiernan, A, Mullee, A, Romieu, I, Thune, I, Uauy, R, Wiseman, MJ, and World Cancer Research Fund International Continuous Update Project Panel

Abstract

Anthropometric measures relating to body size, weight and composition are increasingly being associated with cancer risk and progression. Whilst practical in epidemiologic research, where population-level associations with disease are revealed, it is important to be aware that such measures are imperfect markers of the internal physiological processes that are the actual correlates of cancer development. Body mass index (BMI), the most commonly used marker for adiposity, may mask differences between lean and adipose tissue, or fat distribution, which varies across individuals, ethnicities, and stage in the lifespan. Other measures, such as weight gain in adulthood, waist circumference and waist-to-hip ratio, contribute information on adipose tissue distribution and insulin sensitivity. Single anthropometric measures do not capture maturational events, including the presence of critical windows of susceptibility (i.e., age of menarche and menopause), which presents a challenge in epidemiologic work. Integration of experimental research on underlying dynamic genetic, hormonal, and other non-nutritional mechanisms is necessary for a confident conclusion of the overall evidence in cancer development and progression. This article discusses the challenges confronted in evaluating and interpreting the current evidence linking anthropometric factors and cancer risk as a basis for issuing recommendations for cancer prevention.

Published
2016

35. Recreational physical inactivity and mortality in women with invasive epithelial ovarian cancer: evidence from the Ovarian Cancer Association Consortium.

Author

Cannioto, RA, LaMonte, MJ, Kelemen, LE, Risch, HA, Eng, KH, Minlikeeva, AN, Hong, C-C, Szender, JB, Sucheston-Campbell, L, Joseph, JM, Berchuck, A, Chang-Claude, J, Cramer, DW, DeFazio, A, Diergaarde, B, Dörk, T, Doherty, JA, Edwards, RP, Fridley, BL, Friel, G, Goode, EL, Goodman, MT, Hillemanns, P, Hogdall, E, Hosono, S, Kelley, JL, Kjaer, SK, Klapdor, R, Matsuo, K, Odunsi, K, Nagle, CM, Olsen, CM, Paddock, LE, Pearce, CL, Pike, MC, Rossing, MA, Schmalfeldt, B, Segal, BH, Szamreta, EA, Thompson, PJ, Tseng, C-C, Vierkant, R, Schildkraut, JM, Wentzensen, N, Wicklund, KG, Winham, SJ, Wu, AH, Modugno, F, Ness, RB, Jensen, A, Webb, PM, Terry, K, Bandera, EV, Moysich, KB, Cannioto, RA, LaMonte, MJ, Kelemen, LE, Risch, HA, Eng, KH, Minlikeeva, AN, Hong, C-C, Szender, JB, Sucheston-Campbell, L, Joseph, JM, Berchuck, A, Chang-Claude, J, Cramer, DW, DeFazio, A, Diergaarde, B, Dörk, T, Doherty, JA, Edwards, RP, Fridley, BL, Friel, G, Goode, EL, Goodman, MT, Hillemanns, P, Hogdall, E, Hosono, S, Kelley, JL, Kjaer, SK, Klapdor, R, Matsuo, K, Odunsi, K, Nagle, CM, Olsen, CM, Paddock, LE, Pearce, CL, Pike, MC, Rossing, MA, Schmalfeldt, B, Segal, BH, Szamreta, EA, Thompson, PJ, Tseng, C-C, Vierkant, R, Schildkraut, JM, Wentzensen, N, Wicklund, KG, Winham, SJ, Wu, AH, Modugno, F, Ness, RB, Jensen, A, Webb, PM, Terry, K, Bandera, EV, and Moysich, KB

Abstract

BACKGROUND: Little is known about modifiable behaviours that may be associated with epithelial ovarian cancer (EOC) survival. We conducted a pooled analysis of 12 studies from the Ovarian Cancer Association Consortium to investigate the association between pre-diagnostic physical inactivity and mortality. METHODS: Participants included 6806 women with a primary diagnosis of invasive EOC. In accordance with the Physical Activity Guidelines for Americans, women reporting no regular, weekly recreational physical activity were classified as inactive. We utilised Cox proportional hazard models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) representing the associations of inactivity with mortality censored at 5 years. RESULTS: In multivariate analysis, inactive women had significantly higher mortality risks, with (HR=1.34, 95% CI: 1.18-1.52) and without (HR=1.22, 95% CI: 1.12-1.33) further adjustment for residual disease, respectively. CONCLUSION: In this large pooled analysis, lack of recreational physical activity was associated with increased mortality among women with invasive EOC.

Published
2016

36. A splicing variant of TERT identified by GWAS interacts with menopausal estrogen therapy in risk of ovarian cancer

Author

Lee, AW, Bomkamp, A, Bandera, EV, Jensen, A, Ramus, SJ, Goodman, MT, Rossing, MA, Modugno, F, Moysich, KB, Chang-Claude, J, Rudolph, A, Gentry-Maharaj, A, Terry, KL, Gayther, SA, Cramer, DW, Doherty, JA, Schildkraut, JM, Kjaer, SK, Ness, RB, Menon, U, Berchuck, A, Mukherjee, B, Roman, L, Pharoah, PD, Chenevix-Trench, G, Olson, S, Hogdall, E, Wu, AH, Pike, MC, Stram, DO, Pearce, CL, Lee, AW, Bomkamp, A, Bandera, EV, Jensen, A, Ramus, SJ, Goodman, MT, Rossing, MA, Modugno, F, Moysich, KB, Chang-Claude, J, Rudolph, A, Gentry-Maharaj, A, Terry, KL, Gayther, SA, Cramer, DW, Doherty, JA, Schildkraut, JM, Kjaer, SK, Ness, RB, Menon, U, Berchuck, A, Mukherjee, B, Roman, L, Pharoah, PD, Chenevix-Trench, G, Olson, S, Hogdall, E, Wu, AH, Pike, MC, Stram, DO, and Pearce, CL

Abstract

Menopausal estrogen-alone therapy (ET) is a well-established risk factor for serous and endometrioid ovarian cancer. Genetics also plays a role in ovarian cancer, which is partly attributable to 18 confirmed ovarian cancer susceptibility loci identified by genome-wide association studies. The interplay among these loci, ET use and ovarian cancer risk has yet to be evaluated. We analyzed data from 1,414 serous cases, 337 endometrioid cases and 4,051 controls across 10 case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Conditional logistic regression was used to determine the association between the confirmed susceptibility variants and risk of serous and endometrioid ovarian cancer among ET users and non-users separately and to test for statistical interaction. A splicing variant in TERT, rs10069690, showed a statistically significant interaction with ET use for risk of serous ovarian cancer (pint = 0.013). ET users carrying the T allele had a 51% increased risk of disease (OR = 1.51, 95% CI 1.19-1.91), which was stronger for long-term ET users of 10+ years (OR = 1.85, 95% CI 1.28-2.66, pint = 0.034). Non-users showed essentially no association (OR = 1.08, 95% CI 0.96-1.21). Two additional genomic regions harboring rs7207826 (C allele) and rs56318008 (T allele) also had significant interactions with ET use for the endometrioid histotype (pint = 0.021 and pint = 0.037, respectively). Hence, three confirmed susceptibility variants were identified whose associations with ovarian cancer risk are modified by ET exposure; follow-up is warranted given that these interactions are not adjusted for multiple comparisons. These findings, if validated, may elucidate the mechanism of action of these loci.

Published
2016

38. A targeted genetic association study of epithelial ovarian cancer susceptibility.

Author

Earp, M, Winham, SJ, Larson, N, Permuth, JB, Sicotte, H, Chien, J, Anton-Culver, H, Bandera, EV, Berchuck, A, Cook, LS, Cramer, D, Doherty, JA, Goodman, MT, Levine, DA, Monteiro, ANA, Ness, RB, Pearce, CL, Rossing, MA, Tworoger, SS, Wentzensen, N, Bisogna, M, Brinton, L, Brooks-Wilson, A, Carney, ME, Cunningham, JM, Edwards, RP, Fogarty, ZC, Iversen, ES, Kraft, P, Larson, MC, Le, ND, Lin, H-Y, Lissowska, J, Modugno, F, Moysich, KB, Olson, SH, Pike, MC, Poole, EM, Rider, DN, Terry, KL, Thompson, PJ, van den Berg, D, Vierkant, RA, Vitonis, AF, Wilkens, LR, Wu, AH, Yang, HP, Ziogas, A, Phelan, CM, Schildkraut, JM, Chen, YA, Sellers, TA, Fridley, BL, Goode, EL, Earp, M, Winham, SJ, Larson, N, Permuth, JB, Sicotte, H, Chien, J, Anton-Culver, H, Bandera, EV, Berchuck, A, Cook, LS, Cramer, D, Doherty, JA, Goodman, MT, Levine, DA, Monteiro, ANA, Ness, RB, Pearce, CL, Rossing, MA, Tworoger, SS, Wentzensen, N, Bisogna, M, Brinton, L, Brooks-Wilson, A, Carney, ME, Cunningham, JM, Edwards, RP, Fogarty, ZC, Iversen, ES, Kraft, P, Larson, MC, Le, ND, Lin, H-Y, Lissowska, J, Modugno, F, Moysich, KB, Olson, SH, Pike, MC, Poole, EM, Rider, DN, Terry, KL, Thompson, PJ, van den Berg, D, Vierkant, RA, Vitonis, AF, Wilkens, LR, Wu, AH, Yang, HP, Ziogas, A, Phelan, CM, Schildkraut, JM, Chen, YA, Sellers, TA, Fridley, BL, and Goode, EL

Abstract

BACKGROUND: Genome-wide association studies have identified several common susceptibility alleles for epithelial ovarian cancer (EOC). To further understand EOC susceptibility, we examined previously ungenotyped candidate variants, including uncommon variants and those residing within known susceptibility loci. RESULTS: At nine of eleven previously published EOC susceptibility regions (2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13), novel variants were identified that were more strongly associated with risk than previously reported variants. Beyond known susceptibility regions, no variants were found to be associated with EOC risk at genome-wide statistical significance (p <5x10(-8)), nor were any significant after Bonferroni correction for 17,000 variants (p< 3x10-6). METHODS: A customized genotyping array was used to assess over 17,000 variants in coding, non-coding, regulatory, and known susceptibility regions in 4,973 EOC cases and 5,640 controls from 13 independent studies. Susceptibility for EOC overall and for select histotypes was evaluated using logistic regression adjusted for age, study site, and population substructure. CONCLUSION: Given the novel variants identified within the 2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13 regions, larger follow-up genotyping studies, using imputation where necessary, are needed for fine-mapping and confirmation of low frequency variants that fall below statistical significance.

Published
2016

39. PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS

Author

Southey, MC, Goldgar, DE, Winqvist, R, Pylkas, K, Couch, F, Tischkowitz, M, Foulkes, WD, Dennis, J, Michailidou, K, van Rensburg, EJ, Heikkinen, T, Nevanlinna, H, Hopper, JL, Doerk, T, Claes, KBM, Reis-Filho, J, Teo, ZL, Radice, P, Catucci, I, Peterlongo, P, Tsimiklis, H, Odefrey, FA, Dowty, JG, Schmidt, MK, Broeks, A, Hogervorst, FB, Verhoef, S, Carpenter, J, Clarke, C, Scott, RJ, Fasching, PA, Haeberle, L, Ekici, AB, Beckmann, MW, Peto, J, dos-Santos-Silva, I, Fletcher, O, Johnson, N, Bolla, MK, Sawyer, EJ, Tomlinson, I, Kerin, MJ, Miller, N, Marme, F, Burwinkel, B, Yang, R, Guenel, P, Therese, T, Menegaux, F, Sanchez, M, Bojesen, S, Nielsen, SF, Flyger, H, Benitez, J, Pilar Zamora, M, Arias Perez, JI, Menendez, P, Anton-Culver, H, Neuhausen, S, Ziogas, A, Clarke, CA, Brenner, H, Arndt, V, Stegmaier, C, Brauch, H, Bruening, T, Ko, Y-D, Muranen, TA, Aittomaki, K, Blomqvist, C, Bogdanova, NV, Antonenkova, NN, Lindblom, A, Margolin, S, Mannermaa, A, Kataja, V, Kosma, V-M, Hartikainen, JM, Spurdle, AB, Wauters, E, Smeets, D, Beuselinck, B, Floris, G, Chang-Claude, J, Rudolph, A, Seibold, P, Flesch-Janys, D, Olson, JE, Vachon, C, Pankratz, VS, McLean, C, Haiman, CA, Henderson, BE, Schumacher, F, Le Marchand, L, Kristensen, V, Alnaes, GG, Zheng, W, Hunter, DJ, Lindstrom, S, Hankinson, SE, Kraft, P, Andrulis, I, Knight, JA, Glendon, G, Mulligan, AM, Jukkola-Vuorinen, A, Grip, M, Kauppila, S, Devilee, P, Tollenaar, RAEM, Seynaeve, C, Hollestelle, A, Garcia-Closas, M, Figueroa, J, Chanock, SJ, Lissowska, J, Czene, K, Darabi, H, Eriksson, M, Eccles, DM, Rafiq, S, Tapper, WJ, Gerty, SM, Hooning, MJ, Martens, JWM, Collee, JM, Tilanus-Linthorst, M, Hall, P, Li, J, Brand, JS, Humphreys, K, Cox, A, Reed, MWR, Luccarini, C, Baynes, C, Dunning, AM, Hamann, U, Torres, D, Ulmer, HU, Ruediger, T, Jakubowska, A, Lubinski, J, Jaworska, K, Durda, K, Slager, S, Toland, AE, Ambrosone, CB, Yannoukakos, D, Swerdlow, A, Ashworth, A, Orr, N, Jones, M, Gonzalez-Neira, A, Pita, G, Rosario Alonso, M, Alvarez, N, Herrero, D, Tessier, DC, Vincent, D, Bacot, F, Simard, J, Dumont, M, Soucy, P, Eeles, R, Muir, K, Wiklund, F, Gronberg, H, Schleutker, J, Nordestgaard, BG, Weischer, M, Travis, RC, Neal, D, Donovan, JL, Hamdy, FC, Khaw, K-T, Stanford, JL, Blot, WJ, Thibodeau, S, Schaid, DJ, Kelley, JL, Maier, C, Kibel, AS, Cybulski, C, Cannon-Albright, L, Butterbach, K, Park, J, Kaneva, R, Batra, J, Teixeira, MR, Kote-Jarai, Z, Al Olama, AA, Benlloch, S, Renner, SP, Hartmann, A, Hein, A, Ruebner, M, Lambrechts, D, Van Nieuwenhuysen, E, Vergote, I, Lambretchs, S, Doherty, JA, Rossing, MA, Nickels, S, Eilber, U, Wang-Gohrke, S, Odunsi, K, Sucheston-Campbell, LE, Friel, G, Lurie, G, Killeen, JL, Wilkens, LR, Goodman, MT, Runnebaum, I, Hillemanns, PA, Pelttari, LM, Butzow, R, Modugno, F, Edwards, RP, Ness, RB, Moysich, KB, du Bois, A, Heitz, F, Harter, P, Kommoss, S, Karlan, BY, Walsh, C, Lester, J, Jensen, A, Kjaer, SK, Hogdall, E, Peissel, B, Bonanni, B, Bernard, L, Goode, EL, Fridley, BL, Vierkant, RA, Cunningham, JM, Larson, MC, Fogarty, ZC, Kalli, KR, Liang, D, Lu, KH, Hildebrandt, MAT, Wu, X, Levine, DA, Dao, F, Bisogna, M, Berchuck, A, Iversen, ES, Marks, JR, Akushevich, L, Cramer, DW, Schildkraut, J, Terry, KL, Poole, EM, Stampfer, M, Tworoger, SS, Bandera, EV, Orlow, I, Olson, SH, Bjorge, L, Salvesen, HB, van Altena, AM, Aben, KKH, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bean, Y, Brooks-Wilson, A, Kelemen, LE, Cook, LS, Le, ND, Grski, B, Gronwald, J, Menkiszak, J, Hogdall, CK, Lundvall, L, Nedergaard, L, Engelholm, SA, Dicks, E, Tyrer, J, Campbell, I, McNeish, I, Paul, J, Siddiqui, N, Glasspool, R, Whittemore, AS, Rothstein, JH, McGuire, V, Sieh, W, Cai, H, Shu, X-O, Teten, RT, Sutphen, R, McLaughlin, JR, Narod, SA, Phelan, CM, Monteiro, AN, Fenstermacher, D, Lin, H-Y, Permuth, JB, Sellers, TA, Chen, YA, Tsai, Y-Y, Chen, Z, Gentry-Maharaj, A, Gayther, SA, Ramus, SJ, Menon, U, Wu, AH, Pearce, CL, Van den Berg, D, Pike, MC, Dansonka-Mieszkowska, A, Plisiecka-Halasa, J, Moes-Sosnowska, J, Kupryjanczyk, J, Pharoah, PDP, Song, H, Winship, I, Chenevix-Trench, G, Giles, GG, Tavtigian, SV, Easton, DF, Milne, RL, Southey, MC, Goldgar, DE, Winqvist, R, Pylkas, K, Couch, F, Tischkowitz, M, Foulkes, WD, Dennis, J, Michailidou, K, van Rensburg, EJ, Heikkinen, T, Nevanlinna, H, Hopper, JL, Doerk, T, Claes, KBM, Reis-Filho, J, Teo, ZL, Radice, P, Catucci, I, Peterlongo, P, Tsimiklis, H, Odefrey, FA, Dowty, JG, Schmidt, MK, Broeks, A, Hogervorst, FB, Verhoef, S, Carpenter, J, Clarke, C, Scott, RJ, Fasching, PA, Haeberle, L, Ekici, AB, Beckmann, MW, Peto, J, dos-Santos-Silva, I, Fletcher, O, Johnson, N, Bolla, MK, Sawyer, EJ, Tomlinson, I, Kerin, MJ, Miller, N, Marme, F, Burwinkel, B, Yang, R, Guenel, P, Therese, T, Menegaux, F, Sanchez, M, Bojesen, S, Nielsen, SF, Flyger, H, Benitez, J, Pilar Zamora, M, Arias Perez, JI, Menendez, P, Anton-Culver, H, Neuhausen, S, Ziogas, A, Clarke, CA, Brenner, H, Arndt, V, Stegmaier, C, Brauch, H, Bruening, T, Ko, Y-D, Muranen, TA, Aittomaki, K, Blomqvist, C, Bogdanova, NV, Antonenkova, NN, Lindblom, A, Margolin, S, Mannermaa, A, Kataja, V, Kosma, V-M, Hartikainen, JM, Spurdle, AB, Wauters, E, Smeets, D, Beuselinck, B, Floris, G, Chang-Claude, J, Rudolph, A, Seibold, P, Flesch-Janys, D, Olson, JE, Vachon, C, Pankratz, VS, McLean, C, Haiman, CA, Henderson, BE, Schumacher, F, Le Marchand, L, Kristensen, V, Alnaes, GG, Zheng, W, Hunter, DJ, Lindstrom, S, Hankinson, SE, Kraft, P, Andrulis, I, Knight, JA, Glendon, G, Mulligan, AM, Jukkola-Vuorinen, A, Grip, M, Kauppila, S, Devilee, P, Tollenaar, RAEM, Seynaeve, C, Hollestelle, A, Garcia-Closas, M, Figueroa, J, Chanock, SJ, Lissowska, J, Czene, K, Darabi, H, Eriksson, M, Eccles, DM, Rafiq, S, Tapper, WJ, Gerty, SM, Hooning, MJ, Martens, JWM, Collee, JM, Tilanus-Linthorst, M, Hall, P, Li, J, Brand, JS, Humphreys, K, Cox, A, Reed, MWR, Luccarini, C, Baynes, C, Dunning, AM, Hamann, U, Torres, D, Ulmer, HU, Ruediger, T, Jakubowska, A, Lubinski, J, Jaworska, K, Durda, K, Slager, S, Toland, AE, Ambrosone, CB, Yannoukakos, D, Swerdlow, A, Ashworth, A, Orr, N, Jones, M, Gonzalez-Neira, A, Pita, G, Rosario Alonso, M, Alvarez, N, Herrero, D, Tessier, DC, Vincent, D, Bacot, F, Simard, J, Dumont, M, Soucy, P, Eeles, R, Muir, K, Wiklund, F, Gronberg, H, Schleutker, J, Nordestgaard, BG, Weischer, M, Travis, RC, Neal, D, Donovan, JL, Hamdy, FC, Khaw, K-T, Stanford, JL, Blot, WJ, Thibodeau, S, Schaid, DJ, Kelley, JL, Maier, C, Kibel, AS, Cybulski, C, Cannon-Albright, L, Butterbach, K, Park, J, Kaneva, R, Batra, J, Teixeira, MR, Kote-Jarai, Z, Al Olama, AA, Benlloch, S, Renner, SP, Hartmann, A, Hein, A, Ruebner, M, Lambrechts, D, Van Nieuwenhuysen, E, Vergote, I, Lambretchs, S, Doherty, JA, Rossing, MA, Nickels, S, Eilber, U, Wang-Gohrke, S, Odunsi, K, Sucheston-Campbell, LE, Friel, G, Lurie, G, Killeen, JL, Wilkens, LR, Goodman, MT, Runnebaum, I, Hillemanns, PA, Pelttari, LM, Butzow, R, Modugno, F, Edwards, RP, Ness, RB, Moysich, KB, du Bois, A, Heitz, F, Harter, P, Kommoss, S, Karlan, BY, Walsh, C, Lester, J, Jensen, A, Kjaer, SK, Hogdall, E, Peissel, B, Bonanni, B, Bernard, L, Goode, EL, Fridley, BL, Vierkant, RA, Cunningham, JM, Larson, MC, Fogarty, ZC, Kalli, KR, Liang, D, Lu, KH, Hildebrandt, MAT, Wu, X, Levine, DA, Dao, F, Bisogna, M, Berchuck, A, Iversen, ES, Marks, JR, Akushevich, L, Cramer, DW, Schildkraut, J, Terry, KL, Poole, EM, Stampfer, M, Tworoger, SS, Bandera, EV, Orlow, I, Olson, SH, Bjorge, L, Salvesen, HB, van Altena, AM, Aben, KKH, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bean, Y, Brooks-Wilson, A, Kelemen, LE, Cook, LS, Le, ND, Grski, B, Gronwald, J, Menkiszak, J, Hogdall, CK, Lundvall, L, Nedergaard, L, Engelholm, SA, Dicks, E, Tyrer, J, Campbell, I, McNeish, I, Paul, J, Siddiqui, N, Glasspool, R, Whittemore, AS, Rothstein, JH, McGuire, V, Sieh, W, Cai, H, Shu, X-O, Teten, RT, Sutphen, R, McLaughlin, JR, Narod, SA, Phelan, CM, Monteiro, AN, Fenstermacher, D, Lin, H-Y, Permuth, JB, Sellers, TA, Chen, YA, Tsai, Y-Y, Chen, Z, Gentry-Maharaj, A, Gayther, SA, Ramus, SJ, Menon, U, Wu, AH, Pearce, CL, Van den Berg, D, Pike, MC, Dansonka-Mieszkowska, A, Plisiecka-Halasa, J, Moes-Sosnowska, J, Kupryjanczyk, J, Pharoah, PDP, Song, H, Winship, I, Chenevix-Trench, G, Giles, GG, Tavtigian, SV, Easton, DF, and Milne, RL

Abstract

BACKGROUND: The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study. METHODS: We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant. RESULTS: For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10-5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10-8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants. CONCLUSIONS: This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.

Published
2016

40. Diet and survival after a diagnosis of ovarian cancer: a pooled analysis from the Ovarian Cancer Association Consortium.

Author

Nagle CM, Ibiebele TI, Na R, Bandera EV, Cramer D, Doherty JA, Giles GG, Goodman MT, Hanley GE, Harris HR, Jensen A, Kjaer SK, Lee A, McGuire V, Milne RL, Qin B, Richardson J, Sasamoto N, Schildkraut JM, Sieh W, Terry KL, Titus L, Trabert B, Wentzensen N, Wu AH, Berchuck A, Pike MC, Pearce CL, and Webb PM

Abstract

Background: Prognosis following a diagnosis of invasive epithelial ovarian cancer is poor. Some studies have suggested modifiable behaviors, like diet, are associated with survival but the evidence is inconsistent., Objective: To pool data from studies conducted around the world to evaluate the relation between dietary indices, foods, and nutrients from food sources and survival after a diagnosis of ovarian cancer., Methods: This analysis from the Multidisciplinary Ovarian Cancer Outcomes Group within the Ovarian Cancer Association Consortium included 13 studies with 7,700 individuals with ovarian cancer, who completed food-frequency questionnaires regarding their pre-diagnosis diet. Adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for associations with overall survival were estimated using Cox proportional hazards models., Results: Overall, there was no association between any of the seven dietary indices (representing pre-diagnosis diet) evaluated and survival; however, associations differed by tumor stage. While there were no consistent associations among those with advanced disease, among those with earlier stage (local/regional) disease, higher scores on the alternate Healthy Eating Index (aHR Quartile 4 versus 1 = 0.66, 95% CI=0.50, 0.87), Healthy Eating Index-2015 (aHR 0.75; 95% CI=0.59, 0.97) and alternate Mediterranean diet (aHR 0.76; 95% CI=0.60, 0.98) were associated with better survival. Better survival was also observed for individuals with early-stage disease who reported higher intakes of dietary components that contribute to the healthy diet indices (aHR for Q4 versus Q1: vegetables 0.71; 95% CI=0.56, 0.91), tomatoes (aHR 0.72; 95% CI=0.57, 0.91) and nuts and seeds (aHR 0.71; 95% CI=0.55, 0.92). In contrast, there were suggestions of worse survival with higher scores on two of the three inflammatory indices and higher intake of trans-fatty acids., Conclusions: Adherence to a more heathy, less inflammatory diet may confer a survival benefit for individuals with early-stage ovarian cancer., Competing Interests: Declaration of Competing Interest ☒ The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Penelope M Webb reports a relationship with AstraZeneca Australia that includes: funding grants. Membership of an Advisory Board for Pfizer to enhance minoritized and underrepresented populations in clinical trials, unrelated to this study (EVB). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025. Published by Elsevier Inc.)

Published
2025
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41. Methodologic Approach to Defining Comorbidities in a Cohort of Patients With Cancer: An Example in the Optimal Breast Cancer Chemotherapy Dosing Study.

Author

Wang P, O'Connell K, Bhimani J, Blinder V, Burganowski R, Ergas IJ, Gallagher GB, Griggs JJ, Heon N, Kolevska T, Kotsurovskyy Y, Kroenke CH, Laurent CA, Liu R, Nakata KG, Persaud S, Rivera DR, Roh JM, Tabatabai S, Valice E, Bandera EV, Kushi LH, Aiello Bowles EJ, and Kantor ED

Subjects
Humans, Female, Middle Aged, Aged, Electronic Health Records, Adult, Antineoplastic Combined Chemotherapy Protocols therapeutic use, Antineoplastic Combined Chemotherapy Protocols adverse effects, Chemotherapy, Adjuvant methods, Cohort Studies, Comorbidity, Breast Neoplasms drug therapy, Breast Neoplasms pathology, Breast Neoplasms epidemiology
Abstract

Purpose: We evaluated the definitions of five comorbidities (renal and hepatic impairments, anemia, neutropenia, and thrombocytopenia) in women with breast cancer using data from electronic health records., Methods: In 11,097 women receiving adjuvant chemotherapy for stage I-IIIA breast cancer at Kaiser Permanente Northern California or Kaiser Permanente Washington, we assessed comorbidity definitions in two commonly used lookback windows (1 year before diagnosis, T1; and extending until chemotherapy initiation, T1-2). Within each, we assessed data availability and agreement between International Classification of Diseases (ICD)-defined and lab-defined comorbidities of varying severity. To assess how different pieces of information may affect providers in making treatment decisions, we used multivariable logistic regression to evaluate four-category (with comorbidity indicated by both ICD and lab, ICD-only, lab-only, or neither) and collapsed binary (comorbidity indicated by either ICD or lab v neither) definitions in relation to first cycle chemotherapy dose reduction (FCDR)., Results: Extending the lookback period to chemotherapy initiation increased laboratory data availability (missingness ≤4.1% in T1-2 v >40% in T1). Assessment of agreement guided selection of laboratory cutpoints. In both time periods, the four-category and binary comorbidity variables were associated with use of FCDR, but binary variables had larger cell sizes and more stability of regression models. Ultimately, the comorbidity variables in T1 were defined by a combination of either ICD/qualifying laboratory values. Results were similar in T1-2, except laboratory data alone outperformed the combination variable for renal and hepatic comorbidity., Conclusion: Leveraging both ICD and lab data and extending the lookback period to include postdiagnosis but prechemotherapy initiation may provide better capture of comorbidity. Future studies may consider validating our findings with a gold-standard comorbidity status and in other community health care settings.

Published
2025
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42. Comorbid conditions and survival among Black women with ovarian cancer.

Author

Richards AR, Johnson CE, Montalvo NR, Alberg AJ, Bandera EV, Bondy M, Collin LJ, Cote ML, Hastert TA, Haller K, Khanna N, Marks JR, Peters ES, Qin B, Staples J, Terry PD, Lawson A, Schildkraut JM, and Peres LC

Subjects
Adult, Aged, Female, Humans, Middle Aged, Carcinosarcoma mortality, Carcinosarcoma pathology, Carcinosarcoma epidemiology, Prognosis, Proportional Hazards Models, Prospective Studies, Black or African American statistics & numerical data, Carcinoma, Ovarian Epithelial mortality, Carcinoma, Ovarian Epithelial epidemiology, Carcinoma, Ovarian Epithelial ethnology, Carcinoma, Ovarian Epithelial pathology, Comorbidity, Diabetes Mellitus, Type 2 mortality, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology, Diabetes Mellitus, Type 2 ethnology, Hyperlipidemias epidemiology, Hyperlipidemias complications, Hypertension epidemiology, Hypertension complications, Ovarian Neoplasms mortality, Ovarian Neoplasms pathology, Ovarian Neoplasms ethnology, Ovarian Neoplasms epidemiology
Abstract

Background: Black women with epithelial ovarian cancer (EOC) have worse survival and a higher burden of comorbid conditions compared with other racial groups. This study examines the association of comorbid conditions and medication use for these conditions with survival among Black women with EOC., Methods: In a prospective study of 592 Black women with EOC, the Charlson comorbidity index (CCI) based on self-reported data, three cardiometabolic comorbidities (type 2 diabetes, hypertension, and hyperlipidemia), and medication use for each cardiometabolic comorbidity were evaluated. Cox proportional hazards regression models were used to examine the association of comorbid conditions and related medication use with all-cause mortality while adjusting for relevant covariates overall and by histotype (high-grade serous [HGS]/carcinosarcoma vs. non-HGS/carcinosarcoma) and stage (I/II vs. III/IV)., Results: A CCI of ≥2 was observed in 42% of the cohort, and 21%, 67%, and 34% of women had a history of type 2 diabetes, hypertension, and hyperlipidemia, respectively. After adjusting for prognostic factors, a CCI ≥2 (vs. 0; hazard ratio [HR], 1.33; 95% confidence interval [CI], 1.04-1.71) and type 2 diabetes (HR, 1.42; 95% CI, 1.10-1.84) were associated with an increased risk of mortality. The increased risk of mortality for type 2 diabetes was present specifically among women with HGS/carcinosarcoma (HR, 1.47; 95% CI, 1.10-1.97) and among women with stage III/IV disease (HR, 1.47; 95% CI, 1.10-1.98). The authors did not find evidence that hypertension, hyperlipidemia, or medication use for the cardiometabolic comorbidities meaningfully impacted survival., Conclusion: Comorbid conditions, especially type 2 diabetes, had a significant adverse impact on survival among Black women with EOC., (© 2025 American Cancer Society.)

Published
2025
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43. Household income and county income inequality are associated with financial hardship among cancer survivors in New Jersey.

Author

Grafova IB, Devine KA, Hudson SV, O'Malley D, Paddock LE, Bandera EV, Llanos AAM, Fong AJ, Evens AM, and Manne S

Abstract

Purpose: To examine how household income and county income inequality are linked to financial hardship among cancer survivors., Methods: Cancer survivors (n = 864) identified through the New Jersey State Cancer Registry were surveyed from August 2018 to January 2022. Local area income inequality was reflected by the Gini index a measure of income inequality at the county level. Multivariable logistic regression analyses were performed, and the average marginal effect (AME) was calculated., Results: Compared to survivors residing in households with income of $90,000 or more (higher income), those with household incomes between $50,000 and $89,999 (middle income) had a significantly higher risk of ever being unable to cover their share of the cost of cancer-related medical care (AME = .104, p = .001), higher risk of foregoing care in the past 12 months because of cost, including dental care (AME = .124, p < .001), eye care (AME = .082, p = .005), and mental health care or counseling (AME = .067, p = .002). An increase in the Gini index from the 25th to 75th percentile was associated with an increased risk of unmet needs in paying for follow-up care or medications related to cancer (AME = .021, p = .014) and an increased risk of foregoing doctor visits (AME = .017, p = .02) and eye care (AME = .03, p = .002) because of cost in the past 12 months., Conclusions: Local area income inequality was associated with certain aspects of cancer survivors' experience of financial hardship., Implications for Cancer Survivors: It is important to consider refining and extending financial navigation programs to survivors residing in areas with high income inequality., Competing Interests: Declarations. Conflict of interest: Dr. Bandera reports serving in a Pfizer, Inc Advisory Board to enhance minority participation in clinical trials. No other disclosures were reported., (© 2024. The Author(s).)

Published
2024
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44. Risk factors for breast cancer subtypes by race and ethnicity: a scoping review.

Author

Hurson AN, Ahearn TU, Koka H, Jenkins BD, Harris AR, Roberts S, Fan S, Franklin J, Butera G, Keeman R, Jung AY, Middha P, Gierach GL, Yang XR, Chang-Claude J, Tamimi RM, Troester MA, Bandera EV, Abubakar M, Schmidt MK, and Garcia-Closas M

Subjects
Humans, Female, Risk Factors, Receptors, Estrogen metabolism, Receptors, Estrogen analysis, Racial Groups statistics & numerical data, Breast Neoplasms ethnology, Breast Neoplasms epidemiology, Breast Neoplasms etiology, Ethnicity statistics & numerical data
Abstract

Background: Breast cancer consists of distinct molecular subtypes. Studies have reported differences in risk factor associations with breast cancer subtypes, especially by tumor estrogen receptor (ER) status, but their consistency across racial and ethnic populations has not been comprehensively evaluated., Methods: We conducted a qualitative, scoping literature review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis, extension for Scoping Reviews to investigate consistencies in associations between 18 breast cancer risk factors (reproductive, anthropometric, lifestyle, and medical history) and risk of ER-defined subtypes in women who self-identify as Asian, Black or African American, Hispanic or Latina, or White. We reviewed publications between January 1, 1990 and July 1, 2022. Etiologic heterogeneity evidence (convincing, suggestive, none, or inconclusive) was determined by expert consensus., Results: Publications per risk factor ranged from 14 (benign breast disease history) to 66 (parity). Publications were most abundant for White women, followed by Asian, Black or African American, and Hispanic or Latina women. Etiologic heterogeneity evidence was strongest for parity, followed by age at first birth, postmenopausal body mass index, oral contraceptive use, and estrogen-only and combined menopausal hormone therapy. Evidence was limited for other risk factors. Findings were consistent across racial and ethnic groups, although the strength of evidence varied., Conclusion: The literature supports etiologic heterogeneity by ER for some established risk factors that are consistent across race and ethnicity groups. However, in non-White populations evidence is limited. Larger, more comparable data in diverse populations are needed to better characterize breast cancer etiologic heterogeneity., (Published by Oxford University Press 2024.)

Published
2024
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45. Survivorship care plans and adherence to breast and cervical cancer screening guidelines among cancer survivors in a national sample.

Author

Santos-Teles M, Modugu G, Silva IC, Bandera EV, George M, Qin B, Smith J, Stephenson R, Mattes MD, and Eskander MF

Subjects
Humans, Female, Middle Aged, Cross-Sectional Studies, Adult, Aged, Survivorship, Behavioral Risk Factor Surveillance System, United States, Mammography methods, Mammography statistics & numerical data, Patient Care Planning, Cancer Survivors statistics & numerical data, Uterine Cervical Neoplasms diagnosis, Uterine Cervical Neoplasms therapy, Breast Neoplasms therapy, Early Detection of Cancer methods, Early Detection of Cancer statistics & numerical data, Guideline Adherence statistics & numerical data
Abstract

Purpose: The impact of the components of survivorship care plans on adherence to cancer screening guidelines among cancer survivors is limited. We examined the association of receipt of treatment summaries, follow-up instructions, and type of doctor providing survivorship care with adherence to breast cancer screening (BCS) and cervical cancer screening (CCS) guidelines in female cancer survivors., Methods: A cross-sectional analysis using Behavioral Risk Factor Surveillance System (BRFSS) data from 2014, 2016 and 2018 was conducted. BCS and CCS-eligible women were aged 40-74 and 30-64, respectively. BCS adherence was defined as a mammogram within 2 years and CCS adherence as a pap smear within 3 years or HPV test within 5 years. Univariate analysis with chi-square and multivariable logistic regression are reported., Results: 5,001 BCS and 3,014 CCS-eligible survivors were identified. In the BCS group, recipients of treatment summaries and follow-up instructions were significantly more adherent with BCS (84.1% vs. 77.4%; 83.4% vs. 74%, respectively, p < 0.001). In the CCS group, recipients of follow-up instructions were significantly more adherent with CCS (78.1% vs. 67.7%, p < 0.001). In both groups, there was no significant difference in BCS or CCS based on type of physician providing care (p = 0.087). On multivariate analysis, receipt of follow-up instructions was the only factor significantly associated with BCS (OR:2.81; 95%CI:1.76-4.49) and CCS (OR:3.14; 95%CI:1.88-5.23)., Conclusions: Follow-up instructions, as part of survivorship care plans, have the strongest association with BCS and CCS among female cancer survivors. Additional research should focus on improving the distribution of survivorship care plans, particularly follow-up instructions, as a method to increase BCS and CCS among cancer survivors., Competing Interests: Declarations Ethics approval This is an observational study with publicly available de-identified individual data and did not require approval from the Rutgers University Institutional Board Review. Competing interests The authors declare no competing interests. Disclaimers This research was presented as a poster at the 2023 ASCO Annual Meeting, held in Chicago, IL, June 2 to 6, 2023, and published as an abstract from the meeting., (© 2024. The Author(s).)

Published
2024
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46. The role of multiple mediation with contextual neighborhood measures in ovarian cancer survival.

Author

Lawson AB, Xin Y, Peters ES, Johnson C, Hastert T, Bandera EV, Alberg AJ, Collin L, Terry P, Akonde M, Mandle H, Cote ML, Bondy M, Marks J, Peres LC, Ratnapradipa KL, and Schildkraut JM

Subjects
Adult, Aged, Female, Humans, Middle Aged, Black or African American statistics & numerical data, Mediation Analysis, Socioeconomic Factors, United States epidemiology, Bayes Theorem, Ovarian Neoplasms mortality, Ovarian Neoplasms pathology, Residence Characteristics
Abstract

Background: Mediation by multiple agents can affect the relation between neighborhood deprivation and segregation indices and ovarian cancer survival. In this paper, we examine a variety of potential clinical mediators in the association between deprivation indices (DIs) and segregation indices (SIs) with all-cause survival among women with ovarian cancer in the African American Cancer Epidemiology Study (AACES)., Methods: We use novel Bayesian multiple mediation structural models to assess the joint role of mediators (stage at diagnosis, histology, diagnostic delay) combined with the DIs and SIs (Yost, ADI, Kolak's URB, ICE-income) and a set of confounders with survival. The confounder set is selected in a preliminary step, and each DI or SI is included in separate model fits., Results: When multiple mediators are included, the total impact of DIs and SIs on survival is much reduced. Unlike the single mediator examples previously reported, the Yost, ADI and ICE-income indices do not display significant direct effects. This suggests that when important clinical mediators are included, the impact of neighborhood SES indices is significantly attenuated. It is also clear that certain behavioral and demographic measures such as physical activity, smoking, or adjusted family income do not have a significant role in survival when mediated by clinical factors., Conclusion: Multiple mediation via clinical and diagnostic-related measures reduces the contextual effects of neighborhood measures on ovarian cancer survival. The robust association of the Kolak URB index on survival may be due to its relevance to access to care, unlike SES-based indices whose impact was significantly reduced when important clinical mediators were included., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Andrew B Lawson reports financial support was provided by National Institutes of Health. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Published
2024
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47. Patient characteristics associated with delayed time to adjuvant chemotherapy among women treated for stage I-IIIA breast cancer.

Author

Bhimani J, O'Connell K, Persaud S, Blinder V, Burganowski R, Ergas IJ, Foley MJ, Gallagher GB, Griggs JJ, Heon N, Kolevska T, Kotsurovskyy Y, Kroenke CH, Laurent CA, Liu R, Nakata KG, Rivera DR, Roh JM, Tabatabai S, Valice E, Bandera EV, Bowles EJA, Kushi LH, and Kantor ED

Subjects
Humans, Female, Chemotherapy, Adjuvant, Middle Aged, Aged, Adult, Mastectomy, Neoplasm Recurrence, Local pathology, Neoplasm Recurrence, Local epidemiology, Neoplasm Recurrence, Local prevention & control, Breast Neoplasms drug therapy, Breast Neoplasms pathology, Breast Neoplasms surgery, Neoplasm Staging, Time-to-Treatment statistics & numerical data
Abstract

For patients with breast cancer, delays in chemotherapy initiation have been adversely associated with recurrence and survival. We evaluated patient-level factors associated with delayed chemotherapy initiation, from both diagnosis and surgery, in a community-based cohort of women with early-stage breast cancer. For the Optimal Breast Cancer Chemotherapy Dosing study, we identified a cohort of 34,109 women diagnosed with stage I-IIIA breast cancer at two U.S. integrated healthcare delivery systems between 2004 and 2019. We used logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI) to identify patient factors associated with delays in chemotherapy initiation after diagnosis (≥90 days) and surgery (≥60 days). Among 10,968 women receiving adjuvant chemotherapy, 21.1% experienced delays in chemotherapy initiation after diagnosis and 21.3% after surgery. Older age, non-Hispanic Black and Hispanic race and ethnicity, and ER+ and/or PR+ disease were associated with increased likelihood of delays to chemotherapy initiation after diagnosis and surgery. People diagnosed in 2012-2019 (vs. 2005-2011), with a higher grade and larger tumor size were less likely to experience delays. Other factors were associated with a higher likelihood of delays specifically from diagnosis (earlier stage, mastectomy vs. breast-conserving surgery), or surgery (higher comorbidity, increased nodal number). Women diagnosed with breast cancer who were at highest risk of progression and recurrence were less likely to experience delays in chemotherapy initiation after diagnosis and surgery. Understanding reasons for chemotherapy delays beyond patient factors may be potentially important to reduce risk of breast cancer recurrence and progression., (© 2024 UICC.)

Published
2024
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48. The landscape of use of NCCN-guideline chemotherapy regimens in stage I-IIIA breast cancer in an integrated healthcare delivery system.

Author

Bhimani J, O'Connell K, Persaud S, Blinder V, Burganowski RP, Ergas IJ, Gallagher GB, Griggs JJ, Heon N, Kolevska T, Kotsurovskyy Y, Kroenke CH, Laurent CA, Liu R, Nakata KG, Rivera DR, Roh JM, Tabatabai S, Valice E, Bandera EV, Aiello Bowles EJ, Kushi LH, and Kantor ED

Subjects
Humans, Female, Middle Aged, Aged, Adult, Guideline Adherence, California epidemiology, Breast Neoplasms drug therapy, Breast Neoplasms pathology, Antineoplastic Combined Chemotherapy Protocols therapeutic use, Antineoplastic Combined Chemotherapy Protocols adverse effects, Neoplasm Staging, Delivery of Health Care, Integrated, Practice Guidelines as Topic
Abstract

Purpose: The National Comprehensive Cancer Network (NCCN) guidelines recommend a variety of drug combinations with specific administration schedules for the treatment of early-stage breast cancer, allowing physicians to deliver treatments recognizing individual patient complexities, including comorbidities, and patient-physician preference. While use of guideline regimens has shifted over time, there is little data to describe changes in how treatment for early-stage breast cancer has evolved over time., Methods: In a cohort of 34,109 women treated for stage I-IIIA breast cancer between 2006-2019 at Kaiser Permanente Northern California and Kaiser Permanente Washington, we present the changes in chemotherapy regimens over time, and explore use of NCCN-guideline regimens (GR), guideline regimens used when said regimens were not included in guidelines, referred to as time-discordant regimens (TDR), and non-guideline regimens (NGR). Results are presented by drug combination and over time., Results: Among 12,506 women receiving chemotherapy, 77.4% (n = 9681) received GRs, 9.1% (n = 1140) received TDRs, and 13.5% (n = 1685) received NGRs. In 2006, AC-T (cyclophosphamide-doxorubicin, paclitaxel) was the most common regimen, with TC (cyclophosphamide-docetaxel) becoming the most prevalent by 2019. NGRs were more common in cyclophosphamide-methotrexate-5-fluorouracil (CMF); cyclophosphamide-doxorubicin-paclitaxel-trastuzumab (ACTH); and paclitaxel-trastuzumab (TH). The use of GR has increased over time (p-trend < 0.001), while use of NGR (both in terms of administration schedule and drug combination) and TDR have decreased, although patterns vary by drug combination., Conclusion: Chemotherapy delivery has changed markedly over time, with a move toward more use of GR. These data are important for understanding the landscape of chemotherapy delivery in community healthcare settings., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Published
2024
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49. Patient Characteristics Associated with Intended Nonguideline Chemotherapy in Women with Stage I to IIIA Breast Cancer.

Author

Bhimani J, O'Connell K, Persaud S, Blinder V, Burganowski-Doud RP, Ergas IJ, Gallagher GB, Griggs JJ, Heon N, Kolevska T, Kotsurovskyy Y, Kroenke CH, Laurent CA, Liu R, Nakata KG, Rivera DR, Roh JM, Tabatabai S, Valice E, Bandera EV, Aiello Bowles EJ, Kushi LH, and Kantor ED

Subjects
Humans, Female, Middle Aged, Adult, Aged, Aged, 80 and over, Young Adult, Adolescent, Antineoplastic Combined Chemotherapy Protocols therapeutic use, California epidemiology, Breast Neoplasms drug therapy, Breast Neoplasms pathology, Neoplasm Staging
Abstract

Background: Guidelines informing chemotherapy regimen selection are based on clinical trials with participants who do not necessarily represent general populations with breast cancer. Understanding who receives nonguideline regimens is important for understanding real-world chemotherapy administration and how it relates to patient outcomes., Methods: Using data from the Optimal Breast Cancer Chemotherapy Dosing (OBCD) study, based at Kaiser Permanente Northern California (2006-2019) and Kaiser Permanente Washington (2004-2015), we use logistic regression to examine the associations between patient characteristics and receipt of nonguideline chemotherapy regimens among 11,293 women with primary stage I to IIIA breast cancer receiving chemotherapy., Results: The use of nonguideline regimens was strongly associated with several factors, including older age [≥80 vs. 18-39 years: OR, 5.25; 95% confidence interval (CI), 3.06-9.00; P-trend = 0.002] and HER2 status (HER2+ vs. HER2-: OR, 3.44; 95% CI, 3.06-3.87) and was less likely in women with larger tumor size (>5 cm vs. 0.1 to ≤0.5 cm: OR, 0.56; 95% CI, 0.36-0.87; P-trend = 0.01) and diagnosed in later years (2012-2019 vs. 2005-2011: OR, 0.80; 95% CI, 0.71-0.90). Factors associated varied by type of nonguideline regimens. For example, women with comorbidity and older age were more likely to receive nonguideline drug combinations in particular, whereas women with larger tumor size were less likely to receive nonguideline administration schedules., Conclusions: Nonguideline chemotherapy regimens are more likely in certain patient populations., Impact: These associations highlight that vulnerable patient populations may be less likely to receive guideline care, and thus, real-world studies are essential for understanding how the use of nonguideline regimens impacts patient outcomes in these groups., (©2024 American Association for Cancer Research.)

Published
2024
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50. Pre-diagnosis tea and coffee consumption and survival after a diagnosis of ovarian cancer: results from the Ovarian Cancer Association Consortium.

Author

Nagle CM, Ibiebele TI, Bandera EV, Cramer D, Doherty JA, Giles GG, Goodman MT, Hanley GE, Harris HR, Jensen A, Kjaer SK, Lee AW, Milne RL, Qin B, Richardson J, Sasamoto N, Sieh W, Terry KL, Titus L, Trabert B, Wentzensen N, Wu AH, Berchuck A, Pike M, Pearce CL, and Webb PM

Subjects
Humans, Female, Middle Aged, Aged, Proportional Hazards Models, Adult, Caffeine administration & dosage, Ovarian Neoplasms mortality, Ovarian Neoplasms diagnosis, Tea, Coffee
Abstract

Background: Tea and coffee are the most frequently consumed beverages in the world. Green tea in particular contains compounds with potential anti-cancer effects, but its association with survival after ovarian cancer is uncertain., Methods: We investigated the associations between tea and coffee consumption before diagnosis and survival using data from 10 studies in the Ovarian Cancer Association Consortium. Data on tea (green, black, herbal), coffee and caffeine intake were available for up to 5724 women. We used Cox proportional hazards regression to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CI)., Results: Compared with women who did not drink any green tea, consumption of one or more cups/day was associated with better overall survival (aHR = 0.84, 95% CI 0.71-1.00, p-trend = 0.04). A similar association was seen for ovarian cancer-specific survival in five studies with this information (aHR = 0.81, 0.66-0.99, p-trend = 0.045). There was no consistent variation between subgroups defined by clinical or lifestyle characteristics and adjustment for other aspects of lifestyle did not appreciably alter the estimates. We found no evidence of an association between coffee, black or herbal tea, or caffeine intake and survival., Conclusion: The observed association with green tea consumption before diagnosis raises the possibility that consumption after diagnosis might improve patient outcomes., (© 2024. The Author(s).)

Published
2024
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