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1. 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

2. The effect of variable labels on deep learning models trained to predict breast density

Author

Squires, Steven, Harkness, Elaine F., Evans, D. Gareth, and Astley, Susan M.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Purpose: High breast density is associated with reduced efficacy of mammographic screening and increased risk of developing breast cancer. Accurate and reliable automated density estimates can be used for direct risk prediction and passing density related information to further predictive models. Expert reader assessments of density show a strong relationship to cancer risk but also inter-reader variation. The effect of label variability on model performance is important when considering how to utilise automated methods for both research and clinical purposes. Methods: We utilise subsets of images with density labels to train a deep transfer learning model which is used to assess how label variability affects the mapping from representation to prediction. We then create two end-to-end deep learning models which allow us to investigate the effect of label variability on the model representation formed. Results: We show that the trained mappings from representations to labels are altered considerably by the variability of reader scores. Training on labels with distribution variation removed causes the Spearman rank correlation coefficients to rise from $0.751\pm0.002$ to either $0.815\pm0.006$ when averaging across readers or $0.844\pm0.002$ when averaging across images. However, when we train different models to investigate the representation effect we see little difference, with Spearman rank correlation coefficients of $0.846\pm0.006$ and $0.850\pm0.006$ showing no statistically significant difference in the quality of the model representation with regard to density prediction. Conclusions: We show that the mapping between representation and mammographic density prediction is significantly affected by label variability. However, the effect of the label variability on the model representation is limited.

Published
2022

3. 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

4. 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

5. 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

7. Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420)

Author

Gareth Evans, D., McWilliams, Lorna, Astley, Susan, Brentnall, Adam R., Cuzick, Jack, Dobrashian, Richard, Duffy, Stephen W., Gorman, Louise S., Harkness, Elaine F., Harrison, Fiona, Harvie, Michelle, Jerrison, Andrew, Machin, Matthew, Maxwell, Anthony J., Howell, Sacha J., Wright, Stuart J., Payne, Katherine, Qureshi, Nadeem, Ruane, Helen, Southworth, Jake, Fox, Lynne, Bowers, Sarah, Hutchinson, Gillian, Thorpe, Emma, Ulph, Fiona, Woof, Victoria, Howell, Anthony, and French, David P.

Published
2023
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8. 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

9. 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

11. 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

12. Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Author

Zhang, Haoyu, Ahearn, Thomas U, Lecarpentier, Julie, Barnes, Daniel, Beesley, Jonathan, Qi, Guanghao, Jiang, Xia, O'Mara, Tracy A, Zhao, Ni, Bolla, Manjeet K, Dunning, Alison M, Dennis, Joe, Wang, Qin, Ful, Zumuruda Abu, Aittomäki, Kristiina, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Arun, Banu K, Auer, Paul L, Azzollini, Jacopo, Barrowdale, Daniel, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bialkowska, Katarzyna, Blanco, Ana, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bonanni, Bernardo, Bondavalli, Davide, Borg, Ake, Brauch, Hiltrud, Brenner, Hermann, Briceno, Ignacio, Broeks, Annegien, Brucker, Sara Y, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Byers, Helen, Caldés, Trinidad, Caligo, Maria A, Calvello, Mariarosaria, Campa, Daniele, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Christiaens, Melissa, Christiansen, Hans, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, Cornelissen, Sten, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Diez, Orland, Domchek, Susan M, Dörk, Thilo, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Foretova, Lenka, Fostira, Florentia, Friedman, Eitan, Frost, Debra, Gago-Dominguez, Manuela, Gapstur, Susan M, Garber, Judy, García-Sáenz, José A, Gaudet, Mia M, Gayther, Simon A, Giles, Graham G, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Greene, Mark H, Gronwald, Jacek, Guénel, Pascal, Häberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Hake, Christopher R, Hall, Per, Hamann, Ute, Harkness, Elaine F, Heemskerk-Gerritsen, Bernadette AM, and Hillemanns, Peter

Subjects
kConFab Investigators, ABCTB Investigators, EMBRACE Study, GEMO Study Collaborators, Humans, Breast Neoplasms, Genetic Predisposition to Disease, BRCA1 Protein, Case-Control Studies, Linkage Disequilibrium, Mutation, Female, Genome-Wide Association Study, Triple Negative Breast Neoplasms, Human Genome, Cancer, Prevention, Genetics, Breast Cancer, 2.1 Biological and endogenous factors, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P

Published
2020

13. Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium

Author

Kapoor, Pooja Middha, Lindström, Sara, Behrens, Sabine, Wang, Xiaoliang, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Dunning, Alison M, Pharoah, Paul DP, Schmidt, Marjanka K, Kraft, Peter, García-Closas, Montserrat, Easton, Douglas F, Milne, Roger L, Chang-Claude, Jenny, Ahearn, Thomas, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Freeman, Laura E Beane, Beckmann, Matthias W, Benitez, Javier, Bernstein, Leslie, Berrandou, Takiy, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brock, Ian W, Broeks, Annegien, Brooks-Wilson, Angela, Butterbach, Katja, Cai, Qiuyin, Campa, Daniele, Canzian, Federico, Carter, Brian D, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Cheng, Ting-Yuan David, Clarke, Christine L, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dai, James Y, Dite, Gillian S, Earp, H Shelton, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gapstur, Susan M, Gaudet, Mia M, Giles, Graham G, González-Neira, Anna, Grundy, Anne, Guénel, Pascal, Haeberle, Lothar, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E, Harkness, Elaine F, Harstad, Tricia, He, Wei, Heyworth, Jane, Hoover, Robert N, Hopper, John L, Humphreys, Keith, Hunter, David J, Marrón, Pablo Isidro, John, Esther M, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Krüger, Ute, Lambrechts, Diether, Le Marchand, Loic, Lee, Eunjung, Lejbkowicz, Flavio, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, Lo, Wing-Yee, and Makalic, Enes

Subjects
Genetics, Estrogen, Clinical Research, Cancer, Breast Cancer, Prevention, 2.1 Biological and endogenous factors, Aetiology, Alleles, Breast Neoplasms, Case-Control Studies, Europe, Factor XIII, Female, Gene-Environment Interaction, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Receptors, Estrogen, Risk Factors, White People, Breast Cancer Association Consortium, Europeans, Gene-environment interaction, breast cancer, epidemiology, risk factors, single nucleotide polymorphism, Statistics, Public Health and Health Services, Epidemiology
Abstract

BackgroundPrevious gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.MethodsAnalyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.ResultsNoteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.ConclusionsOverall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.

Published
2020

15. Genome-wide association study of germline variants and breast cancer-specific mortality.

Author

Escala-Garcia, Maria, Guo, Qi, Dörk, Thilo, Canisius, Sander, Keeman, Renske, Dennis, Joe, Beesley, Jonathan, Lecarpentier, Julie, Bolla, Manjeet K, Wang, Qin, Abraham, Jean, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Auer, Paul L, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bernstein, Leslie, Blomqvist, Carl, Boeckx, Bram, Bojesen, Stig E, Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Brenner, Hermann, Brentnall, Adam, Brinton, Louise, Broberg, Per, Brock, Ian W, Brucker, Sara Y, Burwinkel, Barbara, Caldas, Carlos, Caldés, Trinidad, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Carter, Brian D, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Chenevix-Trench, Georgia, Cheng, Ting-Yuan David, Chin, Suet-Feung, Clarke, Christine L, NBCS Collaborators, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, David G, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dunn, Janet A, Dunning, Alison M, Durcan, Lorraine, Dwek, Miriam, Earl, Helena M, Ekici, Arif B, Eliassen, A Heather, Ellberg, Carolina, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Figueroa, Jonine, Flesch-Janys, Dieter, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Galle, Eva, Gapstur, Susan M, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, George, Angela, Georgoulias, Vassilios, Giles, Graham G, Glendon, Gord, Goldgar, David E, González-Neira, Anna, Alnæs, Grethe I Grenaker, Grip, Mervi, Guénel, Pascal, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan, Harkness, Elaine F, Harrington, Patricia A, Hart, Steven N, Hartikainen, Jaana M, Hein, Alexander, Hillemanns, Peter, Hiller, Louise, and Holleczek, Bernd

Subjects
NBCS Collaborators, Chromosomes, Human, Pair 7, Humans, Breast Neoplasms, Receptors, Estrogen, Prognosis, Proportional Hazards Models, Bayes Theorem, Female, Genetic Variation, Genome-Wide Association Study, White People, Genetics, Breast Cancer, Human Genome, Cancer, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Oncology and Carcinogenesis, Public Health and Health Services, Oncology & Carcinogenesis
Abstract

BackgroundWe examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.MethodsMeta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).ResultsWe did not find any variant associated with breast cancer-specific mortality at P

Published
2019

16. Extended gene panel testing in lobular breast cancer

Author

van Veen, Elke M., Evans, D. Gareth, Harkness, Elaine F., Byers, Helen J., Ellingford, Jamie M., Woodward, Emma R., Bowers, Naomi L., Wallace, Andrew J., Howell, Sacha J., Howell, Anthony, Lalloo, Fiona, Newman, William G., and Smith, Miriam J.

Published
2022
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17. Breast cancer risks associated with missense variants in breast cancer susceptibility genes

Author

Dorling, Leila, Carvalho, Sara, Allen, Jamie, Parsons, Michael T., Fortuno, Cristina, González-Neira, Anna, Heijl, Stephan M., Adank, Muriel A., Ahearn, Thomas U., Andrulis, Irene L., Auvinen, Päivi, Becher, Heiko, Beckmann, Matthias W., Behrens, Sabine, Bermisheva, Marina, Bogdanova, Natalia V., Bojesen, Stig E., Bolla, Manjeet K., Bremer, Michael, Briceno, Ignacio, Camp, Nicola J., Campbell, Archie, Castelao, Jose E., Chang-Claude, Jenny, Chanock, Stephen J., Chenevix-Trench, Georgia, Collée, J. Margriet, Czene, Kamila, Dennis, Joe, Dörk, Thilo, Eriksson, Mikael, Evans, D. Gareth, Fasching, Peter A., Figueroa, Jonine, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, García-Closas, Montserrat, Giles, Graham G., Glendon, Gord, Guénel, Pascal, Gündert, Melanie, Hadjisavvas, Andreas, Hahnen, Eric, Hall, Per, Hamann, Ute, Harkness, Elaine F., Hartman, Mikael, Hogervorst, Frans B. L., Hollestelle, Antoinette, Hoppe, Reiner, Howell, Anthony, Jakubowska, Anna, Jung, Audrey, Khusnutdinova, Elza, Kim, Sung-Won, Ko, Yon-Dschun, Kristensen, Vessela N., Lakeman, Inge M. M., Li, Jingmei, Lindblom, Annika, Loizidou, Maria A., Lophatananon, Artitaya, Lubiński, Jan, Luccarini, Craig, Madsen, Michael J., Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Mavroudis, Dimitrios, Milne, Roger L., Mohd Taib, Nur Aishah, Muir, Kenneth, Nevanlinna, Heli, Newman, William G., Oosterwijk, Jan C., Park, Sue K., Peterlongo, Paolo, Radice, Paolo, Saloustros, Emmanouil, Sawyer, Elinor J., Schmutzler, Rita K., Shah, Mitul, Sim, Xueling, Southey, Melissa C., Surowy, Harald, Suvanto, Maija, Tomlinson, Ian, Torres, Diana, Truong, Thérèse, van Asperen, Christi J., Waltes, Regina, Wang, Qin, Yang, Xiaohong R., Pharoah, Paul D. P., Schmidt, Marjanka K., Benitez, Javier, Vroling, Bas, Dunning, Alison M., Teo, Soo Hwang, Kvist, Anders, de la Hoya, Miguel, Devilee, Peter, Spurdle, Amanda B., Vreeswijk, Maaike P. G., and Easton, Douglas F.

Published
2022
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19. Correction To: Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420)

Author

Gareth Evans, D., McWilliams, Lorna, Astley, Susan, Brentnall, Adam R., Cuzick, Jack, Dobrashian, Richard, Duffy, Stephen W., Gorman, Louise S., Harkness, Elaine F., Harrison, Fiona, Harvie, Michelle, Jerrison, Andrew, Machin, Matthew, Maxwell, Anthony J., Howell, Sacha J., Wright, Stuart J., Payne, Katherine, Qureshi, Nadeem, Ruane, Helen, Southworth, Jake, Fox, Lynne, Bowers, Sarah, Hutchinson, Gillian, Thorpe, Emma, Ulph, Fiona, Woof, Victoria, Howell, Anthony, and French, David P.

Published
2023
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22. Contrast enhanced mammography (CEM): is experience necessary? an inter and intra-reader agreement study for lesion classification and breast density

Author

Altokhais, Reham, primary, Eiada, Riham, additional, Khoumayies, Nuha, additional, Zeitouni, Leena, additional, Abunayyan, Deema, additional, Alfuraih, Abdulrahman, additional, Alghamdi, Bandar, additional, Alghamdi, Reem, additional, Harkness, Elaine F., additional, and Astley, Susan, additional

Published
2024
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26. Mainstreaming germline BRCA1/2 testing in non-mucinous epithelial ovarian cancer in the North West of England

Author

Flaum, Nicola, Morgan, Robert D., Burghel, George J., Bulman, Michael, Clamp, Andrew R., Hasan, Jurjees, Mitchell, Claire L., Badea, Doina, Moon, Sarah, Hogg, Martin, Hadjiyiannakis, Dennis, Clancy, Tara, Schlecht, Helene, Woodward, Emma R., Crosbie, Emma J., Edmondson, Richard J., Wallace, Andrew J., Jayson, Gordon C., Lalloo, Fiona I., Harkness, Elaine F., and Evans, D. Gareth R.

Published
2020
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28. Germline testing of BRCA1, BRCA2, PALB2 and CHEK2 c.1100delC in 1514 triple negative familial and isolated breast cancers from a single centre, with extended testing of ATM, RAD51C and RAD51D in over 400.

Author

Woodward, Emma R., Lalloo, Fiona, Forde, Claire, Pugh, Sarah, Burghel, George J., Schlecht, Helene, Harkness, Elaine F., Howell, Anthony, Howell, Sacha J., Gandhi, Ashu, and Evans, D. Gareth

Abstract

Background The identification of germline pathogenic gene variants (PGVs) in triple negative breast cancer (TNBC) is important to inform further primary cancer risk reduction and TNBC treatment strategies. We therefore investigated the contribution of breast cancer associated PGVs to familial and isolated invasive TNBC. Methods Outcomes of germline BRCA1, BRCA2 and CHEK2_c.1100delC testing were recorded in 1514 women (743--isolated, 771--familial), and for PALB2 in 846 women (541--isolated, 305--familial), with TNBC and smaller numbers for additional genes. Breast cancer free controls were identified from Predicting Risk Of Cancer At Screening and BRIDGES (Breast cancer RIsk after Diagnostic GEne Sequencing) studies. Results BRCA1_PGVs were detected in 52 isolated (7.0%) and 195 (25.3%) familial cases (isolated--OR=58.9, 95% CI: 16.6 to 247.0), BRCA2_PGVs in 21 (2.8%) isolated and 67 (8.7%) familial cases (isolated--OR=5.0, 95% CI: 2.3 to 11.2), PALB2_PGVs in 9 (1.7%) isolated and 12 (3.9%) familial cases (isolated--OR=8.8, 95% CI: 2.5 to 30.4) and CHEK2_c.1100delC in 0 isolated and 3 (0.45%) familial cases (isolated--OR=0.0, 95% CI: 0.00 to 2.11). BRCA1_PGV detection rate was >10% for all familial TNBC age groups and significantly higher for younger diagnoses (familial: <50 years, n=165/538 (30.7%); =50 years, n=30/233 (12.9%); p<0.0001). Women with a G3_TNBC were more likely to have a BRCA1_PGV as compared with a BRCA2 or PALB2_PGV (p<0.0001). 0/743 isolated TNBC had the CHEK2_c.1100delC PGV and 0/305 any ATM_PGV, but 2/240 (0.83%) had a RAD51D_PGV. Conclusion PGVs in BRCA1 are associated with G3_ TNBCs. Familial TNBCs and isolated TNBCs <30 years have a >10% likelihood of a PGV in BRCA1. BRCA1_ PGVs are associated with younger age of familial TNBC. There was no evidence for any increased risk of TNBC with CHEK2 or ATM PGVs. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Identifying the deficiencies of current diagnostic criteria for neurofibromatosis 2 using databases of 2777 individuals with molecular testing

Author

Evans, D. Gareth, King, Andrew T., Bowers, Naomi L., Tobi, Simon, Wallace, Andrew J., Perry, Mary, Anup, Raji, Lloyd, Simon K. L., Rutherford, Scott A., Hammerbeck-Ward, Charlotte, Pathmanaban, Omar N., Stapleton, Emma, Freeman, Simon R., Kellett, Mark, Halliday, Dorothy, Parry, Allyson, Gair, Juliette J., Axon, Patrick, Laitt, Roger, Thomas, Owen, Afridi, Shazia, Ferner, Rosalie E., Harkness, Elaine F., Smith, Miriam J., and The English Specialist NF2 Research Group

Published
2019
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31. Should We Adjust Visually Assessed Mammographic Density for Observer Variability?

Author

Harkness, Elaine F., Sergeant, Jamie C., Wilson, Mary, Beetles, Ursula, Gadde, Soujanya, Lim, Yit Y., Howell, Anthony, Evans, D. Gareth, Astley, Susan M., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Tingberg, Anders, editor, Lång, Kristina, editor, and Timberg, Pontus, editor

Published
2016
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32. Variations in Breast Density and Mammographic Risk Factors in Different Ethnic Groups

Author

Harkness, Elaine F., Bashir, Fatik, Foden, Philip, Bydder, Megan, Gadde, Soujanya, Wilson, Mary, Maxwell, Anthony, Hurley, Emma, Howell, Anthony, Evans, D. Gareth, Astley, Susan M., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Tingberg, Anders, editor, Lång, Kristina, editor, and Timberg, Pontus, editor

Published
2016
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33. Mammographic Density Over Time in Women With and Without Breast Cancer

Author

Humphrey, Abigail, Harkness, Elaine F., Moschidis, Emmanouil, Hurley, Emma, Foden, Philip, Bydder, Megan, Wilson, Mary, Gadde, Soujanya, Maxwell, Anthony, Lim, Yit Y., Beetles, Ursula, Howell, Anthony, Evans, D. Gareth, Astley, Susan M., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Tingberg, Anders, editor, Lång, Kristina, editor, and Timberg, Pontus, editor

Published
2016
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37. What are the benefits and harms of risk stratified screening as part of the NHS breast screening Programme? Study protocol for a multi-site non-randomised comparison of BC-predict versus usual screening (NCT04359420)

Author

French, David P., Astley, Susan, Brentnall, Adam R., Cuzick, Jack, Dobrashian, Richard, Duffy, Stephen W., Gorman, Louise S., Harkness, Elaine F., Harrison, Fiona, Harvie, Michelle, Howell, Anthony, Jerrison, Andrew, Machin, Matthew, Maxwell, Anthony J., McWilliams, Lorna, Payne, Katherine, Qureshi, Nadeem, Ruane, Helen, Sampson, Sarah, Stavrinos, Paula, Thorpe, Emma, Ulph, Fiona, van Staa, Tjeerd, Woof, Victoria, and Evans, D. Gareth

Published
2020
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40. Detection of pathogenic variants in breast cancer susceptibility genes in bilateral breast cancer

Author

Evans, D Gareth, primary, Burghel, George J, additional, Schlecht, Helene, additional, Harkness, Elaine F, additional, Gandhi, Ashu, additional, Howell, Sacha J, additional, Howell, Anthony, additional, Forde, Claire, additional, Lalloo, Fiona, additional, Newman, William G, additional, Smith, Miriam Jane, additional, and Woodward, Emma Roisin, additional

Published
2023
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41. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Author

Middha, Pooja K., 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, Thais, 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, Dugue, Pierre-Antoine, Eliassen, A. Heather, Eriksson, Mikael, Evans, D. Gareth, Fasching, Peter A., Figueroa, Jonine, Fletcher, Olivia, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Giles, Graham G., Gonzalez-Neira, Anna, Grassmann, Felix, Grundy, Anne, Guenel, Pascal, Haiman, Christopher A., Hakansson, 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, Jernstroem, 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 C., 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, Borge 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., Sandler, Dale P., Scott, Christopher G., Shah, Mitul T., Shu, Xiao-Ou, Smeets, Ann, Southey, Melissa C., Stone, Jennifer, Tamimi, Rulla M., Taylor, Jack A., Teras, Lauren R., Tomczyk, Katarzyna, Troester, Melissa A., Truong, Therese, Vachon, Celine M., Wang, Sophia S., Weinberg, Clarice R., Wildiers, Hans, Willett, Walter, Winham, Stacey J., Wolk, Alicja, Yang, Xiaohong, Zamora, M. Pilar, Zheng, Wei, Ziogas, Argyrios, Dunning, Alison M., Pharoah, Paul D. P., Garcia-Closas, Montserrat, Schmidt, Marjanka K., Kraft, Peter, Milne, Roger L., Lindstroem, Sara, Easton, Douglas F., Chang-Claude, Jenny, Middha, Pooja K., 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, Thais, 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, Dugue, Pierre-Antoine, Eliassen, A. Heather, Eriksson, Mikael, Evans, D. Gareth, Fasching, Peter A., Figueroa, Jonine, Fletcher, Olivia, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Giles, Graham G., Gonzalez-Neira, Anna, Grassmann, Felix, Grundy, Anne, Guenel, Pascal, Haiman, Christopher A., Hakansson, 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, Jernstroem, 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 C., 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, Borge 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., Sandler, Dale P., Scott, Christopher G., Shah, Mitul T., Shu, Xiao-Ou, Smeets, Ann, Southey, Melissa C., Stone, Jennifer, Tamimi, Rulla M., Taylor, Jack A., Teras, Lauren R., Tomczyk, Katarzyna, Troester, Melissa A., Truong, Therese, Vachon, Celine M., Wang, Sophia S., Weinberg, Clarice R., Wildiers, Hans, Willett, Walter, Winham, Stacey J., Wolk, Alicja, Yang, Xiaohong, Zamora, M. Pilar, Zheng, Wei, Ziogas, Argyrios, Dunning, Alison M., Pharoah, Paul D. P., Garcia-Closas, Montserrat, Schmidt, Marjanka K., Kraft, Peter, Milne, Roger L., Lindstroem, Sara, Easton, Douglas F., and Chang-Claude, Jenny

Abstract

Background Genome-wide studies of gene-environment interactions (GxE) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide GxE analysis of similar to 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer. Methods Analyses 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. Results Assuming a 1 x 10(-5) prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94). Conclusions Overall, the contribution of GxE interactions to the heritability of breast cancer is very small. At the population level, multiplicative GxE interactions do not make an important contribution to risk prediction in breast cancer.

Published
2023
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42. 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, Dork, 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, Garcia-Closas, Montserrat, Garcia-Saenz, Jose A., Genkinger, Jeanine, Gentry-Maharaj, Aleksandra, Grassmann, Felix, Guenel, Pascal, Gundert, Melanie, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A., Hakansson, 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, Investigators, Abctb, 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, Le Marchand, Loic, Li, Jingmei, Linet, Martha, Lo, Wing-Yee, Long, Jirong, Lophatananon, Artitaya, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Matsuo, Keitaro, Mavroudis, Dimitrios, Menon, Usha, Muir, Kenneth, Murphy, Rachel A., Nevanlinna, Heli, Newman, William G., Niederacher, Dieter, O'Brien, Katie M., Obi, Nadia, Offit, Kenneth, Olopade, Olufunmilayo, I, Olshan, Andrew F., Olsson, Hakan, Park, Sue K., Patel, Alpa, V, Patel, Achal, Perou, Charles M., Peto, Julian, Pharoah, Paul D. P., Plaseska-Karanfilska, Dijana, Presneau, Nadege, Rack, Brigitte, Radice, Paolo, Ramachandran, Dhanya, Rashid, Muhammad U., Rennert, Gad, Romero, Atocha, Ruddy, Kathryn J., Ruebner, Matthias, Saloustros, Emmanouil, Sandler, Dale P., Sawyer, Elinor J., Schmidt, Marjanka K., Schmutzler, Rita K., Schneider, Michael O., Scott, Christopher, Shah, Mitul, Sharma, Priyanka, Shen, Chen-Yang, Shu, Xiao-Ou, Simard, Jacques, Surowy, Harald, Tamimi, Rulla M., Tapper, William J., Taylor, Jack A., Teo, Soo Hwang, Teras, Lauren R., Toland, Amanda E., Tollenaar, Rob A. E. M., Torres, Diana, Torres-Mejia, Gabriela, Troester, Melissa A., Truong, Therese, Vachon, Celine M., Vijai, Joseph, Weinberg, Clarice R., Wendt, Camilla, Winqvist, Robert, Wolk, Alicja, Wu, Anna H., Yamaji, Taiki, Yang, Xiaohong R., Yu, Jyh-Cherng, Zheng, Wei, Ziogas, Argyrios, Ziv, Elad, Dunning, Alison M., Easton, Douglas F., Hemingway, Harry, Hamann, Ute, Kuchenbaecker, Karoline B., 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, Dork, 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, Garcia-Closas, Montserrat, Garcia-Saenz, Jose A., Genkinger, Jeanine, Gentry-Maharaj, Aleksandra, Grassmann, Felix, Guenel, Pascal, Gundert, Melanie, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A., Hakansson, 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, Investigators, Abctb, 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, Le Marchand, Loic, Li, Jingmei, Linet, Martha, Lo, Wing-Yee, Long, Jirong, Lophatananon, Artitaya, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Matsuo, Keitaro, Mavroudis, Dimitrios, Menon, Usha, Muir, Kenneth, Murphy, Rachel A., Nevanlinna, Heli, Newman, William G., Niederacher, Dieter, O'Brien, Katie M., Obi, Nadia, Offit, Kenneth, Olopade, Olufunmilayo, I, Olshan, Andrew F., Olsson, Hakan, Park, Sue K., Patel, Alpa, V, Patel, Achal, Perou, Charles M., Peto, Julian, Pharoah, Paul D. P., Plaseska-Karanfilska, Dijana, Presneau, Nadege, Rack, Brigitte, Radice, Paolo, Ramachandran, Dhanya, Rashid, Muhammad U., Rennert, Gad, Romero, Atocha, Ruddy, Kathryn J., Ruebner, Matthias, Saloustros, Emmanouil, Sandler, Dale P., Sawyer, Elinor J., Schmidt, Marjanka K., Schmutzler, Rita K., Schneider, Michael O., Scott, Christopher, Shah, Mitul, Sharma, Priyanka, Shen, Chen-Yang, Shu, Xiao-Ou, Simard, Jacques, Surowy, Harald, Tamimi, Rulla M., Tapper, William J., Taylor, Jack A., Teo, Soo Hwang, Teras, Lauren R., Toland, Amanda E., Tollenaar, Rob A. E. M., Torres, Diana, Torres-Mejia, Gabriela, Troester, Melissa A., Truong, Therese, Vachon, Celine M., Vijai, Joseph, Weinberg, Clarice R., Wendt, Camilla, Winqvist, Robert, Wolk, Alicja, Wu, Anna H., Yamaji, Taiki, Yang, Xiaohong R., Yu, Jyh-Cherng, Zheng, Wei, Ziogas, Argyrios, Ziv, Elad, Dunning, Alison M., Easton, Douglas F., Hemingway, Harry, Hamann, Ute, and Kuchenbaecker, Karoline B.

Abstract

Background: Low-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. Methods: We 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. Results: In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 x 10(-6)) and AC058822.1 (P = 1.47 x 10(-4)), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C. Conclusions: Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 x 10(-5)), demonstrating the importance of diversifying study cohorts.

Published
2023
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43. 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, Czene, Kamila, Daly, Mary B., De Nicolo, Arcangela, Devilee, Peter, Dörk, Thilo, Dunning, Alison M., Dwek, Miriam, Eccles, Diana M., Engel, Christoph, Gareth Evans, D., Fasching, Peter A., Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A., Gentry-Maharaj, Aleksandra, Geurts-Giele, Willemina R.R., Giles, Graham G., Glendon, Gord, Goldberg, Mark S., Gómez Garcia, Encarna B., Göendert, Melanie, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A., Hall, Per, Hamann, Ute, Harkness, Elaine F., Hogervorst, Frans B.L., Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L., Houdayer, Claude, Houlston, Richard S., Howell, Anthony, 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, Lubiski, 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., Shu, Xiao Ou, Simard, Jacques, Southey, Melissa C., Stone, Jennifer, Stoppa-Lyonnet, Dominique, Tamimi, Rulla M., Tapper, William J., Taylor, Jack A., Teo, Soo Hwang, Teras, Lauren R., Terry, Mary Beth, Thomassen, Mads, Troester, Melissa A., Vachon, Celine M., Vega, Ana, Vreeswijk, Maaike P.G., Wang, Qin, Wappenschmidt, Barbara, Weinberg, Clarice R., Wolk, Alicja, Zheng, Wei, Feng, Bingjian, Couch, Fergus J., Spurdle, Amanda B., Easton, Douglas F., Goldgar, David E., Michailidou, Kyriaki, 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, Czene, Kamila, Daly, Mary B., De Nicolo, Arcangela, Devilee, Peter, Dörk, Thilo, Dunning, Alison M., Dwek, Miriam, Eccles, Diana M., Engel, Christoph, Gareth Evans, D., Fasching, Peter A., Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A., Gentry-Maharaj, Aleksandra, Geurts-Giele, Willemina R.R., Giles, Graham G., Glendon, Gord, Goldberg, Mark S., Gómez Garcia, Encarna B., Göendert, Melanie, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A., Hall, Per, Hamann, Ute, Harkness, Elaine F., Hogervorst, Frans B.L., Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L., Houdayer, Claude, Houlston, Richard S., Howell, Anthony, 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, Lubiski, 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., Shu, Xiao Ou, Simard, Jacques, Southey, Melissa C., Stone, Jennifer, Stoppa-Lyonnet, Dominique, Tamimi, Rulla M., Tapper, William J., Taylor, Jack A., Teo, Soo Hwang, Teras, Lauren R., Terry, Mary Beth, Thomassen, Mads, Troester, Melissa A., Vachon, Celine M., Vega, Ana, Vreeswijk, Maaike P.G., Wang, Qin, Wappenschmidt, Barbara, Weinberg, Clarice R., Wolk, Alicja, Zheng, Wei, Feng, Bingjian, Couch, Fergus J., Spurdle, Amanda B., Easton, Douglas F., Goldgar, David E., and Michailidou, Kyriaki

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 analysis 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 with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.

Published
2023

44. Germline testing of BRCA1, BRCA2, PALB2and CHEK2c.1100delC in 1514 triple negative familial and isolated breast cancers from a single centre, with extended testing of ATM, RAD51Cand RAD51Din over 400

Author

Woodward, Emma R, Lalloo, Fiona, Forde, Claire, Pugh, Sarah, Burghel, George J, Schlecht, Helene, Harkness, Elaine F, Howell, Anthony, Howell, Sacha J, Gandhi, Ashu, and Evans, D Gareth

Abstract

BackgroundThe identification of germline pathogenic gene variants (PGVs) in triple negative breast cancer (TNBC) is important to inform further primary cancer risk reduction and TNBC treatment strategies. We therefore investigated the contribution of breast cancer associated PGVs to familial and isolated invasive TNBC.MethodsOutcomes of germline BRCA1, BRCA2and CHEK2_c.1100delC testing were recorded in 1514 women (743—isolated, 771—familial), and for PALB2in 846 women (541—isolated, 305—familial), with TNBC and smaller numbers for additional genes. Breast cancer free controls were identified from Predicting Risk Of Cancer At Screening and BRIDGES (Breast cancer RIsk after Diagnostic GEne Sequencing) studies.ResultsBRCA1_PGVs were detected in 52 isolated (7.0%) and 195 (25.3%) familial cases (isolated—OR=58.9, 95% CI: 16.6 to 247.0), BRCA2_PGVs in 21 (2.8%) isolated and 67 (8.7%) familial cases (isolated—OR=5.0, 95% CI: 2.3 to 11.2), PALB2_PGVs in 9 (1.7%) isolated and 12 (3.9%) familial cases (isolated—OR=8.8, 95% CI: 2.5 to 30.4) and CHEK2_c.1100delC in 0 isolated and 3 (0.45%) familial cases (isolated—OR=0.0, 95% CI: 0.00 to 2.11). BRCA1_PGV detection rate was >10% for all familial TNBC age groups and significantly higher for younger diagnoses (familial: <50 years, n=165/538 (30.7%); ≥50 years, n=30/233 (12.9%); p<0.0001). Women with a G3_TNBC were more likely to have a BRCA1_PGV as compared with a BRCA2or PALB2_PGV (p<0.0001). 0/743 isolated TNBC had the CHEK2_c.1100delC PGV and 0/305 any ATM_PGV, but 2/240 (0.83%) had a RAD51D_PGV.ConclusionPGVs in BRCA1are associated with G3_TNBCs. Familial TNBCs and isolated TNBCs <30 years have a >10% likelihood of a PGV in BRCA1. BRCA1_PGVs are associated with younger age of familial TNBC. There was no evidence for any increased risk of TNBC with CHEK2or ATMPGVs.

Published
2024
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45. TP53 c.455C>T p.(Pro152Leu) pathogenic variant is a lower risk allele with attenuated risks of breast cancer and sarcoma.

Author

Evans, D. Gareth, Harkness, Elaine F., and Woodward, Emma R.

Abstract

Germline (likely) pathogenic TP53 variants cause Li-Fraumeni syndrome (LFS), typically associated with sarcoma, brain, breast and adrenal tumours. Although classical LFS is highly penetrant, the p.R337H variant, common in Brazil, is typically associated with childhood adrenal tumours and an older onset age of other LFS tumours. Previously, we reported the finding of p.P152L in 6 children from 5 families with adrenal tumours. We have now assessed cancer risks over the subsequent 23 years, and in one further family with p.P152L. Cancer risks were compared with those in the 11 families known to our service with classical dominant negative mutations affecting neighbouring codons 245 and 248 (codon 245/248). Compared with codon 245/248 families, we found lower age-related risks for all non-adrenal tumours in codon 152 families (p<0.0001) with an absence of breast cancer as compared with 100% penetrance by age 36 years in codon 245/248 families (p<0.0001), and lower rates of sarcoma in non-irradiated individuals (p=0.0001). Although there were more adrenal tumours in codon 152 families (6/26 individuals, 1/27 for codon 245/248), this was not significant (p=0.05). Understanding codon-specific cancer risks in LFS is important for accurate personalised cancer risk assessment, and subsequent prevention and early detection strategies. [ABSTRACT FROM AUTHOR]

Published
2023
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49. Differential involvement of germline pathogenic variants in breast cancer genes between DCIS and low-grade invasive cancers

Author

Evans, D Gareth, primary, Sithambaram, Siva, additional, van Veen, Elke Maria, additional, Burghel, George J, additional, Schlecht, Helene, additional, Harkness, Elaine F, additional, Byers, Helen, additional, Ellingford, Jamie M, additional, Gandhi, Ashu, additional, Howell, Sacha J, additional, Howell, Anthony, additional, Forde, Claire, additional, Lalloo, Fiona, additional, Newman, William G, additional, Smith, Miriam Jane, additional, and Woodward, Emma Roisin, additional

Published
2022
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50. Obesity at age 20 and weight gain during adulthood increase risk of total and premature all-cause mortality: Findings from women attending breast screening in Manchester

Author

Pegington, Mary, primary, Harvie, Michelle, additional, Harkness, Elaine F, additional, Brentnall, Adam, additional, Malcomson, Lee, additional, Southworth, Jake, additional, Fox, Jill, additional, Howell, Anthony, additional, Cuzick, Jack, additional, and Evans, D Gareth, additional

Published
2022
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