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1. Understanding the genetic complexity of puberty timing across the allele frequency spectrum.

Author

Kentistou, Katherine, Kaisinger, Lena, Stankovic, Stasa, Vaudel, Marc, Mendes de Oliveira, Edson, Messina, Andrea, Walters, Robin, Liu, Xiaoxi, Busch, Alexander, Helgason, Hannes, Thompson, Deborah, Santoni, Federico, Petricek, Konstantin, Zouaghi, Yassine, Huang-Doran, Isabel, Gudbjartsson, Daniel, Bratland, Eirik, Lin, Kuang, Gardner, Eugene, Zhao, Yajie, Jia, Raina, Terao, Chikashi, Riggan, Marjorie, Bolla, Manjeet, Yazdanpanah, Mojgan, Yazdanpanah, Nahid, Bradfield, Jonathan, Broer, Linda, Campbell, Archie, Chasman, Daniel, Cousminer, Diana, Franceschini, Nora, Franke, Lude, Girotto, Giorgia, He, Chunyan, Järvelin, Marjo-Riitta, Joshi, Peter, Kamatani, Yoichiro, Karlsson, Robert, Luan, Jianan, Lunetta, Kathryn, Mägi, Reedik, Mangino, Massimo, Medland, Sarah, Meisinger, Christa, Noordam, Raymond, Nutile, Teresa, Concas, Maria, Polašek, Ozren, Porcu, Eleonora, Ring, Susan, Sala, Cinzia, Smith, Albert, Tanaka, Toshiko, van der Most, Peter, Vitart, Veronique, Wang, Carol, Willemsen, Gonneke, Zygmunt, Marek, Ahearn, Thomas, Andrulis, Irene, Anton-Culver, Hoda, Antoniou, Antonis, Auer, Paul, Barnes, Catriona, Beckmann, Matthias, Berrington de Gonzalez, Amy, Bogdanova, Natalia, Bojesen, Stig, Brenner, Hermann, Buring, Julie, Canzian, Federico, Chang-Claude, Jenny, Couch, Fergus, Cox, Angela, Crisponi, Laura, Czene, Kamila, Daly, Mary, Demerath, Ellen, Dennis, Joe, Devilee, Peter, De Vivo, Immaculata, Dörk, Thilo, Dunning, Alison, Dwek, Miriam, Eriksson, Johan, Fasching, Peter, Fernandez-Rhodes, Lindsay, Ferreli, Liana, Fletcher, Olivia, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José, González-Neira, Anna, Grallert, Harald, Guénel, Pascal, Haiman, Christopher, Hall, Per, Hamann, Ute, and Hakonarson, Hakon

Subjects
Humans, Female, Menarche, Puberty, Gene Frequency, Animals, Multifactorial Inheritance, Mice, Genome-Wide Association Study, Adolescent, Puberty, Precocious, Polymorphism, Single Nucleotide, Receptors, G-Protein-Coupled, Puberty, Delayed, Child
Abstract

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease.

Published
2024

2. Disentangling the relationships of body mass index and circulating sex hormone concentrations in mammographic density using Mendelian randomization

Author

Haas, Cameron B., Chen, Hongjie, Harrison, Tabitha, Fan, Shaoqi, Gago-Dominguez, Manuela, Castelao, Jose E., Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Dunning, Alison M., Easton, Douglas F., Antoniou, Antonis C., Hall, Per, Czene, Kamila, Andrulis, Irene L., Mulligan, Anna Marie, Milne, Roger L., Fasching, Peter A., Haeberle, Lothar, Garcia-Closas, Montserrat, Ahearn, Thomas, Gierach, Gretchen L., Haiman, Christopher, Maskarinec, Gertraud, Couch, Fergus J., Olson, Janet E., John, Esther M., Chenevix-Trench, Geogia, Berrington de Gonzalez, Amy, Jones, Michael, Stone, Jennifer, Murphy, Rachel, Aronson, Kristan J., Wernli, Karen J., Hsu, Li, Vachon, Celine, Tamimi, Rulla M., and Lindström, Sara

Published
2024
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6. Evaluation of European-based polygenic risk score for breast cancer in Ashkenazi Jewish women in Israel

Author

Levi, Hagai, Carmi, Shai, Rosset, Saharon, Yerushalmi, Rinat, Zick, Aviad, Yablonski-Peretz, Tamar, Consortium, The BCAC, Wang, Qin, Bolla, Manjeet K, Dennis, Joe, Michailidou, Kyriaki, Lush, Michael, Ahearn, Thomas, Andrulis, Irene L, Anton-Culver, Hoda, Antoniou, Antonis C, Arndt, Volker, Augustinsson, Annelie, Auvinen, Päivi, Freeman, Laura Beane, Beckmann, Matthias, Behrens, Sabine, Bermisheva, Marina, Bodelon, Clara, Bogdanova, Natalia V, Bojesen, Stig E, Brenner, Hermann, Byers, Helen, Camp, Nicola, Castelao, Jose, Chang-Claude, Jenny, Chirlaque, María-Dolores, Chung, Wendy, Clarke, Christine, Collaborators, NBCS, Collee, Margriet J, Colonna, Sarah, Consortium, CTS, Couch, Fergus, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary, Devilee, Peter, Dork, Thilo, Dossus, Laure, Eccles, Diana M, Eliassen, A Heather, Eriksson, Mikael, Evans, Gareth, Fasching, Peter, Fletcher, Olivia, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, García-Closas, Montserrat, Garcia-Saenz, Jose Angel, Genkinger, Jeanine, Giles, Graham G, Goldberg, Mark, Guénel, Pascal, Hall, Per, Hamann, Ute, He, Wei, Hillemanns, Peter, Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John, Investigators, ABCTB, Jakovchevska, Simona, Jakubowska, Anna, Jernström, Helena, John, Esther, Johnson, Nichola, Jones, Michael, Vijai, Joseph, Kaaks, Rudolf, Khusnutdinova, Elza, Kitahara, Cari, Koutros, Stella, Kristensen, Vessela, Kurian, Allison W, Lacey, James, Lambrechts, Diether, Le Marchand, Loic, Lejbkowicz, Flavio, Lindblom, Annika, Loibl, Sibylle, Lori, Adriana, Lubinski, Jan, Mannermaa, Arto, Manoochehri, Mehdi, Mavroudis, Dimitrios, Menon, Usha, Mulligan, AnnaMarie, Murphy, Rachel, Nevelsteen, Ines, Newman, William G, and Obi, Nadia

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Oncology and Carcinogenesis, Breast Cancer, Prevention, Cancer, Humans, Female, Breast Neoplasms, Genome-Wide Association Study, Jews, Israel, Genetic Predisposition to Disease, Risk Factors, Multifactorial Inheritance, Transcription Factors, Genomics, Polymorphism, Genetic, BCAC Consortium, NBCS Collaborators, CTS Consortium, ABCTB Investigators, Polymorphism, Genetic, Medical and Health Sciences, Genetics & Heredity, Clinical sciences
Abstract

BackgroundPolygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women.MethodsWe generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel.ResultsIn the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28).ConclusionsExtant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.

Published
2023

7. A Likelihood Ratio Approach for Utilizing Case‐Control Data in the Clinical Classification of Rare Sequence Variants: Application to BRCA1 and BRCA2

Author

Zanti, Maria, O′Mahony, Denise G, Parsons, Michael T, Li, Hongyan, Dennis, Joe, Aittomäkkiki, Kristiina, Andrulis, Irene L, Anton-Culver, Hoda, Aronson, Kristan J, Augustinsson, Annelie, Becher, Heiko, Bojesen, Stig E, Bolla, Manjeet K, Brenner, Hermann, Brown, Melissa A, Buys, Saundra S, Canzian, Federico, Caputo, Sandrine M, Castelao, Jose E, Chang-Claude, Jenny, Collaborators, GC-HBOC study, Czene, Kamila, Daly, Mary B, De Nicolo, Arcangela, Devilee, Peter, Dörk, Thilo, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Engel, Christoph, Evans, D Gareth, Fasching, Peter A, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A, Gentry-Maharaj, Aleksandra, Giele, Willemina RR Geurts-, Giles, Graham G, Glendon, Gord, Goldberg, Mark S, Garcia, Encarna B Gómez, Güendert, Melanie, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A, Hall, Per, Hamann, Ute, Harkness, Elaine F, Hogervorst, Frans BL, Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L, Houdayer, Claude, Houlston, Richard S, Howell, Anthony, Investigators, ABCTB, Jakimovska, Milena, Jakubowska, Anna, Jernström, Helena, John, Esther M, Kaaks, Rudolf, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Lacey, James V, Lambrechts, Diether, Léoné, Melanie, Lindblom, Annika, Lubiński, Jan, Lush, Michael, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Martinez, Maria Elena, Menon, Usha, Milne, Roger L, Monteiro, Alvaro N, Murphy, Rachel A, Neuhausen, Susan L, Nevanlinna, Heli, Newman, William G, Offit, Kenneth, Park, Sue K, James, Paul, Peterlongo, Paolo, Peto, Julian, Plaseska-Karanfilska, Dijana, Punie, Kevin, Radice, Paolo, Rashid, Muhammad U, Rennert, Gad, Romero, Atocha, Rosenberg, Efraim H, Saloustros, Emmanouil, Sandler, Dale P, Schmidt, Marjanka K, Schmutzler, Rita K, and Shu, Xiao-Ou

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Genetics, Biotechnology, Genetic Testing, Prevention, Cancer, Human Genome, Women's Health, Breast Cancer, 2.1 Biological and endogenous factors, Good Health and Well Being, Humans, Case-Control Studies, BRCA2 Protein, Genetic Predisposition to Disease, Female, BRCA1 Protein, Breast Neoplasms, Likelihood Functions, Genetic Variation, Penetrance, GC-HBOC study Collaborators, ABCTB Investigators, ACMG/AMP, BRCA, PS4, VUS, case-control, likelihood ratio, variant classification, Clinical Sciences, Genetics & Heredity, Clinical sciences
Abstract

A large number of variants identified through clinical genetic testing in disease susceptibility genes, are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion), can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analyses of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC), and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity - findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in BRCA1, BRCA2 and other high-risk genes with known penetrance.

Published
2023

8. Associations of a Breast Cancer Polygenic Risk Score With Tumor Characteristics and Survival

Author

Lopes Cardozo, Josephine MN, Andrulis, Irene L, Bojesen, Stig E, Dörk, Thilo, Eccles, Diana M, Fasching, Peter A, Hooning, Maartje J, Keeman, Renske, Nevanlinna, Heli, Rutgers, Emiel JT, Easton, Douglas F, Hall, Per, Pharoah, Paul DP, van 't Veer, Laura J, Schmidt, Marjanka K, Ahearn, Thomas U, Anton-Culver, Hoda, Arndt, Volker, Auer, Paul L, Augustinsson, Annelie, Beane Freeman, Laura E, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Bolla, Manjeet K, Bonanni, Bernardo, Boyle, Terry, Brenner, Hermann, Brucker, Sara Y, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Camp, Nicola J, Canzian, Federico, Cardoso, Fatima, Castelao, Jose E, Cessna, Melissa H, Chan, Tsun L, Chang-Claude, Jenny, Chenevix-Trench, Georgia, Choi, Ji-Yeob, Colonna, Sarah V, Copson, Ellen, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Dennis, Joe, Devilee, Peter, Drukker, Caroline A, Dunning, Alison M, Dwek, Miriam, Eliassen, A Heather, Engel, Christoph, Evans, D Gareth, Figueroa, Jonine D, Fletcher, Olivia, Flyger, Henrik, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A, Genkinger, Jeanine, Giles, Graham G, González-Neira, Anna, Guénel, Pascal, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hamann, Ute, Hartman, Mikael, Heemskerk-Gerritsen, Bernadette AM, Hein, Alexander, Ho, Weang-Kee, Hoppe, Reiner, Hopper, John L, Houlston, Richard S, Howell, Anthony, Hunter, David J, Ito, Hidemi, Jakubowska, Anna, Jernström, Helena, John, Esther M, Johnson, Nichola, Jones, Michael E, Joseph, Vijai, Kaaks, Rudolf, Kang, Daehee, Kim, Sung-Won, Kitahara, Cari M, Koppert, Linetta B, Kosma, Veli-Matti, Kraft, Peter, Kristensen, Vessela N, Kubelka-Sabit, Katerina, and Koutros, Stella

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Breast Cancer, Cancer, Good Health and Well Being, Female, Humans, Breast Neoplasms, Risk Factors, Prognosis, Proportional Hazards Models, Breast, Breast Cancer Association Consortium and MINDACT Collaborators, Clinical Sciences, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

PurposeA polygenic risk score (PRS) consisting of 313 common genetic variants (PRS313) is associated with risk of breast cancer and contralateral breast cancer. This study aimed to evaluate the association of the PRS313 with clinicopathologic characteristics of, and survival following, breast cancer.MethodsWomen with invasive breast cancer were included, 98,397 of European ancestry and 12,920 of Asian ancestry, from the Breast Cancer Association Consortium (BCAC), and 683 women from the European MINDACT trial. Associations between PRS313 and clinicopathologic characteristics, including the 70-gene signature for MINDACT, were evaluated using logistic regression analyses. Associations of PRS313 (continuous, per standard deviation) with overall survival (OS) and breast cancer-specific survival (BCSS) were evaluated with Cox regression, adjusted for clinicopathologic characteristics and treatment.ResultsThe PRS313 was associated with more favorable tumor characteristics. In BCAC, increasing PRS313 was associated with lower grade, hormone receptor-positive status, and smaller tumor size. In MINDACT, PRS313 was associated with a low risk 70-gene signature. In European women from BCAC, higher PRS313 was associated with better OS and BCSS: hazard ratio (HR) 0.96 (95% CI, 0.94 to 0.97) and 0.96 (95% CI, 0.94 to 0.98), but the association disappeared after adjustment for clinicopathologic characteristics (and treatment): OS HR, 1.01 (95% CI, 0.98 to 1.05) and BCSS HR, 1.02 (95% CI, 0.98 to 1.07). The results in MINDACT and Asian women from BCAC were consistent.ConclusionAn increased PRS313 is associated with favorable tumor characteristics, but is not independently associated with prognosis. Thus, PRS313 has no role in the clinical management of primary breast cancer at the time of diagnosis. Nevertheless, breast cancer mortality rates will be higher for women with higher PRS313 as increasing PRS313 is associated with an increased risk of disease. This information is crucial for modeling effective stratified screening programs.

Published
2023

10. Publisher Correction: Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Author

Kentistou, Katherine A., Kaisinger, Lena R., Stankovic, Stasa, Vaudel, Marc, Mendes de Oliveira, Edson, Messina, Andrea, Walters, Robin G., Liu, Xiaoxi, Busch, Alexander S., Helgason, Hannes, Thompson, Deborah J., Santoni, Federico, Petricek, Konstantin M., Zouaghi, Yassine, Huang-Doran, Isabel, Gudbjartsson, Daniel F., Bratland, Eirik, Lin, Kuang, Gardner, Eugene J., Zhao, Yajie, Jia, Raina Y., Terao, Chikashi, Riggan, Marjorie J., Bolla, Manjeet K., Yazdanpanah, Mojgan, Yazdanpanah, Nahid, Bradfield, Jonathan P., Broer, Linda, Campbell, Archie, Chasman, Daniel I., Cousminer, Diana L., Franceschini, Nora, Franke, Lude H., Girotto, Giorgia, He, Chunyan, Järvelin, Marjo-Riitta, Joshi, Peter K., Kamatani, Yoichiro, Karlsson, Robert, Luan, Jian’an, Lunetta, Kathryn L., Mägi, Reedik, Mangino, Massimo, Medland, Sarah E., Meisinger, Christa, Noordam, Raymond, Nutile, Teresa, Concas, Maria Pina, Polašek, Ozren, Porcu, Eleonora, Ring, Susan M., Sala, Cinzia, Smith, Albert V., Tanaka, Toshiko, van der Most, Peter J., Vitart, Veronique, Wang, Carol A., Willemsen, Gonneke, Zygmunt, Marek, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Antoniou, Antonis C., Auer, Paul L., Barnes, Catriona L. K., Beckmann, Matthias W., Berrington de Gonzalez, Amy, Bogdanova, Natalia V., Bojesen, Stig E., Brenner, Hermann, Buring, Julie E., Canzian, Federico, Chang-Claude, Jenny, Couch, Fergus J., Cox, Angela, Crisponi, Laura, Czene, Kamila, Daly, Mary B., Demerath, Ellen W., Dennis, Joe, Devilee, Peter, De Vivo, Immaculata, Dörk, Thilo, Dunning, Alison M., Dwek, Miriam, Eriksson, Johan G., Fasching, Peter A., Fernandez-Rhodes, Lindsay, Ferreli, Liana, Fletcher, Olivia, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A., González-Neira, Anna, Grallert, Harald, Guénel, Pascal, Haiman, Christopher A., Hall, Per, Hamann, Ute, Hakonarson, Hakon, Hart, Roger J., Hickey, Martha, Hooning, Maartje J., Hoppe, Reiner, Hopper, John L., Hottenga, Jouke-Jan, Hu, Frank B., Huebner, Hanna, Hunter, David J., Jernström, Helena, John, Esther M., Karasik, David, Khusnutdinova, Elza K., Kristensen, Vessela N., Lacey, James V., Lambrechts, Diether, Launer, Lenore J., Lind, Penelope A., Lindblom, Annika, Magnusson, Patrik K. E., Mannermaa, Arto, McCarthy, Mark I., Meitinger, Thomas, Menni, Cristina, Michailidou, Kyriaki, Millwood, Iona Y., Milne, Roger L., Montgomery, Grant W., Nevanlinna, Heli, Nolte, Ilja M., Nyholt, Dale R., Obi, Nadia, O’Brien, Katie M., Offit, Kenneth, Oldehinkel, Albertine J., Ostrowski, Sisse R., Palotie, Aarno, Pedersen, Ole B., Peters, Annette, Pianigiani, Giulia, Plaseska-Karanfilska, Dijana, Pouta, Anneli, Pozarickij, Alfred, Radice, Paolo, Rennert, Gad, Rosendaal, Frits R., Ruggiero, Daniela, Saloustros, Emmanouil, Sandler, Dale P., Schipf, Sabine, Schmidt, Carsten O., Schmidt, Marjanka K., Small, Kerrin, Spedicati, Beatrice, Stampfer, Meir, Stone, Jennifer, Tamimi, Rulla M., Teras, Lauren R., Tikkanen, Emmi, Turman, Constance, Vachon, Celine M., Wang, Qin, Winqvist, Robert, Wolk, Alicja, Zemel, Babette S., Zheng, Wei, van Dijk, Ko W., Alizadeh, Behrooz Z., Bandinelli, Stefania, Boerwinkle, Eric, Boomsma, Dorret I., Ciullo, Marina, Chenevix-Trench, Georgia, Cucca, Francesco, Esko, Tõnu, Gieger, Christian, Grant, Struan F. A., Gudnason, Vilmundur, Hayward, Caroline, Kolčić, Ivana, Kraft, Peter, Lawlor, Deborah A., Martin, Nicholas G., Nøhr, Ellen A., Pedersen, Nancy L., Pennell, Craig E., Ridker, Paul M., Robino, Antonietta, Snieder, Harold, Sovio, Ulla, Spector, Tim D., Stöckl, Doris, Sudlow, Cathie, Timpson, Nic J., Toniolo, Daniela, Uitterlinden, André, Ulivi, Sheila, Völzke, Henry, Wareham, Nicholas J., Widen, Elisabeth, Wilson, James F., Pharoah, Paul D. P., Li, Liming, Easton, Douglas F., Njølstad, Pål R., Sulem, Patrick, Murabito, Joanne M., Murray, Anna, Manousaki, Despoina, Juul, Anders, Erikstrup, Christian, Stefansson, Kari, Horikoshi, Momoko, Chen, Zhengming, Farooqi, I. Sadaf, Pitteloud, Nelly, Johansson, Stefan, Day, Felix R., Perry, John R. B., and Ong, Ken K.

Published
2024
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11. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Author

Middha, Pooja, Wang, Xiaoliang, Behrens, Sabine, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Baert, Thaïs, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Benitez, Javier, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brooks-Wilson, Angela, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dossus, Laure, Dugué, Pierre-Antoine, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine D, Fletcher, Olivia, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Giles, Graham G, González-Neira, Anna, Grassmann, Felix, Grundy, Anne, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E, Harkness, Elaine F, Holleczek, Bernd, Hoppe, Reiner, Hopper, John L, Houlston, Richard S, Howell, Anthony, Hunter, David J, Ingvar, Christian, Isaksson, Karolin, Jernström, Helena, John, Esther M, Jones, Michael E, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Larson, Nicole L, Larsson, Susanna, Le Marchand, Loic, Lejbkowicz, Flavio, Li, Shuai, Linet, Martha, Lissowska, Jolanta, Martinez, Maria Elena, Maurer, Tabea, Mulligan, Anna Marie, Mulot, Claire, Murphy, Rachel A, Newman, William G, Nielsen, Sune F, Nordestgaard, Børge G, Norman, Aaron, O’Brien, Katie M, Olson, Janet E, Patel, Alpa V, Prentice, Ross, Rees-Punia, Erika, Rennert, Gad, Rhenius, Valerie, Ruddy, Kathryn J, and Sandler, Dale P

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer Genomics, Human Genome, Estrogen, Cancer, Women's Health, Genetics, Prevention, Aging, Breast Cancer, 2.1 Biological and endogenous factors, Adult, Female, Humans, Gene-Environment Interaction, Genetic Predisposition to Disease, Breast Neoplasms, Bayes Theorem, Genome-Wide Association Study, Risk Factors, Polymorphism, Single Nucleotide, Case-Control Studies, Breast cancer, Gene-environment interactions, Genetic epidemiology, European ancestry, CTS Consortium, ABCTB Investigators, kConFab Investigators, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundGenome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.MethodsAnalyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.ResultsAssuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability

Published
2023

12. Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

Author

Mueller, Stefanie H, Lai, Alvina G, Valkovskaya, Maria, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Lush, Michael, Abu-Ful, Zomoruda, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Baert, Thais, Freeman, Laura E Beane, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bonanni, Bernardo, Brenner, Hermann, Brucker, Sara Y, Buys, Saundra S, Castelao, Jose E, Chan, Tsun L, Chang-Claude, Jenny, Chanock, Stephen J, Choi, Ji-Yeob, Chung, Wendy K, Colonna, Sarah V, Cornelissen, Sten, Couch, Fergus J, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dossus, Laure, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eliassen, A Heather, Engel, Christoph, Evans, D Gareth, Fasching, Peter A, Fletcher, Olivia, Flyger, Henrik, Gago-Dominguez, Manuela, Gao, Yu-Tang, García-Closas, Montserrat, García-Sáenz, José A, Genkinger, Jeanine, Gentry-Maharaj, Aleksandra, Grassmann, Felix, Guénel, Pascal, Gündert, Melanie, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Harkness, Elaine F, Harrington, Patricia A, Hartikainen, Jaana M, Hartman, Mikael, Hein, Alexander, Ho, Weang-Kee, Hooning, Maartje J, Hoppe, Reiner, Hopper, John L, Houlston, Richard S, Howell, Anthony, Hunter, David J, Huo, Dezheng, Ito, Hidemi, Iwasaki, Motoki, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Kang, Daehee, Khusnutdinova, Elza K, Kim, Sung-Won, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kubelka-Sabit, Katerina, Kurian, Allison W, Kwong, Ava, Lacey, James V, Lambrechts, Diether, and Le Marchand, Loic

Subjects
Breast Cancer, Genetics, Clinical Research, Cancer, Aetiology, 2.1 Biological and endogenous factors, Humans, Female, Breast Neoplasms, Genetic Predisposition to Disease, Black People, Genetic Testing, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Formins, Breast cancer susceptibility, Diverse ancestry, Rare variants, Gene regulation, Genome-wide association study, NBCS Collaborators, CTS Consortium, ABCTB Investigators, Clinical Sciences
Abstract

BackgroundLow-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.MethodsWe evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.ResultsIn European ancestry samples, 14 genes were significantly associated (q

Published
2023

13. Distinct Reproductive Risk Profiles for Intrinsic-Like Breast Cancer Subtypes: Pooled Analysis of Population-Based Studies

Author

Jung, Audrey Y, Ahearn, Thomas U, Behrens, Sabine, Middha, Pooja, Bolla, Manjeet K, Wang, Qin, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Freeman, Laura E Beane, Becher, Heiko, Brenner, Hermann, Canzian, Federico, Carey, Lisa A, Consortium, CTS, Czene, Kamila, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Figueroa, Jonine D, Fritschi, Lin, Gabrielson, Marike, Giles, Graham G, Guénel, Pascal, Hadjisavvas, Andreas, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hoppe, Reiner, Hopper, John L, Howell, Anthony, Hunter, David J, Hüsing, Anika, Kaaks, Rudolf, Kosma, Veli-Matti, Koutros, Stella, Kraft, Peter, Lacey, James V, Le Marchand, Loic, Lissowska, Jolanta, Loizidou, Maria A, Mannermaa, Arto, Maurer, Tabea, Murphy, Rachel A, Olshan, Andrew F, Olsson, Håkan, Patel, Alpa V, Perou, Charles M, Rennert, Gad, Shibli, Rana, Shu, Xiao-Ou, Southey, Melissa C, Stone, Jennifer, Tamimi, Rulla M, Teras, Lauren R, Troester, Melissa A, Truong, Thérèse, Vachon, Celine M, Wang, Sophia S, Wolk, Alicja, Wu, Anna H, Yang, Xiaohong R, Zheng, Wei, Dunning, Alison M, Pharoah, Paul DP, Easton, Douglas F, Milne, Roger L, Chatterjee, Nilanjan, Schmidt, Marjanka K, García-Closas, Montserrat, and Chang-Claude, Jenny

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer, Breast Cancer, Aging, Reproductive health and childbirth, Female, Humans, Breast Neoplasms, Receptor, ErbB-2, Receptors, Progesterone, Receptors, Estrogen, Triple Negative Breast Neoplasms, Case-Control Studies, Risk Factors, Biomarkers, Tumor, CTS Consortium, Receptor, erbB-2, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundReproductive factors have been shown to be differentially associated with risk of estrogen receptor (ER)-positive and ER-negative breast cancer. However, their associations with intrinsic-like subtypes are less clear.MethodsAnalyses included up to 23 353 cases and 71 072 controls pooled from 31 population-based case-control or cohort studies in the Breast Cancer Association Consortium across 16 countries on 4 continents. Polytomous logistic regression was used to estimate the association between reproductive factors and risk of breast cancer by intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2-like, HER2-enriched-like, and triple-negative breast cancer) and by invasiveness. All statistical tests were 2-sided.ResultsCompared with nulliparous women, parous women had a lower risk of luminal A-like, luminal B-like, luminal B-HER2-like, and HER2-enriched-like disease. This association was apparent only after approximately 10 years since last birth and became stronger with increasing time (odds ratio [OR] = 0.59, 95% confidence interval [CI] = 0.49 to 0.71; and OR = 0.36, 95% CI = 0.28 to 0.46 for multiparous women with luminal A-like tumors 20 to less than 25 years after last birth and 45 to less than 50 years after last birth, respectively). In contrast, parous women had a higher risk of triple-negative breast cancer right after their last birth (for multiparous women: OR = 3.12, 95% CI = 2.02 to 4.83) that was attenuated with time but persisted for decades (OR = 1.03, 95% CI = 0.79 to 1.34, for multiparous women 25 to less than 30 years after last birth). Older age at first birth (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) and breastfeeding (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) were associated with lower risk of triple-negative breast cancer but not with other disease subtypes. Younger age at menarche was associated with higher risk of all subtypes; older age at menopause was associated with higher risk of luminal A-like but not triple-negative breast cancer. Associations for in situ tumors were similar to luminal A-like.ConclusionsThis large and comprehensive study demonstrates a distinct reproductive risk factor profile for triple-negative breast cancer compared with other subtypes, with implications for the understanding of disease etiology and risk prediction.

Published
2022

14. Physical activity, sedentary time and breast cancer risk: a Mendelian randomisation study

Author

Dixon-Suen, Suzanne C, Lewis, Sarah J, Martin, Richard M, English, Dallas R, Boyle, Terry, Giles, Graham G, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Lush, Michael, Investigators, ABCTB, Ahearn, Thomas U, Ambrosone, Christine B, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Auvinen, Päivi, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bermisheva, Marina, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bonanni, Bernardo, Brenner, Hermann, Brüning, Thomas, Buys, Saundra S, Camp, Nicola J, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Cessna, Melissa H, Chang-Claude, Jenny, Chanock, Stephen J, Clarke, Christine L, Conroy, Don M, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dwek, Miriam, Eccles, Diana M, Eliassen, A Heather, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Fletcher, Olivia, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A, Goldberg, Mark S, Guénel, Pascal, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Häberle, Lothar, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hart, Steven N, Harvie, Michelle, Hillemanns, Peter, Hollestelle, Antoinette, Hooning, Maartje J, Hoppe, Reiner, Hopper, John, Howell, Anthony, Hunter, David J, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jung, Audrey, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kubelka-Sabit, Katerina, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Le Marchand, Loic, Lindblom, Annika, Loibl, Sibylle, Lubiński, Jan, Mannermaa, Arto, and Manoochehri, Mehdi

Subjects
Aging, Genetics, Breast Cancer, Clinical Research, Cancer, Prevention, Female, Humans, Breast Neoplasms, Exercise, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, Risk Factors, Sedentary Behavior, Breast Cancer Association Consortium, Breast, Physical activity, Sedentary Behaviour, Engineering, Medical and Health Sciences, Education, Sport Sciences
Abstract

ObjectivesPhysical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics.MethodsWe performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity.ResultsGreater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger).ConclusionOur study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.

Published
2022

15. Polymorphisms in genes of melatonin biosynthesis and signaling support the light-at-night hypothesis for breast cancer

Author

Wichert, Katharina, Hoppe, Reiner, Ickstadt, Katja, Behrens, Thomas, Winter, Stefan, Herold, Robert, Terschüren, Claudia, Lo, Wing-Yee, Guénel, Pascal, Truong, Thérèse, Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Lush, Michael, Andrulis, Irene L., Brenner, Hermann, Chang-Claude, Jenny, Cox, Angela, Cross, Simon S., Czene, Kamila, Eriksson, Mikael, Figueroa, Jonine D., García-Closas, Montserrat, Goldberg, Mark S., Hamann, Ute, He, Wei, Holleczek, Bernd, Hopper, John L., Jakubowska, Anna, Ko, Yon-Dschun, Lubiński, Jan, Mulligan, Anna Marie, Obi, Nadia, Rhenius, Valerie, Shah, Mitul, Shu, Xiao-Ou, Simard, Jacques, Southey, Melissa C., Zheng, Wei, Dunning, Alison M., Pharoah, Paul D. P., Hall, Per, Easton, Douglas F., Brüning, Thomas, Brauch, Hiltrud, Harth, Volker, and Rabstein, Sylvia

Published
2023
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17. Incorporating progesterone receptor expression into the PREDICT breast prognostic model

Author

Grootes, Isabelle, Keeman, Renske, Blows, Fiona M, Milne, Roger L, Giles, Graham G, Swerdlow, Anthony J, Fasching, Peter A, Abubakar, Mustapha, Andrulis, Irene L, Anton-Culver, Hoda, Beckmann, Matthias W, Blomqvist, Carl, Bojesen, Stig E, Bolla, Manjeet K, Bonanni, Bernardo, Briceno, Ignacio, Burwinkel, Barbara, Camp, Nicola J, Castelao, Jose E, Choi, Ji-Yeob, Clarke, Christine L, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Devilee, Peter, Dörk, Thilo, Dunning, Alison M, Dwek, Miriam, Easton, Douglas F, Eccles, Diana M, Eriksson, Mikael, Ernst, Kristina, Evans, D Gareth, Figueroa, Jonine D, Fink, Visnja, Floris, Giuseppe, Fox, Stephen, Gabrielson, Marike, Gago-Dominguez, Manuela, García-Sáenz, José A, González-Neira, Anna, Haeberle, Lothar, Haiman, Christopher A, Hall, Per, Hamann, Ute, Harkness, Elaine F, Hartman, Mikael, Hein, Alexander, Hooning, Maartje J, Hou, Ming-Feng, Howell, Sacha J, Investigators, ABCTB, Investigators, kConFab, Ito, Hidemi, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jung, Audrey, Kang, Daehee, Kristensen, Vessela N, Kwong, Ava, Lambrechts, Diether, Li, Jingmei, Lubiński, Jan, Manoochehri, Mehdi, Margolin, Sara, Matsuo, Keitaro, Taib, Nur Aishah Mohd, Mulligan, Anna Marie, Nevanlinna, Heli, Newman, William G, Offit, Kenneth, Osorio, Ana, Park, Sue K, Park-Simon, Tjoung-Won, Patel, Alpa V, Presneau, Nadege, Pylkäs, Katri, Rack, Brigitte, Radice, Paolo, Rennert, Gad, Romero, Atocha, Saloustros, Emmanouil, Sawyer, Elinor J, Schneeweiss, Andreas, Schochter, Fabienne, Schoemaker, Minouk J, Shen, Chen-Yang, Shibli, Rana, Sinn, Peter, Tapper, William J, Tawfiq, Essa, Teo, Soo Hwang, Teras, Lauren R, Torres, Diana, Vachon, Celine M, van Deurzen, Carolien HM, Wendt, Camilla, and Williams, Justin A

Subjects
Cancer, Breast Cancer, Breast Neoplasms, Female, Humans, Progesterone, Prognosis, Receptor, ErbB-2, Receptors, Progesterone, PREDICT Breast, breast cancer, Progesterone receptor, ABCTB Investigators, kConFab Investigators, Receptor, erbB-2, Oncology and Carcinogenesis, Public Health and Health Services, Oncology & Carcinogenesis
Abstract

BackgroundPredict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).MethodThe prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.ResultsHaving a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.ConclusionThe inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.

Published
2022

21. PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Author

Giardiello, Daniele, Hooning, Maartje J, Hauptmann, Michael, Keeman, Renske, Heemskerk-Gerritsen, BAM, Becher, Heiko, Blomqvist, Carl, Bojesen, Stig E, Bolla, Manjeet K, Camp, Nicola J, Czene, Kamila, Devilee, Peter, Eccles, Diana M, Fasching, Peter A, Figueroa, Jonine D, Flyger, Henrik, García-Closas, Montserrat, Haiman, Christopher A, Hamann, Ute, Hopper, John L, Jakubowska, Anna, Leeuwen, Floor E, Lindblom, Annika, Lubiński, Jan, Margolin, Sara, Martinez, Maria Elena, Nevanlinna, Heli, Nevelsteen, Ines, Pelders, Saskia, Pharoah, Paul DP, Siesling, Sabine, Southey, Melissa C, van der Hout, Annemieke H, van Hest, Liselotte P, Chang-Claude, Jenny, Hall, Per, Easton, Douglas F, Steyerberg, Ewout W, and Schmidt, Marjanka K

Subjects
Genetics, Breast Cancer, Prevention, Cancer, Humans, Female, Breast Neoplasms, Mastectomy, Prophylactic Mastectomy, Germ-Line Mutation, Risk Factors, Contralateral breast cancer, Risk prediction, Contralateral preventive mastectomy, Clinical decision-making, Breast cancer genetic predisposition, Breast Cancer Association Consortium, BCAC, Prediction performance, BRCA1/2 germline mutation, Polygenic risk score, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

BackgroundPrediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors.MethodsWe included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models.ResultsThe discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56-0.74) versus 0.63 (95%PI 0.54-0.71). PredictCBC-2.0 was well calibrated with an observed/expected ratio at 10 years of 0.92 (95%PI 0.34-2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.ConclusionsAdditional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.

Published
2022

22. Common variants in breast cancer risk loci predispose to distinct tumor subtypes

Author

Ahearn, Thomas U, Zhang, Haoyu, Michailidou, Kyriaki, Milne, Roger L, Bolla, Manjeet K, Dennis, Joe, Dunning, Alison M, Lush, Michael, Wang, Qin, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Baten, Adinda, Becher, Heiko, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Bojesen, Stig E, Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Brenner, Hermann, Brooks-Wilson, Angela, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Canzian, Federico, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Chenevix-Trench, Georgia, Clarke, Christine L, Collée, J Margriet, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dwek, Miriam, Eccles, Diana M, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Floris, Giuseppe, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Goldberg, Mark S, González-Neira, Anna, Alnæs, Grethe I Grenaker, Grip, Mervi, Guénel, Pascal, Haiman, Christopher A, Hall, Per, Hamann, Ute, Harkness, Elaine F, Heemskerk-Gerritsen, Bernadette AM, Holleczek, Bernd, Hollestelle, Antoinette, Hooning, Maartje J, Hoover, Robert N, Hopper, John L, Howell, Anthony, Jakimovska, Milena, Jakubowska, Anna, John, Esther M, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Kauppila, Saila, Keeman, Renske, Khusnutdinova, Elza, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kristensen, Vessela N, Krüger, Ute, Kubelka-Sabit, Katerina, Kurian, Allison W, Kyriacou, Kyriacos, Lambrechts, Diether, Lee, Derrick G, Lindblom, Annika, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, Lo, Wing-Yee, MacInnis, Robert J, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Martinez, Maria Elena, and McLean, Catriona

Subjects
Human Genome, Cancer, Genetics, Clinical Research, Breast Cancer, 2.1 Biological and endogenous factors, Aetiology, Biomarkers, Tumor, Breast Neoplasms, Female, Genome-Wide Association Study, Humans, Receptor, ErbB-2, Receptors, Estrogen, Receptors, Progesterone, Risk, Breast cancer, Etiologic heterogeneity, Genetic predisposition, Common breast cancer susceptibility variants, NBCS Collaborators, ABCTB Investigators, kConFab/AOCS Investigators, Receptor, erbB-2, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate

Published
2022

23. Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Author

Wang, Xiaoliang, Kapoor, Pooja Middha, Auer, Paul L, Dennis, Joe, Dunning, Alison M, Wang, Qin, Lush, Michael, Michailidou, Kyriaki, Bolla, Manjeet K, Aronson, Kristan J, Murphy, Rachel A, Brooks-Wilson, Angela, Lee, Derrick G, Cordina-Duverger, Emilie, Guénel, Pascal, Truong, Thérèse, Mulot, Claire, Teras, Lauren R, Patel, Alpa V, Dossus, Laure, Kaaks, Rudolf, Hoppe, Reiner, Lo, Wing-Yee, Brüning, Thomas, Hamann, Ute, Czene, Kamila, Gabrielson, Marike, Hall, Per, Eriksson, Mikael, Jung, Audrey, Becher, Heiko, Couch, Fergus J, Larson, Nicole L, Olson, Janet E, Ruddy, Kathryn J, Giles, Graham G, MacInnis, Robert J, Southey, Melissa C, Le Marchand, Loic, Wilkens, Lynne R, Haiman, Christopher A, Olsson, Håkan, Augustinsson, Annelie, Krüger, Ute, Wagner, Philippe, Scott, Christopher, Winham, Stacey J, Vachon, Celine M, Perou, Charles M, Olshan, Andrew F, Troester, Melissa A, Hunter, David J, Eliassen, Heather A, Tamimi, Rulla M, Brantley, Kristen, Andrulis, Irene L, Figueroa, Jonine, Chanock, Stephen J, Ahearn, Thomas U, García-Closas, Montserrat, Evans, Gareth D, Newman, William G, van Veen, Elke M, Howell, Anthony, Wolk, Alicja, Håkansson, Niclas, Anton-Culver, Hoda, Ziogas, Argyrios, Jones, Michael E, Orr, Nick, Schoemaker, Minouk J, Swerdlow, Anthony J, Kitahara, Cari M, Linet, Martha, Prentice, Ross L, Easton, Douglas F, Milne, Roger L, Kraft, Peter, Chang-Claude, Jenny, and Lindström, Sara

Subjects
Genetics, Cancer, Aging, Human Genome, Breast Cancer, Prevention, Estrogen, 2.1 Biological and endogenous factors, Aetiology, Breast, Breast Neoplasms, Estrogen Replacement Therapy, Female, Hormone Replacement Therapy, Humans, Male, Menopause, Risk Factors
Abstract

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values

Published
2022

24. Rare germline copy number variants (CNVs) and breast cancer risk

Author

Dennis, Joe, Tyrer, Jonathan P, Walker, Logan C, Michailidou, Kyriaki, Dorling, Leila, Bolla, Manjeet K, Wang, Qin, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Freeman, Laura E Beane, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bogdanova, Natalia V, Bojesen, Stig E, Brenner, Hermann, Castelao, Jose E, Chang-Claude, Jenny, Chenevix-Trench, Georgia, Clarke, Christine L, Collée, J Margriet, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Devilee, Peter, Dörk, Thilo, Dossus, Laure, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Fletcher, Olivia, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, García-Closas, Montserrat, Giles, Graham G, González-Neira, Anna, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A, Hall, Per, Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L, Howell, Anthony, Jager, Agnes, Jakubowska, Anna, John, Esther M, Johnson, Nichola, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Keeman, Renske, Khusnutdinova, Elza, Kitahara, Cari M, Ko, Yon-Dschun, Kosma, Veli-Matti, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kubelka-Sabit, Katerina, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Larson, Nicole L, Linet, Martha, Ogrodniczak, Alicja, Mannermaa, Arto, Manoukian, Siranoush, Margolin, Sara, Mavroudis, Dimitrios, Milne, Roger L, Muranen, Taru A, Murphy, Rachel A, Nevanlinna, Heli, Olson, Janet E, Olsson, Håkan, Park-Simon, Tjoung-Won, Perou, Charles M, Peterlongo, Paolo, Plaseska-Karanfilska, Dijana, Pylkäs, Katri, Rennert, Gad, Saloustros, Emmanouil, Sandler, Dale P, Sawyer, Elinor J, Schmidt, Marjanka K, Schmutzler, Rita K, Shibli, Rana, Smeets, Ann, and Soucy, Penny

Subjects
Human Genome, Breast Cancer, Genetics, Clinical Research, Cancer, Prevention, 2.1 Biological and endogenous factors, Aetiology, Breast Neoplasms, Case-Control Studies, DNA Copy Number Variations, Female, Genome, Human, Genome-Wide Association Study, Germ Cells, Humans, Risk Factors, NBCS Collaborators, CTS Consortium, ABCTB Investigators, kConFab/AOCS Investigators
Abstract

Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value

Published
2022

25. Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment

Author

Morra, Anna, Escala-Garcia, Maria, Beesley, Jonathan, Keeman, Renske, Canisius, Sander, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Auer, Paul L, Augustinsson, Annelie, Beane Freeman, Laura E, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bojesen, Stig E, Bolla, Manjeet K, Brenner, Hermann, Brüning, Thomas, Buys, Saundra S, Caan, Bette, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Cheng, Ting-Yuan David, Clarke, Christine L, Colonna, Sarah V, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Dennis, Joe, Dörk, Thilo, Dossus, Laure, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Flyger, Henrik, Fritschi, Lin, Gago-Dominguez, Manuela, García-Sáenz, José A, Giles, Graham G, Grip, Mervi, Guénel, Pascal, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hart, Steven N, Hartikainen, Jaana M, Hartmann, Arndt, He, Wei, Hooning, Maartje J, Hoppe, Reiner, Hopper, John L, Howell, Anthony, Hunter, David J, Jager, Agnes, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jung, Audrey Y, Kaaks, Rudolf, Keupers, Machteld, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Le Marchand, Loic, Lindblom, Annika, Linet, Martha, Luben, Robert N, Lubiński, Jan, Lush, Michael, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Martens, John WM, Martinez, Maria Elena, Mavroudis, Dimitrios, Michailidou, Kyriaki, Milne, Roger L, Mulligan, Anna Marie, Muranen, Taru A, Nevanlinna, Heli, Newman, William G, and Nielsen, Sune F

Subjects
Clinical Research, Cancer, Breast Cancer, Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Breast Neoplasms, Female, Genome-Wide Association Study, Germ-Line Mutation, Humans, Polymorphism, Single Nucleotide, Prognosis, Survival Analysis, Common germline genetic variants, Breast cancer-specific survival, Patient subgroups, Tumor biology, Systemic treatment, NBCS Collaborators, ABCTB Investigators, kConFab Investigators, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

BackgroundGiven the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients.MethodsWe performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP

Published
2021

26. Mendelian randomisation study of smoking exposure in relation to breast cancer risk

Author

Park, Hanla A, Neumeyer, Sonja, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Baten, Adinda, Beane Freeman, Laura E, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bogdanova, Natalia V, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brucker, Sara Y, Burwinkel, Barbara, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Clarke, Christine L, Conroy, Don M, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, dos-Santos-Silva, Isabel, Dwek, Miriam, Eccles, Diana M, Eliassen, A Heather, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Flyger, Henrik, Fritschi, Lin, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Glendon, Gord, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Grip, Mervi, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Han, Sileny, Harkness, Elaine F, Hart, Steven N, He, Wei, Heemskerk-Gerritsen, Bernadette AM, Hopper, John L, Hunter, David J, Jager, Agnes, Jakubowska, Anna, John, Esther M, Jung, Audrey, Kaaks, Rudolf, Kapoor, Pooja Middha, Keeman, Renske, Khusnutdinova, Elza, Kitahara, Cari M, Koppert, Linetta B, Koutros, Stella, Kristensen, Vessela N, Kurian, Allison W, Lacey, James, Lambrechts, Diether, Le Marchand, Loic, Lo, Wing-Yee, Lubiński, Jan, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Martinez, Maria Elena, Mavroudis, Dimitrios, Meindl, Alfons, Menon, Usha, Milne, Roger L, Muranen, Taru A, and Nevanlinna, Heli

Subjects
Genetics, Cancer, Substance Misuse, Clinical Research, Human Genome, Prevention, Drug Abuse (NIDA only), Breast Cancer, Tobacco, Tobacco Smoke and Health, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Breast Neoplasms, Case-Control Studies, Cigarette Smoking, Female, Genetic Pleiotropy, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotyping Techniques, Humans, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, NBCS Collaborators, ABCTB Investigators, kConFab Investigators, Oncology and Carcinogenesis, Public Health and Health Services, Oncology & Carcinogenesis
Abstract

BackgroundDespite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk.MethodsWe applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy.ResultsGenetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10-2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect.ConclusionOur MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.

Published
2021

27. Germline variants and breast cancer survival in patients with distant metastases at primary breast cancer diagnosis.

Author

Escala-Garcia, Maria, Canisius, Sander, Keeman, Renske, Beesley, Jonathan, Anton-Culver, Hoda, Arndt, Volker, Augustinsson, Annelie, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bermisheva, Marina, Bojesen, Stig E, Bolla, Manjeet K, Brenner, Hermann, Canzian, Federico, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Couch, Fergus J, Czene, Kamila, Daly, Mary B, Dennis, Joe, Devilee, Peter, Dörk, Thilo, Dunning, Alison M, Easton, Douglas F, Ekici, Arif B, Eliassen, A Heather, Fasching, Peter A, Flyger, Henrik, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A, Geisler, Jürgen, Giles, Graham G, Grip, Mervi, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hartikainen, Jaana M, Heemskerk-Gerritsen, Bernadette AM, Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L, Hunter, David J, Jacot, William, Jakubowska, Anna, John, Esther M, Jung, Audrey Y, Kaaks, Rudolf, Khusnutdinova, Elza, Koppert, Linetta B, Kraft, Peter, Kristensen, Vessela N, Kurian, Allison W, Lambrechts, Diether, Le Marchand, Loic, Lindblom, Annika, Luben, Robert N, Lubiński, Jan, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Mavroudis, Dimitrios, Muranen, Taru A, Nevanlinna, Heli, Olshan, Andrew F, Olsson, Håkan, Park-Simon, Tjoung-Won, Patel, Alpa V, Peterlongo, Paolo, Pharoah, Paul DP, Punie, Kevin, Radice, Paolo, Rennert, Gad, Rennert, Hedy S, Romero, Atocha, Roylance, Rebecca, Rüdiger, Thomas, Ruebner, Matthias, Saloustros, Emmanouil, Sawyer, Elinor J, Schmutzler, Rita K, Schoemaker, Minouk J, Scott, Christopher, Southey, Melissa C, Surowy, Harald, Swerdlow, Anthony J, Tamimi, Rulla M, Teras, Lauren R, Thomas, Emilie, Tomlinson, Ian, Troester, Melissa A, Vachon, Celine M, Wang, Qin, Winqvist, Robert, and Wolk, Alicja

Subjects
kConFab/AOCS Investigators, Cancer, Genetics, Breast Cancer, Prevention, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies
Abstract

Breast cancer metastasis accounts for most of the deaths from breast cancer. Identification of germline variants associated with survival in aggressive types of breast cancer may inform understanding of breast cancer progression and assist treatment. In this analysis, we studied the associations between germline variants and breast cancer survival for patients with distant metastases at primary breast cancer diagnosis. We used data from the Breast Cancer Association Consortium (BCAC) including 1062 women of European ancestry with metastatic breast cancer, 606 of whom died of breast cancer. We identified two germline variants on chromosome 1, rs138569520 and rs146023652, significantly associated with breast cancer-specific survival (P = 3.19 × 10-8 and 4.42 × 10-8). In silico analysis suggested a potential regulatory effect of the variants on the nearby target genes SDE2 and H3F3A. However, the variants showed no evidence of association in a smaller replication dataset. The validation dataset was obtained from the SNPs to Risk of Metastasis (StoRM) study and included 293 patients with metastatic primary breast cancer at diagnosis. Ultimately, larger replication studies are needed to confirm the identified associations.

Published
2021

28. FANCM missense variants and breast cancer risk: a case-control association study of 75,156 European women

Author

Figlioli, Gisella, Billaud, Amandine, Ahearn, Thomas U., Antonenkova, Natalia N., Becher, Heiko, Beckmann, Matthias W., Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blok, Marinus J., Bogdanova, Natalia V., Bonanni, Bernardo, Burwinkel, Barbara, Camp, Nicola J., Campbell, Archie, Castelao, Jose E., Cessna, Melissa H., Chanock, Stephen J., Czene, Kamila, Devilee, Peter, Dörk, Thilo, Engel, Christoph, Eriksson, Mikael, Fasching, Peter A., Figueroa, Jonine D., Gabrielson, Marike, Gago-Dominguez, Manuela, García-Closas, Montserrat, González-Neira, Anna, Grassmann, Felix, Guénel, Pascal, Gündert, Melanie, Hadjisavvas, Andreas, Hahnen, Eric, Hall, Per, Hamann, Ute, Harrington, Patricia A., He, Wei, Hillemanns, Peter, Hollestelle, Antoinette, Hooning, Maartje J., Hoppe, Reiner, Howell, Anthony, Humphreys, Keith, Jager, Agnes, Jakubowska, Anna, Khusnutdinova, Elza K., Ko, Yon-Dschun, Kristensen, Vessela N., Lindblom, Annika, Lissowska, Jolanta, Lubiński, Jan, Mannermaa, Arto, Manoukian, Siranoush, Margolin, Sara, Mavroudis, Dimitrios, Newman, William G., Obi, Nadia, Panayiotidis, Mihalis I., Rashid, Muhammad U., Rhenius, Valerie, Rookus, Matti A., Saloustros, Emmanouil, Sawyer, Elinor J., Schmutzler, Rita K., Shah, Mitul, Sironen, Reijo, Southey, Melissa C., Suvanto, Maija, Tollenaar, Rob A. E. M., Tomlinson, Ian, Truong, Thérèse, van der Kolk, Lizet E., van Veen, Elke M., Wappenschmidt, Barbara, Yang, Xiaohong R., Bolla, Manjeet K., Dennis, Joe, Dunning, Alison M., Easton, Douglas F., Lush, Michael, Michailidou, Kyriaki, Pharoah, Paul D. P., Wang, Qin, Adank, Muriel A., Schmidt, Marjanka K., Andrulis, Irene L., Chang-Claude, Jenny, Nevanlinna, Heli, Chenevix-Trench, Georgia, Evans, D. Gareth, Milne, Roger L., Radice, Paolo, and Peterlongo, Paolo

Published
2023
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31. Genetic insights into biological mechanisms governing human ovarian ageing

Author

Ruth, Katherine S, Day, Felix R, Hussain, Jazib, Martínez-Marchal, Ana, Aiken, Catherine E, Azad, Ajuna, Thompson, Deborah J, Knoblochova, Lucie, Abe, Hironori, Tarry-Adkins, Jane L, Gonzalez, Javier Martin, Fontanillas, Pierre, Claringbould, Annique, Bakker, Olivier B, Sulem, Patrick, Walters, Robin G, Terao, Chikashi, Turon, Sandra, Horikoshi, Momoko, Lin, Kuang, Onland-Moret, N Charlotte, Sankar, Aditya, Hertz, Emil Peter Thrane, Timshel, Pascal N, Shukla, Vallari, Borup, Rehannah, Olsen, Kristina W, Aguilera, Paula, Ferrer-Roda, Mònica, Huang, Yan, Stankovic, Stasa, Timmers, Paul RHJ, Ahearn, Thomas U, Alizadeh, Behrooz Z, Naderi, Elnaz, Andrulis, Irene L, Arnold, Alice M, Aronson, Kristan J, Augustinsson, Annelie, Bandinelli, Stefania, Barbieri, Caterina M, Beaumont, Robin N, Becher, Heiko, Beckmann, Matthias W, Benonisdottir, Stefania, Bergmann, Sven, Bochud, Murielle, Boerwinkle, Eric, Bojesen, Stig E, Bolla, Manjeet K, Boomsma, Dorret I, Bowker, Nicholas, Brody, Jennifer A, Broer, Linda, Buring, Julie E, Campbell, Archie, Campbell, Harry, Castelao, Jose E, Catamo, Eulalia, Chanock, Stephen J, Chenevix-Trench, Georgia, Ciullo, Marina, Corre, Tanguy, Couch, Fergus J, Cox, Angela, Crisponi, Laura, Cross, Simon S, Cucca, Francesco, Czene, Kamila, Smith, George Davey, de Geus, Eco JCN, de Mutsert, Renée, De Vivo, Immaculata, Demerath, Ellen W, Dennis, Joe, Dunning, Alison M, Dwek, Miriam, Eriksson, Mikael, Esko, Tõnu, Fasching, Peter A, Faul, Jessica D, Ferrucci, Luigi, Franceschini, Nora, Frayling, Timothy M, Gago-Dominguez, Manuela, Mezzavilla, Massimo, García-Closas, Montserrat, Gieger, Christian, Giles, Graham G, Grallert, Harald, Gudbjartsson, Daniel F, Gudnason, Vilmundur, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hayward, Caroline, He, Chunyan, He, Wei, and Heiss, Gerardo

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Estrogen, Prevention, Women's Health, Contraception/Reproduction, Aging, Infertility, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Good Health and Well Being, Adult, Alleles, Animals, Bone and Bones, Checkpoint Kinase 1, Checkpoint Kinase 2, Diabetes Mellitus, Type 2, Diet, Europe, Asia, Eastern, Female, Fertility, Fragile X Mental Retardation Protein, Genetic Predisposition to Disease, Genome-Wide Association Study, Healthy Aging, Humans, Longevity, Menopause, Menopause, Premature, Mice, Mice, Inbred C57BL, Middle Aged, Ovary, Primary Ovarian Insufficiency, Uterus, Biobank-based Integrative Omics Study (BIOS) Consortium, eQTLGen Consortium, Biobank Japan Project, China Kadoorie Biobank Collaborative Group, kConFab Investigators, LifeLines Cohort Study, InterAct consortium, 23andMe Research Team, General Science & Technology
Abstract

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

Published
2021

32. Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element

Author

Baxter, Joseph S, Johnson, Nichola, Tomczyk, Katarzyna, Gillespie, Andrea, Maguire, Sarah, Brough, Rachel, Fachal, Laura, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bogdanova, Natalia V, Bojesen, Stig E, Brenner, Hermann, Brucker, Sara Y, Cai, Qiuyin, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chan, Tsun L, Chang-Claude, Jenny, Chanock, Stephen J, Chenevix-Trench, Georgia, Choi, Ji-Yeob, Clarke, Christine L, Collaborators, NBCS, Colonna, Sarah, Conroy, Don M, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dossus, Laure, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eliassen, A Heather, Engel, Christoph, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Gago-Dominguez, Manuela, Gao, Chi, García-Closas, Montserrat, García-Sáenz, José A, Ghoussaini, Maya, Giles, Graham G, Goldberg, Mark S, González-Neira, Anna, Guénel, Pascal, Gündert, Melanie, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Hall, Per, Hamann, Ute, Hartman, Mikael, Hatse, Sigrid, Hauke, Jan, Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L, Hou, Ming-Feng, Investigators, kConFab, Investigators, ABCTB, Ito, Hidemi, Iwasaki, Motoki, Jager, Agnes, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Joseph, Vijai, Jung, Audrey, Kaaks, Rudolf, Kang, Daehee, Keeman, Renske, Khusnutdinova, Elza, Kim, Sung-Won, Kosma, Veli-Matti, Kraft, Peter, Kristensen, Vessela N, Kubelka-Sabit, Katerina, Kurian, Allison W, Kwong, Ava, and Lacey, James V

Subjects
Human Genome, Genetics, Cancer, Estrogen, Prevention, Breast Cancer, 2.1 Biological and endogenous factors, Aetiology, Breast Neoplasms, CRISPR-Cas Systems, Cell Line, Chromosome Mapping, Chromosomes, Human, Pair 2, Female, Genetic Association Studies, Genetic Variation, Humans, Insulin-Like Growth Factor Binding Protein 5, Molecular Sequence Annotation, Promoter Regions, Genetic, Risk Factors, Sequence Deletion, NBCS Collaborators, kConFab Investigators, ABCTB Investigators, breast cancer risk, functional annotation, risk locus, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10-31).

Published
2021

33. Partitioning of excess mortality in population-based cancer patient survival studies using flexible parametric survival models

Author

Eloranta Sandra, Lambert Paul C, Andersson Therese ML, Czene Kamila, Hall Per, Björkholm Magnus, and Dickman Paul W

Subjects
Survival analysis, Cancer, Relative survival, Regression models, Competing risks, Medicine (General), R5-920
Abstract

Abstract Background Relative survival is commonly used for studying survival of cancer patients as it captures both the direct and indirect contribution of a cancer diagnosis on mortality by comparing the observed survival of the patients to the expected survival in a comparable cancer-free population. However, existing methods do not allow estimation of the impact of isolated conditions (e.g., excess cardiovascular mortality) on the total excess mortality. For this purpose we extend flexible parametric survival models for relative survival, which use restricted cubic splines for the baseline cumulative excess hazard and for any time-dependent effects. Methods In the extended model we partition the excess mortality associated with a diagnosis of cancer through estimating a separate baseline excess hazard function for the outcomes under investigation. This is done by incorporating mutually exclusive background mortality rates, stratified by the underlying causes of death reported in the Swedish population, and by introducing cause of death as a time-dependent effect in the extended model. This approach thereby enables modeling of temporal trends in e.g., excess cardiovascular mortality and remaining cancer excess mortality simultaneously. Furthermore, we illustrate how the results from the proposed model can be used to derive crude probabilities of death due to the component parts, i.e., probabilities estimated in the presence of competing causes of death. Results The method is illustrated with examples where the total excess mortality experienced by patients diagnosed with breast cancer is partitioned into excess cardiovascular mortality and remaining cancer excess mortality. Conclusions The proposed method can be used to simultaneously study disease patterns and temporal trends for various causes of cancer-consequent deaths. Such information should be of interest for patients and clinicians as one way of improving prognosis after cancer is through adapting treatment strategies and follow-up of patients towards reducing the excess mortality caused by side effects of the treatment.

Published
2012
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34. aThe dyslexia candidate gene DYX1C1 is a potential marker of poor survival in breast cancer

Author

Rosin Gustaf, Hannelius Ulf, Lindström Linda, Hall Per, Bergh Jonas, Hartman Johan, and Kere Juha

Subjects
DYX1C1, Breast cancer, Estrogen receptor, Dyslexia, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background The dyslexia candidate gene, DYX1C1, shown to regulate and interact with estrogen receptors and involved in the regulation of neuronal migration, has recently been proposed as a putative cancer biomarker. This study was undertaken to assess the prognostic value and therapy-predictive potential of DYX1C1 mRNA and protein expression in breast cancer. Methods DYX1C1 mRNA expression was assessed at the mRNA level in three independent population-derived patient cohorts. An association to estrogen/progesterone receptor status, Elston grade, gene expression subtype and lymph node status was analyzed within these cohorts. DYX1C1 protein expression was examined using immunohistochemistry in cancer and normal breast tissue. The statistical analyses were performed using the non-parametric Wilcoxon rank-sum test, ANOVA, Fisher's exact test and a multivariate proportional hazard (Cox) model. Results DYX1C1 mRNA is significantly more highly expressed in tumors that have been classified as estrogen receptor α and progesterone receptor-positive. The expression of DYX1C1 among the molecular subtypes shows the lowest median expression within the basal type tumors, which are considered to have the worst prognosis. The expression of DYX1C1 is significantly lower in tumors graded as Elston grade 3 compared with grades 1 and 2. DYX1C1 protein is expressed in 88% of tumors and in all 10 normal breast tissues examined. Positive protein expression was significantly correlated to overall survival (Hazard ratio 3.44 [CI 1.84-6.42]) of the patients but not to any of the variables linked with mRNA expression. Conclusion We show that the expression of DYX1C1 in breast cancer is associated with several clinicopathological parameters and that loss of DYX1C1 correlates with a more aggressive disease, in turn indicating that DYX1C1 is a potential prognostic biomarker in breast cancer.

Published
2012
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35. Genome-Wide Interaction Analysis of Menopausal Hormone Therapy Use and Breast Cancer Risk Among 62,370 Women

Author

Wang, Xiaoliang, Kapoor, Pooja Middha, Auer, Paul L, Dennis, Joe, Dunning, Alison M, Wang, Qin, Lush, Michael, Michailidou, Kyriaki, Bolla, Manjeet K, Aronson, Kristan J, Murphy, Rachel A, Brooks-Wilson, Angela, Lee, Derrick G, Cordina-Duverger, Emilie, Guénel, Pascal, Truong, Thérèse, Mulot, Claire, Teras, Lauren R, Patel, Alpa V, Dossus, Laure, Kaaks, Rudolf, Hoppe, Reiner, Lo, Wing-Yee, Brüning, Thomas, Hamann, Ute, Czene, Kamila, Gabrielson, Marike, Hall, Per, Eriksson, Mikael, Jung, Audrey, Becher, Heiko, Couch, Fergus J, Larson, Nicole L, Olson, Janet E, Ruddy, Kathryn J, Giles, Graham G, MacInnis, Robert J, Southey, Melissa C, Marchand, Loic Le, Wilkens, Lynne R, Haiman, Christopher A, Olsson, Håkan, Augustinsson, Annelie, Krüger, Ute, Wagner, Philippe, Scott, Christopher, Winham, Stacey J, Vachon, Celine M, Perou, Charles M, Olshan, Andrew F, Troester, Melissa A, Hunter, David J, Eliassen, A Heather, Tamimi, Rulla M, Brantley, Kristen, Andrulis, Irene L, Figueroa, Jonine, Chanock, Stephen J, Ahearn, Thomas U, García-Closas, Montserrat, Evans, Gareth D, Newman, William G, Veen, Elke M van, Howell, Anthony, Wolk, Alicja, Håkansson, Niclas, Anton-Culver, Hoda, Ziogas, Argyrios, Jones, Michael E, Orr, Nick, Schoemaker, Minouk J, Swerdlow, Anthony J, Kitahara, Cari M, Linet, Martha, Prentice, Ross L, Easton, Douglas F, Milne, Roger L, Kraft, Peter, Chang-Claude, Jenny, and Lindström, Sara

Subjects
Cancer, Prevention, Breast Cancer, Genetics, Human Genome, Aging, Estrogen, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being
Abstract

Abstract Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values

Published
2021

36. Author Correction: A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.

Author

Coignard, Juliette, Lush, Michael, Beesley, Jonathan, O'Mara, Tracy A, Dennis, Joe, Tyrer, Jonathan P, Barnes, Daniel R, McGuffog, Lesley, Leslie, Goska, Bolla, Manjeet K, Adank, Muriel A, Agata, Simona, Ahearn, Thomas, Aittomäki, Kristiina, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Arnold, Norbert, Aronson, Kristan J, Arun, Banu K, Augustinsson, Annelie, Azzollini, Jacopo, Barrowdale, Daniel, Baynes, Caroline, Becher, Heko, Bermisheva, Marina, Bernstein, Leslie, Białkowska, Katarzyna, Blomqvist, Carl, Bojesen, Stig E, Bonanni, Bernardo, Borg, Ake, Brauch, Hiltrud, Brenner, Hermann, Burwinkel, Barbara, Buys, Saundra S, Caldés, Trinidad, Caligo, Maria A, Campa, Daniele, Carter, Brian D, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, GEMO Study Collaborators, EMBRACE Collaborators, Collée, J Margriet, Conroy, Don M, Czene, Kamila, Daly, Mary B, Devilee, Peter, Diez, Orland, Ding, Yuan Chun, Domchek, Susan M, Dörk, Thilo, Dos-Santos-Silva, Isabel, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Eliassen, A Heather, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Flyger, Henrik, Fostira, Florentia, Friedman, Eitan, Fritschi, Lin, Frost, Debra, Gago-Dominguez, Manuela, Gapstur, Susan M, Garber, Judy, Garcia-Barberan, Vanesa, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, Gayther, Simon A, Gehrig, Andrea, Georgoulias, Vassilios, Giles, Graham G, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Greene, Mark H, Guénel, Pascal, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Harrington, Patricia A, Hart, Steven N, He, Wei, Hogervorst, Frans BL, Hollestelle, Antoinette, and Hopper, John L

Subjects
GEMO Study Collaborators, EMBRACE Collaborators, KConFab Investigators, HEBON Investigators, ABCTB Investigators, Cancer
Abstract

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-23162-4.

Published
2021

37. Breast Cancer Risk Factors and Survival by Tumor Subtype: Pooled Analyses from the Breast Cancer Association ConsortiumBreast Cancer Risk Factors and Survival By Tumor Subtype

Author

Morra, Anna, Jung, Audrey Y, Behrens, Sabine, Keeman, Renske, Ahearn, Thomas U, Anton-Culver, Hoda, Arndt, Volker, Augustinsson, Annelie, Auvinen, Päivi K, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Blomqvist, Carl, Bojesen, Stig E, Bolla, Manjeet K, Brenner, Hermann, Briceno, Ignacio, Brucker, Sara Y, Camp, Nicola J, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chanock, Stephen J, Choi, Ji-Yeob, Clarke, Christine L, Investigators, for the ABCTB, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dörk, Thilo, Dunning, Alison M, Dwek, Miriam, Easton, Douglas F, Eccles, Diana M, Egan, Kathleen M, Evans, D Gareth, Fasching, Peter A, Flyger, Henrik, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Grip, Mervi, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Han, Sileny N, Hart, Steven N, Hartman, Mikael, Heyworth, Jane S, Hoppe, Reiner, Hopper, John L, Hunter, David J, Ito, Hidemi, Jager, Agnes, Jakimovska, Milena, Jakubowska, Anna, Janni, Wolfgang, Kaaks, Rudolf, Kang, Daehee, Kapoor, Pooja Middha, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Collaborators, for the NBCS, Lacey, James V, Lambrechts, Diether, Le Marchand, Loic, Li, Jingmei, Lindblom, Annika, Lubiński, Jan, Lush, Michael, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Mariapun, Shivaani, Matsuo, Keitaro, Mavroudis, Dimitrios, Milne, Roger L, Muranen, Taru A, Newman, William G, Noh, Dong-Young, Nordestgaard, Børge G, Obi, Nadia, Olshan, Andrew F, Olsson, Håkan, Park-Simon, Tjoung-Won, Petridis, Christos, Pharoah, Paul DP, Plaseska-Karanfilska, Dijana, Presneau, Nadege, Rashid, Muhammad U, Rennert, Gad, Rennert, Hedy S, and Rhenius, Valerie

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Oncology and Carcinogenesis, Clinical Research, Aging, Estrogen, Cancer, Prevention, Breast Cancer, Good Health and Well Being, Adult, Aged, Breast Neoplasms, Cause of Death, Female, Humans, Life Style, Middle Aged, Neoplasm Invasiveness, Neoplasm Staging, Prospective Studies, Risk Factors, Survival Analysis, ABCTB Investigators, NBCS Collaborators, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundIt is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype.MethodsWe analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.ResultsThere was no evidence of heterogeneous associations between risk factors and mortality by subtype (P adj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus 0-

Published
2021

38. Protocol for the MoleMate™ UK Trial: a randomised controlled trial of the MoleMate system in the management of pigmented skin lesions in primary care [ISRCTN 79932379]

Author

Wilson Edward CF, Prevost A Toby, Kinmonth Ann, Hall Per N, Humphrys Elka, Morris Helen C, Walter Fiona M, Burrows Nigel, Norris Paul, Johnson Margaret, and Emery Jon

Subjects
Medicine (General), R5-920
Abstract

Abstract Background Suspicious pigmented lesions are a common presenting problem in general practice consultations; while the majority are benign a small minority are melanomas. Differentiating melanomas from other pigmented lesions in primary care is challenging: currently, 95% of all lesions referred to a UK specialist are benign. The MoleMate system is a new diagnostic aid, incorporating a hand-held SIAscopy scanner with a primary care diagnostic algorithm. This trial tests the hypothesis that adding the MoleMate system to current best primary care practice will increase the proportion of appropriate referrals of suspicious pigmented lesions to secondary care compared with current best practice alone. Methods/design The MoleMate UK Trial is a primary care based multi-centre randomised controlled trial, with randomisation at patient level using a validated block randomisation method for two age groups (45 years and under; 46 years and over). We aim to recruit adult patients seen in general practice with a pigmented skin lesion that cannot immediately be diagnosed as benign and the patient reassured. The trial has a 'two parallel groups' design, comparing 'best practice' with 'best practice' plus the MoleMate system in the intervention group. The primary outcome is the positive predictive value (PPV) of referral defined as the proportion of referred lesions seen by secondary care experts that are considered 'clinically significant' (i.e. biopsied or monitored). Secondary outcomes include: the sensitivity, specificity and negative predictive value (NPV) of the decision not to refer; clinical outcomes (melanoma thickness, 5 year melanoma incidence and mortality); clinician outcomes (Index of Suspicion, confidence, learning effects); patient outcomes (satisfaction, general and cancer-specific worry), and cost-utility. Discussion The MoleMate UK Trial tests a new technology designed to improve the management of suspicious pigmented lesions in primary care. If effective, the MoleMate system could reduce the burden on skin cancer clinics of patients with benign pigmented skin lesions, and improve patient care in general practice.

Published
2010
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39. Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk.

Author

Kapoor, Pooja Middha, Mavaddat, Nasim, Choudhury, Parichoy Pal, Wilcox, Amber N, Lindström, Sara, Behrens, Sabine, Michailidou, Kyriaki, Dennis, Joe, Bolla, Manjeet K, Wang, Qin, Jung, Audrey, Abu-Ful, Zomoroda, Ahearn, Thomas, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Benitez, Javier, Bernstein, Leslie, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brüning, Thomas, Cai, Qiuyin, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Carter, Brian D, Castelao, Jose E, Chanock, Stephen J, Chatterjee, Nilanjan, Chenevix-Trench, Georgia, Clarke, Christine L, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dai, James Y, Earp, H Shelton, Ekici, Arif B, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gao, Chi, Gapstur, Susan M, Gaudet, Mia M, Giles, Graham G, González-Neira, Anna, Guénel, Pascal, Haeberle, Lothar, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hatse, Sigrid, Heyworth, Jane, Holleczek, Bernd, Hoover, Robert N, Hopper, John L, Howell, Anthony, Hunter, David J, ABCTB Investigators, kConFab/AOCS Investigators, John, Esther M, Jones, Michael E, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kurian, Allison W, Lambrechts, Diether, Le Marchand, Loic, Lee, Eunjung, Lejbkowicz, Flavio, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, MacInnis, Robert J, Martinez, Maria Elena, Maurer, Tabea, McLean, Catriona, Neuhausen, Susan L, Newman, William G, Norman, Aaron, O'Brien, Katie M, Olshan, Andrew F, Olson, Janet E, Olsson, Håkan, and Orr, Nick

Subjects
ABCTB Investigators, kConFab/AOCS Investigators, Oncology & Carcinogenesis, Oncology and Carcinogenesis
Abstract

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

Published
2021

40. A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.

Author

Coignard, Juliette, Lush, Michael, Beesley, Jonathan, O'Mara, Tracy A, Dennis, Joe, Tyrer, Jonathan P, Barnes, Daniel R, McGuffog, Lesley, Leslie, Goska, Bolla, Manjeet K, Adank, Muriel A, Agata, Simona, Ahearn, Thomas, Aittomäki, Kristiina, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Arnold, Norbert, Aronson, Kristan J, Arun, Banu K, Augustinsson, Annelie, Azzollini, Jacopo, Barrowdale, Daniel, Baynes, Caroline, Becher, Heiko, Bermisheva, Marina, Bernstein, Leslie, Białkowska, Katarzyna, Blomqvist, Carl, Bojesen, Stig E, Bonanni, Bernardo, Borg, Ake, Brauch, Hiltrud, Brenner, Hermann, Burwinkel, Barbara, Buys, Saundra S, Caldés, Trinidad, Caligo, Maria A, Campa, Daniele, Carter, Brian D, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, GEMO Study Collaborators, EMBRACE Collaborators, Collée, J Margriet, Conroy, Don M, Czene, Kamila, Daly, Mary B, Devilee, Peter, Diez, Orland, Ding, Yuan Chun, Domchek, Susan M, Dörk, Thilo, Dos-Santos-Silva, Isabel, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Eliassen, A Heather, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Flyger, Henrik, Fostira, Florentia, Friedman, Eitan, Fritschi, Lin, Frost, Debra, Gago-Dominguez, Manuela, Gapstur, Susan M, Garber, Judy, Garcia-Barberan, Vanesa, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, Gayther, Simon A, Gehrig, Andrea, Georgoulias, Vassilios, Giles, Graham G, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Greene, Mark H, Guénel, Pascal, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Harrington, Patricia A, Hart, Steven N, He, Wei, Hogervorst, Frans BL, Hollestelle, Antoinette, and Hopper, John L

Subjects
GEMO Study Collaborators, EMBRACE Collaborators, KConFab Investigators, HEBON Investigators, ABCTB Investigators, Humans, Breast Neoplasms, Genetic Predisposition to Disease, BRCA1 Protein, BRCA2 Protein, Risk Factors, Genotype, Linkage Disequilibrium, Mutation, Polymorphism, Single Nucleotide, Alleles, Quantitative Trait Loci, Adult, Middle Aged, Female, Genome-Wide Association Study, Breast Cancer, Prevention, Cancer, Genetic Testing, Human Genome, Genetics, 2.1 Biological and endogenous factors
Abstract

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P

Published
2021

41. CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers

Author

Johnson, Nichola, Maguire, Sarah, Morra, Anna, Kapoor, Pooja Middha, Tomczyk, Katarzyna, Jones, Michael E, Schoemaker, Minouk J, Gilham, Clare, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Baynes, Caroline, Freeman, Laura E Beane, Beckmann, Matthias W, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Boeckx, Bram, Bogdanova, Natalia V, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Burwinkel, Barbara, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Clarke, Christine L, Conroy, Don M, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dörk, Thilo, Eliassen, A Heather, Engel, Christoph, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Floris, Giuseppe, Flyger, Henrik, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Closas, Montserrat, Gaudet, Mia M, Giles, Graham G, Goldberg, Mark S, González-Neira, Anna, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Harrington, Patricia A, Hart, Steven N, Hooning, Maartje J, Hopper, John L, Howell, Anthony, Hunter, David J, Jager, Agnes, Jakubowska, Anna, John, Esther M, Kaaks, Rudolf, Keeman, Renske, Khusnutdinova, Elza, Kitahara, Cari M, Kosma, Veli-Matti, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kurian, Allison W, Lambrechts, Diether, Le Marchand, Loic, Linet, Martha, Lubiński, Jan, Mannermaa, Arto, Manoukian, Siranoush, Margolin, Sara, Martens, John WM, Mavroudis, Dimitrios, Mayes, Rebecca, Meindl, Alfons, Milne, Roger L, Neuhausen, Susan L, Nevanlinna, Heli, Newman, William G, Nielsen, Sune F, Nordestgaard, Børge G, Obi, Nadia, Olshan, Andrew F, and Olson, Janet E

Subjects
Estrogen, Human Genome, Clinical Research, Cancer, Aging, Breast Cancer, Genetics, 2.1 Biological and endogenous factors, Aetiology, Alleles, Breast Neoplasms, Case-Control Studies, Cytochrome P-450 CYP3A, Estrone, Female, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Pregnanediol, Premenopause, Progesterone, Receptors, Estrogen, Receptors, Progesterone, NBCS Collaborators, AOCS Group, ABCTB Investigators, kConFab Investigators, Oncology and Carcinogenesis, Public Health and Health Services, Oncology & Carcinogenesis
Abstract

BackgroundEpidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk.MethodsWe carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry.ResultsFor pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10-18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10-8).ConclusionsThe CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.

Published
2021

42. Breast Cancer Risk Genes — Association Analysis in More than 113,000 Women

Author

Dorling, Leila, Carvalho, Sara, Allen, Jamie, González-Neira, Anna, Luccarini, Craig, Wahlström, Cecilia, Pooley, Karen A, Parsons, Michael T, Fortuno, Cristina, Wang, Qin, Bolla, Manjeet K, Dennis, Joe, Keeman, Renske, Alonso, M Rosario, Álvarez, Nuria, Herraez, Belen, Fernandez, Victoria, Núñez-Torres, Rocio, Osorio, Ana, Valcich, Jeanette, Li, Minerva, Törngren, Therese, Harrington, Patricia A, Baynes, Caroline, Conroy, Don M, Decker, Brennan, Fachal, Laura, Mavaddat, Nasim, Ahearn, Thomas, Aittomäki, Kristiina, Antonenkova, Natalia N, Arnold, Norbert, Arveux, Patrick, Ausems, Margreet GEM, Auvinen, Päivi, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bermisheva, Marina, Białkowska, Katarzyna, Blomqvist, Carl, Bogdanova, Natalia V, Bogdanova-Markov, Nadja, Bojesen, Stig E, Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Bremer, Michael, Briceno, Ignacio, Brüning, Thomas, Burwinkel, Barbara, Cameron, David A, Camp, Nicola J, Campbell, Archie, Carracedo, Angel, Castelao, Jose E, Cessna, Melissa H, Chanock, Stephen J, Christiansen, Hans, Collée, J Margriet, Cordina-Duverger, Emilie, Cornelissen, Sten, Czene, Kamila, Dörk, Thilo, Ekici, Arif B, Engel, Christoph, Eriksson, Mikael, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Försti, Asta, Gabrielson, Marike, Gago-Dominguez, Manuela, Georgoulias, Vassilios, Gil, Fabian, Giles, Graham G, Glendon, Gord, Garcia, Encarna B Gómez, Alnæs, Grethe I Grenaker, Guénel, Pascal, Hadjisavvas, Andreas, Haeberle, Lothar, Hahnen, Eric, Hall, Per, Hamann, Ute, Harkness, Elaine F, Hartikainen, Jaana M, Hartman, Mikael, He, Wei, Heemskerk-Gerritsen, Bernadette AM, Hillemanns, Peter, Hogervorst, Frans BL, Hollestelle, Antoinette, Ho, Weang Kee, Hooning, Maartje J, Howell, Anthony, Humphreys, Keith, Idris, Faiza, Jakubowska, Anna, and Jung, Audrey

Subjects
Breast Cancer, Cancer, Genetics, Aetiology, 2.1 Biological and endogenous factors, Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Breast Neoplasms, Female, Genetic Predisposition to Disease, Genetic Variation, Humans, Logistic Models, Middle Aged, Mutation, Missense, Odds Ratio, Risk, Sequence Analysis, DNA, Young Adult, Breast Cancer Association Consortium, Medical and Health Sciences, General & Internal Medicine
Abstract

BackgroundGenetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.MethodsWe used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.ResultsProtein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.ConclusionsThe results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

Published
2021

43. Gene-Environment Interactions Relevant to Estrogen and Risk of Breast Cancer: Can Gene-Environment Interactions Be Detected Only among Candidate SNPs from Genome-Wide Association Studies?

Author

Park, JooYong, Choi, Ji-Yeob, Choi, Jaesung, Chung, Seokang, Song, Nan, Park, Sue K, Han, Wonshik, Noh, Dong-Young, Ahn, Sei-Hyun, Lee, Jong Won, Kim, Mi Kyung, Jee, Sun Ha, Wen, Wanqing, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Shah, Mitul, Conroy, Don M, Harrington, Patricia A, Mayes, Rebecca, Czene, Kamila, Hall, Per, Teras, Lauren R, Patel, Alpa V, Couch, Fergus J, Olson, Janet E, Sawyer, Elinor J, Roylance, Rebecca, Bojesen, Stig E, Flyger, Henrik, Lambrechts, Diether, Baten, Adinda, Matsuo, Keitaro, Ito, Hidemi, Guénel, Pascal, Truong, Thérèse, Keeman, Renske, Schmidt, Marjanka K, Wu, Anna H, Tseng, Chiu-Chen, Cox, Angela, Cross, Simon S, kConFab Investigators, Andrulis, Irene L, Hopper, John L, Southey, Melissa C, Wu, Pei-Ei, Shen, Chen-Yang, Fasching, Peter A, Ekici, Arif B, Muir, Kenneth, Lophatananon, Artitaya, Brenner, Hermann, Arndt, Volker, Jones, Michael E, Swerdlow, Anthony J, Hoppe, Reiner, Ko, Yon-Dschun, Hartman, Mikael, Li, Jingmei, Mannermaa, Arto, Hartikainen, Jaana M, Benitez, Javier, González-Neira, Anna, Haiman, Christopher A, Dörk, Thilo, Bogdanova, Natalia V, Teo, Soo Hwang, Mohd Taib, Nur Aishah, Fletcher, Olivia, Johnson, Nichola, Grip, Mervi, Winqvist, Robert, Blomqvist, Carl, Nevanlinna, Heli, Lindblom, Annika, Wendt, Camilla, Kristensen, Vessela N, Nbcs Collaborators, Tollenaar, Rob AEM, Heemskerk-Gerritsen, Bernadette AM, Radice, Paolo, Bonanni, Bernardo, Hamann, Ute, Manoochehri, Mehdi, Lacey, James V, Martinez, Maria Elena, Dunning, Alison M, Pharoah, Paul DP, Easton, Douglas F, Yoo, Keun-Young, and Kang, Daehee

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Women's Health, Clinical Research, Cancer, Estrogen, Breast Cancer, Human Genome, Genetics, Prevention, Aging, 2.1 Biological and endogenous factors, breast cancer, estrogen, gene-environment interaction, Oncology and carcinogenesis
Abstract

In this study we aim to examine gene-environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 × 10-3). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 × 10-4). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.

Published
2021

44. Ethnic differences in the time trend of female breast cancer incidence: Singapore, 1968 – 2002

Author

Tan Chuen-Seng, Goh Denise, Wedren Sara, Ali R Ayesha, Sim Xueling, Reilly Marie, Hall Per, and Chia Kee-Seng

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background From 1968 to 2002, Singapore experienced an almost three-fold increase in breast cancer incidence. This increase appeared to be different across the three main ethnic groups: Chinese, Malays and Indians. This paper used age-period-cohort (APC) modelling, to determine the effects of age at diagnosis, calendar period, and birth cohort on breast cancer incidence for each ethnic group. Methods This study included all breast cancer cases (n = 15,269) in the three ethnic groups, reported to the Singapore Cancer Registry from 1968 to 2002 between the ages 25 to 79. Age-specific fertility rates from the Department of Statistics were used to explore the role of fertility. Results In the 1970s, Indian women had the highest age-standardized breast cancer but by the mid-1980s the highest rates were seen among the Chinese. Remarkable differences were seen in the age-specific incidence rates by ethnic groups. After age 49, the incidence rates for the Chinese and Malays leveled off whereas it continued to rise in the Indians. While our analyses provided some evidence that an age-drift model described the trend seen in the Indians, age-period-cohort model and age-cohort model had the best fit for the Chinese and Malays aged 25 to 79 respectively. Overall, Chinese and Malay women born in later cohorts were at increased risk of developing breast cancer relative to their counterparts in the earlier cohorts. The three ethnic groups experienced similar changes in their fertility in the 1970s, which likely explained much of the increase in their breast cancer incidence but not the ethnic differences. There was a stronger inverse association between total fertility rate and pre-menopausal breast cancer incidence in the Chinese and Malays than the Indians. Conclusion The observed dissimilarity among ethnic groups suggests ethnic differences in exposure or response to certain risk factors. It is likely that longer and subtler differences in childbearing trends and other risk factors may further explain these ethnic differences.

Published
2006
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45. Hormone-replacement therapy influences gene expression profiles and is associated with breast-cancer prognosis: a cohort study

Author

Skoog Lambert, Shaw Peter, Pawitan Yudi, Nordgren Hans, Miller Lance D, Liu Edison T, Lin Chin-Yo, Huang Fei, Bjöhle Judith, Ploner Alexander, Hall Per, Smeds Johanna, Wedrén Sara, Öhd John, and Bergh Jonas

Subjects
Medicine
Abstract

Abstract Background Postmenopausal hormone-replacement therapy (HRT) increases breast-cancer risk. The influence of HRT on the biology of the primary tumor, however, is not well understood. Methods We obtained breast-cancer gene expression profiles using Affymetrix human genome U133A arrays. We examined the relationship between HRT-regulated gene profiles, tumor characteristics, and recurrence-free survival in 72 postmenopausal women. Results HRT use in patients with estrogen receptor (ER) protein positive tumors (n = 72) was associated with an altered regulation of 276 genes. Expression profiles based on these genes clustered ER-positive tumors into two molecular subclasses, one of which was associated with HRT use and had significantly better recurrence free survival despite lower ER levels. A comparison with external data suggested that gene regulation in tumors associated with HRT was negatively correlated with gene regulation induced by short-term estrogen exposure, but positively correlated with the effect of tamoxifen. Conclusion Our findings suggest that post-menopausal HRT use is associated with a distinct gene expression profile related to better recurrence-free survival and lower ER protein levels. Tentatively, HRT-associated gene expression in tumors resembles the effect of tamoxifen exposure on MCF-7 cells.

Published
2006
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46. Correlation test to assess low-level processing of high-density oligonucleotide microarray data

Author

Bergh Jonas, Hall Per, Miller Lance D, Ploner Alexander, and Pawitan Yudi

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background There are currently a number of competing techniques for low-level processing of oligonucleotide array data. The choice of technique has a profound effect on subsequent statistical analyses, but there is no method to assess whether a particular technique is appropriate for a specific data set, without reference to external data. Results We analyzed coregulation between genes in order to detect insufficient normalization between arrays, where coregulation is measured in terms of statistical correlation. In a large collection of genes, a random pair of genes should have on average zero correlation, hence allowing a correlation test. For all data sets that we evaluated, and the three most commonly used low-level processing procedures including MAS5, RMA and MBEI, the housekeeping-gene normalization failed the test. For a real clinical data set, RMA and MBEI showed significant correlation for absent genes. We also found that a second round of normalization on the probe set level improved normalization significantly throughout. Conclusion Previous evaluation of low-level processing in the literature has been limited to artificial spike-in and mixture data sets. In the absence of a known gold-standard, the correlation criterion allows us to assess the appropriateness of low-level processing of a specific data set and the success of normalization for subsets of genes.

Published
2005
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47. Personalized early detection and prevention of breast cancer: ENVISION consensus statement

Author

Pashayan, Nora, Antoniou, Antonis C, Ivanus, Urska, Esserman, Laura J, Easton, Douglas F, French, David, Sroczynski, Gaby, Hall, Per, Cuzick, Jack, Evans, D Gareth, Simard, Jacques, Garcia-Closas, Montserrat, Schmutzler, Rita, Wegwarth, Odette, Pharoah, Paul, Moorthie, Sowmiya, De Montgolfier, Sandrine, Baron, Camille, Herceg, Zdenko, Turnbull, Clare, Balleyguier, Corinne, Rossi, Paolo Giorgi, Wesseling, Jelle, Ritchie, David, Tischkowitz, Marc, Broeders, Mireille, Reisel, Dan, Metspalu, Andres, Callender, Thomas, de Koning, Harry, Devilee, Peter, Delaloge, Suzette, Schmidt, Marjanka K, and Widschwendter, Martin

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Comparative Effectiveness Research, Prevention, Cancer, Aging, Breast Cancer, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Good Health and Well Being, Breast Neoplasms, Consensus, Early Detection of Cancer, Evidence-Based Medicine, Female, Genetic Predisposition to Disease, Humans, Mass Screening, Precision Medicine, Oncology and carcinogenesis
Abstract

The European Collaborative on Personalized Early Detection and Prevention of Breast Cancer (ENVISION) brings together several international research consortia working on different aspects of the personalized early detection and prevention of breast cancer. In a consensus conference held in 2019, the members of this network identified research areas requiring development to enable evidence-based personalized interventions that might improve the benefits and reduce the harms of existing breast cancer screening and prevention programmes. The priority areas identified were: 1) breast cancer subtype-specific risk assessment tools applicable to women of all ancestries; 2) intermediate surrogate markers of response to preventive measures; 3) novel non-surgical preventive measures to reduce the incidence of breast cancer of poor prognosis; and 4) hybrid effectiveness-implementation research combined with modelling studies to evaluate the long-term population outcomes of risk-based early detection strategies. The implementation of such programmes would require health-care systems to be open to learning and adapting, the engagement of a diverse range of stakeholders and tailoring to societal norms and values, while also addressing the ethical and legal issues. In this Consensus Statement, we discuss the current state of breast cancer risk prediction, risk-stratified prevention and early detection strategies, and their implementation. Throughout, we highlight priorities for advancing each of these areas.

Published
2020

48. Publisher Correction: Personalized early detection and prevention of breast cancer: ENVISION consensus statement

Author

Pashayan, Nora, Antoniou, Antonis C, Ivanus, Urska, Esserman, Laura J, Easton, Douglas F, French, David, Sroczynski, Gaby, Hall, Per, Cuzick, Jack, Evans, D Gareth, Simard, Jacques, Garcia-Closas, Montserrat, Schmutzler, Rita, Wegwarth, Odette, Pharoah, Paul, Moorthie, Sowmiya, De Montgolfier, Sandrine, Baron, Camille, Herceg, Zdenko, Turnbull, Clare, Balleyguier, Corinne, Rossi, Paolo Giorgi, Wesseling, Jelle, Ritchie, David, Tischkowitz, Marc, Broeders, Mireille, Reisel, Dan, Metspalu, Andres, Callender, Thomas, de Koning, Harry, Devilee, Peter, Delaloge, Suzette, Schmidt, Marjanka K, and Widschwendter, Martin

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer, Good Health and Well Being, Oncology and carcinogenesis
Abstract

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

Published
2020

49. Assessment of polygenic architecture and risk prediction based on common variants across fourteen cancers.

Author

Zhang, Yan Dora, Hurson, Amber N, Zhang, Haoyu, Choudhury, Parichoy Pal, Easton, Douglas F, Milne, Roger L, Simard, Jacques, Hall, Per, Michailidou, Kyriaki, Dennis, Joe, Schmidt, Marjanka K, Chang-Claude, Jenny, Gharahkhani, Puya, Whiteman, David, Campbell, Peter T, Hoffmeister, Michael, Jenkins, Mark, Peters, Ulrike, Hsu, Li, Gruber, Stephen B, Casey, Graham, Schmit, Stephanie L, O'Mara, Tracy A, Spurdle, Amanda B, Thompson, Deborah J, Tomlinson, Ian, De Vivo, Immaculata, Landi, Maria Teresa, Law, Matthew H, Iles, Mark M, Demenais, Florence, Kumar, Rajiv, MacGregor, Stuart, Bishop, D Timothy, Ward, Sarah V, Bondy, Melissa L, Houlston, Richard, Wiencke, John K, Melin, Beatrice, Barnholtz-Sloan, Jill, Kinnersley, Ben, Wrensch, Margaret R, Amos, Christopher I, Hung, Rayjean J, Brennan, Paul, McKay, James, Caporaso, Neil E, Berndt, Sonja I, Birmann, Brenda M, Camp, Nicola J, Kraft, Peter, Rothman, Nathaniel, Slager, Susan L, Berchuck, Andrew, Pharoah, Paul DP, Sellers, Thomas A, Gayther, Simon A, Pearce, Celeste L, Goode, Ellen L, Schildkraut, Joellen M, Moysich, Kirsten B, Amundadottir, Laufey T, Jacobs, Eric J, Klein, Alison P, Petersen, Gloria M, Risch, Harvey A, Stolzenberg-Solomon, Rachel Z, Wolpin, Brian M, Li, Donghui, Eeles, Rosalind A, Haiman, Christopher A, Kote-Jarai, Zsofia, Schumacher, Fredrick R, Al Olama, Ali Amin, Purdue, Mark P, Scelo, Ghislaine, Dalgaard, Marlene D, Greene, Mark H, Grotmol, Tom, Kanetsky, Peter A, McGlynn, Katherine A, Nathanson, Katherine L, Turnbull, Clare, Wiklund, Fredrik, Breast Cancer Association Consortium (BCAC), Barrett’s and Esophageal Adenocarcinoma Consortium (BEACON), Colon Cancer Family Registry (CCFR), Transdisciplinary Studies of Genetic Variation in Colorectal Cancer (CORECT), Endometrial Cancer Association Consortium (ECAC), Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), Melanoma Genetics Consortium (GenoMEL), Glioma International Case-Control Study (GICC), International Lung Cancer Consortium (ILCCO), Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Consortium, International Consortium of Investigators Working on Non-Hodgkin’s Lymphoma Epidemiologic Studies (InterLymph), Ovarian Cancer Association Consortium (OCAC), Oral Cancer GWAS, Pancreatic Cancer Case-Control Consortium (PanC4), Pancreatic Cancer Cohort Consortium (PanScan), and Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL)

Subjects
Breast Cancer Association Consortium, Barrett’s and Esophageal Adenocarcinoma Consortium, Colon Cancer Family Registry, Transdisciplinary Studies of Genetic Variation in Colorectal Cancer, Endometrial Cancer Association Consortium, Genetics and Epidemiology of Colorectal Cancer Consortium, Melanoma Genetics Consortium, Glioma International Case-Control Study, International Lung Cancer Consortium, Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Consortium, International Consortium of Investigators Working on Non-Hodgkin’s Lymphoma Epidemiologic Studies, Ovarian Cancer Association Consortium, Oral Cancer GWAS, Pancreatic Cancer Case-Control Consortium, Pancreatic Cancer Cohort Consortium, Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome, Renal Cancer GWAS, Testicular Cancer Consortium, Animals, Humans, Neoplasms, Genetic Predisposition to Disease, Incidence, Risk Assessment, Risk Factors, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Models, Genetic, Female, Male, Genome-Wide Association Study, Human Genome, Prevention, Cancer, Prostate Cancer, Genetics, Urologic Diseases, 2.1 Biological and endogenous factors
Abstract

Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.

Published
2020

50. Germline HOXB13 mutations p.G84E and p.R217C do not confer an increased breast cancer risk.

Author

Liu, Jingjing, Prager-van der Smissen, Wendy JC, Collée, J Margriet, Bolla, Manjeet K, Wang, Qin, Michailidou, Kyriaki, Dennis, Joe, Ahearn, Thomas U, Aittomäki, Kristiina, Ambrosone, Christine B, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Arnold, Norbert, Aronson, Kristan J, Augustinsson, Annelie, Auvinen, Päivi, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bermisheva, Marina, Bernstein, Leslie, Bogdanova, Natalia V, Bogdanova-Markov, Nadja, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Briceno, Ignacio, Brucker, Sara Y, Brüning, Thomas, Burwinkel, Barbara, Cai, Qiuyin, Cai, Hui, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Choi, Ji-Yeob, Christiaens, Melissa, Clarke, Christine L, NBCS Collaborators, Couch, Fergus J, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dos-Santos-Silva, Isabel, Dwek, Miriam, Eccles, Diana M, Eliassen, A Heather, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Fritschi, Lin, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Goldberg, Mark S, Goldgar, David E, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Harrington, Patricia A, Hart, Steven N, Hartman, Mikael, Hillemanns, Peter, Hopper, John L, Hou, Ming-Feng, Hunter, David J, Huo, Dezheng, ABCTB Investigators, Ito, Hidemi, Iwasaki, Motoki, Jakimovska, Milena, Jakubowska, Anna, John, Esther M, Kaaks, Rudolf, Kang, Daehee, Keeman, Renske, Khusnutdinova, Elza, Kim, Sung-Won, Kraft, Peter, Kristensen, Vessela N, Kurian, Allison W, Le Marchand, Loic, Li, Jingmei, Lindblom, Annika, Lophatananon, Artitaya, Luben, Robert N, Lubiński, Jan, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, and Mariapun, Shivaani

Subjects
NBCS Collaborators, ABCTB Investigators
Abstract

In breast cancer, high levels of homeobox protein Hox-B13 (HOXB13) have been associated with disease progression of ER-positive breast cancer patients and resistance to tamoxifen treatment. Since HOXB13 p.G84E is a prostate cancer risk allele, we evaluated the association between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 familial non-BRCA1/2 breast cancer cases and 2,327 controls from the Netherlands. Although both recurrent HOXB13 mutations p.G84E and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not very precise. To provide more conclusive evidence regarding the role of HOXB13 in breast cancer susceptibility, we here evaluated the association between HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breast Cancer Association Consortium containing 68,521 invasive breast cancer patients and 54,865 controls. Both HOXB13 p.G84E and p.R217C did not associate with the development of breast cancer in European women, neither in the overall analysis (OR = 1.035, 95% CI = 0.859-1.246, P = 0.718 and OR = 0.798, 95% CI = 0.482-1.322, P = 0.381 respectively), nor in specific high-risk subgroups or breast cancer subtypes. Thus, although involved in breast cancer progression, HOXB13 is not a material breast cancer susceptibility gene.

Published
2020

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