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2. Association of the CHEK2 c.1100delC variant, radiotherapy, and systemic treatment with contralateral breast cancer risk and breast cancer‐specific survival

Author

Morra, Anna, Schreurs, Maartje AC, Andrulis, Irene L, Anton‐Culver, Hoda, Augustinsson, Annelie, Beckmann, Matthias W, Behrens, Sabine, Bojesen, Stig E, Bolla, Manjeet K, Brauch, Hiltrud, Broeks, Annegien, Buys, Saundra S, Camp, Nicola J, Castelao, Jose E, Cessna, Melissa H, Chang‐Claude, Jenny, Chung, Wendy K, Sahlberg, Kristine K, Børresen‐Dale, Anne‐Lise, Gram, Inger Torhild, Olsen, Karina Standahl, Engebråten, Olav, Naume, Bjørn, Geisler, Jürgen, OSBREAC, Alnæs, Grethe I Grenaker, Colonna, Sarah V, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Dennis, Joe, Devilee, Peter, Dörk, Thilo, Dunning, Alison M, Dwek, Miriam, Easton, Douglas F, Eccles, Diana M, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Fehm, Tanja N, Figueroa, Jonine D, Flyger, Henrik, Gabrielson, Marike, Gago‐Dominguez, Manuela, García‐Closas, Montserrat, García‐Sáenz, José A, Genkinger, Jeanine, Grassmann, Felix, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Hamann, Ute, Harrington, Patricia A, Hartikainen, Jaana M, Hoppe, Reiner, Hopper, John L, Houlston, Richard S, Howell, Anthony, Clarke, Christine, Marsh, Deborah, Scott, Rodney, Baxter, Robert, Yip, Desmond, Carpenter, Jane, Davis, Alison, Pathmanathan, Nirmala, Simpson, Peter, Graham, J Dinny, Sachchithananthan, Mythily, Amor, David, Andrews, Lesley, Antill, Yoland, Balleine, Rosemary, Beesley, Jonathan, Bennett, Ian, Bogwitz, Michael, Botes, Leon, Brennan, Meagan, Brown, Melissa, Buckley, Michael, Burke, Jo, Butow, Phyllis, Caldon, Liz, Campbell, Ian, Cao, Michelle, Chakrabarti, Anannya, Chauhan, Deepa, Chauhan, Manisha, Chenevix‐Trench, Georgia, Christian, Alice, Cohen, Paul, Colley, Alison, Crook, Ashley, Cui, James, Courtney, Eliza, Cummings, Margaret, and Dawson, Sarah‐Jane

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Women's Health, Breast Cancer, Clinical Research, Prevention, Cancer, Female, Humans, Breast Neoplasms, Checkpoint Kinase 2, Genetic Predisposition to Disease, Germ-Line Mutation, Heterozygote, Proportional Hazards Models, CHEK2 c.1100delC germline genetic variant, contralateral breast cancer risk, radiotherapy, survival, systemic treatment, NBCS Collaborators, ABCTB Investigators, kConFab Investigators, Biochemistry and Cell Biology, Oncology and carcinogenesis
Abstract

BackgroundBreast cancer (BC) patients with a germline CHEK2 c.1100delC variant have an increased risk of contralateral BC (CBC) and worse BC-specific survival (BCSS) compared to non-carriers.AimTo assessed the associations of CHEK2 c.1100delC, radiotherapy, and systemic treatment with CBC risk and BCSS.MethodsAnalyses were based on 82,701 women diagnosed with a first primary invasive BC including 963 CHEK2 c.1100delC carriers; median follow-up was 9.1 years. Differential associations with treatment by CHEK2 c.1100delC status were tested by including interaction terms in a multivariable Cox regression model. A multi-state model was used for further insight into the relation between CHEK2 c.1100delC status, treatment, CBC risk and death.ResultsThere was no evidence for differential associations of therapy with CBC risk by CHEK2 c.1100delC status. The strongest association with reduced CBC risk was observed for the combination of chemotherapy and endocrine therapy [HR (95% CI): 0.66 (0.55-0.78)]. No association was observed with radiotherapy. Results from the multi-state model showed shorter BCSS for CHEK2 c.1100delC carriers versus non-carriers also after accounting for CBC occurrence [HR (95% CI): 1.30 (1.09-1.56)].ConclusionSystemic therapy was associated with reduced CBC risk irrespective of CHEK2 c.1100delC status. Moreover, CHEK2 c.1100delC carriers had shorter BCSS, which appears not to be fully explained by their CBC risk.

Published
2023

3. 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

4. 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

5. 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

6. 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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7. 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

8. 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

9. 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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11. Mosquito control exposures and breast cancer risk: analysis of 1071 cases and 2096 controls from the Ghana Breast Health Study

Author

Olivos, Naomie, Banta, Jim E., Spencer-Hwang, Rhonda, Ansong, Daniel, Beane Freeman, Laura E., Clegg-Lamptey, Joe-Nat, Wiafe-Addai, Beatrice, Edusei, Lawrence, Adjei, Ernest, Titiloye, Nicholas, Dedey, Florence, Aitpillah, Francis, Oppong, Joseph, Vanderpuye, Verna, Osei-Bonsu, Ernest, Ahearn, Thomas U., Biritwum, Richard, Yarney, Joel, Awuah, Baffour, Nyarko, Kofi, Garcia-Closas, Montserrat, Abubakar, Mustapha, Brinton, Louise A., Figueroa, Jonine D., and Wiafe, Seth

Published
2023
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14. Associations of fecal microbial profiles with breast cancer and nonmalignant breast disease in the Ghana Breast Health Study

Author

Byrd, Doratha A, Vogtmann, Emily, Wu, Zeni, Han, Yongli, Wan, Yunhu, Clegg‐Lamptey, Joe‐Nat, Yarney, Joel, Wiafe‐Addai, Beatrice, Wiafe, Seth, Awuah, Baffour, Ansong, Daniel, Nyarko, Kofi, Hullings, Autumn G, Hua, Xing, Ahearn, Thomas, Goedert, James J, Shi, Jianxin, Knight, Rob, Figueroa, Jonine D, Brinton, Louise A, Garcia‐Closas, Montserrat, and Sinha, Rashmi

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Breast Cancer, Aging, Cancer, Good Health and Well Being, Adult, Aged, Bacteria, Breast Diseases, Breast Neoplasms, Case-Control Studies, DNA, Bacterial, DNA, Ribosomal, Feces, Female, Gastrointestinal Microbiome, Ghana, High-Throughput Nucleotide Sequencing, Humans, Logistic Models, Middle Aged, Odds Ratio, Phylogeny, RNA, Ribosomal, 16S, Sequence Analysis, DNA, Young Adult, breast cancer, microbiome, nonmalignant breast diseases, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

The gut microbiota may play a role in breast cancer etiology by regulating hormonal, metabolic and immunologic pathways. We investigated associations of fecal bacteria with breast cancer and nonmalignant breast disease in a case-control study conducted in Ghana, a country with rising breast cancer incidence and mortality. To do this, we sequenced the V4 region of the 16S rRNA gene to characterize bacteria in fecal samples collected at the time of breast biopsy (N = 379 breast cancer cases, N = 102 nonmalignant breast disease cases, N = 414 population-based controls). We estimated associations of alpha diversity (observed amplicon sequence variants [ASVs], Shannon index, and Faith's phylogenetic diversity), beta diversity (Bray-Curtis and unweighted/weighted UniFrac distance), and the presence and relative abundance of select taxa with breast cancer and nonmalignant breast disease using multivariable unconditional polytomous logistic regression. All alpha diversity metrics were strongly, inversely associated with odds of breast cancer and for those in the highest relative to lowest tertile of observed ASVs, the odds ratio (95% confidence interval) was 0.21 (0.13-0.36; Ptrend

Published
2021

16. The impact of coding germline variants on contralateral breast cancer risk and survival

Author

Sahlberg, Kristine K., Børresen-Dale, Anne-Lise, Gram, Inger Torhild, Olsen, Karina Standahl, Engebråten, Olav, Naume, Bjørn, Geisler, Jürgen, OSBREAC, Grenaker Alnæs, Grethe I., Amor, David, Andrews, Lesley, Antill, Yoland, Balleine, Rosemary, Beesley, Jonathan, Bennett, Ian, Bogwitz, Michael, Botes, Leon, Brennan, Meagan, Brown, Melissa, Buckley, Michael, Burke, Jo, Butow, Phyllis, Caldon, Liz, Campbell, Ian, Cao, Michelle, Chakrabarti, Anannya, Chauhan, Deepa, Chauhan, Manisha, Chenevix-Trench, Georgia, Christian, Alice, Cohen, Paul, Colley, Alison, Crook, Ashley, Cui, James, Courtney, Eliza, Cummings, Margaret, Dawson, Sarah-Jane, DeFazio, Anna, Delatycki, Martin, Dickson, Rebecca, Dixon, Joanne, Edkins, Ted, Edwards, Stacey, Farshid, Gelareh, Fellows, Andrew, Fenton, Georgina, Field, Michael, Flanagan, James, Fong, Peter, Forrest, Laura, Fox, Stephen, French, Juliet, Friedlander, Michael, Gaff, Clara, Gattas, Mike, George, Peter, Greening, Sian, Harris, Marion, Hart, Stewart, Hayward, Nick, Hopper, John, Hoskins, Cass, Hunt, Clare, James, Paul, Jenkins, Mark, Kidd, Alexa, Kirk, Judy, Koehler, Jessica, Kollias, James, Lakhani, Sunil, Lawrence, Mitchell, Lee, Jason, Li, Shuai, Lindeman, Geoff, Lipton, Lara, Lobb, Liz, Loi, Sherene, Mann, Graham, Marsh, Deborah, McLachlan, Sue Anne, Meiser, Bettina, Milne, Roger, Nightingale, Sophie, O'Connell, Shona, O'Sullivan, Sarah, Ortega, David Gallego, Pachter, Nick, Pang, Jia-Min, Pathak, Gargi, Patterson, Briony, Pearn, Amy, Phillips, Kelly, Pieper, Ellen, Ramus, Susan, Rickard, Edwina, Robinson, Bridget, Saleh, Mona, Skandarajah, Anita, Salisbury, Elizabeth, Saunders, Christobel, Saunus, Jodi, Scott, Rodney, Scott, Clare, Sexton, Adrienne, Shelling, Andrew, Simpson, Peter, Southey, Melissa, Spurdle, Amanda, Taylor, Jessica, Taylor, Renea, Thorne, Heather, Trainer, Alison, Tucker, Kathy, Visvader, Jane, Walker, Logan, Williams, Rachael, Winship, Ingrid, Young, Mary Ann, Zaheed, Milita, Morra, Anna, Mavaddat, Nasim, Muranen, Taru A., Ahearn, Thomas U., Allen, Jamie, Andrulis, Irene L., Auvinen, Päivi, Becher, Heiko, Behrens, Sabine, Blomqvist, Carl, Bojesen, Stig E., Bolla, Manjeet K., Brauch, Hiltrud, Camp, Nicola J., Carvalho, Sara, Castelao, Jose E., Cessna, Melissa H., Chang-Claude, Jenny, Czene, Kamila, Decker, Brennan, Dennis, Joe, Dörk, Thilo, Dorling, Leila, Dunning, Alison M., Ekici, Arif B., Eriksson, Mikael, Evans, D. Gareth, Fasching, Peter A., Figueroa, Jonine D., Flyger, Henrik, Gago-Dominguez, Manuela, García-Closas, Montserrat, Geurts-Giele, Willemina R.R., Giles, Graham G., Guénel, Pascal, Gündert, Melanie, Hahnen, Eric, Hall, Per, Hamann, Ute, Harrington, Patricia A., He, Wei, Heikkilä, Päivi, Hooning, Maartje J., Hoppe, Reiner, Howell, Anthony, Humphreys, Keith, Jakubowska, Anna, Jung, Audrey Y., Keeman, Renske, Kristensen, Vessela N., Lubiński, Jan, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Mavroudis, Dimitrios, Milne, Roger L., Mulligan, Anna Marie, Newman, William G., Park-Simon, Tjoung-Won, Peterlongo, Paolo, Pharoah, Paul D.P., Rhenius, Valerie, Saloustros, Emmanouil, Sawyer, Elinor J., Schmutzler, Rita K., Shah, Mitul, Spurdle, Amanda B., Tomlinson, Ian, Truong, Thérèse, van Veen, Elke M., Vreeswijk, Maaike P.G., Wang, Qin, Wendt, Camilla, Yang, Xiaohong R., Nevanlinna, Heli, Devilee, Peter, Easton, Douglas F., and Schmidt, Marjanka K.

Published
2023
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18. Correction: 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, B. A. M., 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 D. P., 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.

Published
2022
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20. Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

Author

Machiela, Mitchell J, Zhou, Weiyin, Karlins, Eric, Sampson, Joshua N, Freedman, Neal D, Yang, Qi, Hicks, Belynda, Dagnall, Casey, Hautman, Christopher, Jacobs, Kevin B, Abnet, Christian C, Aldrich, Melinda C, Amos, Christopher, Amundadottir, Laufey T, Arslan, Alan A, Beane-Freeman, Laura E, Berndt, Sonja I, Black, Amanda, Blot, William J, Bock, Cathryn H, Bracci, Paige M, Brinton, Louise A, Bueno-de-Mesquita, H Bas, Burdett, Laurie, Buring, Julie E, Butler, Mary A, Canzian, Federico, Carreon, Tania, Chaffee, Kari G, Chang, I-Shou, Chatterjee, Nilanjan, Chen, Chu, Chen, Constance, Chen, Kexin, Chung, Charles C, Cook, Linda S, Bou, Marta Crous, Cullen, Michael, Davis, Faith G, De Vivo, Immaculata, Ding, Ti, Doherty, Jennifer, Duell, Eric J, Epstein, Caroline G, Fan, Jin-Hu, Figueroa, Jonine D, Fraumeni, Joseph F, Friedenreich, Christine M, Fuchs, Charles S, Gallinger, Steven, Gao, Yu-Tang, Gapstur, Susan M, Garcia-Closas, Montserrat, Gaudet, Mia M, Gaziano, J Michael, Giles, Graham G, Gillanders, Elizabeth M, Giovannucci, Edward L, Goldin, Lynn, Goldstein, Alisa M, Haiman, Christopher A, Hallmans, Goran, Hankinson, Susan E, Harris, Curtis C, Henriksson, Roger, Holly, Elizabeth A, Hong, Yun-Chul, Hoover, Robert N, Hsiung, Chao A, Hu, Nan, Hu, Wei, Hunter, David J, Hutchinson, Amy, Jenab, Mazda, Johansen, Christoffer, Khaw, Kay-Tee, Kim, Hee Nam, Kim, Yeul Hong, Kim, Young Tae, Klein, Alison P, Klein, Robert, Koh, Woon-Puay, Kolonel, Laurence N, Kooperberg, Charles, Kraft, Peter, Krogh, Vittorio, Kurtz, Robert C, LaCroix, Andrea, Lan, Qing, Landi, Maria Teresa, Le Marchand, Loic, Li, Donghui, Liang, Xiaolin, Liao, Linda M, Lin, Dongxin, Liu, Jianjun, Lissowska, Jolanta, Lu, Lingeng, Magliocco, Anthony M, and Malats, Nuria

Published
2016

21. Identification of a novel susceptibility locus at 13q34 and refinement of the 20p12.2 region as a multi-signal locus associated with bladder cancer risk in individuals of European ancestry

Author

Figueroa, Jonine D, Middlebrooks, Candace D, Banday, A Rouf, Ye, Yuanqing, Garcia-Closas, Montserrat, Chatterjee, Nilanjan, Koutros, Stella, Kiemeney, Lambertus A, Rafnar, Thorunn, Bishop, Timothy, Furberg, Helena, Matullo, Giuseppe, Golka, Klaus, Gago-Dominguez, Manuela, Taylor, Jack A, Fletcher, Tony, Siddiq, Afshan, Cortessis, Victoria K, Kooperberg, Charles, Cussenot, Olivier, Benhamou, Simone, Prescott, Jennifer, Porru, Stefano, Dinney, Colin P, Malats, Núria, Baris, Dalsu, Purdue, Mark P, Jacobs, Eric J, Albanes, Demetrius, Wang, Zhaoming, Chung, Charles C, Vermeulen, Sita H, Aben, Katja K, Galesloot, Tessel E, Thorleifsson, Gudmar, Sulem, Patrick, Stefansson, Kari, Kiltie, Anne E, Harland, Mark, Teo, Mark, Offit, Kenneth, Vijai, Joseph, Bajorin, Dean, Kopp, Ryan, Fiorito, Giovanni, Guarrera, Simonetta, Sacerdote, Carlotta, Selinski, Silvia, Hengstler, Jan G, Gerullis, Holger, Ovsiannikov, Daniel, Blaszkewicz, Meinolf, Castelao, Jose Esteban, Calaza, Manuel, Martinez, Maria Elena, Cordeiro, Patricia, Xu, Zongli, Panduri, Vijayalakshmi, Kumar, Rajiv, Gurzau, Eugene, Koppova, Kvetoslava, Bueno-De-Mesquita, H Bas, Ljungberg, Börje, Clavel-Chapelon, Françoise, Weiderpass, Elisabete, Krogh, Vittorio, Dorronsoro, Miren, Travis, Ruth C, Tjønneland, Anne, Brennan, Paul, Chang-Claude, Jenny, Riboli, Elio, Conti, David, Stern, Marianna C, Pike, Malcolm C, Van Den Berg, David, Yuan, Jian-Min, Hohensee, Chancellor, Jeppson, Rebecca P, Cancel-Tassin, Geraldine, Roupret, Morgan, Comperat, Eva, Turman, Constance, De Vivo, Immaculata, Giovannucci, Edward, Hunter, David J, Kraft, Peter, Lindstrom, Sara, Carta, Angela, Pavanello, Sofia, Arici, Cecilia, Mastrangelo, Giuseppe, Kamat, Ashish M, Zhang, Liren, Gong, Yilei, Pu, Xia, Hutchinson, Amy, Burdett, Laurie, Wheeler, William A, and Karagas, Margaret R

Subjects
Cancer, Prevention, Human Genome, Genetics, Biotechnology, Urologic Diseases, Aetiology, 2.1 Biological and endogenous factors, Biomarkers, Tumor, Case-Control Studies, Chromosomes, Human, Pair 13, Chromosomes, Human, Pair 20, Female, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Polymorphism, Single Nucleotide, Risk Factors, Urinary Bladder Neoplasms, White People, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 × 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 × 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 × 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P ≤ 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer.

Published
2016

23. Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types

Author

Sampson, Joshua N, Wheeler, William A, Yeager, Meredith, Panagiotou, Orestis, Wang, Zhaoming, Berndt, Sonja I, Lan, Qing, Abnet, Christian C, Amundadottir, Laufey T, Figueroa, Jonine D, Landi, Maria Teresa, Mirabello, Lisa, Savage, Sharon A, Taylor, Philip R, De Vivo, Immaculata, McGlynn, Katherine A, Purdue, Mark P, Rajaraman, Preetha, Adami, Hans-Olov, Ahlbom, Anders, Albanes, Demetrius, Amary, Maria Fernanda, An, She-Juan, Andersson, Ulrika, Andriole, Gerald, Andrulis, Irene L, Angelucci, Emanuele, Ansell, Stephen M, Arici, Cecilia, Armstrong, Bruce K, Arslan, Alan A, Austin, Melissa A, Baris, Dalsu, Barkauskas, Donald A, Bassig, Bryan A, Becker, Nikolaus, Benavente, Yolanda, Benhamou, Simone, Berg, Christine, Van Den Berg, David, Bernstein, Leslie, Bertrand, Kimberly A, Birmann, Brenda M, Black, Amanda, Boeing, Heiner, Boffetta, Paolo, Boutron-Ruault, Marie-Christine, Bracci, Paige M, Brinton, Louise, Brooks-Wilson, Angela R, Bueno-de-Mesquita, H Bas, Burdett, Laurie, Buring, Julie, Butler, Mary Ann, Cai, Qiuyin, Cancel-Tassin, Geraldine, Canzian, Federico, Carrato, Alfredo, Carreon, Tania, Carta, Angela, Chan, John KC, Chang, Ellen T, Chang, Gee-Chen, Chang, I-Shou, Chang, Jiang, Chang-Claude, Jenny, Chen, Chien-Jen, Chen, Chih-Yi, Chen, Chu, Chen, Chung-Hsing, Chen, Constance, Chen, Hongyan, Chen, Kexin, Chen, Kuan-Yu, Chen, Kun-Chieh, Chen, Ying, Chen, Ying-Hsiang, Chen, Yi-Song, Chen, Yuh-Min, Chien, Li-Hsin, Chirlaque, María-Dolores, Choi, Jin Eun, Choi, Yi Young, Chow, Wong-Ho, Chung, Charles C, Clavel, Jacqueline, Clavel-Chapelon, Françoise, Cocco, Pierluigi, Colt, Joanne S, Comperat, Eva, Conde, Lucia, Connors, Joseph M, Conti, David, Cortessis, Victoria K, Cotterchio, Michelle, Cozen, Wendy, Crouch, Simon, Crous-Bou, Marta, Cussenot, Olivier, and Davis, Faith G

Subjects
Tobacco, Clinical Research, Urologic Diseases, Lung, Genetics, Rare Diseases, Lung Cancer, Human Genome, Hematology, Cancer, Tobacco Smoke and Health, Prevention, Lymphoma, Adult, Aged, Asian People, Bone Neoplasms, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Kidney Neoplasms, Leukemia, Lymphocytic, Chronic, B-Cell, Lung Neoplasms, Lymphoma, Large B-Cell, Diffuse, Male, Middle Aged, Neoplasms, Osteosarcoma, Polymorphism, Single Nucleotide, Smoking, Testicular Neoplasms, Tissue Array Analysis, Urinary Bladder Neoplasms, White People, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

BackgroundStudies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.MethodsBetween 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.ResultsGWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.ConclusionOur results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.

Published
2015

24. Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for Thirteen Cancer Types.

Author

Sampson, Joshua N, Wheeler, William A, Yeager, Meredith, Panagiotou, Orestis, Wang, Zhaoming, Berndt, Sonja I, Lan, Qing, Abnet, Christian C, Amundadottir, Laufey T, Figueroa, Jonine D, Landi, Maria Teresa, Mirabello, Lisa, Savage, Sharon A, Taylor, Philip R, De Vivo, Immaculata, McGlynn, Katherine A, Purdue, Mark P, Rajaraman, Preetha, Adami, Hans-Olov, Ahlbom, Anders, Albanes, Demetrius, Amary, Maria Fernanda, An, She-Juan, Andersson, Ulrika, Andriole, Gerald, Andrulis, Irene L, Angelucci, Emanuele, Ansell, Stephen M, Arici, Cecilia, Armstrong, Bruce K, Arslan, Alan A, Austin, Melissa A, Baris, Dalsu, Barkauskas, Donald A, Bassig, Bryan A, Becker, Nikolaus, Benavente, Yolanda, Benhamou, Simone, Berg, Christine, Van Den Berg, David, Bernstein, Leslie, Bertrand, Kimberly A, Birmann, Brenda M, Black, Amanda, Boeing, Heiner, Boffetta, Paolo, Boutron-Ruault, Marie-Christine, Bracci, Paige M, Brinton, Louise, Brooks-Wilson, Angela R, Bueno-de-Mesquita, H Bas, Burdett, Laurie, Buring, Julie, Butler, Mary Ann, Cai, Qiuyin, Cancel-Tassin, Geraldine, Canzian, Federico, Carrato, Alfredo, Carreon, Tania, Carta, Angela, Chan, John KC, Chang, Ellen T, Chang, Gee-Chen, Chang, I-Shou, Chang, Jiang, Chang-Claude, Jenny, Chen, Chien-Jen, Chen, Chih-Yi, Chen, Chu, Chen, Chung-Hsing, Chen, Constance, Chen, Hongyan, Chen, Kexin, Chen, Kuan-Yu, Chen, Kun-Chieh, Chen, Ying, Chen, Ying-Hsiang, Chen, Yi-Song, Chen, Yuh-Min, Chien, Li-Hsin, Chirlaque, María-Dolores, Choi, Jin Eun, Choi, Yi Young, Chow, Wong-Ho, Chung, Charles C, Clavel, Jacqueline, Clavel-Chapelon, Françoise, Cocco, Pierluigi, Colt, Joanne S, Comperat, Eva, Conde, Lucia, Connors, Joseph M, Conti, David, Cortessis, Victoria K, Cotterchio, Michelle, Cozen, Wendy, Crouch, Simon, Crous-Bou, Marta, Cussenot, Olivier, and Davis, Faith G

Subjects
Humans, Neoplasms, Osteosarcoma, Bone Neoplasms, Testicular Neoplasms, Lung Neoplasms, Kidney Neoplasms, Genetic Predisposition to Disease, Tissue Array Analysis, Smoking, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, Asian Continental Ancestry Group, European Continental Ancestry Group, Female, Male, Urinary Bladder Neoplasms, Leukemia, Lymphocytic, Chronic, B-Cell, Lymphoma, Large B-Cell, Diffuse, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Leukemia, Lymphocytic, Chronic, B-Cell, Lymphoma, Large B-Cell, Diffuse, Oncology And Carcinogenesis, Oncology & Carcinogenesis, Oncology and Carcinogenesis
Abstract

BackgroundStudies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.MethodsBetween 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.ResultsGWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.ConclusionOur results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.

Published
2015

25. Characterization of Large Structural Genetic Mosaicism in Human Autosomes

Author

Machiela, Mitchell J, Zhou, Weiyin, Sampson, Joshua N, Dean, Michael C, Jacobs, Kevin B, Black, Amanda, Brinton, Louise A, Chang, I-Shou, Chen, Chu, Chen, Constance, Chen, Kexin, Cook, Linda S, Bou, Marta Crous, De Vivo, Immaculata, Doherty, Jennifer, Friedenreich, Christine M, Gaudet, Mia M, Haiman, Christopher A, Hankinson, Susan E, Hartge, Patricia, Henderson, Brian E, Hong, Yun-Chul, Hosgood, H Dean, Hsiung, Chao A, Hu, Wei, Hunter, David J, Jessop, Lea, Kim, Hee Nam, Kim, Yeul Hong, Kim, Young Tae, Klein, Robert, Kraft, Peter, Lan, Qing, Lin, Dongxin, Liu, Jianjun, Le Marchand, Loic, Liang, Xiaolin, Lissowska, Jolanta, Lu, Lingeng, Magliocco, Anthony M, Matsuo, Keitaro, Olson, Sara H, Orlow, Irene, Park, Jae Yong, Pooler, Loreall, Prescott, Jennifer, Rastogi, Radhai, Risch, Harvey A, Schumacher, Fredrick, Seow, Adeline, Setiawan, Veronica Wendy, Shen, Hongbing, Sheng, Xin, Shin, Min-Ho, Shu, Xiao-Ou, Berg, David VanDen, Wang, Jiu-Cun, Wentzensen, Nicolas, Wong, Maria Pik, Wu, Chen, Wu, Tangchun, Wu, Yi-Long, Xia, Lucy, Yang, Hannah P, Yang, Pan-Chyr, Zheng, Wei, Zhou, Baosen, Abnet, Christian C, Albanes, Demetrius, Aldrich, Melinda C, Amos, Christopher, Amundadottir, Laufey T, Berndt, Sonja I, Blot, William J, Bock, Cathryn H, Bracci, Paige M, Burdett, Laurie, Buring, Julie E, Butler, Mary A, Carreón, Tania, Chatterjee, Nilanjan, Chung, Charles C, Cook, Michael B, Cullen, Michael, Davis, Faith G, Ding, Ti, Duell, Eric J, Epstein, Caroline G, Fan, Jin-Hu, Figueroa, Jonine D, Fraumeni, Joseph F, Freedman, Neal D, Fuchs, Charles S, Gao, Yu-Tang, Gapstur, Susan M, Patiño-Garcia, Ana, Garcia-Closas, Montserrat, Gaziano, J Michael, Giles, Graham G, and Gillanders, Elizabeth M

Subjects
Biological Sciences, Genetics, Human Genome, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Aged, Chromosome Aberrations, Female, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Mosaicism, Neoplasms, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.

Published
2015

28. Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33

Author

Wang, Zhaoming, Zhu, Bin, Zhang, Mingfeng, Parikh, Hemang, Jia, Jinping, Chung, Charles C, Sampson, Joshua N, Hoskins, Jason W, Hutchinson, Amy, Burdette, Laurie, Ibrahim, Abdisamad, Hautman, Christopher, Raj, Preethi S, Abnet, Christian C, Adjei, Andrew A, Ahlbom, Anders, Albanes, Demetrius, Allen, Naomi E, Ambrosone, Christine B, Aldrich, Melinda, Amiano, Pilar, Amos, Christopher, Andersson, Ulrika, Andriole, Gerald, Andrulis, Irene L, Arici, Cecilia, Arslan, Alan A, Austin, Melissa A, Baris, Dalsu, Barkauskas, Donald A, Bassig, Bryan A, Beane Freeman, Laura E, Berg, Christine D, Berndt, Sonja I, Bertazzi, Pier Alberto, Biritwum, Richard B, Black, Amanda, Blot, William, Boeing, Heiner, Boffetta, Paolo, Bolton, Kelly, Boutron-Ruault, Marie-Christine, Bracci, Paige M, Brennan, Paul, Brinton, Louise A, Brotzman, Michelle, Bueno-de-Mesquita, H Bas, Buring, Julie E, Butler, Mary Ann, Cai, Qiuyin, Cancel-Tassin, Geraldine, Canzian, Federico, Cao, Guangwen, Caporaso, Neil E, Carrato, Alfredo, Carreon, Tania, Carta, Angela, Chang, Gee-Chen, Chang, I-Shou, Chang-Claude, Jenny, Che, Xu, Chen, Chien-Jen, Chen, Chih-Yi, Chen, Chung-Hsing, Chen, Constance, Chen, Kuan-Yu, Chen, Yuh-Min, Chokkalingam, Anand P, Chu, Lisa W, Clavel-Chapelon, Francoise, Colditz, Graham A, Colt, Joanne S, Conti, David, Cook, Michael B, Cortessis, Victoria K, Crawford, E David, Cussenot, Olivier, Davis, Faith G, De Vivo, Immaculata, Deng, Xiang, Ding, Ti, Dinney, Colin P, Di Stefano, Anna Luisa, Diver, W Ryan, Duell, Eric J, Elena, Joanne W, Fan, Jin-Hu, Feigelson, Heather Spencer, Feychting, Maria, Figueroa, Jonine D, Flanagan, Adrienne M, Fraumeni, Joseph F, Freedman, Neal D, Fridley, Brooke L, Fuchs, Charles S, Gago-Dominguez, Manuela, Gallinger, Steven, Gao, Yu-Tang, Gapstur, Susan M, and Garcia-Closas, Montserrat

Subjects
Biological Sciences, Genetics, Cancer, Clinical Research, Human Genome, Prevention, Aetiology, 2.1 Biological and endogenous factors, Alleles, Chromosomes, Human, Pair 5, Computational Biology, DNA Methylation, Epigenesis, Genetic, Female, Gene Expression Regulation, Neoplastic, Gene Frequency, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Membrane Proteins, Neoplasm Proteins, Neoplasms, Odds Ratio, Polymorphism, Single Nucleotide, Risk, Telomerase, Medical and Health Sciences, Genetics & Heredity
Abstract

Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.

Published
2014

29. Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene‐Environment Interactions

Author

Schoeps, Anja, Rudolph, Anja, Seibold, Petra, Dunning, Alison M, Milne, Roger L, Bojesen, Stig E, Swerdlow, Anthony, Andrulis, Irene, Brenner, Hermann, Behrens, Sabine, Orr, Nicholas, Jones, Michael, Ashworth, Alan, Li, Jingmei, Cramp, Helen, Connley, Dan, Czene, Kamila, Darabi, Hatef, Chanock, Stephen J, Lissowska, Jolanta, Figueroa, Jonine D, Knight, Julia, Glendon, Gord, Mulligan, Anna M, Dumont, Martine, Severi, Gianluca, Baglietto, Laura, Olson, Janet, Vachon, Celine, Purrington, Kristen, Moisse, Matthieu, Neven, Patrick, Wildiers, Hans, Spurdle, Amanda, Kosma, Veli‐Matti, Kataja, Vesa, Hartikainen, Jaana M, Hamann, Ute, Ko, Yon‐Dschun, Dieffenbach, Aida K, Arndt, Volker, Stegmaier, Christa, Malats, Núria, Perez, José I Arias, Benítez, Javier, Flyger, Henrik, Nordestgaard, Børge G, Truong, Thérèse, Cordina‐Duverger, Emilie, Menegaux, Florence, dos Santos Silva, Isabel, Fletcher, Olivia, Johnson, Nichola, Häberle, Lothar, Beckmann, Matthias W, Ekici, Arif B, Braaf, Linde, Atsma, Femke, Broek, Alexandra J den, Makalic, Enes, Schmidt, Daniel F, Southey, Melissa C, Cox, Angela, Simard, Jacques, Giles, Graham G, Lambrechts, Diether, Mannermaa, Arto, Brauch, Hiltrud, Guénel, Pascal, Peto, Julian, Fasching, Peter A, Hopper, John, Flesch‐Janys, Dieter, Couch, Fergus, Chenevix‐Trench, Georgia, Pharoah, Paul DP, Garcia‐Closas, Montserrat, Schmidt, Marjanka K, Hall, Per, Easton, Douglas F, and Chang‐Claude, Jenny

Subjects
Biological Sciences, Genetics, Epidemiology, Health Services and Systems, Health Sciences, Genetic Testing, Human Genome, Prevention, Breast Cancer, Aging, Clinical Research, Cancer, Aetiology, 2.1 Biological and endogenous factors, Adolescent, Body Height, Body Mass Index, Breast Neoplasms, Chromosomes, Human, Pair 21, Chromosomes, Human, Pair 6, Female, Gene-Environment Interaction, Genetic Loci, Genetic Predisposition to Disease, Humans, Linkage Disequilibrium, Menarche, Middle Aged, Parity, Polymorphism, Single Nucleotide, Postmenopause, White People, breast cancer risk, gene-environment interaction, polymorphisms, body mass index, case-control study, Public Health and Health Services
Abstract

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10(-07)), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m(2) (OR = 1.26, 95% CI 1.15-1.38) but not in women with a BMI of 30 kg/m(2) or higher (OR = 0.89, 95% CI 0.72-1.11, P for interaction = 3.2 × 10(-05)). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.

Published
2014

30. Supplementary Table 3 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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31. Supplementary Table 1 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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32. FIGURE 2 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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33. Supplementary Figure 3 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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34. FIGURE 3 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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35. FIGURE 1 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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36. Supplementary Figure 5 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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37. Data from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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38. Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, additional, Byun, Jung S., additional, Dorsey, Tiffany H., additional, Yfantis, Harris G., additional, Ajao, Anuoluwapo, additional, Liu, Huaitian, additional, Pichardo, Margaret S., additional, Pichardo, Catherine M., additional, Harris, Alexandra R., additional, Yang, Xiaohong R., additional, Figueroa, Jonine D., additional, Sayed, Shahin, additional, Makokha, Francis W., additional, and Ambs, Stefan, additional

Published
2023
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39. Supplementary Figure 1 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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40. Supplementary Table 2 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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41. FIGURE 4 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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42. Supplementary Figure 2 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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43. Supplementary Figure 4 from Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Author

Tang, Wei, primary, Zhang, Flora, primary, Byun, Jung S., primary, Dorsey, Tiffany H., primary, Yfantis, Harris G., primary, Ajao, Anuoluwapo, primary, Liu, Huaitian, primary, Pichardo, Margaret S., primary, Pichardo, Catherine M., primary, Harris, Alexandra R., primary, Yang, Xiaohong R., primary, Figueroa, Jonine D., primary, Sayed, Shahin, primary, Makokha, Francis W., primary, and Ambs, Stefan, primary

Published
2023
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44. Co-observation of germline pathogenic variants in breast cancer predisposition genes: Results from analysis of the BRIDGES sequencing dataset

Author

Sahlberg, Kristine K., Børresen-Dale, Anne-Lise, Gram, Inger Torhild, Olsen, Karina Standahl, Engebråten, Olav, Naume, Bjørn, Geisler, Jürgen, OSBREAC, Grenaker Alnæs, Grethe I., Amor, David, Andrews, Lesley, Antill, Yoland, Balleine, Rosemary, Beesley, Jonathan, Bennett, Ian, Bogwitz, Michael, Bodek, Simon, Botes, Leon, Brennan, Meagan, Brown, Melissa, Buckley, Michael, Burke, Jo, Butow, Phyllis, Caldon, Liz, Campbell, Ian, Cao, Michelle, Chakrabarti, Anannya, Chauhan, Deepa, Chauhan, Manisha, Christian, Alice, Cohen, Paul, Colley, Alison, Crook, Ashley, Cui, James, Courtney, Eliza, Cummings, Margaret, Dawson, Sarah-Jane, deFazio, Anna, Delatycki, Martin, Dickson, Rebecca, Dixon, Joanne, Edwards, Stacey, Farshid, Gelareh, Fellows, Andrew, Fenton, Georgina, Field, Michael, Flanagan, James, Fong, Peter, Forrest, Laura, Fox, Stephen, French, Juliet, Friedlander, Michael, Gaff, Clara, Gattas, Mike, George, Peter, Greening, Sian, Harris, Marion, Hart, Stewart, Harraka, Philip, Hayward, Nick, Hopper, John, Hoskins, Cass, Hunt, Clare, Jenkins, Mark, Kidd, Alexa, Kirk, Judy, Koehler, Jessica, Kollias, James, Lakhani, Sunil, Lawrence, Mitchell, Lee, Jason, Li, Shuai, Lindeman, Geoff, Lippey, Jocelyn, Lipton, Lara, Lobb, Liz, Loi, Sherene, Mann, Graham, Marsh, Deborah, McLachlan, Sue Anne, Meiser, Bettina, Nightingale, Sophie, O'Connell, Shona, O'Sullivan, Sarah, Ortega, David Gallego, Pachter, Nick, Pang, Jia-Min, Pathak, Gargi, Patterson, Briony, Pearn, Amy, Phillips, Kelly, Pieper, Ellen, Ramus, Susan, Rickard, Edwina, Ragunathan, Abi, Robinson, Bridget, Saleh, Mona, Skandarajah, Anita, Salisbury, Elizabeth, Saunders, Christobel, Saunus, Jodi, Savas, Peter, Scott, Rodney, Scott, Clare, Sexton, Adrienne, Shaw, Joanne, Shelling, Andrew, Srinivasa, Shweta, Simpson, Peter, Taylor, Jessica, Taylor, Renea, Thorne, Heather, Trainer, Alison, Tucker, Kathy, Visvader, Jane, Walker, Logan, Williams, Rachael, Winship, Ingrid, Young, Mary Ann, Zaheed, Milita, Davidson, Aimee L., Michailidou, Kyriaki, Parsons, Michael T., Fortuno, Cristina, Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Naven, Marc, Abubakar, Mustapha, Ahearn, Thomas U., Alonso, M. Rosario, Andrulis, Irene L., Antoniou, Antonis C., Auvinen, Päivi, Behrens, Sabine, Bermisheva, Marina A., Bogdanova, Natalia V., Bojesen, Stig E., Brüning, Thomas, Byers, Helen J., Camp, Nicola J., Campbell, Archie, Castelao, Jose E., Cessna, Melissa H., Chang-Claude, Jenny, Chanock, Stephen J., Chenevix-Trench, Georgia, Collée, J. Margriet, Czene, Kamila, Dörk, Thilo, Eriksson, Mikael, Evans, D. Gareth, Fasching, Peter A., Figueroa, Jonine D., Flyger, Henrik, Gago-Dominguez, Manuela, García-Closas, Montserrat, Glendon, Gord, González-Neira, Anna, Grassmann, Felix, Gronwald, Jacek, Guénel, Pascal, Hadjisavvas, Andreas, Haeberle, Lothar, Hall, Per, Hamann, Ute, Hartman, Mikael, Ho, Peh Joo, Hooning, Maartje J., Hoppe, Reiner, Howell, Anthony, Jakubowska, Anna, Khusnutdinova, Elza K., Kristensen, Vessela N., Li, Jingmei, Lim, Joanna, Lindblom, Annika, Liu, Jenny, Lophatananon, Artitaya, Mannermaa, Arto, Mavroudis, Dimitrios A., Mensenkamp, Arjen R., Milne, Roger L., Muir, Kenneth R., Newman, William G., Obi, Nadia, Panayiotidis, Mihalis I., Park, Sue K., Park-Simon, Tjoung-Won, Peterlongo, Paolo, Radice, Paolo, Rashid, Muhammad U., Rhenius, Valerie, Saloustros, Emmanouil, Sawyer, Elinor J., Schmidt, Marjanka K., Seibold, Petra, Shah, Mitul, Southey, Melissa C., Teo, Soo Hwang, Tomlinson, Ian, Torres, Diana, Truong, Thérèse, van de Beek, Irma, van der Hout, Annemieke H., Wendt, Camilla C., Dunning, Alison M., Pharoah, Paul D.P., Devilee, Peter, Easton, Douglas F., James, Paul A., and Spurdle, Amanda B.

Published
2024
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45. Disinfection By-Products in Drinking Water and Bladder Cancer: Evaluation of Risk Modification by Common Genetic Polymorphisms in Two Case-Control Studies

Author

Freeman, Laura E. Beane, Kogevinas, Manolis, Cantor, Kenneth P., Villanueva, Cristina M., Prokunina-Olsson, Ludmila, Florez-Vargas, Oscar, Figueroa, Jonine D., Ward, Mary H., Koutros, Stella, Baris, Dalsu, Garcia-Closas, Montserrat, Schwenn, Molly, Johnson, Allison, Serra, Consol, Tardon, Adonina, Garcia-Closas, Reina, Carrato, Alfredo, Malats, Nuria, Karagas, Margaret R., Rothman, Nathaniel, and Silverman, Debra T.

Subjects
Toxicogenomics -- Research, Drinking water -- Contamination -- Health aspects, Bladder cancer -- Risk factors -- Environmental aspects -- Genetic aspects, Single nucleotide polymorphisms -- Health aspects, Trihalomethanes -- Environmental aspects -- Health aspects, Environmental issues, Health
Abstract

Background: By-products are formed when disinfectants react with organic matter in source water. The most common class of disinfection byproducts, trihalomethanes (THMs), have been linked to bladder cancer. Several studies have shown exposure-response associations with THMs in drinking water and bladder cancer risk. Few epidemiologic studies have evaluated gene-environment interactions for total THMs (TTHMs) with known bladder cancer susceptibility variants. Objectives: In this study, we investigated the combined effect on bladder cancer risk contributed by TTHMs, bladder cancer susceptibility variants identified through genome-wide association studies, and variants in several candidate genes. Methods: We analyzed data from two large case-control studies--the New England Bladder Cancer Study (n/n = 989 cases/1,162 controls), a population-based study, and the Spanish Bladder Cancer Study (n/n = 706 cases/772 controls), a hospital-based study. Because of differences in exposure distributions and metrics, we estimated effects of THMs and genetic variants within each study separately using adjusted logistic regression models to calculate odds ratios (ORs) and 95% confidence intervals (CI) with and without interaction terms, and then combined the results using meta-analysis. Results: Of the 16 loci showing strong evidence of association with bladder cancer, rs907611 at 11p15.5 [leukocyte- specific protein 1 (LSP1 region)] showed the strongest associations in the highest exposure category in each study, with evidence of interaction in both studies and in metaanalysis. In the highest exposure category, we observed OR= 1.66 (95% CI: 1.17, 2.34, p- trend = 0.005) for those with the rs907611-GG genotype and p-interaction = 0.02. No other genetic variants tested showed consistent evidence of interaction. Discussion: We found novel suggestive evidence for a multiplicative interaction between a putative bladder carcinogen, TTHMs, and genotypes of rs907611. Given the ubiquitous exposure to THMs, further work is needed to replicate and extend this finding and to understand potential molecular mechanisms. https://doi.org/10.1289/EHP9895, Introduction Worldwide, bladder cancer ranks as the ninth most common incident cancer and the 13th in mortality, with ~400,000 cases diagnosed each year. (1) Approximately 75% of incident cases occur [...]

Published
2022
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46. A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11

Author

Siddiq, Afshan, Couch, Fergus J, Chen, Gary K, Lindström, Sara, Eccles, Diana, Millikan, Robert C, Michailidou, Kyriaki, Stram, Daniel O, Beckmann, Lars, Rhie, Suhn Kyong, Ambrosone, Christine B, Aittomäki, Kristiina, Amiano, Pilar, Apicella, Carmel, Investigators, Australian Breast Cancer Tissue Bank, Baglietto, Laura, Bandera, Elisa V, Beckmann, Matthias W, Berg, Christine D, Bernstein, Leslie, Blomqvist, Carl, Brauch, Hiltrud, Brinton, Louise, Bui, Quang M, Buring, Julie E, Buys, Saundra S, Campa, Daniele, Carpenter, Jane E, Chasman, Daniel I, Chang-Claude, Jenny, Chen, Constance, Clavel-Chapelon, Françoise, Cox, Angela, Cross, Simon S, Czene, Kamila, Deming, Sandra L, Diasio, Robert B, Diver, W Ryan, Dunning, Alison M, Durcan, Lorraine, Ekici, Arif B, Fasching, Peter A, Study, Familial Breast Cancer, Feigelson, Heather Spencer, Fejerman, Laura, Figueroa, Jonine D, Fletcher, Olivia, Flesch-Janys, Dieter, Gaudet, Mia M, Consortium, The GENICA, Gerty, Susan M, Rodriguez-Gil, Jorge L, Giles, Graham G, van Gils, Carla H, Godwin, Andrew K, Graham, Nikki, Greco, Dario, Hall, Per, Hankinson, Susan E, Hartmann, Arndt, Hein, Rebecca, Heinz, Judith, Hoover, Robert N, Hopper, John L, Hu, Jennifer J, Huntsman, Scott, Ingles, Sue A, Irwanto, Astrid, Isaacs, Claudine, Jacobs, Kevin B, John, Esther M, Justenhoven, Christina, Kaaks, Rudolf, Kolonel, Laurence N, Coetzee, Gerhard A, Lathrop, Mark, Le Marchand, Loic, Lee, Adam M, Lee, I-Min, Lesnick, Timothy, Lichtner, Peter, Liu, Jianjun, Lund, Eiliv, Makalic, Enes, Martin, Nicholas G, McLean, Catriona A, Meijers-Heijboer, Hanne, Meindl, Alfons, Miron, Penelope, Monroe, Kristine R, Montgomery, Grant W, Müller-Myhsok, Bertram, Nickels, Stefan, Nyante, Sarah J, Olswold, Curtis, Overvad, Kim, Palli, Domenico, Park, Daniel J, Palmer, Julie R, and Pathak, Harsh

Subjects
Biological Sciences, Genetics, Clinical Research, Aging, Human Genome, Breast Cancer, Cancer, Aetiology, 2.1 Biological and endogenous factors, Breast Neoplasms, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Receptors, Estrogen, Australian Breast Cancer Tissue Bank Investigators, Familial Breast Cancer Study, GENICA Consortium, Medical and Health Sciences, Genetics & Heredity
Abstract

Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10(-5) in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10(-8)) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10(-6)) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10(-9)), and with both ER-positive (OR = 1.09; P = 1.5 × 10(-5)) and ER-negative (OR = 1.16, P = 2.5 × 10(-7)) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.

Published
2012

47. Associations of Circulating Estrogens and Estrogen Metabolites with Fecal and Oral Microbiome in Postmenopausal Women in the Ghana Breast Health Study

Author

Wu, Zeni, primary, Pfeiffer, Ruth M., additional, Byrd, Doratha A., additional, Wan, Yunhu, additional, Ansong, Daniel, additional, Clegg-Lamptey, Joe-Nat, additional, Wiafe-Addai, Beatrice, additional, Edusei, Lawrence, additional, Adjei, Ernest, additional, Titiloye, Nicholas, additional, Dedey, Florence, additional, Aitpillah, Francis, additional, Oppong, Joseph, additional, Vanderpuye, Verna, additional, Osei-Bonsu, Ernest, additional, Dagnall, Casey L., additional, Jones, Kristine, additional, Hutchinson, Amy, additional, Hicks, Belynda D., additional, Ahearn, Thomas U., additional, Knight, Rob, additional, Biritwum, Richard, additional, Yarney, Joel, additional, Wiafe, Seth, additional, Awuah, Baffour, additional, Nyarko, Kofi, additional, Garcia-Closas, Montserrat, additional, Sinha, Rashmi, additional, Figueroa, Jonine D., additional, Brinton, Louise A., additional, Trabert, Britton, additional, and Vogtmann, Emily, additional

Published
2023
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48. Polygenic risk score for the prediction of breast cancer is related to lesser terminal duct lobular unit involution of the breast

Author

Bodelon, Clara, Oh, Hannah, Derkach, Andriy, Sampson, Joshua N., Sprague, Brian L., Vacek, Pamela, Weaver, Donald L., Fan, Shaoqi, Palakal, Maya, Papathomas, Daphne, Xiang, Jackie, Patel, Deesha A., Linville, Laura, Clare, Susan E., Visscher, Daniel W., Mies, Carolyn, Hewitt, Stephen M., Brinton, Louise A., Storniolo, Anna Maria V., He, Chunyan, Chanock, Stephen J., Garcia-Closas, Montserrat, Gierach, Gretchen L., and Figueroa, Jonine D.

Published
2020
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