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534 results on '"Celine M. Vachon"'

1. Genetically determined telomere length in monoclonal gammopathy of undetermined significance, multiple myeloma risk and outcome

Author: Matteo Giaccherini, Alyssa I. Clay-Gilmour, Romano Liotti, Angelica Macauda, Manuel Gentiluomo, Elizabeth E. Brown, Mitchell J. Machiela, Stephen J. Chanock, Michelle A. T. Hildebrandt, Aaron D. Norman, Elisabet Manasanch, S. Vincent Rajkumar, Jonathan N. Hofmann, Sonja I. Berndt, Parveen Bhatti, Graham G. Giles, Elad Ziv, Shaji K. Kumar, Nicola J. Camp, Wendy Cozen, Susan L. Slager, Federico Canzian, Federica Gemignani, Celine M. Vachon, and Daniele Campa
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Published: 2024
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2. Mosaic chromosomal alterations (mCAs) in individuals with monoclonal B-cell lymphocytosis (MBL)

Author: Aswin Sekar, Rosalie Griffin, Sameer A. Parikh, Giulio Genovese, Dennis P. Robinson, Aaron D. Norman, Janet E. Olson, Kari G. Rabe, Mingma S. Hoel, Nicholas J. Boddicker, Paul J. Hampel, Neil E. Kay, James R. Cerhan, Esteban Braggio, Curtis A. Hanson, Celine M. Vachon, Tait D. Shanafelt, Benjamin L. Ebert, and Susan L. Slager
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract MBL is a precursor condition to chronic lymphocytic leukemia (CLL), characterized by monoclonal B-cells in blood. Mosaic chromosomal alterations (mCAs) are a form of clonal hematopoiesis that include gains, losses, and copy-neutral loss-of-heterozygosity of large DNA segments. Both MBL and mCAs have been found to increase the risk of CLL and lymphoid malignancies, and the aim of our study was to investigate how mCAs relate to MBL, which is currently unknown. We analyzed genetic, flow cytometric, and hematologic data from 4632 individuals from the Mayo Clinic Biobank and CLL Database. MBL was detected using flow cytometry and classified as high-count (HC) or low-count (LC) MBL based on clone size. mCAs were detected primarily from whole blood DNA using sensitive SNP-array-based analyses. mCAs commonly altered in CLL (deletion of 6q, 11q, 13q, 17p, and trisomy 12) were specific (>99%) to individuals with MBL and CLL. HC-MBL and LC-MBL individuals were 881-fold and 8-fold, respectively, more likely to harbor CLL-associated mCAs than those without MBL. The cell fraction bearing these mCAs typically exceeded the B-cell fraction, suggesting their origin prior to the B-cell lineage. Integrating genetic and blood count data enabled detecting HC-MBL with high specificity in a biobank sample. These results quantify the contribution of mCAs to MBL and could enable large studies of HC-MBL without the need for flow cytometric screening.
Published: 2024
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3. Multivariate testing and effect size measures for batch effect evaluation in radiomic features

Author: Hannah Horng, Christopher Scott, Stacey Winham, Matthew Jensen, Lauren Pantalone, Walter Mankowski, Karla Kerlikowske, Celine M. Vachon, Despina Kontos, and Russell T. Shinohara
Subjects: Medicine, Science
Abstract: Abstract While precision medicine applications of radiomics analysis are promising, differences in image acquisition can cause “batch effects” that reduce reproducibility and affect downstream predictive analyses. Harmonization methods such as ComBat have been developed to correct these effects, but evaluation methods for quantifying batch effects are inconsistent. In this study, we propose the use of the multivariate statistical test PERMANOVA and the Robust Effect Size Index (RESI) to better quantify and characterize batch effects in radiomics data. We evaluate these methods in both simulated and real radiomics features extracted from full-field digital mammography (FFDM) data. PERMANOVA demonstrated higher power than standard univariate statistical testing, and RESI was able to interpretably quantify the effect size of site at extremely large sample sizes. These methods show promise as more powerful and interpretable methods for the detection and quantification of batch effects in radiomics studies.
Published: 2024
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4. Association of early menarche with breast tumor molecular features and recurrence

Author: Alexandra R. Harris, Tengteng Wang, Yujing J. Heng, Gabrielle M. Baker, Phuong Anh Le, Jun Wang, Christine Ambrosone, Adam Brufsky, Fergus J. Couch, Francesmary Modugno, Christopher G. Scott, Celine M. Vachon, Susan E. Hankinson, Bernard A. Rosner, Rulla M. Tamimi, Cheng Peng, and A. Heather Eliassen
Subjects: Age at menarche, Reproductive risk factors of breast cancer, Early-life risk factors of breast tumor biology, Breast cancer recurrence, Early menarche gene expression signature, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Early menarche is an established risk factor for breast cancer but its molecular contribution to tumor biology and prognosis remains unclear. Methods We profiled transcriptome-wide gene expression in breast tumors (N = 846) and tumor-adjacent normal tissues (N = 666) from women in the Nurses’ Health Studies (NHS) to investigate whether early menarche (age
Published: 2024
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5. Association of the CHEK2 c.1100delC variant, radiotherapy, and systemic treatment with contralateral breast cancer risk and breast cancer‐specific survival

Author: Anna Morra, Maartje A. C. Schreurs, Irene L. Andrulis, Hoda Anton‐Culver, Annelie Augustinsson, Matthias W. Beckmann, Sabine Behrens, Stig E. Bojesen, Manjeet K. Bolla, Hiltrud Brauch, Annegien Broeks, Saundra S. Buys, Nicola J. Camp, Jose E. Castelao, Melissa H. Cessna, Jenny Chang‐Claude, Wendy K. Chung, NBCS Collaborators, Sarah V. Colonna, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Joe Dennis, Peter Devilee, Thilo Dörk, Alison M. Dunning, Miriam Dwek, Douglas F. Easton, Diana M. Eccles, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Tanja N. Fehm, Jonine D. Figueroa, Henrik Flyger, Marike Gabrielson, Manuela Gago‐Dominguez, Montserrat García‐Closas, José A. García‐Sáenz, Jeanine Genkinger, Felix Grassmann, Melanie Gündert, Eric Hahnen, Christopher A. Haiman, Ute Hamann, Patricia A. Harrington, Jaana M. Hartikainen, Reiner Hoppe, John L. Hopper, Richard S. Houlston, Anthony Howell, ABCTB Investigators, kConFab Investigators, Anna Jakubowska, Wolfgang Janni, Helena Jernström, Esther M. John, Nichola Johnson, Michael E. Jones, Vessela N. Kristensen, Allison W. Kurian, Diether Lambrechts, Loic Le Marchand, Annika Lindblom, Jan Lubiński, Michael P. Lux, Arto Mannermaa, Dimitrios Mavroudis, Anna Marie Mulligan, Taru A. Muranen, Heli Nevanlinna, Ines Nevelsteen, Patrick Neven, William G. Newman, Nadia Obi, Kenneth Offit, Andrew F. Olshan, Tjoung‐Won Park‐Simon, Alpa V. Patel, Paolo Peterlongo, Kelly‐Anne Phillips, Dijana Plaseska‐Karanfilska, Eric C. Polley, Nadege Presneau, Katri Pylkäs, Brigitte Rack, Paolo Radice, Muhammad U. Rashid, Valerie Rhenius, Mark Robson, Atocha Romero, Emmanouil Saloustros, Elinor J. Sawyer, Rita K. Schmutzler, Sabine Schuetze, Christopher Scott, Mitul Shah, Snezhana Smichkoska, Melissa C. Southey, William J. Tapper, Lauren R. Teras, Rob A. E. M. Tollenaar, Katarzyna Tomczyk, Ian Tomlinson, Melissa A. Troester, Celine M. Vachon, Elke M. vanVeen, Qin Wang, Camilla Wendt, Hans Wildiers, Robert Winqvist, Argyrios Ziogas, Per Hall, Paul D. P. Pharoah, Muriel A. Adank, Antoinette Hollestelle, Marjanka K. Schmidt, and Maartje J. Hooning
Subjects: CHEK2 c.1100delC germline genetic variant, contralateral breast cancer risk, radiotherapy, survival, systemic treatment, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Breast 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. Aim To assessed the associations of CHEK2 c.1100delC, radiotherapy, and systemic treatment with CBC risk and BCSS. Methods Analyses 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. Results There 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)]. Conclusion Systemic 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
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6. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Author: Pooja Middha, Xiaoliang Wang, Sabine Behrens, Manjeet K. Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Thomas U. Ahearn, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J. Aronson, Paul L. Auer, Annelie Augustinsson, Thaïs Baert, Laura E. Beane Freeman, Heiko Becher, Matthias W. Beckmann, Javier Benitez, Stig E. Bojesen, Hiltrud Brauch, Hermann Brenner, Angela Brooks-Wilson, Daniele Campa, Federico Canzian, Angel Carracedo, Jose E. Castelao, Stephen J. Chanock, Georgia Chenevix-Trench, CTS Consortium, Emilie Cordina-Duverger, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Laure Dossus, Pierre-Antoine Dugué, A. Heather Eliassen, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Jonine D. Figueroa, Olivia Fletcher, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Graham G. Giles, Anna González-Neira, Felix Grassmann, Anne Grundy, Pascal Guénel, Christopher A. Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Susan E. Hankinson, Elaine F. Harkness, Bernd Holleczek, Reiner Hoppe, John L. Hopper, Richard S. Houlston, Anthony Howell, David J. Hunter, Christian Ingvar, ABCTB Investigators, kConFab Investigators, Karolin Isaksson, Helena Jernström, Esther M. John, Michael E. Jones, Rudolf Kaaks, Renske Keeman, Cari M. Kitahara, Yon-Dschun Ko, Stella Koutros, Allison W. Kurian, James V. Lacey, Diether Lambrechts, Nicole L. Larson, Susanna Larsson, Loic Le Marchand, Flavio Lejbkowicz, Shuai Li, Martha Linet, Jolanta Lissowska, Maria Elena Martinez, Tabea Maurer, Anna Marie Mulligan, Claire Mulot, Rachel A. Murphy, William G. Newman, Sune F. Nielsen, Børge G. Nordestgaard, Aaron Norman, Katie M. O’Brien, Janet E. Olson, Alpa V. Patel, Ross Prentice, Erika Rees-Punia, Gad Rennert, Valerie Rhenius, Kathryn J. Ruddy, Dale P. Sandler, Christopher G. Scott, Mitul Shah, Xiao-Ou Shu, Ann Smeets, Melissa C. Southey, Jennifer Stone, Rulla M. Tamimi, Jack A. Taylor, Lauren R. Teras, Katarzyna Tomczyk, Melissa A. Troester, Thérèse Truong, Celine M. Vachon, Sophia S. Wang, Clarice R. Weinberg, Hans Wildiers, Walter Willett, Stacey J. Winham, Alicja Wolk, Xiaohong R. Yang, M. Pilar Zamora, Wei Zheng, Argyrios Ziogas, Alison M. Dunning, Paul D. P. Pharoah, Montserrat García-Closas, Marjanka K. Schmidt, Peter Kraft, Roger L. Milne, Sara Lindström, Douglas F. Easton, and Jenny Chang-Claude
Subjects: Breast cancer, Gene-environment interactions, Genetic epidemiology, European ancestry, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Genome-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. 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 × 10–5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability
Published: 2023
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7. Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

Author: Stefanie H. Mueller, Alvina G. Lai, Maria Valkovskaya, Kyriaki Michailidou, Manjeet K. Bolla, Qin Wang, Joe Dennis, Michael Lush, Zomoruda Abu-Ful, Thomas U. Ahearn, Irene L. Andrulis, Hoda Anton-Culver, Natalia N. Antonenkova, Volker Arndt, Kristan J. Aronson, Annelie Augustinsson, Thais Baert, Laura E. Beane Freeman, Matthias W. Beckmann, Sabine Behrens, Javier Benitez, Marina Bermisheva, Carl Blomqvist, Natalia V. Bogdanova, Stig E. Bojesen, Bernardo Bonanni, Hermann Brenner, Sara Y. Brucker, Saundra S. Buys, Jose E. Castelao, Tsun L. Chan, Jenny Chang-Claude, Stephen J. Chanock, Ji-Yeob Choi, Wendy K. Chung, NBCS Collaborators, Sarah V. Colonna, CTS Consortium, Sten Cornelissen, Fergus J. Couch, Kamila Czene, Mary B. Daly, Peter Devilee, Thilo Dörk, Laure Dossus, Miriam Dwek, Diana M. Eccles, Arif B. Ekici, A. Heather Eliassen, Christoph Engel, D. Gareth Evans, Peter A. Fasching, Olivia Fletcher, Henrik Flyger, Manuela Gago-Dominguez, Yu-Tang Gao, Montserrat García-Closas, José A. García-Sáenz, Jeanine Genkinger, Aleksandra Gentry-Maharaj, Felix Grassmann, Pascal Guénel, Melanie Gündert, Lothar Haeberle, Eric Hahnen, Christopher A. Haiman, Niclas Håkansson, Per Hall, Elaine F. Harkness, Patricia A. Harrington, Jaana M. Hartikainen, Mikael Hartman, Alexander Hein, Weang-Kee Ho, Maartje J. Hooning, Reiner Hoppe, John L. Hopper, Richard S. Houlston, Anthony Howell, David J. Hunter, Dezheng Huo, ABCTB Investigators, Hidemi Ito, Motoki Iwasaki, Anna Jakubowska, Wolfgang Janni, Esther M. John, Michael E. Jones, Audrey Jung, Rudolf Kaaks, Daehee Kang, Elza K. Khusnutdinova, Sung-Won Kim, Cari M. Kitahara, Stella Koutros, Peter Kraft, Vessela N. Kristensen, Katerina Kubelka-Sabit, Allison W. Kurian, Ava Kwong, James V. Lacey, Diether Lambrechts, Loic Le Marchand, Jingmei Li, Martha Linet, Wing-Yee Lo, Jirong Long, Artitaya Lophatananon, Arto Mannermaa, Mehdi Manoochehri, Sara Margolin, Keitaro Matsuo, Dimitrios Mavroudis, Usha Menon, Kenneth Muir, Rachel A. Murphy, Heli Nevanlinna, William G. Newman, Dieter Niederacher, Katie M. O’Brien, Nadia Obi, Kenneth Offit, Olufunmilayo I. Olopade, Andrew F. Olshan, Håkan Olsson, Sue K. Park, Alpa V. Patel, Achal Patel, Charles M. Perou, Julian Peto, Paul D. P. Pharoah, Dijana Plaseska-Karanfilska, Nadege Presneau, Brigitte Rack, Paolo Radice, Dhanya Ramachandran, Muhammad U. Rashid, Gad Rennert, Atocha Romero, Kathryn J. Ruddy, Matthias Ruebner, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Marjanka K. Schmidt, Rita K. Schmutzler, Michael O. Schneider, Christopher Scott, Mitul Shah, Priyanka Sharma, Chen-Yang Shen, Xiao-Ou Shu, Jacques Simard, Harald Surowy, Rulla M. Tamimi, William J. Tapper, Jack A. Taylor, Soo Hwang Teo, Lauren R. Teras, Amanda E. Toland, Rob A. E. M. Tollenaar, Diana Torres, Gabriela Torres-Mejía, Melissa A. Troester, Thérèse Truong, Celine M. Vachon, Joseph Vijai, Clarice R. Weinberg, Camilla Wendt, Robert Winqvist, Alicja Wolk, Anna H. Wu, Taiki Yamaji, Xiaohong R. Yang, Jyh-Cherng Yu, Wei Zheng, Argyrios Ziogas, Elad Ziv, Alison M. Dunning, Douglas F. Easton, Harry Hemingway, Ute Hamann, and Karoline B. Kuchenbaecker
Subjects: Breast cancer susceptibility, Diverse ancestry, Rare variants, Gene regulation, Genome-wide association study, Medicine, Genetics, QH426-470
Abstract: 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
Published: 2023
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8. Rates of Asymptomatic COVID-19 Infection and Associated Factors in Olmsted County, Minnesota, in the Prevaccination Era

Author: Celine M. Vachon, PhD, Aaron D. Norman, MPH, Kavita Prasad, MD, Dan Jensen, MPH, Gavin M. Schaeferle, BA, Kristy L. Vierling, MA, Meaghan Sherden, MPH, Michelle R. Majerus, MBA, FACHE, Katherine A. Bews, BA, Ethan P. Heinzen, MS, Amy Hebl, BS, Kathleen J. Yost, PhD, Richard B. Kennedy, PhD, Elitza S. Theel, PhD, Aditya Ghosh, MD, Meghan Fries, Chung-Il Wi, MD, Young J. Juhn, MD, Priya Sampathkumar, MD, William G. Morice, II, MD, PHD, Walter A. Rocca, MD, MPH, Aaron J. Tande, MD, James R. Cerhan, MD, PhD, Andrew H. Limper, MD, Henry H. Ting, MD, Gianrico Farrugia, MD, Rickey E. Carter, PhD, Lila J. Finney Rutten, PhD, Robert M. Jacobson, MD, and Jennifer St. Sauver, PhD
Subjects: Medicine (General), R5-920
Abstract: Objective: To estimate rates and identify factors associated with asymptomatic COVID-19 in the population of Olmsted County during the prevaccination era. Patients and Methods: We screened first responders (n=191) and Olmsted County employees (n=564) for antibodies to SARS-CoV-2 from November 1, 2020 to February 28, 2021 to estimate seroprevalence and asymptomatic infection. Second, we retrieved all polymerase chain reaction (PCR)-confirmed COVID-19 diagnoses in Olmsted County from March 2020 through January 2021, abstracted symptom information, estimated rates of asymptomatic infection and examined related factors. Results: Twenty (10.5%; 95% CI, 6.9%-15.6%) first responders and 38 (6.7%; 95% CI, 5.0%-9.1%) county employees had positive antibodies; an additional 5 (2.6%) and 10 (1.8%) had prior positive PCR tests per self-report or medical record, but no antibodies detected. Of persons with symptom information, 4 of 20 (20%; 95% CI, 3.0%-37.0%) first responders and 10 of 39 (26%; 95% CI, 12.6%-40.0%) county employees were asymptomatic. Of 6020 positive PCR tests in Olmsted County with symptom information between March 1, 2020, and January 31, 2021, 6% (n=385; 95% CI, 5.8%-7.1%) were asymptomatic. Factors associated with asymptomatic disease included age (0-18 years [odds ratio {OR}, 2.3; 95% CI, 1.7-3.1] and >65 years [OR, 1.40; 95% CI, 1.0-2.0] compared with ages 19-44 years), body mass index (overweight [OR, 0.58; 95% CI, 0.44-0.77] or obese [OR, 0.48; 95% CI, 0.57-0.62] compared with normal or underweight) and tests after November 20, 2020 ([OR, 1.35; 95% CI, 1.13-1.71] compared with prior dates). Conclusion: Asymptomatic rates in Olmsted County before COVID-19 vaccine rollout ranged from 6% to 25%, and younger age, normal weight, and later tests dates were associated with asymptomatic infection.
Published: 2022
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9. A genome-wide association study of mammographic texture variation

Author: Yuxi Liu, Hongjie Chen, John Heine, Sara Lindstrom, Constance Turman, Erica T. Warner, Stacey J. Winham, Celine M. Vachon, Rulla M. Tamimi, Peter Kraft, and Xia Jiang
Subjects: Breast cancer, Breast parenchymal texture feature, Texture variation, V measure, Mammographic density, GWAS, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Breast parenchymal texture features, including grayscale variation (V), capture the patterns of texture variation on a mammogram and are associated with breast cancer risk, independent of mammographic density (MD). However, our knowledge on the genetic basis of these texture features is limited. Methods We conducted a genome-wide association study of V in 7040 European-ancestry women. V assessments were generated from digitized film mammograms. We used linear regression to test the single-nucleotide polymorphism (SNP)-phenotype associations adjusting for age, body mass index (BMI), MD phenotypes, and the top four genetic principal components. We further calculated genetic correlations and performed SNP-set tests of V with MD, breast cancer risk, and other breast cancer risk factors. Results We identified three genome-wide significant loci associated with V: rs138141444 (6q24.1) in ECT2L, rs79670367 (8q24.22) in LINC01591, and rs113174754 (12q22) near PGAM1P5. 6q24.1 and 8q24.22 have not previously been associated with MD phenotypes or breast cancer risk, while 12q22 is a known locus for both MD and breast cancer risk. Among known MD and breast cancer risk SNPs, we identified four variants that were associated with V at the Bonferroni-corrected thresholds accounting for the number of SNPs tested: rs335189 (5q23.2) in PRDM6, rs13256025 (8p21.2) in EBF2, rs11836164 (12p12.1) near SSPN, and rs17817449 (16q12.2) in FTO. We observed significant genetic correlations between V and mammographic dense area (r g = 0.79, P = 5.91 × 10−5), percent density (r g = 0.73, P = 1.00 × 10−4), and adult BMI (r g = − 0.36, P = 3.88 × 10−7). Additional significant relationships were observed for non-dense area (z = − 4.14, P = 3.42 × 10−5), estrogen receptor-positive breast cancer (z = 3.41, P = 6.41 × 10−4), and childhood body fatness (z = − 4.91, P = 9.05 × 10−7) from the SNP-set tests. Conclusions These findings provide new insights into the genetic basis of mammographic texture variation and their associations with MD, breast cancer risk, and other breast cancer risk factors.
Published: 2022
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10. Distribution of clonal hematopoiesis of indeterminate potential (CHIP) is not associated with race in patients with plasma cell neoplasms

Author: Marie-France Gagnon, Shulan Tian, Susan Geyer, Neeraj Sharma, Celine M. Vachon, Yael Kusne, P. Leif Bergsagel, A. Keith Stewart, S. Vincent Rajkumar, Shaji Kumar, Sikander Ailawadhi, and Linda B. Baughn
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Published: 2022
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11. The risk of coronavirus disease 2019 (COVID-19) among individuals with monoclonal B cell lymphocytosis

Author: Sameer A. Parikh, Sara J. Achenbach, Kari G. Rabe, Aaron D. Norman, Nicholas J. Boddicker, Janet E. Olson, Timothy G. Call, James R. Cerhan, Celine M. Vachon, Neil E. Kay, Esteban Braggio, Curtis A. Hanson, Susan L. Slager, and Tait D. Shanafelt
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Published: 2022
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12. Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci

Author: Hongjie Chen, Shaoqi Fan, Jennifer Stone, Deborah J. Thompson, Julie Douglas, Shuai Li, Christopher Scott, Manjeet K. Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Christopher Li, Ulrike Peters, John L. Hopper, Melissa C. Southey, Tu Nguyen-Dumont, Tuong L. Nguyen, Peter A. Fasching, Annika Behrens, Gemma Cadby, Rachel A. Murphy, Kristan Aronson, Anthony Howell, Susan Astley, Fergus Couch, Janet Olson, Roger L. Milne, Graham G. Giles, Christopher A. Haiman, Gertraud Maskarinec, Stacey Winham, Esther M. John, Allison Kurian, Heather Eliassen, Irene Andrulis, D. Gareth Evans, William G. Newman, Per Hall, Kamila Czene, Anthony Swerdlow, Michael Jones, Marina Pollan, Pablo Fernandez-Navarro, Daniel S. McConnell, Vessela N. Kristensen, NBCS Investigators, Joseph H. Rothstein, Pei Wang, Laurel A. Habel, Weiva Sieh, Alison M. Dunning, Paul D. P. Pharoah, Douglas F. Easton, Gretchen L. Gierach, Rulla M. Tamimi, Celine M. Vachon, and Sara Lindström
Subjects: Mammographic density, Breast cancer, Genome-wide association study (GWAS), Transcriptome-wide association study (TWAS), Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. Methods We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. Results We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p
Published: 2022
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13. Genome-wide meta-analysis of monoclonal gammopathy of undetermined significance (MGUS) identifies risk loci impacting IRF-6

Author: Alyssa Clay-Gilmour, Subhayan Chattopadhyay, Michelle A. T. Hildebrandt, Hauke Thomsen, Niels Weinhold, Pavel Vodicka, Ludmila Vodickova, Per Hoffmann, Markus M. Nöthen, Karl-Heinz Jöckel, Börge Schmidt, Christian Langer, Roman Hajek, Göran Hallmans, Ulrika Pettersson-Kymmer, Claes Ohlsson, Florentin Späth, Richard Houlston, Hartmut Goldschmidt, Elisabet E. Manasanch, Aaron Norman, Shaji Kumar, S. Vincent Rajkumar, Susan Slager, Asta Försti, Celine M. Vachon, and Kari Hemminki
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Published: 2022
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14. Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Author: Xiaoliang Wang, Pooja Middha Kapoor, Paul L. Auer, Joe Dennis, Alison M. Dunning, Qin Wang, Michael Lush, Kyriaki Michailidou, Manjeet K. Bolla, Kristan J. Aronson, Rachel A. Murphy, Angela Brooks-Wilson, Derrick G. Lee, Emilie Cordina-Duverger, Pascal Guénel, Thérèse Truong, Claire Mulot, Lauren R. Teras, Alpa V. Patel, Laure Dossus, Rudolf Kaaks, Reiner Hoppe, Wing-Yee Lo, Thomas Brüning, Ute Hamann, Kamila Czene, Marike Gabrielson, Per Hall, Mikael Eriksson, Audrey Jung, Heiko Becher, Fergus J. Couch, Nicole L. Larson, Janet E. Olson, Kathryn J. Ruddy, Graham G. Giles, Robert J. MacInnis, Melissa C. Southey, Loic Le Marchand, Lynne R. Wilkens, Christopher A. Haiman, Håkan Olsson, Annelie Augustinsson, Ute Krüger, Philippe Wagner, Christopher Scott, Stacey J. Winham, Celine M. Vachon, Charles M. Perou, Andrew F. Olshan, Melissa A. Troester, David J. Hunter, Heather A. Eliassen, Rulla M. Tamimi, Kristen Brantley, Irene L. Andrulis, Jonine Figueroa, Stephen J. Chanock, Thomas U. Ahearn, Montserrat García-Closas, Gareth D. Evans, William G. Newman, Elke M. van Veen, Anthony Howell, Alicja Wolk, Niclas Håkansson, Hoda Anton-Culver, Argyrios Ziogas, Michael E. Jones, Nick Orr, Minouk J. Schoemaker, Anthony J. Swerdlow, Cari M. Kitahara, Martha Linet, Ross L. Prentice, Douglas F. Easton, Roger L. Milne, Peter Kraft, Jenny Chang-Claude, and Sara Lindström
Subjects: Medicine, Science
Abstract: Abstract Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values
Published: 2022
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15. Body mass index associated with monoclonal gammopathy of undetermined significance (MGUS) progression in Olmsted County, Minnesota

Author: Geffen Kleinstern, Dirk R. Larson, Cristine Allmer, Aaron D. Norman, Grace Muntifering, Jason Sinnwell, Alissa Visram, Vincent Rajkumar, Angela Dispenzieri, Robert A. Kyle, Susan L. Slager, Shaji Kumar, and Celine M. Vachon
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant clonal disorder that progresses to multiple myeloma (MM), or other plasma-cell or lymphoid disorders at a rate of 1%/year. We evaluate the contribution of body mass index (BMI) to MGUS progression beyond established clinical factors in a population-based study. We identified 594 MGUS through a population-based screening study in Olmsted County, Minnesota, between 1995 and 2003. Follow-up time was calculated from the date of MGUS to last follow-up, death, or progression to MM/another plasma-cell/lymphoid disorder. BMI (kg/m2
Published: 2022
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16. Common variants in breast cancer risk loci predispose to distinct tumor subtypes

Author: Thomas U. Ahearn, Haoyu Zhang, Kyriaki Michailidou, Roger L. Milne, Manjeet K. Bolla, Joe Dennis, Alison M. Dunning, Michael Lush, Qin Wang, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J. Aronson, Paul L. Auer, Annelie Augustinsson, Adinda Baten, Heiko Becher, Sabine Behrens, Javier Benitez, Marina Bermisheva, Carl Blomqvist, Stig E. Bojesen, Bernardo Bonanni, Anne-Lise Børresen-Dale, Hiltrud Brauch, Hermann Brenner, Angela Brooks-Wilson, Thomas Brüning, Barbara Burwinkel, Saundra S. Buys, Federico Canzian, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Georgia Chenevix-Trench, Christine L. Clarke, NBCS Collaborators, J. Margriet Collée, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Peter Devilee, Thilo Dörk, Miriam Dwek, Diana M. Eccles, D. Gareth Evans, Peter A. Fasching, Jonine Figueroa, Giuseppe Floris, Manuela Gago-Dominguez, Susan M. Gapstur, José A. García-Sáenz, Mia M. Gaudet, Graham G. Giles, Mark S. Goldberg, Anna González-Neira, Grethe I. Grenaker Alnæs, Mervi Grip, Pascal Guénel, Christopher A. Haiman, Per Hall, Ute Hamann, Elaine F. Harkness, Bernadette A. M. Heemskerk-Gerritsen, Bernd Holleczek, Antoinette Hollestelle, Maartje J. Hooning, Robert N. Hoover, John L. Hopper, Anthony Howell, ABCTB Investigators, kConFab/AOCS Investigators, Milena Jakimovska, Anna Jakubowska, Esther M. John, Michael E. Jones, Audrey Jung, Rudolf Kaaks, Saila Kauppila, Renske Keeman, Elza Khusnutdinova, Cari M. Kitahara, Yon-Dschun Ko, Stella Koutros, Vessela N. Kristensen, Ute Krüger, Katerina Kubelka-Sabit, Allison W. Kurian, Kyriacos Kyriacou, Diether Lambrechts, Derrick G. Lee, Annika Lindblom, Martha Linet, Jolanta Lissowska, Ana Llaneza, Wing-Yee Lo, Robert J. MacInnis, Arto Mannermaa, Mehdi Manoochehri, Sara Margolin, Maria Elena Martinez, Catriona McLean, Alfons Meindl, Usha Menon, Heli Nevanlinna, William G. Newman, Jesse Nodora, Kenneth Offit, Håkan Olsson, Nick Orr, Tjoung-Won Park-Simon, Alpa V. Patel, Julian Peto, Guillermo Pita, Dijana Plaseska-Karanfilska, Ross Prentice, Kevin Punie, Katri Pylkäs, Paolo Radice, Gad Rennert, Atocha Romero, Thomas Rüdiger, Emmanouil Saloustros, Sarah Sampson, Dale P. Sandler, Elinor J. Sawyer, Rita K. Schmutzler, Minouk J. Schoemaker, Ben Schöttker, Mark E. Sherman, Xiao-Ou Shu, Snezhana Smichkoska, Melissa C. Southey, John J. Spinelli, Anthony J. Swerdlow, Rulla M. Tamimi, William J. Tapper, Jack A. Taylor, Lauren R. Teras, Mary Beth Terry, Diana Torres, Melissa A. Troester, Celine M. Vachon, Carolien H. M. van Deurzen, Elke M. van Veen, Philippe Wagner, Clarice R. Weinberg, Camilla Wendt, Jelle Wesseling, Robert Winqvist, Alicja Wolk, Xiaohong R. Yang, Wei Zheng, Fergus J. Couch, Jacques Simard, Peter Kraft, Douglas F. Easton, Paul D. P. Pharoah, Marjanka K. Schmidt, Montserrat García-Closas, and Nilanjan Chatterjee
Subjects: Breast cancer, Etiologic heterogeneity, Genetic predisposition, Common breast cancer susceptibility variants, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Genome-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. Methods Among 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. Results Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate
Published: 2022
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17. Rare germline copy number variants (CNVs) and breast cancer risk

Author: Joe Dennis, Jonathan P. Tyrer, Logan C. Walker, Kyriaki Michailidou, Leila Dorling, Manjeet K. Bolla, Qin Wang, Thomas U. Ahearn, Irene L. Andrulis, Hoda Anton-Culver, Natalia N. Antonenkova, Volker Arndt, Kristan J. Aronson, Laura E. Beane Freeman, Matthias W. Beckmann, Sabine Behrens, Javier Benitez, Marina Bermisheva, Natalia V. Bogdanova, Stig E. Bojesen, Hermann Brenner, Jose E. Castelao, Jenny Chang-Claude, Georgia Chenevix-Trench, Christine L. Clarke, NBCS Collaborators, J. Margriet Collée, CTS Consortium, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Peter Devilee, Thilo Dörk, Laure Dossus, A. Heather Eliassen, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Jonine Figueroa, Olivia Fletcher, Henrik Flyger, Lin Fritschi, Marike Gabrielson, Manuela Gago-Dominguez, Montserrat García-Closas, Graham G. Giles, Anna González-Neira, Pascal Guénel, Eric Hahnen, Christopher A. Haiman, Per Hall, Antoinette Hollestelle, Reiner Hoppe, John L. Hopper, Anthony Howell, ABCTB Investigators, kConFab/AOCS Investigators, Agnes Jager, Anna Jakubowska, Esther M. John, Nichola Johnson, Michael E. Jones, Audrey Jung, Rudolf Kaaks, Renske Keeman, Elza Khusnutdinova, Cari M. Kitahara, Yon-Dschun Ko, Veli-Matti Kosma, Stella Koutros, Peter Kraft, Vessela N. Kristensen, Katerina Kubelka-Sabit, Allison W. Kurian, James V. Lacey, Diether Lambrechts, Nicole L. Larson, Martha Linet, Alicja Ogrodniczak, Arto Mannermaa, Siranoush Manoukian, Sara Margolin, Dimitrios Mavroudis, Roger L. Milne, Taru A. Muranen, Rachel A. Murphy, Heli Nevanlinna, Janet E. Olson, Håkan Olsson, Tjoung-Won Park-Simon, Charles M. Perou, Paolo Peterlongo, Dijana Plaseska-Karanfilska, Katri Pylkäs, Gad Rennert, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Marjanka K. Schmidt, Rita K. Schmutzler, Rana Shibli, Ann Smeets, Penny Soucy, Melissa C. Southey, Anthony J. Swerdlow, Rulla M. Tamimi, Jack A. Taylor, Lauren R. Teras, Mary Beth Terry, Ian Tomlinson, Melissa A. Troester, Thérèse Truong, Celine M. Vachon, Camilla Wendt, Robert Winqvist, Alicja Wolk, Xiaohong R. Yang, Wei Zheng, Argyrios Ziogas, Jacques Simard, Alison M. Dunning, Paul D. P. Pharoah, and Douglas F. Easton
Subjects: Biology (General), QH301-705.5
Abstract: Dennis et al. investigate potential breast cancer associations with rare germline copy number variants (CNVs) by conducting a genome-wide analysis in a large breast cancer case-control dataset. The authors detected associations with exonic deletions in established breast cancer susceptibility genes and suggestive associations for a number of non-coding CNVs.
Published: 2022
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18. Germline variants and breast cancer survival in patients with distant metastases at primary breast cancer diagnosis

Author: Maria Escala-Garcia, Sander Canisius, Renske Keeman, Jonathan Beesley, Hoda Anton-Culver, Volker Arndt, Annelie Augustinsson, Heiko Becher, Matthias W. Beckmann, Sabine Behrens, Marina Bermisheva, Stig E. Bojesen, Manjeet K. Bolla, Hermann Brenner, Federico Canzian, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Fergus J. Couch, Kamila Czene, Mary B. Daly, Joe Dennis, Peter Devilee, Thilo Dörk, Alison M. Dunning, Douglas F. Easton, Arif B. Ekici, A. Heather Eliassen, Peter A. Fasching, Henrik Flyger, Manuela Gago-Dominguez, Montserrat García-Closas, José A. García-Sáenz, Jürgen Geisler, Graham G. Giles, Mervi Grip, Melanie Gündert, Eric Hahnen, Christopher A. Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Jaana M. Hartikainen, Bernadette A. M. Heemskerk-Gerritsen, Antoinette Hollestelle, Reiner Hoppe, John L. Hopper, David J. Hunter, William Jacot, Anna Jakubowska, Esther M. John, Audrey Y. Jung, Rudolf Kaaks, Elza Khusnutdinova, Linetta B. Koppert, Peter Kraft, Vessela N. Kristensen, Allison W. Kurian, Diether Lambrechts, Loic Le Marchand, Annika Lindblom, Robert N. Luben, Jan Lubiński, Arto Mannermaa, Mehdi Manoochehri, Sara Margolin, Dimitrios Mavroudis, Taru A. Muranen, Heli Nevanlinna, Andrew F. Olshan, Håkan Olsson, Tjoung-Won Park-Simon, Alpa V. Patel, Paolo Peterlongo, Paul D. P. Pharoah, Kevin Punie, Paolo Radice, Gad Rennert, Hedy S. Rennert, Atocha Romero, Rebecca Roylance, Thomas Rüdiger, Matthias Ruebner, Emmanouil Saloustros, Elinor J. Sawyer, Rita K. Schmutzler, Minouk J. Schoemaker, Christopher Scott, Melissa C. Southey, Harald Surowy, Anthony J. Swerdlow, Rulla M. Tamimi, Lauren R. Teras, Emilie Thomas, Ian Tomlinson, Melissa A. Troester, Celine M. Vachon, Qin Wang, Robert Winqvist, Alicja Wolk, Argyrios Ziogas, kConFab/AOCS Investigators, Kyriaki Michailidou, Georgia Chenevix-Trench, Thomas Bachelot, and Marjanka K. Schmidt
Subjects: Medicine, Science
Abstract: Abstract Breast cancer metastasis accounts for most of the deaths from breast cancer. Identification of germline variants associated with survival in aggressive types of breast cancer may inform understanding of breast cancer progression and assist treatment. In this analysis, we studied the associations between germline variants and breast cancer survival for patients with distant metastases at primary breast cancer diagnosis. We used data from the Breast Cancer Association Consortium (BCAC) including 1062 women of European ancestry with metastatic breast cancer, 606 of whom died of breast cancer. We identified two germline variants on chromosome 1, rs138569520 and rs146023652, significantly associated with breast cancer-specific survival (P = 3.19 × 10−8 and 4.42 × 10−8). In silico analysis suggested a potential regulatory effect of the variants on the nearby target genes SDE2 and H3F3A. However, the variants showed no evidence of association in a smaller replication dataset. The validation dataset was obtained from the SNPs to Risk of Metastasis (StoRM) study and included 293 patients with metastatic primary breast cancer at diagnosis. Ultimately, larger replication studies are needed to confirm the identified associations.
Published: 2021
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19. Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment

Author: Anna Morra, Maria Escala-Garcia, Jonathan Beesley, Renske Keeman, Sander Canisius, Thomas U. Ahearn, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Paul L. Auer, Annelie Augustinsson, Laura E. Beane Freeman, Heiko Becher, Matthias W. Beckmann, Sabine Behrens, Stig E. Bojesen, Manjeet K. Bolla, Hermann Brenner, Thomas Brüning, Saundra S. Buys, Bette Caan, Daniele Campa, Federico Canzian, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Ting-Yuan David Cheng, Christine L. Clarke, NBCS Collaborators, Sarah V. Colonna, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Joe Dennis, Thilo Dörk, Laure Dossus, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Arif B. Ekici, A. Heather Eliassen, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Henrik Flyger, Lin Fritschi, Manuela Gago-Dominguez, José A. García-Sáenz, Graham G. Giles, Mervi Grip, Pascal Guénel, Melanie Gündert, Eric Hahnen, Christopher A. Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Steven N. Hart, Jaana M. Hartikainen, Arndt Hartmann, Wei He, Maartje J. Hooning, Reiner Hoppe, John L. Hopper, Anthony Howell, David J. Hunter, ABCTB Investigators, kConFab Investigators, Agnes Jager, Anna Jakubowska, Wolfgang Janni, Esther M. John, Audrey Y. Jung, Rudolf Kaaks, Machteld Keupers, Cari M. Kitahara, Stella Koutros, Peter Kraft, Vessela N. Kristensen, Allison W. Kurian, James V. Lacey, Diether Lambrechts, Loic Le Marchand, Annika Lindblom, Martha Linet, Robert N. Luben, Jan Lubiński, Michael Lush, Arto Mannermaa, Mehdi Manoochehri, Sara Margolin, John W. M. Martens, Maria Elena Martinez, Dimitrios Mavroudis, Kyriaki Michailidou, Roger L. Milne, Anna Marie Mulligan, Taru A. Muranen, Heli Nevanlinna, William G. Newman, Sune F. Nielsen, Børge G. Nordestgaard, Andrew F. Olshan, Håkan Olsson, Nick Orr, Tjoung-Won Park-Simon, Alpa V. Patel, Bernard Peissel, Paolo Peterlongo, Dijana Plaseska-Karanfilska, Karolina Prajzendanc, Ross Prentice, Nadege Presneau, Brigitte Rack, Gad Rennert, Hedy S. Rennert, Valerie Rhenius, Atocha Romero, Rebecca Roylance, Matthias Ruebner, Emmanouil Saloustros, Elinor J. Sawyer, Rita K. Schmutzler, Andreas Schneeweiss, Christopher Scott, Mitul Shah, Snezhana Smichkoska, Melissa C. Southey, Jennifer Stone, Harald Surowy, Anthony J. Swerdlow, Rulla M. Tamimi, William J. Tapper, Lauren R. Teras, Mary Beth Terry, Rob A. E. M. Tollenaar, Ian Tomlinson, Melissa A. Troester, Thérèse Truong, Celine M. Vachon, Qin Wang, Amber N. Hurson, Robert Winqvist, Alicja Wolk, Argyrios Ziogas, Hiltrud Brauch, Montserrat García-Closas, Paul D. P. Pharoah, Douglas F. Easton, Georgia Chenevix-Trench, and Marjanka K. Schmidt
Subjects: Common germline genetic variants, Breast cancer-specific survival, Patient subgroups, Tumor biology, Systemic treatment, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients. Methods We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP
Published: 2021
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20. Automated percent mammographic density, mammographic texture variation, and risk of breast cancer: a nested case-control study

Author: Erica T. Warner, Megan S. Rice, Oana A. Zeleznik, Erin E. Fowler, Divya Murthy, Celine M. Vachon, Kimberly A. Bertrand, Bernard A. Rosner, John Heine, and Rulla M. Tamimi
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Percent mammographic density (PMD) is a strong breast cancer risk factor, however, other mammographic features, such as V, the standard deviation (SD) of pixel intensity, may be associated with risk. We assessed whether PMD, automated PMD (APD), and V, yielded independent associations with breast cancer risk. We included 1900 breast cancer cases and 3921 matched controls from the Nurses’ Health Study (NHS) and the NHSII. Using digitized film mammograms, we estimated PMD using a computer-assisted thresholding technique. APD and V were determined using an automated computer algorithm. We used logistic regression to generate odds ratios (ORs) and 95% confidence intervals (CIs). Median time from mammogram to diagnosis was 4.1 years (interquartile range: 1.6–6.8 years). PMD (OR per SD:1.52, 95% CI: 1.42, 1.63), APD (OR per SD:1.32, 95% CI: 1.24, 1.41), and V (OR per SD:1.32, 95% CI: 1.24, 1.40) were positively associated with breast cancer risk. Associations for APD were attenuated but remained statistically significant after mutual adjustment for PMD or V. Women in the highest quartile of both APD and V (OR vs Q1/Q1: 2.49, 95% CI: 2.02, 3.06), or PMD and V (OR vs Q1/Q1: 3.57, 95% CI: 2.79, 4.58) had increased breast cancer risk. An automated method of PMD assessment is feasible and yields similar, but somewhat weaker, estimates to a manual measure. PMD, APD and V are each independently, positively associated with breast cancer risk. Women with dense breasts and greater texture variation are at the highest relative risk of breast cancer.
Published: 2021
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21. Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization

Author: Esther Clavero, José Manuel Sanchez-Maldonado, Angelica Macauda, Rob Ter Horst, Belém Sampaio-Marques, Artur Jurczyszyn, Alyssa Clay-Gilmour, Angelika Stein, Michelle A. T. Hildebrandt, Niels Weinhold, Gabriele Buda, Ramón García-Sanz, Waldemar Tomczak, Ulla Vogel, Andrés Jerez, Daria Zawirska, Marzena Wątek, Jonathan N. Hofmann, Stefano Landi, John J. Spinelli, Aleksandra Butrym, Abhishek Kumar, Joaquín Martínez-López, Sara Galimberti, María Eugenia Sarasquete, Edyta Subocz, Elzbieta Iskierka-Jażdżewska, Graham G. Giles, Malwina Rybicka-Ramos, Marcin Kruszewski, Niels Abildgaard, Francisco García Verdejo, Pedro Sánchez Rovira, Miguel Inacio da Silva Filho, Katalin Kadar, Małgorzata Razny, Wendy Cozen, Matteo Pelosini, Manuel Jurado, Parveen Bhatti, Marek Dudzinski, Agnieszka Druzd-Sitek, Enrico Orciuolo, Yang Li, Aaron D. Norman, Jan Maciej Zaucha, Rui Manuel Reis, Miroslaw Markiewicz, Juan José Rodríguez Sevilla, Vibeke Andersen, Krzysztof Jamroziak, Kari Hemminki, Sonja I. Berndt, Vicent Rajkumar, Grzegorz Mazur, Shaji K. Kumar, Paula Ludovico, Arnon Nagler, Stephen J. Chanock, Charles Dumontet, Mitchell J. Machiela, Judit Varkonyi, Nicola J. Camp, Elad Ziv, Annette Juul Vangsted, Elizabeth E. Brown, Daniele Campa, Celine M. Vachon, Mihai G. Netea, Federico Canzian, Asta Försti, and Juan Sainz
Subjects: multiple myeloma, autophagy, genetic variants, genetic susceptibility, Biology (General), QH301-705.5, Chemistry, QD1-999
Abstract: Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10−9) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10−4−5.79 × 10−14). Mechanistically, we found that the ULK4rs6599175 SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10−4), whereas the IKBKErs17433804 SNP correlated with the number of transitional CD24+CD38+ B cells (p = 4.8 × 10−4) and circulating serum concentrations of Monocyte Chemoattractant Protein (MCP)-2 (p = 3.6 × 10−4). We also found that the CD46rs1142469 SNP correlated with numbers of CD19+ B cells, CD19+CD3− B cells, CD5+IgD− cells, IgM− cells, IgD−IgM− cells, and CD4−CD8− PBMCs (p = 4.9 × 10−4−8.6 × 10−4) and circulating concentrations of interleukin (IL)-20 (p = 0.00082). Finally, we observed that the CDKN2Ars2811710 SNP correlated with levels of CD4+EMCD45RO+CD27− cells (p = 9.3 × 10−4). These results suggest that genetic variants within these six loci influence MM risk through the modulation of specific subsets of immune cells, as well as vitamin D3−, MCP-2−, and IL20-dependent pathways.
Published: 2023
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22. A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers

Author: Juliette Coignard, Michael Lush, Jonathan Beesley, Tracy A. O’Mara, Joe Dennis, Jonathan P. Tyrer, Daniel R. Barnes, Lesley McGuffog, Goska Leslie, Manjeet K. Bolla, Muriel A. Adank, Simona Agata, Thomas Ahearn, Kristiina Aittomäki, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Norbert Arnold, Kristan J. Aronson, Banu K. Arun, Annelie Augustinsson, Jacopo Azzollini, Daniel Barrowdale, Caroline Baynes, Heko Becher, Marina Bermisheva, Leslie Bernstein, Katarzyna Białkowska, Carl Blomqvist, Stig E. Bojesen, Bernardo Bonanni, Ake Borg, Hiltrud Brauch, Hermann Brenner, Barbara Burwinkel, Saundra S. Buys, Trinidad Caldés, Maria A. Caligo, Daniele Campa, Brian D. Carter, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Wendy K. Chung, Kathleen B. M. Claes, Christine L. Clarke, GEMO Study Collaborators, EMBRACE Collaborators, J. Margriet Collée, Don M. Conroy, Kamila Czene, Mary B. Daly, Peter Devilee, Orland Diez, Yuan Chun Ding, Susan M. Domchek, Thilo Dörk, Isabel dos-Santos-Silva, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, A. Heather Eliassen, Christoph Engel, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Henrik Flyger, Florentia Fostira, Eitan Friedman, Lin Fritschi, Debra Frost, Manuela Gago-Dominguez, Susan M. Gapstur, Judy Garber, Vanesa Garcia-Barberan, Montserrat García-Closas, José A. García-Sáenz, Mia M. Gaudet, Simon A. Gayther, Andrea Gehrig, Vassilios Georgoulias, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Anna González-Neira, Mark H. Greene, Pascal Guénel, Lothar Haeberle, Eric Hahnen, Christopher A. Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Patricia A. Harrington, Steven N. Hart, Wei He, Frans B. L. Hogervorst, Antoinette Hollestelle, John L. Hopper, Darling J. Horcasitas, Peter J. Hulick, David J. Hunter, Evgeny N. Imyanitov, KConFab Investigators, HEBON Investigators, ABCTB Investigators, Agnes Jager, Anna Jakubowska, Paul A. James, Uffe Birk Jensen, Esther M. John, Michael E. Jones, Rudolf Kaaks, Pooja Middha Kapoor, Beth Y. Karlan, Renske Keeman, Elza Khusnutdinova, Johanna I. Kiiski, Yon-Dschun Ko, Veli-Matti Kosma, Peter Kraft, Allison W. Kurian, Yael Laitman, Diether Lambrechts, Loic Le Marchand, Jenny Lester, Fabienne Lesueur, Tricia Lindstrom, Adria Lopez-Fernández, Jennifer T. Loud, Craig Luccarini, Arto Mannermaa, Siranoush Manoukian, Sara Margolin, John W. M. Martens, Noura Mebirouk, Alfons Meindl, Austin Miller, Roger L. Milne, Marco Montagna, Katherine L. Nathanson, Susan L. Neuhausen, Heli Nevanlinna, Finn C. Nielsen, Katie M. O’Brien, Olufunmilayo I. Olopade, Janet E. Olson, Håkan Olsson, Ana Osorio, Laura Ottini, Tjoung-Won Park-Simon, Michael T. Parsons, Inge Sokilde Pedersen, Beth Peshkin, Paolo Peterlongo, Julian Peto, Paul D. P. Pharoah, Kelly-Anne Phillips, Eric C. Polley, Bruce Poppe, Nadege Presneau, Miquel Angel Pujana, Kevin Punie, Paolo Radice, Johanna Rantala, Muhammad U. Rashid, Gad Rennert, Hedy S. Rennert, Mark Robson, Atocha Romero, Maria Rossing, Emmanouil Saloustros, Dale P. Sandler, Regina Santella, Maren T. Scheuner, Marjanka K. Schmidt, Gunnar Schmidt, Christopher Scott, Priyanka Sharma, Penny Soucy, Melissa C. Southey, John J. Spinelli, Zoe Steinsnyder, Jennifer Stone, Dominique Stoppa-Lyonnet, Anthony Swerdlow, Rulla M. Tamimi, William J. Tapper, Jack A. Taylor, Mary Beth Terry, Alex Teulé, Darcy L. Thull, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Alison H. Trainer, Thérèse Truong, Nadine Tung, Celine M. Vachon, Ana Vega, Joseph Vijai, Qin Wang, Barbara Wappenschmidt, Clarice R. Weinberg, Jeffrey N. Weitzel, Camilla Wendt, Alicja Wolk, Siddhartha Yadav, Xiaohong R. Yang, Drakoulis Yannoukakos, Wei Zheng, Argyrios Ziogas, Kristin K. Zorn, Sue K. Park, Mads Thomassen, Kenneth Offit, Rita K. Schmutzler, Fergus J. Couch, Jacques Simard, Georgia Chenevix-Trench, Douglas F. Easton, Nadine Andrieu, and Antonis C. Antoniou
Subjects: Science
Abstract: Breast cancer risk for BRCA1/BRCA2 mutation carriers varies depending on other genetic factors. Here, the authors perform a case-only genome-wide association study and highlight novel loci associated with breast cancer risk for BRCA1/BRCA2 mutation carriers.
Published: 2021
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23. A network analysis to identify mediators of germline-driven differences in breast cancer prognosis

Author: Maria Escala-Garcia, Jean Abraham, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Alan Ashworth, Paul L. Auer, Päivi Auvinen, Matthias W. Beckmann, Jonathan Beesley, Sabine Behrens, Javier Benitez, Marina Bermisheva, Carl Blomqvist, William Blot, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Anne-Lise Børresen-Dale, Hiltrud Brauch, Hermann Brenner, Sara Y. Brucker, Barbara Burwinkel, Carlos Caldas, Federico Canzian, Jenny Chang-Claude, Stephen J. Chanock, Suet-Feung Chin, Christine L. Clarke, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Joe Dennis, Peter Devilee, Janet A. Dunn, Alison M. Dunning, Miriam Dwek, Helena M. Earl, Diana M. Eccles, A. Heather Eliassen, Carolina Ellberg, D. Gareth Evans, Peter A. Fasching, Jonine Figueroa, Henrik Flyger, Manuela Gago-Dominguez, Susan M. Gapstur, Montserrat García-Closas, José A. García-Sáenz, Mia M. Gaudet, Angela George, Graham G. Giles, David E. Goldgar, Anna González-Neira, Mervi Grip, Pascal Guénel, Qi Guo, Christopher A. Haiman, Niclas Håkansson, Ute Hamann, Patricia A. Harrington, Louise Hiller, Maartje J. Hooning, John L. Hopper, Anthony Howell, Chiun-Sheng Huang, Guanmengqian Huang, David J. Hunter, Anna Jakubowska, Esther M. John, Rudolf Kaaks, Pooja Middha Kapoor, Renske Keeman, Cari M. Kitahara, Linetta B. Koppert, Peter Kraft, Vessela N. Kristensen, Diether Lambrechts, Loic Le Marchand, Flavio Lejbkowicz, Annika Lindblom, Jan Lubiński, Arto Mannermaa, Mehdi Manoochehri, Siranoush Manoukian, Sara Margolin, Maria Elena Martinez, Tabea Maurer, Dimitrios Mavroudis, Alfons Meindl, Roger L. Milne, Anna Marie Mulligan, Susan L. Neuhausen, Heli Nevanlinna, William G. Newman, Andrew F. Olshan, Janet E. Olson, Håkan Olsson, Nick Orr, Paolo Peterlongo, Christos Petridis, Ross L. Prentice, Nadege Presneau, Kevin Punie, Dhanya Ramachandran, Gad Rennert, Atocha Romero, Mythily Sachchithananthan, Emmanouil Saloustros, Elinor J. Sawyer, Rita K. Schmutzler, Lukas Schwentner, Christopher Scott, Jacques Simard, Christof Sohn, Melissa C. Southey, Anthony J. Swerdlow, Rulla M. Tamimi, William J. Tapper, Manuel R. Teixeira, Mary Beth Terry, Heather Thorne, Rob A. E. M. Tollenaar, Ian Tomlinson, Melissa A. Troester, Thérèse Truong, Clare Turnbull, Celine M. Vachon, Lizet E. van der Kolk, Qin Wang, Robert Winqvist, Alicja Wolk, Xiaohong R. Yang, Argyrios Ziogas, Paul D. P. Pharoah, Per Hall, Lodewyk F. A. Wessels, Georgia Chenevix-Trench, Gary D. Bader, Thilo Dörk, Douglas F. Easton, Sander Canisius, and Marjanka K. Schmidt
Subjects: Science
Abstract: In breast cancer the contribution of different genetic variants to disease heritability is complex and not fully understood. Here, the authors present a network-based analysis in 84,567 patients studying ~7.3 million variants, identifying gene modules associated with breast cancer survival.
Published: 2020
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24. Behavioral and psychological impact of returning breast density results to Latinas: study protocol for a randomized clinical trial

Author: Bhavika K. Patel, Jennifer L. Ridgeway, Karthik Ghosh, Deborah J. Rhodes, Bijan Borah, Sarah Jenkins, Vera J. Suman, Aaron Norman, Matt Jewett, Davinder Singh, Celine M. Vachon, and Carmen Radecki Breitkopf
Subjects: Mammographic breast density (MBD), Mammography, Breast density, Breast density legislation, Breast cancer, Hispanic, Medicine (General), R5-920
Abstract: Abstract Background Breast cancer is the most common cancer and the leading cause of cancer mortality among Latinas. As more is learned about the association between mammographic breast density (MBD) and breast cancer risk, a number of U.S. states adopted legislation and now a federal law mandates written notification of MBD along with mammogram results. These notifications vary in content and readability, though, which may limit their effectiveness and create confusion or concern, especially among women with low health literacy or barriers to screening. The purpose of this study is to determine whether educational enhancement of MBD notification results in increased knowledge, decreased anxiety, and adherence to continued mammography screening among Latina women in a limited-resources setting. Methods Latinas LEarning About Density (LLEAD) is a randomized clinical trial (RCT) comparing the impact of three notification approaches on behavioral and psychological outcomes in Latina women. Approximately 2000 Latinas undergoing screening mammography in a safety-net community clinic will be randomized 1:1:1 to mailed notification (usual care); mailed notification plus written educational materials (enhanced); or mailed notification, written educational materials, plus verbal explanation by a promotora (interpersonal). The educational materials and verbal explanations are available in Spanish or English. Mechanisms through which written or verbal information influences future screening motivation and behavior will be examined, as well as moderating factors such as depression and worry about breast cancer, which have been linked to diagnostic delays among Latinas. The study includes multiple psychological measures (anxiety, depression, knowledge about MBD, perceived risk of breast cancer, worry, self-efficacy) and behavioral outcomes (continued adherence to mammography). Measurement time points include enrollment, 2–4 weeks post-randomization, and 1 and 2 years post-randomization. Qualitative inquiry related to process and outcomes of the interpersonal arm and cost analysis related to its implementation will be undertaken to understand the intervention’s delivery and transferability. Discussion Legislation mandating written MBD notification may have unintended consequences on behavioral and psychological outcomes, particularly among Latinas with limited health literacy and resources. This study has implications for cancer risk communication and will offer evidence on the potential of generalizable educational strategies for delivering information on breast density to Latinas in limited-resource settings. Trial registration ClinicalTrials.gov, NCT02910986. Registered on 21 September 2016. Items from the WHO Trial Registration Data Set can be found in this protocol.
Published: 2019
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25. Automated volumetric breast density measures: differential change between breasts in women with and without breast cancer

Author: Kathleen R. Brandt, Christopher G. Scott, Diana L. Miglioretti, Matthew R. Jensen, Amir P. Mahmoudzadeh, Carrie Hruska, Lin Ma, Fang Fang Wu, Steven R. Cummings, Aaron D. Norman, Natalie J. Engmann, John A. Shepherd, Stacey J. Winham, Karla Kerlikowske, and Celine M. Vachon
Subjects: Volumetric density, Breast density, Breast cancer, Tissue asymmetry, Risk, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Given that breast cancer and normal dense fibroglandular tissue have similar radiographic attenuation, we examine whether automated volumetric density measures identify a differential change between breasts in women with cancer and compare to healthy controls. Methods Eligible cases (n = 1160) had unilateral invasive breast cancer and bilateral full-field digital mammograms (FFDMs) at two time points: within 2 months and 1–5 years before diagnosis. Controls (n = 2360) were matched to cases on age and date of FFDMs. Dense volume (DV) and volumetric percent density (VPD) for each breast were assessed using Volpara™. Differences in DV and VPD between mammograms (median 3 years apart) were calculated per breast separately for cases and controls and their difference evaluated by using the Wilcoxon signed-rank test. To simulate clinical practice where cancer laterality is unknown, we examined whether the absolute difference between breasts can discriminate cases from controls using area under the ROC curve (AUC) analysis, adjusting for age, BMI, and time. Results Among cases, the VPD and DV between mammograms of the cancerous breast decreased to a lesser degree (− 0.26% and − 2.10 cm3) than the normal breast (− 0.39% and − 2.74 cm3) for a difference of 0.13% (p value
Published: 2019
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26. Publisher Correction: Shared heritability and functional enrichment across six solid cancers

Author: Xia Jiang, Hilary K. Finucane, Fredrick R. Schumacher, Stephanie L. Schmit, Jonathan P. Tyrer, Younghun Han, Kyriaki Michailidou, Corina Lesseur, Karoline B. Kuchenbaecker, Joe Dennis, David V. Conti, Graham Casey, Mia M. Gaudet, Jeroen R. Huyghe, Demetrius Albanes, Melinda C. Aldrich, Angeline S. Andrew, Irene L. Andrulis, Hoda Anton-Culver, Antonis C. Antoniou, Natalia N. Antonenkova, Susanne M. Arnold, Kristan J. Aronson, Banu K. Arun, Elisa V. Bandera, Rosa B. Barkardottir, Daniel R. Barnes, Jyotsna Batra, Matthias W. Beckmann, Javier Benitez, Sara Benlloch, Andrew Berchuck, Sonja I. Berndt, Heike Bickeböller, Stephanie A. Bien, Carl Blomqvist, Stefania Boccia, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Hiltrud Brauch, Hermann Brenner, James D. Brenton, Mark N. Brook, Joan Brunet, Hans Brunnström, Daniel D. Buchanan, Barbara Burwinkel, Ralf Butzow, Gabriella Cadoni, Trinidad Caldés, Maria A. Caligo, Ian Campbell, Peter T. Campbell, Géraldine Cancel-Tassin, Lisa Cannon-Albright, Daniele Campa, Neil Caporaso, André L. Carvalho, Andrew T. Chan, Jenny Chang-Claude, Stephen J. Chanock, Chu Chen, David C. Christiani, Kathleen B. M. Claes, Frank Claessens, Judith Clements, J. Margriet Collée, Marcia Cruz Correa, Fergus J. Couch, Angela Cox, Julie M. Cunningham, Cezary Cybulski, Kamila Czene, Mary B. Daly, Anna deFazio, Peter Devilee, Orland Diez, Manuela Gago-Dominguez, Jenny L. Donovan, Thilo Dörk, Eric J. Duell, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Christopher K. Edlund, Digna R. Velez Edwards, Carolina Ellberg, D. Gareth Evans, Peter A. Fasching, Robert L. Ferris, Triantafillos Liloglou, Jane C. Figueiredo, Olivia Fletcher, Renée T. Fortner, Florentia Fostira, Silvia Franceschi, Eitan Friedman, Steven J. Gallinger, Patricia A. Ganz, Judy Garber, José A. García-Sáenz, Simon A. Gayther, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Ellen L. Goode, Marc T. Goodman, Gary Goodman, Kjell Grankvist, Mark H. Greene, Henrik Gronberg, Jacek Gronwald, Pascal Guénel, Niclas Håkansson, Per Hall, Ute Hamann, Freddie C. Hamdy, Robert J. Hamilton, Jochen Hampe, Aage Haugen, Florian Heitz, Rolando Herrero, Peter Hillemanns, Michael Hoffmeister, Estrid Høgdall, Yun-Chul Hong, John L. Hopper, Richard Houlston, Peter J. Hulick, David J. Hunter, David G. Huntsman, Gregory Idos, Evgeny N. Imyanitov, Sue Ann Ingles, Claudine Isaacs, Anna Jakubowska, Paul James, Mark A. Jenkins, Mattias Johansson, Mikael Johansson, Esther M. John, Amit D. Joshi, Radka Kaneva, Beth Y. Karlan, Linda E. Kelemen, Tabea Kühl, Kay-Tee Khaw, Elza Khusnutdinova, Adam S. Kibel, Lambertus A. Kiemeney, Jeri Kim, Susanne K. Kjaer, Julia A. Knight, Manolis Kogevinas, Zsofia Kote-Jarai, Stella Koutros, Vessela N. Kristensen, Jolanta Kupryjanczyk, Martin Lacko, Stephan Lam, Diether Lambrechts, Maria Teresa Landi, Philip Lazarus, Nhu D. Le, Eunjung Lee, Flavio Lejbkowicz, Heinz-Josef Lenz, Goska Leslie, Davor Lessel, Jenny Lester, Douglas A. Levine, Li Li, Christopher I. Li, Annika Lindblom, Noralane M. Lindor, Geoffrey Liu, Fotios Loupakis, Jan Lubiński, Lovise Maehle, Christiane Maier, Arto Mannermaa, Loic Le Marchand, Sara Margolin, Taymaa May, Lesley McGuffog, Alfons Meindl, Pooja Middha, Austin Miller, Roger L. Milne, Robert J. MacInnis, Francesmary Modugno, Marco Montagna, Victor Moreno, Kirsten B. Moysich, Lorelei Mucci, Kenneth Muir, Anna Marie Mulligan, Katherine L. Nathanson, David E. Neal, Andrew R. Ness, Susan L. Neuhausen, Heli Nevanlinna, Polly A. Newcomb, Lisa F. Newcomb, Finn Cilius Nielsen, Liene Nikitina-Zake, Børge G. Nordestgaard, Robert L. Nussbaum, Kenneth Offit, Edith Olah, Ali Amin Al Olama, Olufunmilayo I. Olopade, Andrew F. Olshan, Håkan Olsson, Ana Osorio, Hardev Pandha, Jong Y. Park, Nora Pashayan, Michael T. Parsons, Tanja Pejovic, Kathryn L. Penney, Wilbert H. M. Peters, Catherine M. Phelan, Amanda I. Phipps, Dijana Plaseska-Karanfilska, Miranda Pring, Darya Prokofyeva, Paolo Radice, Kari Stefansson, Susan J. Ramus, Leon Raskin, Gad Rennert, Hedy S. Rennert, Elizabeth J. van Rensburg, Marjorie J. Riggan, Harvey A. Risch, Angela Risch, Monique J. Roobol, Barry S. Rosenstein, Mary Anne Rossing, Kim De Ruyck, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Matthew B. Schabath, Johanna Schleutker, Marjanka K. Schmidt, V. Wendy Setiawan, Hongbing Shen, Erin M. Siegel, Weiva Sieh, Christian F. Singer, Martha L. Slattery, Karina Dalsgaard Sorensen, Melissa C. Southey, Amanda B. Spurdle, Janet L. Stanford, Victoria L. Stevens, Sebastian Stintzing, Jennifer Stone, Karin Sundfeldt, Rebecca Sutphen, Anthony J. Swerdlow, Eloiza H. Tajara, Catherine M. Tangen, Adonina Tardon, Jack A. Taylor, M. Dawn Teare, Manuel R. Teixeira, Mary Beth Terry, Kathryn L. Terry, Stephen N. Thibodeau, Mads Thomassen, Line Bjørge, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Paul A. Townsend, Ruth C. Travis, Nadine Tung, Shelley S. Tworoger, Cornelia M. Ulrich, Nawaid Usmani, Celine M. Vachon, Els Van Nieuwenhuysen, Ana Vega, Miguel Elías Aguado-Barrera, Qin Wang, Penelope M. Webb, Clarice R. Weinberg, Stephanie Weinstein, Mark C. Weissler, Jeffrey N. Weitzel, Catharine M. L. West, Emily White, Alice S. Whittemore, H-Erich Wichmann, Fredrik Wiklund, Robert Winqvist, Alicja Wolk, Penella Woll, Michael Woods, Anna H. Wu, Xifeng Wu, Drakoulis Yannoukakos, Wei Zheng, Shanbeh Zienolddiny, Argyrios Ziogas, Kristin K. Zorn, Jacqueline M. Lane, Richa Saxena, Duncan Thomas, Rayjean J. Hung, Brenda Diergaarde, James McKay, Ulrike Peters, Li Hsu, Montserrat García-Closas, Rosalind A. Eeles, Georgia Chenevix-Trench, Paul J. Brennan, Christopher A. Haiman, Jacques Simard, Douglas F. Easton, Stephen B. Gruber, Paul D. P. Pharoah, Alkes L. Price, Bogdan Pasaniuc, Christopher I. Amos, Peter Kraft, and Sara Lindström
Subjects: Science
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2019
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27. Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk

Author: Celine M. Vachon, Christopher G. Scott, Rulla M. Tamimi, Deborah J. Thompson, Peter A. Fasching, Jennifer Stone, Melissa C. Southey, Stacey Winham, Sara Lindström, Jenna Lilyquist, Graham G. Giles, Roger L. Milne, Robert J. MacInnis, Laura Baglietto, Jingmei Li, Kamila Czene, Manjeet K. Bolla, Qin Wang, Joe Dennis, Lothar Haeberle, Mikael Eriksson, Peter Kraft, Robert Luben, Nick Wareham, Janet E. Olson, Aaron Norman, Eric C. Polley, Gertraud Maskarinec, Loic Le Marchand, Christopher A. Haiman, John L. Hopper, Fergus J. Couch, Douglas F. Easton, Per Hall, Nilanjan Chatterjee, and Montse Garcia-Closas
Subjects: Breast density, Breast cancer risk, Polygenic risk score, Genetic variation, Risk models, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. Methods Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. Results Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38–1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28–1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45–1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. Conclusions The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.
Published: 2019
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28. Body mass index, mammographic density, and breast cancer risk by estrogen receptor subtype

Author: Yiwey Shieh, Christopher G. Scott, Matthew R. Jensen, Aaron D. Norman, Kimberly A. Bertrand, V. Shane Pankratz, Kathleen R. Brandt, Daniel W. Visscher, John A. Shepherd, Rulla M. Tamimi, Celine M. Vachon, and Karla Kerlikowske
Subjects: Breast neoplasms, Epidemiology, Risk factors, Mammographic breast density, Prevention, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Obesity and elevated breast density are common risk factors for breast cancer, and their effects may vary by estrogen receptor (ER) subtype. However, their joint effects on ER subtype-specific risk are unknown. Understanding this relationship could enhance risk stratification for screening and prevention. Thus, we assessed the association between breast density and ER subtype according to body mass index (BMI) and menopausal status. Methods We conducted a case-control study nested within two mammography screening cohorts, the Mayo Mammography Health Study and the San Francisco Bay Area Breast Cancer SPORE/San Francisco Mammography Registry. Our pooled analysis contained 1538 ER-positive and 285 ER-negative invasive breast cancer cases and 4720 controls matched on age, menopausal status at time of mammogram, and year of mammogram. Percent density was measured on digitized film mammograms using computer-assisted techniques. We used polytomous logistic regression to evaluate the association between percent density and ER subtype by BMI subgroup (normal/underweight,
Published: 2019
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29. Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer

Author: Manuel A. Ferreira, Eric R. Gamazon, Fares Al-Ejeh, Kristiina Aittomäki, Irene L. Andrulis, Hoda Anton-Culver, Adalgeir Arason, Volker Arndt, Kristan J. Aronson, Banu K. Arun, Ella Asseryanis, Jacopo Azzollini, Judith Balmaña, Daniel R. Barnes, Daniel Barrowdale, Matthias W. Beckmann, Sabine Behrens, Javier Benitez, Marina Bermisheva, Katarzyna Białkowska, Carl Blomqvist, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Ake Borg, Hiltrud Brauch, Hermann Brenner, Annegien Broeks, Barbara Burwinkel, Trinidad Caldés, Maria A. Caligo, Daniele Campa, Ian Campbell, Federico Canzian, Jonathan Carter, Brian D. Carter, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Hans Christiansen, Wendy K. Chung, Kathleen B. M. Claes, Christine L. Clarke, EMBRACE Collaborators, GC-HBOC Study Collaborators, GEMO Study Collaborators, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Miguel de la Hoya, Joe Dennis, Peter Devilee, Orland Diez, Thilo Dörk, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Bent Ejlertsen, Carolina Ellberg, Christoph Engel, Mikael Eriksson, Peter A. Fasching, Olivia Fletcher, Henrik Flyger, Eitan Friedman, Debra Frost, Marike Gabrielson, Manuela Gago-Dominguez, Patricia A. Ganz, Susan M. Gapstur, Judy Garber, Montserrat García-Closas, José A. García-Sáenz, Mia M. Gaudet, Graham G. Giles, Gord Glendon, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Anna González-Neira, Mark H. Greene, Jacek Gronwald, Pascal Guénel, Christopher A. Haiman, Per Hall, Ute Hamann, Wei He, Jane Heyworth, Frans B. L. Hogervorst, Antoinette Hollestelle, Robert N. Hoover, John L. Hopper, Peter J. Hulick, Keith Humphreys, Evgeny N. Imyanitov, ABCTB Investigators, HEBON Investigators, BCFR Investigators, Claudine Isaacs, Milena Jakimovska, Anna Jakubowska, Paul A. James, Ramunas Janavicius, Rachel C. Jankowitz, Esther M. John, Nichola Johnson, Vijai Joseph, Beth Y. Karlan, Elza Khusnutdinova, Johanna I. Kiiski, Yon-Dschun Ko, Michael E. Jones, Irene Konstantopoulou, Vessela N. Kristensen, Yael Laitman, Diether Lambrechts, Conxi Lazaro, Goska Leslie, Jenny Lester, Fabienne Lesueur, Sara Lindström, Jirong Long, Jennifer T. Loud, Jan Lubiński, Enes Makalic, Arto Mannermaa, Mehdi Manoochehri, Sara Margolin, Tabea Maurer, Dimitrios Mavroudis, Lesley McGuffog, Alfons Meindl, Usha Menon, Kyriaki Michailidou, Austin Miller, Marco Montagna, Fernando Moreno, Lidia Moserle, Anna Marie Mulligan, Katherine L. Nathanson, Susan L. Neuhausen, Heli Nevanlinna, Ines Nevelsteen, Finn C. Nielsen, Liene Nikitina-Zake, Robert L. Nussbaum, Kenneth Offit, Edith Olah, Olufunmilayo I. Olopade, Håkan Olsson, Ana Osorio, Janos Papp, Tjoung-Won Park-Simon, Michael T. Parsons, Inge Sokilde Pedersen, Ana Peixoto, Paolo Peterlongo, Paul D. P. Pharoah, Dijana Plaseska-Karanfilska, Bruce Poppe, Nadege Presneau, Paolo Radice, Johanna Rantala, Gad Rennert, Harvey A. Risch, Emmanouil Saloustros, Kristin Sanden, Elinor J. Sawyer, Marjanka K. Schmidt, Rita K. Schmutzler, Priyanka Sharma, Xiao-Ou Shu, Jacques Simard, Christian F. Singer, Penny Soucy, Melissa C. Southey, John J. Spinelli, Amanda B. Spurdle, Jennifer Stone, Anthony J. Swerdlow, William J. Tapper, Jack A. Taylor, Manuel R. Teixeira, Mary Beth Terry, Alex Teulé, Mads Thomassen, Kathrin Thöne, Darcy L. Thull, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Thérèse Truong, Nadine Tung, Celine M. Vachon, Christi J. van Asperen, Ans M. W. van den Ouweland, Elizabeth J. van Rensburg, Ana Vega, Alessandra Viel, Qin Wang, Barbara Wappenschmidt, Jeffrey N. Weitzel, Camilla Wendt, Robert Winqvist, Xiaohong R. Yang, Drakoulis Yannoukakos, Argyrios Ziogas, Peter Kraft, Antonis C. Antoniou, Wei Zheng, Douglas F. Easton, Roger L. Milne, Jonathan Beesley, and Georgia Chenevix-Trench
Subjects: Science
Abstract: Over 170 susceptibility loci have been identified by genome-wide association studies in breast cancer. Here, the authors interrogated the role of risk-associated variants from non-breast tissue, and using expression quantitative trait loci, identify potential target genes of known breast cancer susceptibility variants, as well as 11 regions not previously known to be associated with breast cancer risk.
Published: 2019
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30. Impact of short-term low-dose tamoxifen on molecular breast imaging background parenchymal uptake: a pilot study

Author: Carrie B. Hruska, Katie N. Hunt, Amy Lynn Conners, Jennifer R. Geske, Kathleen R. Brandt, Amy C. Degnim, Celine M. Vachon, Michael K. O’Connor, and Deborah J. Rhodes
Subjects: Molecular breast imaging, Tamoxifen, Tc-99m sestamibi, Background parenchymal uptake, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background High background parenchymal uptake (BPU) on molecular breast imaging (MBI) has been identified as a breast cancer risk factor. We explored the feasibility of offering a short-term intervention of low-dose oral tamoxifen to women with high BPU and examined whether this intervention would reduce BPU. Methods Women with a history of high BPU and no breast cancer history were invited to the study. Participants had an MBI exam, followed by 30 days of low-dose oral tamoxifen at either 5 mg or 10 mg/day, and a post-tamoxifen MBI exam. BPU on pre- and post-tamoxifen MBI exams was quantitatively assessed as the ratio of average counts in breast fibroglandular tissue vs. average counts in subcutaneous fat. Pre-tamoxifen and post-tamoxifen BPU were compared with paired t tests. Results Of 47 women invited, 22 enrolled and 21 completed the study (10 taking 5 mg tamoxifen, 11 taking 10 mg tamoxifen). Mean age was 47.7 years (range 41–56 years). After 30 days low-dose tamoxifen, 8 of 21 women (38%) showed a decline in BPU, defined as a decrease from the pre-tamoxifen MBI of at least 15%; 11 of 21 (52%) had no change in BPU (within ± 15%); 2 of 21 (10%) had an increase in BPU of greater than 15%. Overall, the average post-tamoxifen BPU was not significantly different from pre-tamoxifen BPU (1.34 post vs. 1.43 pre, p = 0.11). However, among women taking 10 mg tamoxifen, 5 of 11 (45%) showed a decline in BPU; average BPU was 1.19 post-tamoxifen vs. 1.34 pre-tamoxifen (p = 0.005). In women taking 5 mg tamoxifen, 2 of 10 (20%) showed a decline in BPU; average BPU was 1.51 post-tamoxifen vs.1.53 pre-tamoxifen (p = 0.99). Conclusions Short-term intervention with low-dose tamoxifen may reduce high BPU on MBI for some patients. Our preliminary findings suggest that 10 mg tamoxifen per day may be more effective than 5 mg for inducing declines in BPU within 30 days. Given the variability in BPU response to tamoxifen observed among study participants, future study is warranted to determine if BPU response could predict the effectiveness of tamoxifen for breast cancer risk reduction within an individual. Trial registration ClinicalTrials.gov NCT02979301. Registered 01 December 2016.
Published: 2019
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31. Shared heritability and functional enrichment across six solid cancers

Author: Xia Jiang, Hilary K. Finucane, Fredrick R. Schumacher, Stephanie L. Schmit, Jonathan P. Tyrer, Younghun Han, Kyriaki Michailidou, Corina Lesseur, Karoline B. Kuchenbaecker, Joe Dennis, David V. Conti, Graham Casey, Mia M. Gaudet, Jeroen R. Huyghe, Demetrius Albanes, Melinda C. Aldrich, Angeline S. Andrew, Irene L. Andrulis, Hoda Anton-Culver, Antonis C. Antoniou, Natalia N. Antonenkova, Susanne M. Arnold, Kristan J. Aronson, Banu K. Arun, Elisa V. Bandera, Rosa B. Barkardottir, Daniel R. Barnes, Jyotsna Batra, Matthias W. Beckmann, Javier Benitez, Sara Benlloch, Andrew Berchuck, Sonja I. Berndt, Heike Bickeböller, Stephanie A. Bien, Carl Blomqvist, Stefania Boccia, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Hiltrud Brauch, Hermann Brenner, James D. Brenton, Mark N. Brook, Joan Brunet, Hans Brunnström, Daniel D. Buchanan, Barbara Burwinkel, Ralf Butzow, Gabriella Cadoni, Trinidad Caldés, Maria A. Caligo, Ian Campbell, Peter T. Campbell, Géraldine Cancel-Tassin, Lisa Cannon-Albright, Daniele Campa, Neil Caporaso, André L. Carvalho, Andrew T. Chan, Jenny Chang-Claude, Stephen J. Chanock, Chu Chen, David C. Christiani, Kathleen B. M. Claes, Frank Claessens, Judith Clements, J. Margriet Collée, Marcia Cruz Correa, Fergus J. Couch, Angela Cox, Julie M. Cunningham, Cezary Cybulski, Kamila Czene, Mary B. Daly, Anna deFazio, Peter Devilee, Orland Diez, Manuela Gago-Dominguez, Jenny L. Donovan, Thilo Dörk, Eric J. Duell, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Christopher K. Edlund, Digna R Velez Edwards, Carolina Ellberg, D. Gareth Evans, Peter A. Fasching, Robert L. Ferris, Triantafillos Liloglou, Jane C. Figueiredo, Olivia Fletcher, Renée T. Fortner, Florentia Fostira, Silvia Franceschi, Eitan Friedman, Steven J. Gallinger, Patricia A. Ganz, Judy Garber, José A. García-Sáenz, Simon A. Gayther, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Ellen L. Goode, Marc T. Goodman, Gary Goodman, Kjell Grankvist, Mark H. Greene, Henrik Gronberg, Jacek Gronwald, Pascal Guénel, Niclas Håkansson, Per Hall, Ute Hamann, Freddie C. Hamdy, Robert J. Hamilton, Jochen Hampe, Aage Haugen, Florian Heitz, Rolando Herrero, Peter Hillemanns, Michael Hoffmeister, Estrid Høgdall, Yun-Chul Hong, John L. Hopper, Richard Houlston, Peter J. Hulick, David J. Hunter, David G. Huntsman, Gregory Idos, Evgeny N. Imyanitov, Sue Ann Ingles, Claudine Isaacs, Anna Jakubowska, Paul James, Mark A. Jenkins, Mattias Johansson, Mikael Johansson, Esther M. John, Amit D. Joshi, Radka Kaneva, Beth Y. Karlan, Linda E. Kelemen, Tabea Kühl, Kay-Tee Khaw, Elza Khusnutdinova, Adam S. Kibel, Lambertus A. Kiemeney, Jeri Kim, Susanne K. Kjaer, Julia A. Knight, Manolis Kogevinas, Zsofia Kote-Jarai, Stella Koutros, Vessela N. Kristensen, Jolanta Kupryjanczyk, Martin Lacko, Stephan Lam, Diether Lambrechts, Maria Teresa Landi, Philip Lazarus, Nhu D. Le, Eunjung Lee, Flavio Lejbkowicz, Heinz-Josef Lenz, Goska Leslie, Davor Lessel, Jenny Lester, Douglas A. Levine, Li Li, Christopher I. Li, Annika Lindblom, Noralane M. Lindor, Geoffrey Liu, Fotios Loupakis, Jan Lubiński, Lovise Maehle, Christiane Maier, Arto Mannermaa, Loic Le Marchand, Sara Margolin, Taymaa May, Lesley McGuffog, Alfons Meindl, Pooja Middha, Austin Miller, Roger L. Milne, Robert J. MacInnis, Francesmary Modugno, Marco Montagna, Victor Moreno, Kirsten B. Moysich, Lorelei Mucci, Kenneth Muir, Anna Marie Mulligan, Katherine L. Nathanson, David E. Neal, Andrew R. Ness, Susan L. Neuhausen, Heli Nevanlinna, Polly A. Newcomb, Lisa F. Newcomb, Finn Cilius Nielsen, Liene Nikitina-Zake, Børge G. Nordestgaard, Robert L. Nussbaum, Kenneth Offit, Edith Olah, Ali Amin Al Olama, Olufunmilayo I. Olopade, Andrew F. Olshan, Håkan Olsson, Ana Osorio, Hardev Pandha, Jong Y. Park, Nora Pashayan, Michael T. Parsons, Tanja Pejovic, Kathryn L. Penney, Wilbert H M. Peters, Catherine M. Phelan, Amanda I. Phipps, Dijana Plaseska-Karanfilska, Miranda Pring, Darya Prokofyeva, Paolo Radice, Kari Stefansson, Susan J. Ramus, Leon Raskin, Gad Rennert, Hedy S. Rennert, Elizabeth J. van Rensburg, Marjorie J. Riggan, Harvey A. Risch, Angela Risch, Monique J. Roobol, Barry S. Rosenstein, Mary Anne Rossing, Kim De Ruyck, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Matthew B. Schabath, Johanna Schleutker, Marjanka K. Schmidt, V. Wendy Setiawan, Hongbing Shen, Erin M. Siegel, Weiva Sieh, Christian F. Singer, Martha L. Slattery, Karina Dalsgaard Sorensen, Melissa C. Southey, Amanda B. Spurdle, Janet L. Stanford, Victoria L. Stevens, Sebastian Stintzing, Jennifer Stone, Karin Sundfeldt, Rebecca Sutphen, Anthony J. Swerdlow, Eloiza H. Tajara, Catherine M. Tangen, Adonina Tardon, Jack A. Taylor, M. Dawn Teare, Manuel R. Teixeira, Mary Beth Terry, Kathryn L. Terry, Stephen N. Thibodeau, Mads Thomassen, Line Bjørge, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Paul A. Townsend, Ruth C. Travis, Nadine Tung, Shelley S. Tworoger, Cornelia M. Ulrich, Nawaid Usmani, Celine M. Vachon, Els Van Nieuwenhuysen, Ana Vega, Miguel Elías Aguado-Barrera, Qin Wang, Penelope M. Webb, Clarice R. Weinberg, Stephanie Weinstein, Mark C. Weissler, Jeffrey N. Weitzel, Catharine M. L. West, Emily White, Alice S. Whittemore, H-Erich Wichmann, Fredrik Wiklund, Robert Winqvist, Alicja Wolk, Penella Woll, Michael Woods, Anna H. Wu, Xifeng Wu, Drakoulis Yannoukakos, Wei Zheng, Shanbeh Zienolddiny, Argyrios Ziogas, Kristin K. Zorn, Jacqueline M. Lane, Richa Saxena, Duncan Thomas, Rayjean J. Hung, Brenda Diergaarde, James McKay, Ulrike Peters, Li Hsu, Montserrat García-Closas, Rosalind A. Eeles, Georgia Chenevix-Trench, Paul J. Brennan, Christopher A. Haiman, Jacques Simard, Douglas F. Easton, Stephen B. Gruber, Paul D. P. Pharoah, Alkes L. Price, Bogdan Pasaniuc, Christopher I. Amos, Peter Kraft, and Sara Lindström
Subjects: Science
Abstract: Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.
Published: 2019
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32. Assessing Biomarkers of Breast Cancer Risk in Underserved Women in a Midwestern County

Author: Marla A. DeWitt, Ivana T. Croghan, Celine M. Vachon, Thomas D. Thacher, Marcia R. Venegas Pont, Lonzetta Neal, Daniela L. Stan, Sarah M. Jenkins, and Sandhya Pruthi
Subjects: Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract: Objective: The primary aim of this study was to evaluate the feasibility of collecting risk factor information and accessing digitized mammographic data in a medically marginalized population. A secondary aim was to examine the association between vitamin D status and mammographic density. Methods: Breast-screening examinations were provided for age-appropriate patients, and a referral for no-cost screening mammography was offered. Study participants were asked to undergo 25-hydroxyvitamin D testing at mammography and 1-year follow-up. Results: Of 62 women approached, 35 (56%) consented to participate. Of 32 participants who had baseline mammography, the median mammographic density measured by VolparaDensity (Volpara Solutions Limited) was 5.7%. After 1 year, 9 women obtained follow-up mammograms, with a median density of 5.7%. Vitamin D status was measured for 31 participants at baseline and 13 participants in the following year. Insufficient vitamin D status (
Published: 2021
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33. Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study

Author: Carrie B. Hruska, Jennifer R. Geske, Tiffinee N. Swanson, Alyssa N. Mammel, David S. Lake, Armando Manduca, Amy Lynn Conners, Dana H. Whaley, Christopher G. Scott, Rickey E. Carter, Deborah J. Rhodes, Michael K. O’Connor, and Celine M. Vachon
Subjects: Breast density, Breast cancer risk, Molecular breast imaging, Tc-99m sestamibi, Mammography, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Background parenchymal uptake (BPU), which refers to the level of Tc-99m sestamibi uptake within normal fibroglandular tissue on molecular breast imaging (MBI), has been identified as a breast cancer risk factor, independent of mammographic density. Prior analyses have used subjective categories to describe BPU. We evaluate a new quantitative method for assessing BPU by testing its reproducibility, comparing quantitative results with previously established subjective BPU categories, and determining the association of quantitative BPU with breast cancer risk. Methods Two nonradiologist operators independently performed region-of-interest analysis on MBI images viewed in conjunction with corresponding digital mammograms. Quantitative BPU was defined as a unitless ratio of the average pixel intensity (counts/pixel) within the fibroglandular tissue versus the average pixel intensity in fat. Operator agreement and the correlation of quantitative BPU measures with subjective BPU categories assessed by expert radiologists were determined. Percent density on mammograms was estimated using Cumulus. The association of quantitative BPU with breast cancer (per one unit BPU) was examined within an established case-control study of 62 incident breast cancer cases and 177 matched controls. Results Quantitative BPU ranged from 0.4 to 3.2 across all subjects and was on average higher in cases compared to controls (1.4 versus 1.2, p
Published: 2018
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34. The association of mammographic density with risk of contralateral breast cancer and change in density with treatment in the WECARE study

Author: Julia A. Knight, Kristina M. Blackmore, Jing Fan, Kathleen E. Malone, Esther M. John, Charles F. Lynch, Celine M. Vachon, Leslie Bernstein, Jennifer D. Brooks, Anne S. Reiner, Xiaolin Liang, Meghan Woods, WECARE Study Collaborative Group, and Jonine L. Bernstein
Subjects: Mammographic density, Contralateral breast cancer, Breast cancer treatment, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Mammographic density (MD) is an established predictor of risk of a first breast cancer, but the relationship of MD to contralateral breast cancer (CBC) risk is not clear, including the roles of age, mammogram timing, and change with treatment. Multivariable prediction models for CBC risk are needed and MD could contribute to these. Methods We conducted a case-control study of MD and CBC risk in phase II of the WECARE study where cases had a CBC diagnosed ≥ 2 years after first diagnosis at age
Published: 2018
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35. Association between mammographic breast density and histologic features of benign breast disease

Author: Karthik Ghosh, Robert A. Vierkant, Ryan D. Frank, Stacey Winham, Daniel W. Visscher, Vernon S. Pankratz, Christopher G. Scott, Kathleen Brandt, Mark E. Sherman, Derek C. Radisky, Marlene H. Frost, Lynn C. Hartmann, Amy C. Degnim, and Celine M. Vachon
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Over 40% of women undergoing breast screening have mammographically dense breasts. Elevated mammographic breast density (MBD) is an established breast cancer risk factor and is known to mask tumors within the dense tissue. However, the association of MBD with high risk benign breast disease (BBD) is unknown. Method We analyzed data for 3400 women diagnosed with pathologically confirmed BBD in the Mayo Clinic BBD cohort from 1985–2001, with a clinical MBD measure (either parenchymal pattern (PP) or Breast Imaging Reporting and Data Systems (BI-RADS) density) and expert pathology review. Risk factor information was collected from medical records and questionnaires. MBD was dichotomized as dense (PP classification P2 or DY, or BI-RADS classification c or d) or non-dense (PP classification N1 or P1, or BI-RADS classification a or b). Associations of clinical and histologic characteristics with MBD were examined using logistic regression analysis to estimate odds ratios (ORs) with 95% confidence intervals (CIs). Results Of 3400 women in the study, 2163 (64%) had dense breasts. Adjusting for age and body mass index (BMI), there were positive associations of dense breasts with use of hormone therapy (HT), lack of lobular involution, presence of atypical lobular hyperplasia (ALH), histologic fibrosis, columnar cell hyperplasia/flat epithelia atypia (CCH/FEA), sclerosing adenosis (SA), cyst, usual ductal hyperplasia, and calcifications. In fully adjusted multivariate models, HT (1.3, 95% CI 1.1–1.5), ALH (1.5, 95% CI 1.0–2.2), lack of lobular involution (OR 1.6, 95% CI 1.2–2.1, compared to complete involution), fibrosis (OR 2.2, 95% CI 1.9–2.6) and CCH/FEA (OR 1.3, 95% CI 1.0–1.6) remained significantly associated with high MBD. Conclusion Our findings support an association between high risk BBD and high MBD, suggesting that risks associated with the latter may act early in breast carcinogenesis.
Published: 2017
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36. Author Correction: A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers

Author: Juliette Coignard, Michael Lush, Jonathan Beesley, Tracy A. O’Mara, Joe Dennis, Jonathan P. Tyrer, Daniel R. Barnes, Lesley McGuffog, Goska Leslie, Manjeet K. Bolla, Muriel A. Adank, Simona Agata, Thomas Ahearn, Kristiina Aittomäki, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Norbert Arnold, Kristan J. Aronson, Banu K. Arun, Annelie Augustinsson, Jacopo Azzollini, Daniel Barrowdale, Caroline Baynes, Heko Becher, Marina Bermisheva, Leslie Bernstein, Katarzyna Białkowska, Carl Blomqvist, Stig E. Bojesen, Bernardo Bonanni, Ake Borg, Hiltrud Brauch, Hermann Brenner, Barbara Burwinkel, Saundra S. Buys, Trinidad Caldés, Maria A. Caligo, Daniele Campa, Brian D. Carter, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Wendy K. Chung, Kathleen B. M. Claes, Christine L. Clarke, GEMO Study Collaborators, EMBRACE Collaborators, J. Margriet Collée, Don M. Conroy, Kamila Czene, Mary B. Daly, Peter Devilee, Orland Diez, Yuan Chun Ding, Susan M. Domchek, Thilo Dörk, Isabel dos-Santos-Silva, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, A. Heather Eliassen, Christoph Engel, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Henrik Flyger, Florentia Fostira, Eitan Friedman, Lin Fritschi, Debra Frost, Manuela Gago-Dominguez, Susan M. Gapstur, Judy Garber, Vanesa Garcia-Barberan, Montserrat García-Closas, José A. García-Sáenz, Mia M. Gaudet, Simon A. Gayther, Andrea Gehrig, Vassilios Georgoulias, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Anna González-Neira, Mark H. Greene, Pascal Guénel, Lothar Haeberle, Eric Hahnen, Christopher A. Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Patricia A. Harrington, Steven N. Hart, Wei He, Frans B. L. Hogervorst, Antoinette Hollestelle, John L. Hopper, Darling J. Horcasitas, Peter J. Hulick, David J. Hunter, Evgeny N. Imyanitov, KConFab Investigators, HEBON Investigators, ABCTB Investigators, Agnes Jager, Anna Jakubowska, Paul A. James, Uffe Birk Jensen, Esther M. John, Michael E. Jones, Rudolf Kaaks, Pooja Middha Kapoor, Beth Y. Karlan, Renske Keeman, Elza Khusnutdinova, Johanna I. Kiiski, Yon-Dschun Ko, Veli-Matti Kosma, Peter Kraft, Allison W. Kurian, Yael Laitman, Diether Lambrechts, Loic Le Marchand, Jenny Lester, Fabienne Lesueur, Tricia Lindstrom, Adria Lopez-Fernández, Jennifer T. Loud, Craig Luccarini, Arto Mannermaa, Siranoush Manoukian, Sara Margolin, John W. M. Martens, Noura Mebirouk, Alfons Meindl, Austin Miller, Roger L. Milne, Marco Montagna, Katherine L. Nathanson, Susan L. Neuhausen, Heli Nevanlinna, Finn C. Nielsen, Katie M. O’Brien, Olufunmilayo I. Olopade, Janet E. Olson, Håkan Olsson, Ana Osorio, Laura Ottini, Tjoung-Won Park-Simon, Michael T. Parsons, Inge Sokilde Pedersen, Beth Peshkin, Paolo Peterlongo, Julian Peto, Paul D. P. Pharoah, Kelly-Anne Phillips, Eric C. Polley, Bruce Poppe, Nadege Presneau, Miquel Angel Pujana, Kevin Punie, Paolo Radice, Johanna Rantala, Muhammad U. Rashid, Gad Rennert, Hedy S. Rennert, Mark Robson, Atocha Romero, Maria Rossing, Emmanouil Saloustros, Dale P. Sandler, Regina Santella, Maren T. Scheuner, Marjanka K. Schmidt, Gunnar Schmidt, Christopher Scott, Priyanka Sharma, Penny Soucy, Melissa C. Southey, John J. Spinelli, Zoe Steinsnyder, Jennifer Stone, Dominique Stoppa-Lyonnet, Anthony Swerdlow, Rulla M. Tamimi, William J. Tapper, Jack A. Taylor, Mary Beth Terry, Alex Teulé, Darcy L. Thull, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Alison H. Trainer, Thérèse Truong, Nadine Tung, Celine M. Vachon, Ana Vega, Joseph Vijai, Qin Wang, Barbara Wappenschmidt, Clarice R. Weinberg, Jeffrey N. Weitzel, Camilla Wendt, Alicja Wolk, Siddhartha Yadav, Xiaohong R. Yang, Drakoulis Yannoukakos, Wei Zheng, Argyrios Ziogas, Kristin K. Zorn, Sue K. Park, Mads Thomassen, Kenneth Offit, Rita K. Schmutzler, Fergus J. Couch, Jacques Simard, Georgia Chenevix-Trench, Douglas F. Easton, Nadine Andrieu, and Antonis C. Antoniou
Subjects: Science
Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-23162-4
Published: 2021
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37. Alcohol consumption and breast tumor gene expression

Author: Jun Wang, Yujing J. Heng, A. Heather Eliassen, Rulla M. Tamimi, Aditi Hazra, Vincent J. Carey, Christine B. Ambrosone, Victor P. de Andrade, Adam Brufsky, Fergus J. Couch, Tari A. King, Francesmary Modugno, Celine M. Vachon, David J. Hunter, Andrew H. Beck, and Susan E. Hankinson
Subjects: Alcohol, Prospective, Epidemiology, Breast tumor, Gene expression, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Alcohol consumption is an established risk factor for breast cancer and the association generally appears stronger among estrogen receptor (ER)-positive tumors. However, the biological mechanisms underlying this association are not completely understood. Methods We analyzed messenger RNA (mRNA) microarray data from both invasive breast tumors (N = 602) and tumor-adjacent normal tissues (N = 508) from participants diagnosed with breast cancer in the Nurses’ Health Study (NHS) and NHSII. Multivariable linear regression, controlling for other known breast cancer risk factors, was used to identify differentially expressed genes by pre-diagnostic alcohol intake. For pathway analysis, we performed gene set enrichment analysis (GSEA). Differentially expressed genes or enriched pathway-defined gene sets with false discovery rate (FDR)
Published: 2017
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38. Tissue-based associations of mammographic breast density with breast stem cell markers

Author: Lusine Yaghjyan, Ethan Stoll, Karthik Ghosh, Christopher G. Scott, Matthew R. Jensen, Kathleen R. Brandt, Daniel Visscher, and Celine M. Vachon
Subjects: Breast density, Stem cell markers, Breast cancer risk, Immunohistochemistry, Staining extent, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Mammographic breast density is a well-established, strong breast cancer risk factor but the biology underlying this association remains unclear. Breast density may reflect underlying alterations in the size and activity of the breast stem cell pool. We examined, for the first time, associations of CD44, CD24, and aldehyde dehydrogenase family 1 member A1 (ALDH1A1) breast stem cell markers with breast density. Methods We included in this study 64 asymptomatic healthy women who previously volunteered for a unique biopsy study of normal breast tissue at the Mayo Clinic (2006-2008). Mammographically identified dense and non-dense areas were confirmed/localized by ultrasound and biopsied. Immunohistochemical analysis of the markers was performed according to a standard protocol and the staining was assessed by a single blinded pathologist. In core biopsy samples retrieved from areas of high vs. low density within the same woman, we compared staining extent and an expression score (the product of staining intensity and extent), using the signed rank test. All tests of statistical significance were two-sided. Results A total of 64, 28, and 10 women were available for CD44, CD24, and ALDH1A1 staining, respectively. For all three markers, we found higher levels of staining extent in dense as compared to non-dense tissue, though for CD24 and ALDH1A1 the difference did not reach statistical significance (CD44, 6.3% vs. 2.0%, p
Published: 2017
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39. Meta-analysis of genome-wide association studies discovers multiple loci for chronic lymphocytic leukemia

Author: Sonja I. Berndt, Nicola J. Camp, Christine F. Skibola, Joseph Vijai, Zhaoming Wang, Jian Gu, Alexandra Nieters, Rachel S. Kelly, Karin E. Smedby, Alain Monnereau, Wendy Cozen, Angela Cox, Sophia S. Wang, Qing Lan, Lauren R. Teras, Moara Machado, Meredith Yeager, Angela R. Brooks-Wilson, Patricia Hartge, Mark P. Purdue, Brenda M. Birmann, Claire M. Vajdic, Pierluigi Cocco, Yawei Zhang, Graham G. Giles, Anne Zeleniuch-Jacquotte, Charles Lawrence, Rebecca Montalvan, Laurie Burdett, Amy Hutchinson, Yuanqing Ye, Timothy G. Call, Tait D. Shanafelt, Anne J. Novak, Neil E. Kay, Mark Liebow, Julie M. Cunningham, Cristine Allmer, Henrik Hjalgrim, Hans-Olov Adami, Mads Melbye, Bengt Glimelius, Ellen T. Chang, Martha Glenn, Karen Curtin, Lisa A. Cannon-Albright, W Ryan Diver, Brian K. Link, George J. Weiner, Lucia Conde, Paige M. Bracci, Jacques Riby, Donna K. Arnett, Degui Zhi, Justin M. Leach, Elizabeth A. Holly, Rebecca D. Jackson, Lesley F. Tinker, Yolanda Benavente, Núria Sala, Delphine Casabonne, Nikolaus Becker, Paolo Boffetta, Paul Brennan, Lenka Foretova, Marc Maynadie, James McKay, Anthony Staines, Kari G. Chaffee, Sara J. Achenbach, Celine M. Vachon, Lynn R. Goldin, Sara S. Strom, Jose F. Leis, J. Brice Weinberg, Neil E. Caporaso, Aaron D. Norman, Anneclaire J. De Roos, Lindsay M. Morton, Richard K. Severson, Elio Riboli, Paolo Vineis, Rudolph Kaaks, Giovanna Masala, Elisabete Weiderpass, María- Dolores Chirlaque, Roel C. H. Vermeulen, Ruth C. Travis, Melissa C. Southey, Roger L. Milne, Demetrius Albanes, Jarmo Virtamo, Stephanie Weinstein, Jacqueline Clavel, Tongzhang Zheng, Theodore R. Holford, Danylo J. Villano, Ann Maria, John J. Spinelli, Randy D. Gascoyne, Joseph M. Connors, Kimberly A. Bertrand, Edward Giovannucci, Peter Kraft, Anne Kricker, Jenny Turner, Maria Grazia Ennas, Giovanni M. Ferri, Lucia Miligi, Liming Liang, Baoshan Ma, Jinyan Huang, Simon Crouch, Ju-Hyun Park, Nilanjan Chatterjee, Kari E. North, John A. Snowden, Josh Wright, Joseph F. Fraumeni, Kenneth Offit, Xifeng Wu, Silvia de Sanjose, James R. Cerhan, Stephen J. Chanock, Nathaniel Rothman, and Susan L. Slager
Subjects: Science
Abstract: Chronic lymphocytic leukemia is a highly inheritable cancer. Here the authors conduct a metaanalysis of four genome-wide association studies and identify three novel loci located near EOMES, SERPINB6 and LPPassociated with risk of this disease.
Published: 2016
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40. Classification Using Deep Transfer Learning on Structured Healthcare Data.

Author: Ayda Farhadi, David Chen 0003, Rozalina G. McCoy, Christopher Scott, Ping Ma, Celine M. Vachon, Jingyi Zhang, Che Ngufor, and John A. Miller 0001
Published: 2023
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41. Breast Cancer Classification using Deep Transfer Learning on Structured Healthcare Data.

Author: Akram Farhadi, David Chen 0003, Rozalina G. McCoy, Christopher Scott, John A. Miller 0001, Celine M. Vachon, and Che Ngufor
Published: 2019
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42. Benign Breast Disease, NSAIDs, and Postmenopausal Breast Cancer Risk in the CPS-II Cohort

Author: Mark E. Sherman, Robert A. Vierkant, Matthew Masters, Derek C. Radisky, Stacey J. Winham, Amy C. Degnim, Celine M. Vachon, Alpa V. Patel, and Lauren R. Teras
Subjects: Cancer Research, Oncology
Abstract: Nonsteroidal anti-inflammatory agents (NSAID) are associated with modest inconsistent reductions in breast cancer risk in population-based cohorts, whereas two focused studies of patients with benign breast disease (BBD) have found lower risk with NSAID use. Given that BBD includes fibroinflammatory lesions linked to elevated breast cancer risk, we assessed whether NSAID use was associated with lower breast cancer risk among patients with BBD.Participants were postmenopausal women in the Cancer Prevention Study-II (CPS-II), a prospective study of cancer incidence and mortality, who completed follow-up surveys in 1997 with follow-up through June 30, 2015. History of BBD, NSAID use, and covariate data were updated biennially. This analysis included 23,615 patients with BBD and 36,751 patients with non-BBD, including 3,896 incident breast cancers over an average of 12.72 years of follow-up among participants. NSAID use, overall and by formulation, recency, duration, and pills per month was analyzed versus breast cancer risk overall and by BBD status using multivariable-adjusted Cox models; BBD status and NSAID use were modeled as time-dependent exposures.Patients with BBD who reported using NSAIDs experienced lower breast cancer risk (HR, 0.87; 95% CI, 0.78–0.97), with similar effects for estrogen receptor (ER)-positive breast cancers [HR, 0.85; 95% confidence interval (CI), 0.74–0.97] and ER-negative breast cancers (HR, 0.87; 95% CI, 0.59–1.29); among women without BBD, NSAID use was unrelated to risk (HR, 1.02; 95% CI, 0.92–1.13; Pinteraction = 0.04). Associations stratified by age, obesity, menopausal hormone use, and cardiovascular disease were similar.Among patients with BBD, NSAID use appears linked to lower breast cancer risk. Further studies to assess the value of NSAID use among patients with BBD are warranted.Prevention Relevance:We examined whether NSAID use, a modifiable exposure, is associated with breast cancer risk in postmenopausal women from the Cancer Prevention Study-II with self-reported benign breast disease, an often inflammatory condition associated with higher rates of breast cancer.
Published: 2023

43. Progression and survival of MBL: a screening study of 10 139 individuals

Author: Susan L. Slager, Sameer A. Parikh, Sara J. Achenbach, Aaron D. Norman, Kari G. Rabe, Nicholas J. Boddicker, Janet E. Olson, Geffen Kleinstern, Connie E. Lesnick, Timothy G. Call, James R. Cerhan, Celine M. Vachon, Neil E. Kay, Esteban Braggio, Curtis A. Hanson, and Tait D. Shanafelt
Subjects: Adult, B-Lymphocytes, Hematologic Neoplasms, Immunology, Humans, Lymphocytosis, Cell Biology, Hematology, Leukemia, Lymphocytic, Chronic, B-Cell, Neoplasms, Plasma Cell, Precancerous Conditions, Biochemistry
Abstract: Monoclonal B-cell lymphocytosis (MBL) is a common hematological premalignant condition that is understudied in screening cohorts. MBL can be classified into low-count (LC) and high-count (HC) types based on the size of the B-cell clone. Using the Mayo Clinic Biobank, we screened for MBL and evaluated its association with future hematologic malignancy and overall survival (OS). We had a two-stage study design including discovery and validation cohorts. We screened for MBL using an eight-color flow-cytometry assay. Medical records were abstracted for hematological cancers and death. We used Cox regression to evaluate associations and estimate hazard ratios and 95% confidence intervals (CIs), adjusting for age and sex. We identified 1712 (17%) individuals with MBL (95% LC-MBL), and the median follow-up time for OS was 34.4 months with 621 individuals who died. We did not observe an association with OS among individuals with LC-MBL (P = .78) but did among HC-MBL (hazard ratio, 1.8; 95% CI, 1.1-3.1; P = .03). Among the discovery cohort with a median of 10.0 years follow-up, 31 individuals developed hematological cancers with two-thirds being lymphoid malignancies. MBL was associated with 3.6-fold risk of hematological cancer compared to controls (95% CI, 1.7-7.7; P < .001) and 7.7-fold increased risk for lymphoid malignancies (95% CI:3.1-19.2; P < .001). LC-MBL was associated with 4.3-fold risk of lymphoid malignancies (95% CI, 1.4-12.7; P = .009); HC-MBL had a 74-fold increased risk (95% CI, 22-246; P < .001). In this large screening cohort, we observed similar survival among individuals with and without LC-MBL, yet individuals with LC-MBL have a fourfold increased risk of lymphoid malignancies. Accumulating evidence indicates that there are clinical consequences to LC-MBL, a condition that affects 8 to 10 million adults in the United States.
Published: 2022

44. Does a Multiple Myeloma Polygenic Risk Score Predict Overall Survival of Patients with Myeloma?

Author: Angelica Macauda, Alyssa Clay-Gilmour, Thomas Hielscher, Michelle A.T. Hildebrandt, Marcin Kruszewski, Robert Z. Orlowski, Shaji K. Kumar, Elad Ziv, Enrico Orciuolo, Elizabeth E. Brown, Asta Försti, Rosalie G. Waller, Mitchell J. Machiela, Stephen J. Chanock, Nicola J. Camp, Marcin Rymko, Małgorzata Raźny, Wendy Cozen, Judit Várkonyi, Chiara Piredda, Matteo Pelosini, Alem A. Belachew, Edyta Subocz, Kari Hemminki, Malwina Rybicka-Ramos, Graham G. Giles, Roger L. Milne, Jonathan N. Hofmann, Jan Maciej Zaucha, Annette Juul Vangsted, Hartmut Goldschmidt, S. Vincent Rajkumar, Waldemar Tomczak, Juan Sainz, Aleksandra Butrym, Marzena Watek, Elżbieta Iskierka-Jazdzewska, Gabriele Buda, Dennis P. Robinson, Artur Jurczyszyn, Marek Dudziński, Joaquin Martinez-Lopez, Jason P. Sinnwell, Susan L. Slager, Krzysztof Jamroziak, Rui Manuel Vieira Reis, Niels Weinhold, Parveen Bhatti, Luis G. Carvajal-Carmona, Daria Zawirska, Aaron D. Norman, Grzegorz Mazur, Sonja I. Berndt, Daniele Campa, Celine M. Vachon, and Federico Canzian
Subjects: Oncology, Risk Factors, Epidemiology, Humans, Genetic Predisposition to Disease, Multiple Myeloma, Polymorphism, Single Nucleotide, Genome-Wide Association Study
Abstract: Background: Genome-wide association studies (GWAS) of multiple myeloma in populations of European ancestry (EA) identified and confirmed 24 susceptibility loci. For other cancers (e.g., colorectum and melanoma), risk loci have also been associated with patient survival. Methods: We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with multiple myeloma overall survival (OS) in multiple populations of EA [the International Multiple Myeloma rESEarch (IMMEnSE) consortium, the International Lymphoma Epidemiology consortium, CoMMpass, and the German GWAS] for a total of 3,748 multiple myeloma cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associations were meta-analyzed. Results: SNP associations were meta-analyzed. From the meta-analysis, two multiple myeloma risk SNPs were associated with OS (P < 0.05), specifically POT1-AS1-rs2170352 [HR = 1.37; 95% confidence interval (CI) = 1.09–1.73; P = 0.007] and TNFRSF13B-rs4273077 (HR = 1.19; 95% CI = 1.01–1.41; P = 0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. Conclusions: Overall, our results did not support an association between the majority of multiple myeloma risk SNPs and OS. Impact: This is the first study to investigate the association between multiple myeloma PRS and OS in multiple myeloma.
Published: 2022

45. Relationship among three common hematological premalignant conditions

Author: Nicholas J. Boddicker, Sameer A. Parikh, Aaron D. Norman, Kari G. Rabe, Rosalie Griffin, Timothy G. Call, Dennis P. Robinson, Janet E. Olson, Angela Dispenzieri, Vincent Rajkumar, Shaji Kumar, Neil E. Kay, Curtis A. Hanson, James R. Cerhan, David Murray, Esteban Braggio, Tait D. Shanafelt, Celine M. Vachon, and Susan L. Slager
Subjects: Cancer Research, Oncology, Hematology
Published: 2023

46. Impact of Artificial Intelligence System and Volumetric Density on Risk Prediction of Interval, Screen-Detected, and Advanced Breast Cancer

Author: Celine M. Vachon, Christopher G. Scott, Aaron D. Norman, Sadia A. Khanani, Matthew R. Jensen, Carrie B. Hruska, Kathleen R. Brandt, Stacey J. Winham, and Karla Kerlikowske
Subjects: Cancer Research, Oncology
Abstract: PURPOSE Artificial intelligence (AI) algorithms improve breast cancer detection on mammography, but their contribution to long-term risk prediction for advanced and interval cancers is unknown. METHODS We identified 2,412 women with invasive breast cancer and 4,995 controls matched on age, race, and date of mammogram, from two US mammography cohorts, who had two-dimensional full-field digital mammograms performed 2-5.5 years before cancer diagnosis. We assessed Breast Imaging Reporting and Data System density, an AI malignancy score (1-10), and volumetric density measures. We used conditional logistic regression to estimate odds ratios (ORs), 95% CIs, adjusted for age and BMI, and C-statistics (AUC) to describe the association of AI score with invasive cancer and its contribution to models with breast density measures. Likelihood ratio tests (LRTs) and bootstrapping methods were used to compare model performance. RESULTS On mammograms between 2-5.5 years prior to cancer, a one unit increase in AI score was associated with 20% greater odds of invasive breast cancer (OR, 1.20; 95% CI, 1.17 to 1.22; AUC, 0.63; 95% CI, 0.62 to 0.64) and was similarly predictive of interval (OR, 1.20; 95% CI, 1.13 to 1.27; AUC, 0.63) and advanced cancers (OR, 1.23; 95% CI, 1.16 to 1.31; AUC, 0.64) and in dense (OR, 1.18; 95% CI, 1.15 to 1.22; AUC, 0.66) breasts. AI score improved prediction of all cancer types in models with density measures ( PLRT values < .001); discrimination improved for advanced cancer (ie, AUC for dense volume increased from 0.624 to 0.679, Δ AUC 0.065, P = .01) but did not reach statistical significance for interval cancer. CONCLUSION AI imaging algorithms coupled with breast density independently contribute to long-term risk prediction of invasive breast cancers, in particular, advanced cancer.
Published: 2023

47. Supplementary Data from Impact of Personalized Genetic Breast Cancer Risk Estimation With Polygenic Risk Scores on Preventive Endocrine Therapy Intention and Uptake

Author: Sandhya Pruthi, Lori A. Thicke, Amy C. Degnim, Debjani Grenier, Lonzetta Neal, Benjamin Goldenberg, Daniela L. Stan, Linda Hasadsri, Jason P. Sinnwell, Christina A. Kim, Fergus J. Couch, Andrew Cooke, Celine M. Vachon, Daniel J. Schaid, and Julian O. Kim
Abstract: Supplementary Tables 1-3, Supplementary Figures 1 and 2, Supplementary Data 1 and 2
Published: 2023

48. Supplementary Table S2 from Benign Breast Disease, NSAIDs, and Postmenopausal Breast Cancer Risk in the CPS-II Cohort

Author: Lauren R. Teras, Alpa V. Patel, Celine M. Vachon, Amy C. Degnim, Stacey J. Winham, Derek C. Radisky, Matthew Masters, Robert A. Vierkant, and Mark E. Sherman
Abstract: Supplementary Table S2: Associations of demographic and clinical characteristics with risk of breast cancer.
Published: 2023

49. Data from Breast Cancer Risk and Use of Nonsteroidal Anti-inflammatory Agents After a Benign Breast Biopsy

Author: Amy C. Degnim, Celine M. Vachon, Derek C. Radisky, Matthew R. Jensen, Stacey J. Winham, Jodi M. Carter, Daniel W. Visscher, Lori Denison, Marlene H. Frost, Tanya L. Hoskin, Suneetha Kaggal, Robert A. Vierkant, and Mark E. Sherman
Abstract: Over one million women in the United States receive biopsy diagnoses of benign breast disease (BBD) each year, which confer a 1.5–4.0-fold increase in breast cancer risk. Studies in the general population suggest that nonsteroidal anti-inflammatory agents (NSAID) lower breast cancer risk; however, associations among women with BBD are unknown. We assessed whether NSAID use among women diagnosed with BBD is associated with lower breast cancer risk. Participants included 3,080 women (mean age = 50.3 ± 13.5 years) in the Mayo BBD surgical biopsy cohort diagnosed between January 1, 1992 and December 31, 2001 who completed breast cancer risk factor questionnaires that assessed NSAID use, and whose biopsies underwent detailed pathology review, masked to outcome. Women were followed from date of BBD biopsy to breast cancer diagnosis (main outcome) or censoring (death, prophylactic mastectomy, reduction mammoplasty, lobular carcinoma in situ or last contact). Median follow-up time was 16.4 ± 6.0 years. Incident breast cancer was diagnosed among 312 women over a median follow-up of 9.9 years. Regular non-aspirin NSAID use was associated with lower breast cancer risk [HR = 0.63; 95% confidence interval (CI) = 0.46–0.85; P = 0.002] with trends of lower risk (highest tertiles of use vs. nonuse) for greater number of years used [HR = 0.55; 95% CI = 0.31–0.97; Ptrend = 0.003), days used per month (HR = 0.51; 95% CI = 0.33–0.80; Ptrend = 0.001) and lifetime number of doses taken (HR = 0.53; 95% CI = 0.31–0.89; Ptrend = 0.003). We conclude that nonaspirin NSAID use is associated with statistically significant lower breast cancer risk after a BBD biopsy, including a dose–response effect, suggesting a potential role for NSAIDs in breast cancer prevention among patients with BBD.
Published: 2023

50. Data from Impact of Personalized Genetic Breast Cancer Risk Estimation With Polygenic Risk Scores on Preventive Endocrine Therapy Intention and Uptake

Author: Sandhya Pruthi, Lori A. Thicke, Amy C. Degnim, Debjani Grenier, Lonzetta Neal, Benjamin Goldenberg, Daniela L. Stan, Linda Hasadsri, Jason P. Sinnwell, Christina A. Kim, Fergus J. Couch, Andrew Cooke, Celine M. Vachon, Daniel J. Schaid, and Julian O. Kim
Abstract: Endocrine therapy is underutilized to reduce breast cancer incidence among women at increased risk. Polygenic risk scores (PRSs) assessing 77 breast cancer genetic susceptibility loci personalizes risk estimates. We examined effect of personalized PRS breast cancer risk prediction on intention to take and endocrine therapy uptake among women at increased risk. Eligible participants had a 10-year breast cancer risk ≥5% by Tyrer–Cuzick model [International Breast Cancer Intervention Study (IBIS)] or ≥3.0 % 5-year Gail Model risk with no breast cancer history or hereditary breast cancer syndrome. Breast cancer risk was estimated, endocrine therapy options were discussed, and endocrine therapy intent was assessed at baseline. After genotyping, PRS-updated breast cancer risk estimates, endocrine therapy options, and intent to take endocrine therapy were reassessed; endocrine therapy uptake was assessed during follow-up. From March 2016 to October 2017, 151 patients were enrolled [median (range) age, 56.1 (36.0–76.4 years)]. Median 10-year and lifetime IBIS risks were 7.9% and 25.3%. Inclusion of PRS increased lifetime IBIS breast cancer risk estimates for 81 patients (53.6%) and reduced risk for 70 (46.4%). Of participants with increased breast cancer risk by PRS, 39 (41.9%) had greater intent to take endocrine therapy; of those with decreased breast cancer risk by PRS, 28 (46.7%) had less intent to take endocrine therapy (P < 0.001). On multivariable regression, increased breast cancer risk by PRS was associated with greater intent to take endocrine therapy (P < 0.001). Endocrine therapy uptake was greater among participants with increased breast cancer risk by PRS (53.4%) than with decreased risk (20.9%; P < 0.001). PRS testing influenced intent to take and endocrine therapy uptake. Assessing PRS effect on endocrine therapy adherence is needed.Prevention Relevance: Counseling women at increased breast cancer risk using polygenic risk score (PRS) risk estimates can significantly impact preventive endocrine therapy uptake. Further development of PRS testing to personalize breast cancer risk assessments and endocrine therapy counselling may serve to potentially reduce the incidence of breast cancer in the future.
Published: 2023

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