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Mitra T, Gulati R, Ramachandran K, Rajiv R, Enninga EAL, Pierret CK, Kumari R S, Janardhanan R. Endocrine disrupting chemicals: gestational diabetes and beyond. Diabetol Metab Syndr 2024; 16:95. [PMID: 38664841 PMCID: PMC11046910 DOI: 10.1186/s13098-024-01317-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 03/21/2024] [Indexed: 04/28/2024] Open
Abstract
Gestational Diabetes Mellitus (GDM) has been on the rise for the last two decades along with the growing incidence of obesity. The ubiquitous use of Endocrine-Disrupting Chemicals (EDCs) worldwide has been associated with this increase in GDM incidence. Epigenetic modifications such as DNA methylation, histone acetylation, and methylation have been associated with prenatal exposure to EDCs. EDC exposure can also drive a sustained disruption of the hypothalamus-pituitary-thyroid axis and various other signaling pathways such as thyroid signaling, PPARγ signaling, PI3K-AKT signaling. This disruption leads to impaired glucose metabolism, insulin resistance as well as β-cell dysfunction, which culminate into GDM. Persistent EDC exposure in pregnant women also increases adipogenesis, which results in gestational weight gain. Importantly, pregnant mothers transfer these EDCs to the fetus via the placenta, thus leading to other pregnancy-associated complications such as intrauterine growth restriction (IUGR), and large for gestational age neonates. Furthermore, this early EDC exposure of the fetus increases the susceptibility of the infant to metabolic diseases in early life. The transgenerational impact of EDCs is also associated with higher vascular tone, cognitive aberrations, and enhanced susceptibility to lifestyle disorders including reproductive health anomalies. The review focuses on the impact of environmental toxins in inducing epigenetic alterations and increasing the susceptibility to metabolic diseases during pregnancy needs to be extensively studied such that interventions can be developed to break this vicious cycle. Furthermore, the use of EDC-associated ExomiRs from the serum of patients can help in the early diagnosis of GDM, thereby leading to triaging of patients based on increasing risk factor of the clinicopathological condition.
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Affiliation(s)
- Tridip Mitra
- Division of Medical Research, Faculty of Medicine and Health Sciences, SRM Institute of Science and Technology, 603 203, Kattankulathur, Tamil Nadu, India
| | - Richa Gulati
- Division of Medical Research, Faculty of Medicine and Health Sciences, SRM Institute of Science and Technology, 603 203, Kattankulathur, Tamil Nadu, India
| | - Krithika Ramachandran
- Division of Medical Research, Faculty of Medicine and Health Sciences, SRM Institute of Science and Technology, 603 203, Kattankulathur, Tamil Nadu, India
| | - Rohan Rajiv
- Dietrich School of Arts and Sciences, University of Pittsburgh, 15260, Pittsburgh, PA, USA
| | | | - Chris K Pierret
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, USA
| | - Sajeetha Kumari R
- Department of Obstetrics and Gynecology, Faculty of Medicine and Health Sciences, SRM Institute of Science and Technology, 603 203, Kattankulathur, Tamil Nadu, India
| | - Rajiv Janardhanan
- Division of Medical Research, Faculty of Medicine and Health Sciences, SRM Institute of Science and Technology, 603 203, Kattankulathur, Tamil Nadu, India.
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Behrens A, Fasching PA, Schwenke E, Gass P, Häberle L, Heindl F, Heusinger K, Lotz L, Lubrich H, Preuß C, Schneider MO, Schulz-Wendtland R, Stumpfe FM, Uder M, Wunderle M, Zahn AL, Hack CC, Beckmann MW, Emons J. Predicting mammographic density with linear ultrasound transducers. Eur J Med Res 2023; 28:384. [PMID: 37770952 PMCID: PMC10537934 DOI: 10.1186/s40001-023-01327-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 08/28/2023] [Indexed: 09/30/2023] Open
Abstract
BACKGROUND High mammographic density (MD) is a risk factor for the development of breast cancer (BC). Changes in MD are influenced by multiple factors such as age, BMI, number of full-term pregnancies and lactating periods. To learn more about MD, it is important to establish non-radiation-based, alternative examination methods to mammography such as ultrasound assessments. METHODS We analyzed data from 168 patients who underwent standard-of-care mammography and performed additional ultrasound assessment of the breast using a high-frequency (12 MHz) linear probe of the VOLUSON® 730 Expert system (GE Medical Systems Kretztechnik GmbH & Co OHG, Austria). Gray level bins were calculated from ultrasound images to characterize mammographic density. Percentage mammographic density (PMD) was predicted by gray level bins using various regression models. RESULTS Gray level bins and PMD correlated to a certain extent. Spearman's ρ ranged from - 0.18 to 0.32. The random forest model turned out to be the most accurate prediction model (cross-validated R2, 0.255). Overall, ultrasound images from the VOLUSON® 730 Expert device in this study showed limited predictive power for PMD when correlated with the corresponding mammograms. CONCLUSIONS In our present work, no reliable prediction of PMD using ultrasound imaging could be observed. As previous studies showed a reasonable correlation, predictive power seems to be highly dependent on the device used. Identifying feasible non-radiation imaging methods of the breast and their predictive power remains an important topic and warrants further evaluation. Trial registration 325-19 B (Ethics Committee of the medical faculty at Friedrich Alexander University of Erlangen-Nuremberg, Erlangen, Germany).
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Affiliation(s)
- Annika Behrens
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany.
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Eva Schwenke
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Paul Gass
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Lothar Häberle
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
- Biostatistics Unit, Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Felix Heindl
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Katharina Heusinger
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Laura Lotz
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Hannah Lubrich
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Caroline Preuß
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Michael O Schneider
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Rüdiger Schulz-Wendtland
- Department of Radiology, Erlangen University Hospital, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Florian M Stumpfe
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Michael Uder
- Department of Radiology, Erlangen University Hospital, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Marius Wunderle
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Anna L Zahn
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Carolin C Hack
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Julius Emons
- Department of Gynecology and Obstetrics, Erlangen University Hospital, University Breast Center for Franconia, Comprehensive Cancer Center European Metropolitan Area Nuremberg (CCC ER-EMN), Friedrich-Alexander University Erlangen-Nuremberg, Universitätsstrasse 21-23, 91054, Erlangen, Germany
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Androulakis I, Sumser K, Machielse MND, Koppert L, Jager A, Nout R, Franckena M, van Rhoon GC, Curto S. Patient-derived breast model repository, a tool for hyperthermia treatment planning and applicator design. Int J Hyperthermia 2022; 39:1213-1221. [DOI: 10.1080/02656736.2022.2121862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022] Open
Affiliation(s)
- Ioannis Androulakis
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands
| | - Kemal Sumser
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands
| | - Melanie N. D. Machielse
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands
| | - Linetta Koppert
- Department of Surgical Oncology, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands
| | - Agnes Jager
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands
| | - Remi Nout
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands
| | - Martine Franckena
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands
| | - Gerard C. van Rhoon
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands
- Department of Radiation Science and Technology, Delft University of Technology, Delft, The Netherlands
| | - Sergio Curto
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands
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Kamal RM, Mostafa S, Salem D, ElHatw AM, Mokhtar SM, Wessam R, Fakhry S. Body mass index, breast density, and the risk of breast cancer development in relation to the menopausal status; results from a population-based screening program in a native African-Arab country. Acta Radiol Open 2022; 11:20584601221111704. [PMID: 35795247 PMCID: PMC9252007 DOI: 10.1177/20584601221111704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 06/17/2022] [Indexed: 12/04/2022] Open
Abstract
Background Risk factors are traits or behaviors that have an influence on the development of breast cancer (BC). Awareness of the prevalent risk factors can guide in developing prevention interventions. Purpose To evaluate the correlation between the breast density, body mass index, and the risk of breast cancer development in relation to the menopausal status in a native African-Arab population. Material and methods The study included 30,443 screened females who were classified into cancer and non-cancer groups and each group was further sub-classified into pre- and postmenopausal groups. The breast density (BD) was reported and subjectively classified according to the 2013 ACR BI-RADS breast density classification. The weight and height were measured, and the body mass index (BMI) was calculated and classified according to the WHO BMI classification. Results A statistically significant difference was calculated between the mean BMI in the cancer and non-cancer groups (p: .027) as well as between the pre- and postmenopausal groups (p < .001). A positive statistically insignificant correlation was calculated between the breast density and the risk of breast cancer in the premenopausal group (OR: 1.062, p: .919) and a negative highly significant correlation was calculated in the postmenopausal group (OR: 0.234, p < .001). Conclusion BMI and BD are inversely associated with each other. The current studied population presented unique ethnic characteristics, where a decreased BD and an increased BMI were found to be independent risk factors for developing breast cancer.
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Affiliation(s)
- Rasha M Kamal
- Department of Radiology, Cairo University – Baheya Breast Cancer Foundation, Giza, Egypt
| | - Salma Mostafa
- Department of Radiology, Cairo University, Giza, Egypt
| | - Dorria Salem
- Department of Radiology, Cairo University, Giza, Egypt
| | - Ahmed M ElHatw
- Resident of Radiology, National Cancer Institute, Cairo, Egypt
| | | | - Rasha Wessam
- Department of Radiology, Cairo University – Baheya Breast Cancer Foundation, Giza, Egypt
| | - Sherihan Fakhry
- Department of Radiology, Cairo University – Baheya Breast Cancer Foundation, Giza, Egypt
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Coradini D, Ambrogi F. Differential expression of the genes coding for adipokines and epithelial cell polarity components in women with low and high mammographic density. Clin Breast Cancer 2022; 22:715-723. [DOI: 10.1016/j.clbc.2022.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 05/03/2022] [Accepted: 05/16/2022] [Indexed: 11/30/2022]
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Lester SP, Kaur AS, Vegunta S. OUP accepted manuscript. Oncologist 2022; 27:548-554. [PMID: 35536728 PMCID: PMC9256023 DOI: 10.1093/oncolo/oyac084] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 03/18/2022] [Indexed: 12/03/2022] Open
Abstract
In screening for breast cancer (BC), mammographic breast density (MBD) is a powerful risk factor that increases breast carcinogenesis and synergistically reduces the sensitivity of mammography. It also reduces specificity of lesion identification, leading to recalls, additional testing, and delayed and later-stage diagnoses, which result in increased health care costs. These findings provide the foundation for dense breast notification laws and lead to the increase in patient and provider interest in MBD. However, unlike other risk factors for BC, MBD is dynamic through a woman’s lifetime and is modifiable. Although MBD is known to change as a result of factors such as reproductive history and hormonal status, few conclusions have been reached for lifestyle factors such as alcohol, diet, physical activity, smoking, body mass index (BMI), and some commonly used medications. Our review examines the emerging evidence for the association of modifiable factors on MBD and the influence of MBD on BC risk. There are clear associations between alcohol use and menopausal hormone therapy and increased MBD. Physical activity and the Mediterranean diet lower the risk of BC without significant effect on MBD. Although high BMI and smoking are known risk factors for BC, they have been found to decrease MBD. The influence of several other factors, including caffeine intake, nonhormonal medications, and vitamins, on MBD is unclear. We recommend counseling patients on these modifiable risk factors and using this knowledge to help with informed decision making for tailored BC prevention strategies.
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Affiliation(s)
- Sara P Lester
- Corresponding author: Sara P. Lester, MD, Division of General Internal Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.
| | - Aparna S Kaur
- Division of General Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Suneela Vegunta
- Division of Women’s Health Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
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Hooshmand S, Reed WM, Suleiman ME, Brennan PC. SCREENING MAMMOGRAPHY: DIAGNOSTIC EFFICACY-ISSUES AND CONSIDERATIONS FOR THE 2020S. RADIATION PROTECTION DOSIMETRY 2021; 197:54-62. [PMID: 34729603 DOI: 10.1093/rpd/ncab160] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 10/04/2021] [Accepted: 10/08/2021] [Indexed: 06/13/2023]
Abstract
Diagnostic efficacy in medical imaging is ultimately a reflection of radiologist performance. This can be influenced by numerous factors, some of which are patient related, such as the physical size and density of the breast, and machine related, where some lesions are difficult to visualise on traditional imaging techniques. Other factors are human reader errors that occur during the diagnostic process, which relate to reader experience and their perceptual and cognitive oversights. Given the large-scale nature of breast cancer screening, even small increases in diagnostic performance equate to large numbers of women saved. It is important to identify the causes of diagnostic errors and how detection efficacy can be improved. This narrative review will therefore explore the various factors that influence mammographic performance and the potential solutions used in an attempt to ameliorate the errors made.
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Affiliation(s)
- Sahand Hooshmand
- Faculty of Medicine and Health, The Discipline of Medical Imaging Sciences, The University of Sydney, Susan Wakil Health Building (D18), Sydney, NSW 2050, Australia
| | - Warren M Reed
- Faculty of Medicine and Health, The Discipline of Medical Imaging Sciences, The University of Sydney, Susan Wakil Health Building (D18), Sydney, NSW 2050, Australia
| | - Mo'ayyad E Suleiman
- Faculty of Medicine and Health, The Discipline of Medical Imaging Sciences, The University of Sydney, Susan Wakil Health Building (D18), Sydney, NSW 2050, Australia
| | - Patrick C Brennan
- Faculty of Medicine and Health, The Discipline of Medical Imaging Sciences, The University of Sydney, Susan Wakil Health Building (D18), Sydney, NSW 2050, Australia
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Tapia E, Villa-Guillen DE, Chalasani P, Centuori S, Roe DJ, Guillen-Rodriguez J, Huang C, Galons JP, Thomson CA, Altbach M, Trujillo J, Pinto L, Martinez JA, Algotar AM, Chow HHS. A randomized controlled trial of metformin in women with components of metabolic syndrome: intervention feasibility and effects on adiposity and breast density. Breast Cancer Res Treat 2021; 190:69-78. [PMID: 34383179 PMCID: PMC8560579 DOI: 10.1007/s10549-021-06355-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 08/06/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE Obesity is a known risk factor for post-menopausal breast cancer and may increase risk for triple negative breast cancer in premenopausal women. Intervention strategies are clearly needed to reduce obesity-associated breast cancer risk. METHODS We conducted a Phase II double-blind, randomized, placebo-controlled trial of metformin in overweight/obese premenopausal women with components of metabolic syndrome to assess the potential of metformin for primary breast cancer prevention. Eligible participants were randomized to receive metformin (850 mg BID, n = 76) or placebo (n = 75) for 12 months. Outcomes included breast density, assessed by fat/water MRI with change in percent breast density as the primary endpoint, anthropometric measures, and intervention feasibility. RESULTS Seventy-six percent in the metformin arm and 83% in the placebo arm (p = 0.182) completed the 12-month intervention. Adherence to study agent was high with more than 80% of participants taking ≥ 80% assigned pills. The most common adverse events reported in the metformin arm were gastrointestinal in nature and subsided over time. Compared to placebo, metformin intervention led to a significant reduction in waist circumference (p < 0.001) and waist-to-hip ratio (p = 0.019). Compared to placebo, metformin did not change percent breast density and dense breast volume but led to a numerical but not significant decrease in non-dense breast volume (p = 0.070). CONCLUSION We conclude that metformin intervention resulted in favorable changes in anthropometric measures of adiposity and a borderline decrease in non-dense breast volume in women with metabolic dysregulation. More research is needed to understand the impact of metformin on breast cancer risk reduction. TRIAL REGISTRATION ClinicalTrials.gov NCT02028221. Registered January 7, 2014, https://clinicaltrials.gov/ct2/show/NCT02028221.
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Affiliation(s)
- Edgar Tapia
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
| | | | - Pavani Chalasani
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
- Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Sara Centuori
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
- Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Denise J Roe
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA
| | - Jose Guillen-Rodriguez
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
| | - Chuan Huang
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Jean-Phillippe Galons
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
- Department of Medical Imaging, University of Arizona, Tucson, AZ, USA
| | - Cynthia A Thomson
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
- Department of Health Promotion Sciences, University of Arizona, Tucson, AZ, USA
| | - Maria Altbach
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
- Department of Medical Imaging, University of Arizona, Tucson, AZ, USA
| | - Jesse Trujillo
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
| | - Liane Pinto
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
| | - Jessica A Martinez
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
- Department of Nutritional Sciences, University of Arizona, Tucson, AZ, USA
| | - Amit M Algotar
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA
- Department of Family and Community Medicine, University of Arizona, Tucson, AZ, USA
| | - H-H Sherry Chow
- University of Arizona Cancer Center, University of Arizona, 1515 N Campbell Ave, Tucson, AZ, 85724, USA.
- Department of Medicine, University of Arizona, Tucson, AZ, USA.
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Bao Z, Zhao Y, Chen S, Chen X, Xu X, Wei L, Chen L. Evidence and assessment of parenchymal patterns of ultrasonography for breast cancer detection among Chinese women: a cross-sectional study. BMC Med Imaging 2021; 21:152. [PMID: 34666701 PMCID: PMC8527662 DOI: 10.1186/s12880-021-00687-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Accepted: 09/23/2021] [Indexed: 11/17/2022] Open
Abstract
Background Screening of breast cancer in asymptomatic women is important to evaluate for early diagnosis. In China ultrasound is a more frequently used method than mammography for the detection of breast cancer. The objectives of the study were to provide evidence and assessment of parenchymal patterns of ultrasonography for breast cancer detection among Chinese women. Methods Breast ultrasound examinations including the parenchymatous pattern of cytopathological confirmed breast cancer (n = 541) and age-matched cytopathological not confirmed breast cancer (n = 849) women were retrospectively reviewed by seven sonographer physicians. According to compositions of ducts, the thickness of the breast, diameter of ducts, fat lobules, and fibro glandular tissues, the breast parenchymatous pattern was categorized into heterogeneous (high percentage of fatty tissues), ductal (the inner diameters of ducts > 50% of the thick mass of the breast), mixed (the inner diameters of ducts was 50% of the thick mass of the breast), and fibrous categories (a dense classification of the breast). Results Heterogeneous (p < 0.0001, OR = 3.972) and fibrous categories (p < 0.0001, OR = 2.702) were higher among women who have cytopathological confirmed breast cancer than those who have not cytopathological confirmed breast cancer. The heterogeneous category was high-risk ultrasonographic examination category followed by the fibrous category. Agreements between sonographer physicians for categories of ultrasonic examinations were fair to good (Cohen’s k = 0.591). Conclusions Breast cancer risk in Chinese asymptomatic women differ according to the ultrasonographic breast parenchymal pattern. Level of Evidence: III. Technical efficacy stage: 2.
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Affiliation(s)
- Zhongtao Bao
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China.
| | - Yanchun Zhao
- Department of Ultrasound, Provincial Clinical Academy of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, 350001, Fujian, China
| | - Shuqiang Chen
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China
| | - Xiaoyu Chen
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China
| | - Xiang Xu
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China
| | - Linglin Wei
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China
| | - Ling Chen
- Department of Ultrasound, First Affiliated Hospital of Fujian Medical University, No 20 Cha zhong Road, Taijiang District, Fuzhou, 350000, Fujian, China
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Chen H, Yaghjyan L, Li C, Peters U, Rosner B, Lindström S, Tamimi RM. Association of Interactions Between Mammographic Density Phenotypes and Established Risk Factors With Breast Cancer Risk, by Tumor Subtype and Menopausal Status. Am J Epidemiol 2021; 190:44-58. [PMID: 32639533 DOI: 10.1093/aje/kwaa131] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 06/29/2020] [Accepted: 06/30/2020] [Indexed: 12/11/2022] Open
Abstract
Previous studies suggest that the association between mammographic density (MD) and breast cancer risk might be modified by other breast cancer risk factors. In this study, we assessed multiplicative interactions between MD measures and established risk factors on the risk of invasive breast cancer overall and according to menopausal and estrogen receptor status. We used data on 2,137 cases and 4,346 controls from a nested case-control study within the Nurses' Health Study (1976-2004) and Nurses' Health Study II (1989-2007), whose data on percent mammographic density (PMD) and absolute area of dense tissue and nondense tissue (NDA) were available. No interaction remained statistically significant after adjusting for number of comparisons. For breast cancer overall, we observed nominally significant interactions (P < 0.05) between nulliparity and PMD/NDA, age at menarche and area of dense tissue, and body mass index and NDA. Individual nominally significant interactions across MD measures and risk factors were also observed in analyses stratified by either menopausal or estrogen receptor status. Our findings help provide further insights into potential mechanisms underlying the association between MD and breast cancer.
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11
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Kleinstern G, Scott CG, Tamimi RM, Jensen MR, Pankratz VS, Bertrand KA, Norman AD, Visscher DW, Couch FJ, Brandt K, Shepherd J, Wu FF, Chen YY, Cummings SR, Winham S, Kerlikowske K, Vachon CM. Association of mammographic density measures and breast cancer "intrinsic" molecular subtypes. Breast Cancer Res Treat 2021; 187:215-224. [PMID: 33392844 DOI: 10.1007/s10549-020-06049-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 12/07/2020] [Indexed: 01/29/2023]
Abstract
PURPOSE We evaluated the association of percent mammographic density (PMD), absolute dense area (DA), and non-dense area (NDA) with risk of "intrinsic" molecular breast cancer (BC) subtypes. METHODS We pooled 3492 invasive BC and 10,148 controls across six studies with density measures from prediagnostic, digitized film-screen mammograms. We classified BC tumors into subtypes [63% Luminal A, 21% Luminal B, 5% HER2 expressing, and 11% as triple negative (TN)] using information on estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and tumor grade. We used polytomous logistic regression to calculate odds ratio (OR) and 95% confidence intervals (CI) for density measures (per SD) across the subtypes compared to controls, adjusting for age, body mass index and study, and examined differences by age group. RESULTS All density measures were similarly associated with BC risk across subtypes. Significant interaction of PMD by age (P = 0.001) was observed for Luminal A tumors, with stronger effect sizes seen for younger women < 45 years (OR = 1.69 per SD PMD) relative to women of older ages (OR = 1.53, ages 65-74, OR = 1.44 ages 75 +). Similar but opposite trends were seen for NDA by age for risk of Luminal A: risk for women: < 45 years (OR = 0.71 per SD NDA) was lower than older women (OR = 0.83 and OR = 0.84 for ages 65-74 and 75 + , respectively) (P < 0.001). Although not significant, similar patterns of associations were seen by age for TN cancers. CONCLUSIONS Mammographic density measures were associated with risk of all "intrinsic" molecular subtypes. However, findings of significant interactions between age and density measures may have implications for subtype-specific risk models.
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Affiliation(s)
- Geffen Kleinstern
- School of Public Health, University of Haifa, Haifa, Israel
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Christopher G Scott
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Rulla M Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Matthew R Jensen
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | | | - Kimberly A Bertrand
- Slone Epidemiology Center, Boston University School of Medicine, Boston, MA, USA
| | - Aaron D Norman
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Daniel W Visscher
- Department of Anatomic Pathology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Kathleen Brandt
- Department of Radiology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | | | - Fang-Fang Wu
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First St. SW, Rochester, MN, 55905, USA
| | - Yunn-Yi Chen
- Department of Pathology and Laboratory Services, University of California, San Francisco, CA, USA
| | - Steven R Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Stacey Winham
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Karla Kerlikowske
- Departments of Epidemiology and Biostatistics and General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, CA, USA
| | - Celine M Vachon
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First St. SW, Rochester, MN, 55905, USA.
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12
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Pizzato M, Carioli G, Rosso S, Zanetti R, La Vecchia C. Mammographic breast density and characteristics of invasive breast cancer. Cancer Epidemiol 2020; 70:101879. [PMID: 33373798 DOI: 10.1016/j.canep.2020.101879] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 12/15/2020] [Accepted: 12/15/2020] [Indexed: 11/29/2022]
Abstract
INTRODUCTION Inconclusive data exist on the association between breast density and breast cancer characteristics. MATERIALS AND METHODS We conducted a case-only study on 667 invasive breast cancers, using data from the Piedmont Cancer Registry. We applied a multivariate logistic regression model to estimate odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) of high breast density (Breast Imaging Reporting and Data System, BI-RADS 3-4) versus low (BI-RADS 1-2) in relation to histologic grade, pathological tumour size and lymph node status, histotype, estrogen and progesterone receptor, HER2 and Ki67 status. Histopathological data were assessed according to the American Joint Committee on Cancer (AJCC) Staging Manual guidelines. The model includes terms for age at diagnosis, education level, body mass index, reproductive factors, family history of breast cancer, smoking and diabetes. RESULTS As regards histologic grade, compared to well differentiated tumours, the OR of high (versus low) breast density cases was 0.61 (95% CI 0.38-0.98) for moderately-poorly differentiated tumours. No other associations with hormonal and histopathological characteristics were observed. DISCUSSION Our results indicate that low breast density is associated with moderately-poorly differentiated breast tumours.
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Affiliation(s)
- M Pizzato
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - G Carioli
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy.
| | - S Rosso
- Piedmont Cancer Registry, A.O.U, Citta` della Salute e della Scienza di Torino, Turin, Italy
| | - R Zanetti
- Piedmont Cancer Registry, A.O.U, Citta` della Salute e della Scienza di Torino, Turin, Italy; Fondo Elena Moroni for Oncology, Turin, Italy
| | - C La Vecchia
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
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13
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Konishi T, Fujiogi M, Michihata N, Morita K, Matsui H, Fushimi K, Tanabe M, Seto Y, Yasunaga H. Association between body mass index and localization of breast cancer: results from a nationwide inpatient database in Japan. Breast Cancer Res Treat 2020; 185:175-182. [PMID: 32949351 DOI: 10.1007/s10549-020-05934-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 09/05/2020] [Indexed: 11/27/2022]
Abstract
PURPOSE Although both localization of breast cancer and body mass index (BMI) are associated with prognosis, the association between localization of breast cancer and BMI remains unclear. This study aimed to investigate the association between localization of breast cancer and BMI at diagnosis. METHODS Patients who underwent surgery for stage 0-III breast cancer July 2010-March 2017 were identified retrospectively in a Japanese nationwide inpatient database. Multinomial logistic regression analyses adjusting for patient's age were conducted to compare the outcomes among five BMI groups: < 18.5 kg/m2 (n = 31,724; 9.3%), 18.5-24.9 kg/m2 (n = 218,244; 64.3%), 25.0-29.9 kg/m2 (n = 69,813; 20.6%), 30.0-34.9 kg/m2 (n = 16,052; 4.7%), and ≥ 35.0 kg/m2 (n = 3716; 1.1%). The outcomes were the quadrant and side of the breast where tumors were detected. RESULTS In total, about half of the patients had breast cancer in the upper-outer quadrant (49.7%) and in the left breast (51.1%). In the multinomial analysis, BMI ≥ 25.0 kg/m2 was associated with the occurrence of breast cancer in the upper-inner and lower-outer quadrants and in the central area, whereas BMI < 18.5 kg/m2 was associated with the occurrence of breast cancer in the central area only. The side of breast cancer did not differ significantly among the five BMI groups. CONCLUSIONS Localization of breast cancer was associated with BMI in this large nationwide cohort. The findings may benefit patients' self-checks and doctors' examinations, potentially resulting in early detection and treatment.
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Affiliation(s)
- Takaaki Konishi
- Department of Breast and Endocrine Surgery, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan. .,Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
| | - Michimasa Fujiogi
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.,Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, MA, 02114, USA
| | - Nobuaki Michihata
- Department of Health Services Research, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Kojiro Morita
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.,Department of Health Services, Faculty of Medicine, University of Tsukuba, 1-1-1 Ten-nodai, Tsukuba, Ibaraki, 305-8577, Japan
| | - Hiroki Matsui
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Kiyohide Fushimi
- Department of Health Policy and Informatics, Tokyo Medical and Dental University Graduate School, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan
| | - Masahiko Tanabe
- Department of Breast and Endocrine Surgery, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Yasuyuki Seto
- Department of Breast and Endocrine Surgery, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.,Department of Gastrointestinal Surgery, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Hideo Yasunaga
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
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14
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Yaghjyan L, Wijayabahu A, Eliassen AH, Colditz G, Rosner B, Tamimi RM. Associations of aspirin and other anti-inflammatory medications with mammographic breast density and breast cancer risk. Cancer Causes Control 2020; 31:827-837. [PMID: 32476101 DOI: 10.1007/s10552-020-01321-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 05/26/2020] [Indexed: 11/24/2022]
Abstract
PURPOSE We investigated the associations of aspirin and other non-steroid anti-inflammatory drugs with mammographic breast density (MBD) and their interactions in relation to breast cancer risk. METHODS This study included 3,675 cancer-free women within the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII) cohorts. Percent breast density (PD), absolute dense area (DA), and non-dense area (NDA) were measured from digitized film mammograms using a computer-assisted thresholding technique; all measures were square root-transformed. Information on medication use was collected in 1980 (NHS) and 1989 (NHSII) and updated biennially. Medication use was defined as none, past or current; average cumulative dose and frequency were calculated for all past or current users from all bi-annual questionnaires preceding the mammogram date. We used generalized linear regression to quantify associations of medications with MBD. Two-way interactions were examined in logistic regression models. RESULTS In multivariate analysis, none of the anti-inflammatory medications were associated with PD, DA, and NDA. We found no interactions of any of the medications with PD with respect to breast cancer risk (all p-interactions > 0.05). However, some of the aspirin variables appeared to have positive associations with breast cancer risk limited only to women with PD 10-24% (past aspirin OR 1.56, 95% CI 1.03-2.35; current aspirin with < 5 years of use OR 1.82, 95% CI 1.01-3.28; current aspirin with ≥ 5 years of use OR 1.89, 95% CI 1.26-2.82). CONCLUSIONS Aspirin and NSAIDs are not associated with breast density measures. We found no interactions of aspirin with MBD in relation to breast cancer risk.
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Affiliation(s)
- Lusine Yaghjyan
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, 2004 Mowry Rd, Gainesville, FL, 32610, USA.
| | - Akemi Wijayabahu
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, 2004 Mowry Rd, Gainesville, FL, 32610, USA
| | - A Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Graham Colditz
- Department of Surgery, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.,Institute for Public Health, Washington University in St. Louis, St. Louis, MO, USA
| | - Bernard Rosner
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Rulla M Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
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15
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Oncogenic Signaling in Tumorigenesis and Applications of siRNA Nanotherapeutics in Breast Cancer. Cancers (Basel) 2019; 11:cancers11050632. [PMID: 31064156 PMCID: PMC6562835 DOI: 10.3390/cancers11050632] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 04/06/2019] [Accepted: 04/08/2019] [Indexed: 12/16/2022] Open
Abstract
Overexpression of oncogenes and cross-talks of the oncoproteins-regulated signaling cascades with other intracellular pathways in breast cancer could lead to massive abnormal signaling with the consequence of tumorigenesis. The ability to identify the genes having vital roles in cancer development would give a promising therapeutics strategy in combating the disease. Genetic manipulations through siRNAs targeting the complementary sequence of the oncogenic mRNA in breast cancer is one of the promising approaches that can be harnessed to develop more efficient treatments for breast cancer. In this review, we highlighted the effects of major signaling pathways stimulated by oncogene products on breast tumorigenesis and discussed the potential therapeutic strategies for targeted delivery of siRNAs with nanoparticles in suppressing the stimulated signaling pathways.
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16
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Hudson S, Vik Hjerkind K, Vinnicombe S, Allen S, Trewin C, Ursin G, dos-Santos-Silva I, De Stavola BL. Adjusting for BMI in analyses of volumetric mammographic density and breast cancer risk. Breast Cancer Res 2018; 20:156. [PMID: 30594212 PMCID: PMC6311032 DOI: 10.1186/s13058-018-1078-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2018] [Accepted: 11/08/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Fully automated assessment of mammographic density (MD), a biomarker of breast cancer risk, is being increasingly performed in screening settings. However, data on body mass index (BMI), a confounder of the MD-risk association, are not routinely collected at screening. We investigated whether the amount of fat in the breast, as captured by the amount of mammographic non-dense tissue seen on the mammographic image, can be used as a proxy for BMI when data on the latter are unavailable. METHODS Data from a UK case control study (numbers of cases/controls: 414/685) and a Norwegian cohort study (numbers of cases/non-cases: 657/61059), both with volumetric MD measurements (dense volume (DV), non-dense volume (NDV) and percent density (%MD)) from screening-age women, were analysed. BMI (self-reported) and NDV were taken as measures of adiposity. Correlations between BMI and NDV, %MD and DV were examined after log-transformation and adjustment for age, menopausal status and parity. Logistic regression models were fitted to the UK study, and Cox regression models to the Norwegian study, to assess associations between MD and breast cancer risk, expressed as odds/hazard ratios per adjusted standard deviation (OPERA). Adjustments were first made for standard risk factors except BMI (minimally adjusted models) and then also for BMI or NDV. OPERA pooled relative risks (RRs) were estimated by fixed-effect models, and between-study heterogeneity was assessed by the I2 statistics. RESULTS BMI was positively correlated with NDV (adjusted r = 0.74 in the UK study and r = 0.72 in the Norwegian study) and with DV (r = 0.33 and r = 0.25, respectively). Both %MD and DV were positively associated with breast cancer risk in minimally adjusted models (pooled OPERA RR (95% confidence interval): 1.34 (1.25, 1.43) and 1.46 (1.36, 1.56), respectively; I2 = 0%, P >0.48 for both). Further adjustment for BMI or NDV strengthened the %MD-risk association (1.51 (1.41, 1.61); I2 = 0%, P = 0.33 and 1.51 (1.41, 1.61); I2 = 0%, P = 0.32, respectively). Adjusting for BMI or NDV marginally affected the magnitude of the DV-risk association (1.44 (1.34, 1.54); I2 = 0%, P = 0.87 and 1.49 (1.40, 1.60); I2 = 0%, P = 0.36, respectively). CONCLUSIONS When volumetric MD-breast cancer risk associations are investigated, NDV can be used as a measure of adiposity when BMI data are unavailable.
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Affiliation(s)
- Sue Hudson
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT UK
| | - Kirsti Vik Hjerkind
- Cancer Registry of Norway, Institute of Population-based Cancer Research, Oslo, Norway
| | - Sarah Vinnicombe
- Division of Imaging and Technology, Ninewells Hospital Medical School, University of Dundee, Dundee, DD2 1SY UK
| | - Steve Allen
- Royal Marsden NHS Foundation Trust, London, SW3 6JJ UK
| | - Cassia Trewin
- Cancer Registry of Norway, Institute of Population-based Cancer Research, Oslo, Norway
| | - Giske Ursin
- Cancer Registry of Norway, Institute of Population-based Cancer Research, Oslo, Norway
| | - Isabel dos-Santos-Silva
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT UK
| | - Bianca L. De Stavola
- Faculty of Population Health Sciences, Institute of Child Health, University College London, London, WC1N 1EH UK
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17
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Hüser S, Guth S, Joost HG, Soukup ST, Köhrle J, Kreienbrock L, Diel P, Lachenmeier DW, Eisenbrand G, Vollmer G, Nöthlings U, Marko D, Mally A, Grune T, Lehmann L, Steinberg P, Kulling SE. Effects of isoflavones on breast tissue and the thyroid hormone system in humans: a comprehensive safety evaluation. Arch Toxicol 2018; 92:2703-2748. [PMID: 30132047 PMCID: PMC6132702 DOI: 10.1007/s00204-018-2279-8] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2018] [Accepted: 07/31/2018] [Indexed: 02/06/2023]
Abstract
Isoflavones are secondary plant constituents of certain foods and feeds such as soy, linseeds, and red clover. Furthermore, isoflavone-containing preparations are marketed as food supplements and so-called dietary food for special medical purposes to alleviate health complaints of peri- and postmenopausal women. Based on the bioactivity of isoflavones, especially their hormonal properties, there is an ongoing discussion regarding their potential adverse effects on human health. This review evaluates and summarises the evidence from interventional and observational studies addressing potential unintended effects of isoflavones on the female breast in healthy women as well as in breast cancer patients and on the thyroid hormone system. In addition, evidence from animal and in vitro studies considered relevant in this context was taken into account along with their strengths and limitations. Key factors influencing the biological effects of isoflavones, e.g., bioavailability, plasma and tissue concentrations, metabolism, temporality (pre- vs. postmenopausal women), and duration of isoflavone exposure, were also addressed. Final conclusions on the safety of isoflavones are guided by the aim of precautionary consumer protection.
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Affiliation(s)
- S Hüser
- Institute for Food Toxicology, Senate Commission on Food Safety, University of Veterinary Medicine Hannover, Hannover, Germany
| | - S Guth
- Institute for Food Toxicology, Senate Commission on Food Safety, University of Veterinary Medicine Hannover, Hannover, Germany
| | - H G Joost
- Department of Experimental Diabetology, German Institute of Human Nutrition (DIfE), Nuthetal, Germany
| | - S T Soukup
- Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Haid-und-Neu-Str. 9, 76131, Karlsruhe, Germany
| | - J Köhrle
- Institut für Experimentelle Endokrinologie, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, CVK, Berlin, Germany
| | - L Kreienbrock
- Department of Biometry, Epidemiology and Information Processing, University of Veterinary Medicine Hannover, Hannover, Germany
| | - P Diel
- Department of Molecular and Cellular Sports Medicine, Institute of Cardiovascular Research and Sports Medicine, German Sport University Cologne, Cologne, Germany
| | - D W Lachenmeier
- Chemisches und Veterinäruntersuchungsamt Karlsruhe, Karlsruhe, Germany
| | - G Eisenbrand
- Division of Food Chemistry and Toxicology, Molecular Nutrition, Department of Chemistry, Technische Universität Kaiserslautern, Kaiserslautern, Germany
| | - G Vollmer
- Department of Biology, Molecular Cell Physiology and Endocrinology, Technische Universität Dresden, Dresden, Germany
| | - U Nöthlings
- Department of Nutrition and Food Sciences, Nutritional Epidemiology, Rheinische Friedrich-Wilhelms University Bonn, Bonn, Germany
| | - D Marko
- Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, Vienna, Austria
| | - A Mally
- Department of Toxicology, University of Würzburg, Würzburg, Germany
| | - T Grune
- Department of Molecular Toxicology, German Institute of Human Nutrition (DIfE), Nuthetal, Germany
| | - L Lehmann
- Department of Food Chemistry, Institute for Pharmacy and Food Chemistry, University of Würzburg, Würzburg, Germany
| | - P Steinberg
- Institute for Food Toxicology, University of Veterinary Medicine Hannover, Hannover, Germany
- Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Haid-und-Neu-Str. 9, 76131, Karlsruhe, Germany
| | - S E Kulling
- Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Haid-und-Neu-Str. 9, 76131, Karlsruhe, Germany.
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18
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Yaghjyan L, Colditz G, Eliassen H, Rosner B, Gasparova A, Tamimi RM. Interactions of alcohol and postmenopausal hormone use in regards to mammographic breast density. Cancer Causes Control 2018; 29:751-758. [PMID: 29938357 DOI: 10.1007/s10552-018-1053-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Accepted: 06/20/2018] [Indexed: 12/12/2022]
Abstract
PURPOSE We investigated the association of alcohol intake with mammographic breast density in postmenopausal women by their hormone therapy (HT) status. METHODS This study included 2,100 cancer-free postmenopausal women within the Nurses' Health Study and Nurses' Health Study II cohorts. Percent breast density (PD), absolute dense (DA), and non-dense areas (NDA) were measured from digitized film mammograms using a computer-assisted thresholding technique; all measures were square root transformed. Alcohol consumption was assessed with a food frequency questionnaire (0, < 5, and ≥ 5 g/day). Information regarding breast cancer risk factors was obtained from baseline or biennial questionnaires closest to the mammogram date. We used generalized linear regression to examine associations between alcohol and breast density measures in women with no HT history, current, and past HT users. RESULTS In multivariable analyses, we found no associations of alcohol consumption with PD (p trend = 0.32) and DA (p trend = 0.53) and an inverse association with NDA (β = - 0.41, 95% CI - 0.73, - 0.09 for ≥ 5 g/day, p trend < 0.01). In the stratified analysis by HT status, alcohol was not associated with PD in any of the strata. We found a significant inverse association of alcohol with NDA among past HT users (β = - 0.79, 95% CI - 1.51, - 0.07 for ≥ 5 g/day, p trend = 0.02). There were no significant interactions between alcohol and HT in relation to PD, DA, and NDA (p interaction = 0.19, 0.42, and 0.43, respectively). CONCLUSIONS Our findings suggest that associations of alcohol with breast density do not vary by HT status.
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Affiliation(s)
- Lusine Yaghjyan
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, 2004 Mowry Rd., Gainesville, FL, 32610, USA.
| | - Graham Colditz
- Department of Surgery, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.,Institute for Public Health, Washington University in St. Louis, St. Louis, MO, USA
| | - Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Bernard Rosner
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Aleksandra Gasparova
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, 2004 Mowry Rd., Gainesville, FL, 32610, USA
| | - Rulla M Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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19
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Velásquez García HA, Sobolev BG, Gotay CC, Wilson CM, Lohrisch CA, Lai AS, Aronson KJ, Spinelli JJ. Mammographic non-dense area and breast cancer risk in postmenopausal women: a causal inference approach in a case-control study. Breast Cancer Res Treat 2018. [PMID: 29516373 DOI: 10.1007/s10549-018-4737-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
PURPOSE The association between high mammographic density (MD) and elevated breast cancer risk is well established. However, the role of absolute non-dense area remains unclear. We estimated the effect of the mammographic non-dense area and other density parameters on the risk of breast cancer. METHODS This study utilizes data from a population-based case-control study conducted in Greater Vancouver, British Columbia, with 477 female postmenopausal breast cancer cases and 588 female postmenopausal controls. MD measures were determined from digitized screening mammograms using computer-assisted software (Cumulus). Marginal odds ratios were estimated by inverse-probability weighting using a causal diagram for confounder selection. Akaike information criteria and receiver operating characteristic curves were used to assess the goodness of fit and predictive power of unconditional logistic models containing MD parameters. RESULTS The risk of breast cancer is 60% lower for the highest quartile compared to the lowest quartile of mammographic non-dense area (marginal OR 0.40, 95% CI 0.26-0.61, p-trend < 0.001). The cancer risk almost doubles for the highest quartile compared to the lowest quartile of dense area (marginal OR 1.81, 95% CI 1.19-2.43, p-trend < 0.001). For the highest quartile of percent density, breast cancer risk was more than three times higher than for the lowest quartile (marginal OR 3.15, 95% CI 1.90-4.40, p-trend < 0.001). No difference was seen in predictive accuracy between models using percent density alone, dense area alone, or non-dense area plus dense area. CONCLUSIONS In this study, non-dense area is an independent risk factor after adjustment for dense area and other covariates, inversely related with the risk of breast cancer. However, non-dense area does not improve prediction over that offered by percent density or dense area alone.
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Affiliation(s)
- Héctor A Velásquez García
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada. .,Department of Cancer Control Research, BC Cancer, Vancouver, BC, Canada.
| | - Boris G Sobolev
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | - Carolyn C Gotay
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | | | | | - Agnes S Lai
- Department of Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | - Kristan J Aronson
- Division of Cancer Care and Epidemiology, Department of Public Health Sciences, Cancer Research Institute, Queen's University, Kingston, ON, Canada
| | - John J Spinelli
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada.,Department of Cancer Control Research, BC Cancer, Vancouver, BC, Canada
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20
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Bertrand KA, Eliassen AH, Hankinson SE, Rosner BA, Tamimi RM. Circulating Hormones and Mammographic Density in Premenopausal Women. Discov Oncol 2018; 9:117-127. [PMID: 29330698 DOI: 10.1007/s12672-017-0321-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 12/26/2017] [Indexed: 12/23/2022] Open
Abstract
Prior research suggests that several endogenous hormones in premenopausal women are associated with breast cancer risk; however, few studies have evaluated associations of endogenous hormones with mammographic density (MD) in premenopausal women. We conducted a cross-sectional study of plasma hormone levels in relation to MD among 634 cancer-free premenopausal women in the Nurses' Health Study II. We measured percent MD from screening mammograms using a computer-assisted method. We assayed estradiol, estrone, and estrone sulfate in blood samples timed in early follicular and mid-luteal phases of the menstrual cycle as well as testosterone, androstenedione, progesterone, dehydroepiandrosterone (DHEA), DHEA sulfate, sex hormone-binding globulin (SHBG), and anti-Müllerian hormone in luteal or untimed samples. We used multivariable linear regression to quantify the association of %MD with quartiles of each hormone, adjusting for age, body mass index, and breast cancer risk factors. Women in the highest quartile of follicular estradiol levels had significantly greater %MD compared to those in the lowest quartile [difference, 6.7 percentage points; 95% confidence interval (CI) 2.2, 11.3; p-trend < 0.001]. Similar associations were observed for follicular free estradiol but not luteal-phase estradiol. Also, women in the top (vs. bottom) quartile of free testosterone had significantly lower %MD (difference, - 4.7; 95% CI - 8.7, - 0.8; p-trend = 0.04). Higher SHBG was significantly associated with higher percent MD (difference, 4.8; 95% CI 1.1, 8.6; p-trend = 0.002). Percent MD was not strongly associated with other measured hormones. Results were similar in analyses that excluded women with anovulatory cycles. Our findings suggest that follicular estradiol and SHBG may play an important role in premenopausal percent MD.
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Affiliation(s)
- Kimberly A Bertrand
- Slone Epidemiology Center at Boston University, 72 East Concord Street, L-7, Boston, MA, 02118, USA.
| | - A Heather Eliassen
- Channing Division of Network Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Susan E Hankinson
- Channing Division of Network Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA
| | - Bernard A Rosner
- Channing Division of Network Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rulla M Tamimi
- Channing Division of Network Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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21
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Vinnicombe SJ. Breast density: why all the fuss? Clin Radiol 2017; 73:334-357. [PMID: 29273225 DOI: 10.1016/j.crad.2017.11.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2017] [Accepted: 11/17/2017] [Indexed: 01/06/2023]
Abstract
The term "breast density" or mammographic density (MD) denotes those components of breast parenchyma visualised at mammography that are denser than adipose tissue. MD is composed of a mixture of epithelial and stromal components, notably collagen, in variable proportions. MD is most commonly assessed in clinical practice with the time-honoured method of visual estimation of area-based percent density (PMD) on a mammogram, with categorisation into quartiles. The computerised semi-automated thresholding method, Cumulus, also yielding area-based percent density, is widely used for research purposes; however, the advent of fully automated volumetric methods developed as a consequence of the widespread use of digital mammography (DM) and yielding both absolute and percent dense volumes, has resulted in an explosion of interest in MD recently. Broadly, the importance of MD is twofold: firstly, the presence of marked MD significantly reduces mammographic sensitivity for breast cancer, even with state-of-the-art DM. Recognition of this led to the formation of a powerful lobby group ('Are You Dense') in the US, as a consequence of which 32 states have legislated for mandatory disclosure of MD to women undergoing mammography. Secondly, it is now widely accepted that MD is in itself a risk factor for breast cancer, with a four-to sixfold increased relative risk in women with PMD in the highest quintile compared to those with PMD in the lowest quintile. Consequently, major research efforts are underway to assess whether use of MD could provide a major step forward towards risk-adapted, personalised breast cancer prevention, imaging, and treatment.
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Affiliation(s)
- S J Vinnicombe
- Cancer Research, School of Medicine, Level 7, Mailbox 4, Ninewells Hospital and Medical School, University of Dundee, Dundee DD1 9SY, UK.
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22
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Soguel L, Durocher F, Tchernof A, Diorio C. Adiposity, breast density, and breast cancer risk: epidemiological and biological considerations. Eur J Cancer Prev 2017; 26:511-520. [PMID: 27571214 PMCID: PMC5627530 DOI: 10.1097/cej.0000000000000310] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2016] [Revised: 01/29/2016] [Indexed: 12/16/2022]
Abstract
Excess total body fat and abdominal adipose tissue are recognized risk factors for metabolic diseases but also for some types of cancers, including breast cancer. Several biological mechanisms in connection with local and systemic effects of adiposity are believed to be implicated in breast cancer development, and may involve breast fat. Breast adipose tissue can be studied through mammography by looking at breast density features such as the nondense area mainly composed of fat, or the percent breast density, which is the proportion of fibroglandular tissue in relation to fat. The relation between adiposity, breast density features, and breast cancer is complex. Studies suggest a paradoxical association as adiposity and absolute nondense area correlate positively with each other, but in contrast to adiposity, absolute nondense area seems to be associated negatively with breast cancer risk. As breast density is one of the strongest risk factors for breast cancer, it is therefore critical to understand how these factors interrelate. In this review, we discuss these relations by first presenting how adiposity measurements and breast density features are linked to breast cancer risk. Then, we used a systematic approach to capture the literature to review the relation between adiposity and breast density features. Finally, the role of adipose tissue in carcinogenesis is discussed briefly from a biological perspective.
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Affiliation(s)
- Ludivine Soguel
- Departments of Social and Preventive Medicine
- CHU de Québec Research Center
- Department of Nutrition and Dietetics, University of Applied Sciences Western Switzerland (HES-SO) Geneva, 25 rue des Caroubiers, Carouge, Switzerland
| | - Francine Durocher
- Molecular Medicine, Cancer Research Center, Laval University, 2325 rue de l’Université
- CHU de Québec Research Center, CHUL, 2724 Laurier Boulevard
| | - André Tchernof
- CHU de Québec Research Center, CHUL, 2724 Laurier Boulevard
- Department of Nutrition, Laval University, 2425 rue de l’Agriculture, Quebec City, Quebec, Canada
| | - Caroline Diorio
- Departments of Social and Preventive Medicine
- CHU de Québec Research Center
- Deschênes-Fabia Center for Breast Diseases, Saint-Sacrement Hospital, 1050 Chemin Ste-Foy
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23
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Ali MA, Czene K, Eriksson L, Hall P, Humphreys K. Breast Tissue Organisation and its Association with Breast Cancer Risk. Breast Cancer Res 2017; 19:103. [PMID: 28877713 PMCID: PMC5586066 DOI: 10.1186/s13058-017-0894-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 08/07/2017] [Indexed: 11/13/2022] Open
Abstract
Background Mammographic percentage density is an established and important risk factor for breast cancer. In this paper, we investigate the role of the spatial organisation of (dense vs. fatty) regions of the breast defined from mammographic images in terms of breast cancer risk. Methods We present a novel approach that provides a thorough description of the spatial organisation of different types of tissue in the breast. Each mammogram is first segmented into four regions (fatty, semi-fatty, semi-dense and dense tissue). The spatial relations between each pair of regions is described using so-called forces histograms (FHs) and summarised using functional principal component analysis. In our main analysis, association with case–control status is assessed using a Swedish population-based case–control study (1,170 cases and 1283 controls), for which digitised mammograms were available. We also carried out a small validation study based on digital images. Results For our main analysis, we obtained a global p value of 2×10−7 indicating a significant association between the spatial relations of the four segmented regions and breast cancer status after adjustment for percentage density and other important breast cancer risk factors. Our (spatial relations) score had a per standard deviation odds ratio 1.29, after accounting for overfitting (percentage density had a per standard deviation odds ratio of 1.34). The spatial relations between the fatty and semi-fatty tissue and the spatial relations between the fatty and dense tissue were the most significant. The spatial relations between the fatty and semi-fatty tissue were associated with parity and age at first birth (p=6×10−4). Using digital images, we were able to verify that the same characteristics of tissue organisation can be identified and we validated the association for the spatial relations between the fatty and semi-fatty tissue. Conclusions Our findings are consistent with the notion that fibroglandular and adipose tissue plays a role in breast cancer risk and, more specifically, they suggest that fatty tissue in the lower quadrants and the absence of density in the retromammary space, as shown in mediolateral oblique images, are protective against breast cancer.
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Affiliation(s)
- Maya Alsheh Ali
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Swedish eScience Research Centre (SeRC), Karolinska Institutet, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Louise Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Department of Oncology and Pathology, Cancer Centre Karolinska, Karolinska Institutet and University Hospital, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Keith Humphreys
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. .,Swedish eScience Research Centre (SeRC), Karolinska Institutet, Stockholm, Sweden.
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24
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Qualitative Versus Quantitative Mammographic Breast Density Assessment: Applications for the US and Abroad. Diagnostics (Basel) 2017; 7:diagnostics7020030. [PMID: 28561776 PMCID: PMC5489950 DOI: 10.3390/diagnostics7020030] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Revised: 05/22/2017] [Accepted: 05/24/2017] [Indexed: 12/14/2022] Open
Abstract
Mammographic breast density (MBD) has been proven to be an important risk factor for breast cancer and an important determinant of mammographic screening performance. The measurement of density has changed dramatically since its inception. Initial qualitative measurement methods have been found to have limited consistency between readers, and in regards to breast cancer risk. Following the introduction of full-field digital mammography, more sophisticated measurement methodology is now possible. Automated computer-based density measurements can provide consistent, reproducible, and objective results. In this review paper, we describe various methods currently available to assess MBD, and provide a discussion on the clinical utility of such methods for breast cancer screening.
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25
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Hou XY, Niu HY, Huang XL, Gao Y. Correlation of Breast Ultrasound Classifications with Breast Cancer in Chinese Women. ULTRASOUND IN MEDICINE & BIOLOGY 2016; 42:2616-2621. [PMID: 27554070 DOI: 10.1016/j.ultrasmedbio.2016.07.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Revised: 06/17/2016] [Accepted: 07/09/2016] [Indexed: 06/06/2023]
Abstract
The aim of this study was to identify potential links between ultrasonographic breast parenchymal patterns and the risk of breast cancer in Chinese women. The population of Chinese women at high risk for breast cancer was explored using the ultrasonographic classification. Ultrasonographic parenchymal patterns were classified into four types: heterogeneous type, ductal type, mixed type and fibrous type. A total of 5879 Chinese women underwent breast ultrasound examination from May 2010 to April 2014. Of the 5879 women, 256 women had pathology-confirmed breast cancer. Among the remaining 5623 women, 512 randomly selected, age-matched women were recruited into the present study. The correlation between ultrasonographic type and breast cancer revealed that the odds ratio (OR) was highest for the heterogeneous type (odds ratio = 4.11, 95% confidence interval: 2.01-8.41, p < 0.001), followed by the fibrous type (odds ratio = 2.05, 95% confidence interval: 1.51-2.78, p < 0.001). The odds ratios of the ductal and mixed types were both less than 1 (p < 0.05). This study indicates that the heterogeneous and fibrous types in the ultrasonographic classification are associated with an increased risk of breast cancer and, therefore, can be used as a marker of breast cancer risk in the female population of China.
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Affiliation(s)
- Xin-Yan Hou
- Department of Ultrasound, PLA Beijing Military General Hospital, Beijing, China.
| | - Hai-Yan Niu
- Department of Ultrasound, PLA Beijing Military General Hospital, Beijing, China
| | - Xiao-Ling Huang
- Department of Ultrasound, PLA Beijing Military General Hospital, Beijing, China
| | - Yu Gao
- Department of Ultrasound, PLA Beijing Military General Hospital, Beijing, China
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26
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Huo CW, Waltham M, Khoo C, Fox SB, Hill P, Chen S, Chew GL, Price JT, Nguyen CH, Williams ED, Henderson M, Thompson EW, Britt KL. Mammographically dense human breast tissue stimulates MCF10DCIS.com progression to invasive lesions and metastasis. Breast Cancer Res 2016; 18:106. [PMID: 27776557 PMCID: PMC5078949 DOI: 10.1186/s13058-016-0767-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Accepted: 10/05/2016] [Indexed: 12/22/2022] Open
Abstract
Background High mammographic density (HMD) not only confers a significantly increased risk of breast cancer (BC) but also is associated with BCs of more advanced stages. However, it is unclear whether BC progression and metastasis are stimulated by HMD. We investigated whether patient-derived HMD breast tissue could stimulate the progression of MCF10DCIS.com cells compared with patient-matched low mammographic density (LMD) tissue. Methods Sterile breast specimens were obtained immediately after prophylactic mastectomy from high-risk women (n = 10). HMD and LMD regions of each specimen were resected under radiological guidance. Human MCF10DCIS.com cells, a model of ductal carcinoma in situ (DCIS), were implanted into silicone biochambers in the groins of severe combined immunodeficiency mice, either alone or with matched LMD or HMD tissue (1:1), and maintained for 6 weeks. We assessed biochamber weight as a measure of primary tumour growth, histological grade of the biochamber material, circulating tumour cells and metastatic burden by luciferase and histology. All statistical tests were two-sided. Results HMD breast tissue led to increased primary tumour take, increased biochamber weight and increased proportions of high-grade DCIS and grade 3 invasive BCs compared with LMD. This correlated with an increased metastatic burden in the mice co-implanted with HMD tissue. Conclusions Our study is the first to explore the direct effect of HMD and LMD human breast tissue on the progression and dissemination of BC cells in vivo. The results suggest that HMD status should be a consideration in decision-making for management of patients with DCIS lesions. Electronic supplementary material The online version of this article (doi:10.1186/s13058-016-0767-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Cecilia W Huo
- Department of Surgery, University of Melbourne, St Vincent's Hospital, Melbourne, VIC, 3156, Australia
| | - Mark Waltham
- Department of Surgery, University of Melbourne, St Vincent's Hospital, Melbourne, VIC, 3156, Australia.,St Vincent's Institute of Medical Research, Melbourne, VIC, 3156, Australia
| | - Christine Khoo
- Department of Pathology, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC, 3000, Australia
| | - Stephen B Fox
- Department of Pathology, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC, 3000, Australia.,Department of Pathology, University of Melbourne, Grattan Street, Parkville, VIC, 3010, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Grattan Street, Parkville, VIC, 3010, Australia
| | - Prue Hill
- Department of Pathology, St Vincent's Hospital, Melbourne, VIC, 3156, Australia
| | - Shou Chen
- Department of Pathology, St Vincent's Hospital, Melbourne, VIC, 3156, Australia
| | - Grace L Chew
- Department of Surgery, University of Melbourne, St Vincent's Hospital, Melbourne, VIC, 3156, Australia.,Austin Health and Northern Health, Melbourne, VIC, 3084, Australia
| | - John T Price
- College of Health and Biomedicine, Victoria University, St Albans, VIC, 8001, Australia.,Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Monash University, Clayton, VIC, 3800, Australia.,Australian Institute for Musculoskeletal Science (AIMSS), Victoria University, University of Melbourne and Western Health, Sunshine Hospital, St Albans, VIC, 3021, Australia
| | - Chau H Nguyen
- College of Health and Biomedicine, Victoria University, St Albans, VIC, 8001, Australia
| | - Elizabeth D Williams
- Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, 2 George Street, Brisbane, QLD, 4001, Australia.,Translational Research Institute, 37 Kent Street, Woolloongabba, QLD, 4102, Australia.,Australian Prostate Cancer Centre - Queensland, Brisbane, QLD, 4102, Australia
| | - Michael Henderson
- Department of Surgery, University of Melbourne, St Vincent's Hospital, Melbourne, VIC, 3156, Australia.,Division of Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC, 3002, Australia
| | - Erik W Thompson
- Department of Surgery, University of Melbourne, St Vincent's Hospital, Melbourne, VIC, 3156, Australia. .,St Vincent's Institute of Medical Research, Melbourne, VIC, 3156, Australia. .,Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, 2 George Street, Brisbane, QLD, 4001, Australia. .,Translational Research Institute, 37 Kent Street, Woolloongabba, QLD, 4102, Australia.
| | - Kara L Britt
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Grattan Street, Parkville, VIC, 3010, Australia.,Department of Anatomy and Developmental Biology, Monash University, Melbourne, VIC, 3800, Australia.,Metastasis Research Laboratory, Peter MacCallum Cancer Centre, Melbourne, Victoria, 3000, Australia
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27
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Farland LV, Tamimi RM, Eliassen AH, Spiegelman D, Bertrand KA, Missmer SA. Endometriosis and mammographic density measurements in the Nurses' Health Study II. Cancer Causes Control 2016; 27:1229-37. [PMID: 27549771 DOI: 10.1007/s10552-016-0801-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 08/15/2016] [Indexed: 01/08/2023]
Abstract
PURPOSE Endometriosis and mammographic density have been hypothesized to be influenced by sex steroid hormonal exposures in adolescence and early adulthood. We investigated the association between endometriosis and mammographic density, a consistent and independent risk factor for breast cancer. METHODS We conducted a cross-sectional analysis among 1,581 pre- and postmenopausal women not previously diagnosed with breast cancer in the Nurses' Health Study II cohort. We measured average percent mammographic density and absolute dense and non-dense breast area using a validated computer-assisted method. Multivariable linear regression was used to estimate the association between endometriosis and mammographic density among pre- and postmenopausal women separately. RESULTS Among premenopausal women, average percent mammographic density was 43.1 % among women with endometriosis (n = 91) and 40.5 % among women without endometriosis (n = 1,150). Endometriosis was not associated significantly with mammographic density among premenopausal (% difference = 2.00 percentage points 95 % CI -1.33, 5.33) or among postmenopausal women (% difference = -0.89 percentage points 95 % CI -5.10, 3.33). Among premenopausal women, there was heterogeneity by BMI at age 18 (p value = 0.003), with a suggested association among those who were lean at age 18 (BMI < 20.6 kg/m(2)) (% difference = 3.74 percentage points 95 % CI -0.29, 7.78). CONCLUSION Endometriosis was not found to be associated with overall measurements of mammographic density.
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Affiliation(s)
- Leslie V Farland
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA. .,Department of Obstetrics, Gynecology, and Reproductive Biology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Rulla M Tamimi
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - A Heather Eliassen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Donna Spiegelman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Stacey A Missmer
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.,Department of Obstetrics, Gynecology, and Reproductive Biology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
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28
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Felix AS, Lenz P, Pfeiffer RM, Hewitt SM, Morris J, Patel DA, Geller B, Vacek PM, Weaver DL, Chicoine RE, Shepherd J, Mahmoudzadeh AP, Wang J, Fan B, Malkov S, Herschorn SD, Johnson JM, Cora RL, Brinton LA, Sherman ME, Gierach GL. Relationships between mammographic density, tissue microvessel density, and breast biopsy diagnosis. Breast Cancer Res 2016; 18:88. [PMID: 27552842 PMCID: PMC4995674 DOI: 10.1186/s13058-016-0746-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 07/28/2016] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Women with high levels of mammographic density (MD) have a four- to six-fold increased risk of developing breast cancer; however, most neither have a prevalent tumor nor will they develop one. Magnetic resonance imaging (MRI) studies suggest that background parenchymal enhancement, an indicator of vascularity, is related to increased breast cancer risk. Correlations of microvessel density (MVD) in tissue, MD and biopsy diagnosis have not been defined, and we investigated these relationships among 218 women referred for biopsy. METHODS MVD was determined by counting CD31-positive vessels in whole sections of breast biopsies in three representative areas; average MVD was transformed to approximate normality. Using digital mammograms, we quantified MD volume with single X-ray absorptiometry. We used linear regression to evaluate associations between MVD and MD adjusted for age and body mass index (BMI) overall, and stratified by biopsy diagnosis: cases (in situ or invasive cancer, n = 44) versus non-cases (non-proliferative or proliferative benign breast disease, n = 174). Logistic regression adjusted for age, BMI, and MD was used to calculate odds ratios (ORs) and 95 % confidence intervals (CIs) for associations between MVD and biopsy diagnosis. We also assessed whether the MVD-breast cancer association varied by MD. RESULTS MVD and MD were not consistently associated. Higher MVD was significantly associated with higher odds of in situ/invasive disease (ORAdjusted = 1.69, 95 % CI = 1.17-2.44). MVD-breast cancer associations were strongest among women with greater non-dense volume. CONCLUSIONS Increased MVD in tissues is associated with breast cancer, independently of MD, consistent with MRI findings suggestive of its possible value as a radiological cancer biomarker.
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Affiliation(s)
- Ashley S. Felix
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
- Cancer Prevention Fellowship Program, Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
- Present address: Division of Epidemiology, The Ohio State University College of Public Health, 1841 Neil Avenue, 300C Cunz Hall, Columbus, OH 43210 USA
| | - Petra Lenz
- Clinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD USA
| | - Ruth M. Pfeiffer
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Stephen M. Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Jennifer Morris
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Deesha A. Patel
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Berta Geller
- Department of Family Medicine, University of Vermont, Burlington, VT USA
| | - Pamela M. Vacek
- Department of Pathology, University of Vermont, Burlington, VT USA
| | - Donald L. Weaver
- Department of Pathology, University of Vermont, Burlington, VT USA
| | - Rachael E. Chicoine
- Office of Health Promotion Research, University of Vermont, Burlington, VT USA
| | | | | | - Jeff Wang
- University of California, San Francisco, CA USA
- Present address: Hokkaido University, Graduate School of Medicine, Sapporo, Japan
| | - Bo Fan
- University of California, San Francisco, CA USA
| | | | | | - Jason M. Johnson
- Department of Diagnostic Radiology, Neuroradiology Section, MD Anderson Cancer Center, Houston, TX USA
| | - Renata L. Cora
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Louise A. Brinton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Mark E. Sherman
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Gretchen L. Gierach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
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Yaghjyan L, Ghita GL, Rosner B, Farvid M, Bertrand KA, Tamimi RM. Adolescent fiber intake and mammographic breast density in premenopausal women. Breast Cancer Res 2016; 18:85. [PMID: 27520794 PMCID: PMC4983022 DOI: 10.1186/s13058-016-0747-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Accepted: 07/29/2016] [Indexed: 12/12/2022] Open
Abstract
Background To date, there is limited and inconsistent epidemiologic evidence for associations of adolescent diet with mammographic breast density, a strong and consistent predictor of breast cancer. We investigated the association of adolescent fiber intake with mammographic density in premenopausal women. Methods This study included 743 cancer-free premenopausal women (mean age, 44.9 years) within the Nurses’ Health Study II cohort. Percent breast density, absolute dense and non-dense areas were measured from digitized film mammograms using a computer-assisted thresholding technique. Adolescent and adult diet were assessed with a food frequency questionnaire; energy-adjusted nutrient intakes were estimated for each food item. Information regarding breast cancer risk factors was obtained from baseline or biennial questionnaires closest to the mammogram date. We used generalized linear regression to quantify associations between quartiles of adolescent fiber intake and each of the breast density measures, adjusted for potential confounders. Associations were examined separately for total fiber intake; fiber from fruits, vegetables, legumes, and cereal; and food sources of fiber (fruits, vegetables, and nuts). Results In multivariable analyses, total fiber intake during adolescence was not associated with percent breast density (p for trend = 0.64), absolute dense area (p for trend = 0.80), or non-dense area (p for trend = 0.75). Similarly, neither consumption of fiber from fruits, vegetables, legumes, or cereal nor specific sources of fiber intake (fruits, vegetables, or nuts) during adolescence were associated with any of the mammographic density phenotypes. Conclusions Our findings do not support the hypothesis that adolescent fiber intake is associated with premenopausal mammographic breast density.
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Affiliation(s)
- Lusine Yaghjyan
- Department of Epidemiology, University of Florida, College of Public Health and Health Professions and College of Medicine, 2004 Mowry Rd., Gainesville, 32610, FL, USA.
| | - Gabriela L Ghita
- Department of Biostatistics, University of Florida, College of Public Health and Health Professions and College of Medicine, Gainesville, FL, USA
| | - Bernard Rosner
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Maryam Farvid
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Harvard/Massachusetts General Hospital Center on Genomics, Vulnerable Populations, and Health Disparities, Mongan Institute for Health Policy, Massachusetts General Hospital, Boston, MA, USA
| | | | - Rulla M Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
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30
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Reproductive factors related to childbearing and mammographic breast density. Breast Cancer Res Treat 2016; 158:351-9. [PMID: 27351801 DOI: 10.1007/s10549-016-3884-y] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Accepted: 06/21/2016] [Indexed: 10/21/2022]
Abstract
We investigated the associations of reproductive factors related to childbearing with percent breast density, absolute dense and nondense areas, by menopausal status. This study included 4110 cancer-free women within the Nurses' Health Study and Nurses' Health Study II cohorts. Percent breast density, absolute dense and nondense areas were measured from digitized mammography film images with computerized techniques. All density measures were square root-transformed in all the analyses to improve normality. The data on reproductive variables and other breast cancer risk factors were obtained from biennial questionnaires, at the time of the mammogram date. As compared to nulliparous women, parous postmenopausal women had lower percent density (β = -0.60, 95 % CI -0.84; -0.37), smaller absolute dense area (β = -0.66, 95 % CI -1.03; -0.29), and greater nondense area (β = 0.72, 95 % CI 0.27; 1.16). Among parous women, number of children was inversely associated with percent density in pre- (β per one child = -0.12, 95 % CI -0.20; -0.05) and postmenopausal women (β per one child = -0.07, 95 % CI -0.12; -0.02). The positive associations of breastfeeding with absolute dense and nondense areas were limited to premenopausal women, while the positive association of the age at first child's birth with percent density and the inverse association with nondense area were limited to postmenopausal women. Women with greater number of children and younger age at first child's birth have more favorable breast density patterns that could explain subsequent breast cancer risk reduction.
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31
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Oliver A, Tortajada M, Lladó X, Freixenet J, Ganau S, Tortajada L, Vilagran M, Sentís M, Martí R. Breast Density Analysis Using an Automatic Density Segmentation Algorithm. J Digit Imaging 2016; 28:604-12. [PMID: 25720749 DOI: 10.1007/s10278-015-9777-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Breast density is a strong risk factor for breast cancer. In this paper, we present an automated approach for breast density segmentation in mammographic images based on a supervised pixel-based classification and using textural and morphological features. The objective of the paper is not only to show the feasibility of an automatic algorithm for breast density segmentation but also to prove its potential application to the study of breast density evolution in longitudinal studies. The database used here contains three complete screening examinations, acquired 2 years apart, of 130 different patients. The approach was validated by comparing manual expert annotations with automatically obtained estimations. Transversal analysis of the breast density analysis of craniocaudal (CC) and mediolateral oblique (MLO) views of both breasts acquired in the same study showed a correlation coefficient of ρ = 0.96 between the mammographic density percentage for left and right breasts, whereas a comparison of both mammographic views showed a correlation of ρ = 0.95. A longitudinal study of breast density confirmed the trend that dense tissue percentage decreases over time, although we noticed that the decrease in the ratio depends on the initial amount of breast density.
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Affiliation(s)
- Arnau Oliver
- Department of Computer Architecture and Technology, University of Girona, 17071, Girona, Spain.
| | - Meritxell Tortajada
- Department of Computer Architecture and Technology, University of Girona, 17071, Girona, Spain
- UDIAT-Centre Diagnòstic, Corporació Parc Taulí, 08208, Sabadell, Spain
| | - Xavier Lladó
- Department of Computer Architecture and Technology, University of Girona, 17071, Girona, Spain
| | - Jordi Freixenet
- Department of Computer Architecture and Technology, University of Girona, 17071, Girona, Spain
| | - Sergi Ganau
- UDIAT-Centre Diagnòstic, Corporació Parc Taulí, 08208, Sabadell, Spain
| | - Lidia Tortajada
- UDIAT-Centre Diagnòstic, Corporació Parc Taulí, 08208, Sabadell, Spain
| | - Mariona Vilagran
- UDIAT-Centre Diagnòstic, Corporació Parc Taulí, 08208, Sabadell, Spain
| | - Melcior Sentís
- UDIAT-Centre Diagnòstic, Corporació Parc Taulí, 08208, Sabadell, Spain
| | - Robert Martí
- Department of Computer Architecture and Technology, University of Girona, 17071, Girona, Spain
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32
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Densité mammographique et risque de cancer du sein : qu’en reste-t-il ? IMAGERIE DE LA FEMME 2016. [DOI: 10.1016/j.femme.2016.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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McDonald JA, Michels KB, Cohn BA, Flom JD, Tehranifar P, Terry MB. Alcohol intake from early adulthood to midlife and mammographic density. Cancer Causes Control 2016; 27:493-502. [PMID: 26830901 DOI: 10.1007/s10552-016-0723-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Accepted: 01/16/2016] [Indexed: 12/13/2022]
Abstract
PURPOSE Moderate alcohol consumption (15 g/day) has been consistently associated with increased breast cancer risk; however, the association between alcohol and mammographic density, a strong marker of breast cancer risk, has been less consistent. Less is known about the effect of patterns of alcohol intake across the lifecourse. METHODS Using the Early Determinants of Mammographic Density study, an adult follow-up of women born in two US birth cohorts (n = 697; Collaborative Perinatal Project in Boston and Providence sites and the Childhood Health and Development Studies in California), we examined the association between alcohol intake in early adulthood (ages 20-29 years) and at time of interview and mammographic density (percent density and total dense area). We report the difference between nondrinkers and three levels of alcohol intake. We considered confounding by age at mammogram, body mass index, geographic site, race/ethnicity, and reproductive characteristics. RESULTS Seventy-nine percent of women reported ever consuming alcohol. Compared to nondrinkers in early adulthood, we observed an inverse association between >7 servings/week and percent density in fully adjusted models (β = -5.1, 95% CI -8.7, -1.5; p for trend = <0.01). Associations with dense area were inverse for the highest category of drinking in early adulthood but not statistically significant (p for trend = 0.15). Compared to noncurrent drinkers, the association for current intake of >7 servings/week and percent density was also inverse (β = -3.1, 95% CI -7.0, 0.8; p for trend = 0.01). In contrast, moderate alcohol intake (>0-≤7 servings/week) in either time period was positively associated with dense area; but associations were not statistically significant in fully adjusted models. CONCLUSIONS Our study does not lend support to the hypothesis that the positive association between alcohol intake and breast cancer risk is through increasing mammographic density.
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Affiliation(s)
- Jasmine A McDonald
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA.
| | - Karin B Michels
- Obstetrics and Gynecology, Epidemiology Center Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA.,Division of Cancer Epidemiology, Comprehensive Cancer Center Freiburg, Freiburg University, Freiburg, Germany
| | - Barbara A Cohn
- Public Health Institute, Child Health and Development Studies, Berkeley, CA, USA
| | - Julie D Flom
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
| | - Parisa Tehranifar
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
| | - Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA.,The Imprints Center for Genetic and Environmental Lifecourse Studies, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
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34
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Soguel L, Diorio C. Anthropometric factors, adult weight gain, and mammographic features. Cancer Causes Control 2015; 27:333-40. [PMID: 26667319 DOI: 10.1007/s10552-015-0706-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2015] [Accepted: 12/06/2015] [Indexed: 12/16/2022]
Abstract
PURPOSE To evaluate the association between anthropometric factors, weight gain during adulthood, and mammographic features among 1,435 women recruited at screening mammography. METHODS Spearman's partial coefficients were used to evaluate the correlation of anthropometric factors with mammographic features (percent density, absolute dense area, and non-dense area). Multivariate generalized linear models were used to evaluate the associations between weight change categories and mammographic features. RESULTS Body mass index was inversely correlated with percent density (r = -0.49, p < 0.0001) or absolute dense area (r = -0.21, p < 0.0001) and positively correlated with absolute non-dense area (r = 0.69, p < 0.0001). However, body mass index was positively correlated with absolute dense area when adjusting for absolute non-dense area (r = 0.16, p < 0.0001). Similar results were observed for weight, waist circumference, and waist-to-hip ratio with mammographic features. Within increasing categories of weight change, percent density (p trend < 0.0001) and absolute dense area (p trend = 0.025) increased, while absolute non-dense area decreased (p trend < 0.0001). After stratification by the median of non-dense area, the positive association between weight gain and absolute dense area remained only among women with higher non-dense area. CONCLUSIONS Adiposity seems positively associated with both dense and non-dense areas following adjustment for each other. Our findings suggest a higher breast dense area among women who gained weight and that a minimum of breast fat may be needed to promote the proliferation of this fibroglandular tissue.
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Affiliation(s)
- Ludivine Soguel
- Department of Social and Preventive Medicine, Cancer Research Center, Laval University, 2325, rue de l'Université, Quebec City, QC, G1V 0A6, Canada.,Oncology Unit, CHU de Québec Research Center, Saint-Sacrement Hospital, 1050, chemin Ste-Foy, Quebec City, QC, G1S 4L8, Canada.,Nutrition and Dietetics Department, University of Applied Sciences Western Switzerland (HES-SO) Geneva, rue des Caroubiers 25, 1227, Carouge, Switzerland
| | - Caroline Diorio
- Department of Social and Preventive Medicine, Cancer Research Center, Laval University, 2325, rue de l'Université, Quebec City, QC, G1V 0A6, Canada. .,Oncology Unit, CHU de Québec Research Center, Saint-Sacrement Hospital, 1050, chemin Ste-Foy, Quebec City, QC, G1S 4L8, Canada. .,Deschênes-Fabia Center for Breast Diseases, Saint-Sacrement Hospital, 1050, chemin Ste-Foy, Quebec City, QC, G1S 4L8, Canada.
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35
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Ng KH, Lau S. Vision 20/20: Mammographic breast density and its clinical applications. Med Phys 2015; 42:7059-77. [PMID: 26632060 DOI: 10.1118/1.4935141] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Affiliation(s)
- Kwan-Hoong Ng
- Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Susie Lau
- Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia
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36
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Mammographic Breast Density in Chinese Women: Spatial Distribution and Autocorrelation Patterns. PLoS One 2015; 10:e0136881. [PMID: 26332221 PMCID: PMC4558090 DOI: 10.1371/journal.pone.0136881] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Accepted: 08/10/2015] [Indexed: 01/01/2023] Open
Abstract
Mammographic breast density (MBD) is a strong risk factor for breast cancer. The spatial distribution of MBD in the breast is variable and dependent on physiological, genetic, environmental and pathological factors. This pilot study aims to define the spatial distribution and autocorrelation patterns of MBD in Chinese women aged 40–60. By analyzing their digital mammographic images using a public domain Java image processing program for segmentation and quantification of MBD, we found their left and right breasts were symmetric to each other in regard to their breast size (Total Breast Area), the amount of BMD (overall PD) and Moran's I values. Their MBD was also spatially autocorrelated together in the anterior part of the breast in those with a smaller breast size, while those with a larger breast size tend to have their MBD clustered near the posterior part of the breast. Finally, we observed that the autocorrelation pattern of MBD was dispersed after a 3-year observation period.
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37
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Bertrand KA, Baer HJ, Orav EJ, Klifa C, Shepherd JA, Van Horn L, Snetselaar L, Stevens VJ, Hylton NM, Dorgan JF. Body fatness during childhood and adolescence and breast density in young women: a prospective analysis. Breast Cancer Res 2015; 17:95. [PMID: 26174168 PMCID: PMC4502611 DOI: 10.1186/s13058-015-0601-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2015] [Accepted: 06/18/2015] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION Overweight and obesity in childhood and adolescence are associated with reduced breast cancer risk, independent of adult body mass index (BMI). These associations may be mediated through breast density. METHODS We prospectively examined associations of early life body fatness with adult breast density measured by MRI in 182 women in the Dietary Intervention Study in Children (DISC) who were ages 25-29 at follow-up. Height, weight, and other factors were measured at baseline (ages 8-10) and annual clinic visits through adolescence. We used linear mixed-effects models to quantify associations of percent breast density and dense and non-dense breast volume at ages 25-29 with quartiles of age-specific youth body mass index (BMI) Z-scores, adjusting for clinic, treatment group, current adult BMI, and other well-established risk factors for breast cancer and predictors of breast density. RESULTS We observed inverse associations between age-specific BMI Z-scores at all youth clinic visits and percent breast density, adjusting for current adult BMI and other covariates (all p values <0.01). Women whose baseline BMI Z-scores (at ages 8-10 years) were in the top quartile had significantly lower adult breast density, after adjusting for current adult BMI and other covariates [least squares mean (LSM): 23.4 %; 95 % confidence interval (CI): 18.0 %, 28.8 %] compared to those in the bottom quartile (LSM: 31.8 %; 95 % CI: 25.2 %, 38.4 %) (p trend <0.01). Significant inverse associations were also observed for absolute dense breast volume (all p values <0.01), whereas there were no clear associations with non-dense breast volume. CONCLUSIONS These results support the hypothesis that body fatness during childhood and adolescence may play an important role in premenopausal breast density, independent of current BMI, and further suggest direct or indirect influences on absolute dense breast volume. CLINICAL TRIALS REGISTRATION NUMBER NCT00458588 ; April 9, 2007.
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Affiliation(s)
- Kimberly A Bertrand
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA. .,Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA.
| | - Heather J Baer
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA. .,Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02120, USA.
| | - E John Orav
- Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02120, USA. .,Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA.
| | - Catherine Klifa
- Dangeard Group, 740 chemin de la Commanderie St Jean de Malte, 13080, Luynes, France.
| | - John A Shepherd
- Department of Radiology, University of California, 505 Parnassus Avenue, San Francisco, CA, 94143, USA.
| | - Linda Van Horn
- Department of Preventive Medicine, Northwestern University, 680 North Lake Shore Drive, Chicago, IL, 60611, USA.
| | - Linda Snetselaar
- Department of Epidemiology, University of Iowa College of Public Health, 145 North Riverside Drive, Iowa City, IA, 52242, USA.
| | - Victor J Stevens
- Kaiser Permanente Center for Health Research, 3800 North Interstate Avenue, Portland, OR, 97227, USA.
| | - Nola M Hylton
- Department of Radiology, University of California, 505 Parnassus Avenue, San Francisco, CA, 94143, USA.
| | - Joanne F Dorgan
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, 655 West Baltimore Street, Baltimore, MD, 21201, USA.
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Stone J, Thompson DJ, Dos Santos Silva I, Scott C, Tamimi RM, Lindstrom S, Kraft P, Hazra A, Li J, Eriksson L, Czene K, Hall P, Jensen M, Cunningham J, Olson JE, Purrington K, Couch FJ, Brown J, Leyland J, Warren RML, Luben RN, Khaw KT, Smith P, Wareham NJ, Jud SM, Heusinger K, Beckmann MW, Douglas JA, Shah KP, Chan HP, Helvie MA, Le Marchand L, Kolonel LN, Woolcott C, Maskarinec G, Haiman C, Giles GG, Baglietto L, Krishnan K, Southey MC, Apicella C, Andrulis IL, Knight JA, Ursin G, Alnaes GIG, Kristensen VN, Borresen-Dale AL, Gram IT, Bolla MK, Wang Q, Michailidou K, Dennis J, Simard J, Pharoah P, Dunning AM, Easton DF, Fasching PA, Pankratz VS, Hopper JL, Vachon CM. Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures. Cancer Res 2015; 75:2457-67. [PMID: 25862352 PMCID: PMC4470785 DOI: 10.1158/0008-5472.can-14-2012] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2014] [Accepted: 03/10/2015] [Indexed: 12/30/2022]
Abstract
Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.
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Affiliation(s)
- Jennifer Stone
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Western Australia, Australia
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Isabel Dos Santos Silva
- Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Christopher Scott
- Department of Health Sciences Research, Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Rulla M Tamimi
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Sara Lindstrom
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Aditi Hazra
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Jingmei Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Louise Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Matt Jensen
- Department of Health Sciences Research, Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Julie Cunningham
- Department of Laboratory Medicine and Pathology, Division of Experimental Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Janet E Olson
- Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
| | - Kristen Purrington
- Department of Oncology, Wayne State University School of Medicine and Karmanos Cancer Institute, Detroit, Michigan
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Division of Experimental Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota. Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
| | - Judith Brown
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jean Leyland
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Ruth M L Warren
- Department of Radiology, University of Cambridge, Addenbrooke's NHS Foundation Trust, Cambridge, United Kingdom
| | - Robert N Luben
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Kay-Tee Khaw
- MRC Centre for Nutritional Epidemiology in Cancer Prevention and Survival (CNC), University of Cambridge, Cambridge, United Kingdom
| | - Paula Smith
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Sebastian M Jud
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-Nuremberg, Erlangen-Nuremberg, Germany
| | - Katharina Heusinger
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-Nuremberg, Erlangen-Nuremberg, Germany
| | - Matthias W Beckmann
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-Nuremberg, Erlangen-Nuremberg, Germany
| | - Julie A Douglas
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan
| | - Kaanan P Shah
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan
| | - Heang-Ping Chan
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Mark A Helvie
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | | | | | - Christy Woolcott
- Department of Obstetrics and Genecology, IWK Health Centre, Halifax, Canada
| | | | - Christopher Haiman
- Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Laura Baglietto
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia. Centre for Research in Epidemiology and Population Health, Gustave Roussy Institute, Villejuif Cedex, France. Paris-South University, Villejuif, France
| | - Kavitha Krishnan
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Melissa C Southey
- Department of Pathology, University of Melbourne, Melbourne, Australia
| | - Carmel Apicella
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Irene L Andrulis
- Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada. Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Julia A Knight
- Prosserman Centre for Health Research, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Giske Ursin
- Institute of Basic Medical Sciences, University of Oslo, Norway. Department of Preventive Medicine, University of Southern California, California
| | - Grethe I Grenaker Alnaes
- Department of Genetics, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, Oslo, Norway
| | - Vessela N Kristensen
- Department of Genetics, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, Oslo, Norway
| | - Anne-Lise Borresen-Dale
- Department of Genetics, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, Oslo, Norway
| | - Inger Torhild Gram
- Faculty of Health Sciences, Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Qin Wang
- Faculty of Health Sciences, Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jacques Simard
- Centre Hospitalier Universitaire de Québec Research Center and Laval University, Quebec, Canada
| | - Paul Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Peter A Fasching
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-Nuremberg, Erlangen-Nuremberg, Germany. Department of Medicine, Division of Hematology and Oncology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
| | - V Shane Pankratz
- Department of Health Sciences Research, Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Celine M Vachon
- Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota.
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Huo CW, Chew G, Hill P, Huang D, Ingman W, Hodson L, Brown KA, Magenau A, Allam AH, McGhee E, Timpson P, Henderson MA, Thompson EW, Britt K. High mammographic density is associated with an increase in stromal collagen and immune cells within the mammary epithelium. Breast Cancer Res 2015; 17:79. [PMID: 26040322 PMCID: PMC4485361 DOI: 10.1186/s13058-015-0592-1] [Citation(s) in RCA: 120] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2015] [Accepted: 05/20/2015] [Indexed: 02/07/2023] Open
Abstract
INTRODUCTION Mammographic density (MD), after adjustment for a women's age and body mass index, is a strong and independent risk factor for breast cancer (BC). Although the BC risk attributable to increased MD is significant in healthy women, the biological basis of high mammographic density (HMD) causation and how it raises BC risk remain elusive. We assessed the histological and immunohistochemical differences between matched HMD and low mammographic density (LMD) breast tissues from healthy women to define which cell features may mediate the increased MD and MD-associated BC risk. METHODS Tissues were obtained between 2008 and 2013 from 41 women undergoing prophylactic mastectomy because of their high BC risk profile. Tissue slices resected from the mastectomy specimens were X-rayed, then HMD and LMD regions were dissected based on radiological appearance. The histological composition, aromatase immunoreactivity, hormone receptor status and proliferation status were assessed, as were collagen amount and orientation, epithelial subsets and immune cell status. RESULTS HMD tissue had a significantly greater proportion of stroma, collagen and epithelium, as well as less fat, than LMD tissue did. Second harmonic generation imaging demonstrated more organised stromal collagen in HMD tissues than in LMD tissues. There was significantly more aromatase immunoreactivity in both the stromal and glandular regions of HMD tissues than in those regions of LMD tissues, although no significant differences in levels of oestrogen receptor, progesterone receptor or Ki-67 expression were detected. The number of macrophages within the epithelium or stroma did not change; however, HMD stroma exhibited less CD206(+) alternatively activated macrophages. Epithelial cell maturation was not altered in HMD samples, and no evidence of epithelial-mesenchymal transition was seen; however, there was a significant increase in vimentin(+)/CD45(+) immune cells within the epithelial layer in HMD tissues. CONCLUSIONS We confirmed increased proportions of stroma and epithelium, increased aromatase activity and no changes in hormone receptor or Ki-67 marker status in HMD tissue. The HMD region showed increased collagen deposition and organisation as well as decreased alternatively activated macrophages in the stroma. The HMD epithelium may be a site for local inflammation, as we observed a significant increase in CD45(+)/vimentin(+) immune cells in this area.
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Affiliation(s)
- Cecilia W Huo
- University of Melbourne Department of Surgery, St. Vincent's Hospital, Level 2, Clinical Sciences Building, 29 Regent Street, Fitzroy, VIC, 3065, Australia.
| | - Grace Chew
- University of Melbourne Department of Surgery, St. Vincent's Hospital, Level 2, Clinical Sciences Building, 29 Regent Street, Fitzroy, VIC, 3065, Australia.
| | - Prue Hill
- Department of Pathology, St. Vincent's Hospital, 41 Victoria Parade, Fitzroy, VIC, 3065, Australia.
| | - Dexing Huang
- St. Vincent's Institute, 9 Princes Street, Fitzroy, VIC, 3065, Australia.
| | - Wendy Ingman
- Discipline of Surgery, Faculty of Health Sciences, School of Medicine, The Queen Elizabeth Hospital, University of Adelaide, Adelaide, Australia. .,Robinson Research Institute, University of Adelaide, Ground Floor, Norwich Centre, 55 King William Road, North Adelaide, SA, 5006, Australia.
| | - Leigh Hodson
- Discipline of Surgery, Faculty of Health Sciences, School of Medicine, The Queen Elizabeth Hospital, University of Adelaide, Adelaide, Australia. .,Robinson Research Institute, University of Adelaide, Ground Floor, Norwich Centre, 55 King William Road, North Adelaide, SA, 5006, Australia.
| | - Kristy A Brown
- Hudson Institute of Medical Research, 27-31 Wright Street, Clayton, VIC, 3168, Australia.
| | - Astrid Magenau
- Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, Australia. .,St Vincent's Clinical School, Faculty of Medicine, University of NSW, Sydney, Australia. .,St Vincent's Clinical School, Faculty of Medicine, University of NSW, Clayton, Australia.
| | - Amr H Allam
- Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, Australia. .,St Vincent's Clinical School, Faculty of Medicine, University of NSW, Sydney, Australia. .,St Vincent's Clinical School, Faculty of Medicine, University of NSW, Clayton, Australia.
| | - Ewan McGhee
- St Vincent's Clinical School, Faculty of Medicine, University of NSW, Sydney, Australia.
| | - Paul Timpson
- Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, Australia. .,St Vincent's Clinical School, Faculty of Medicine, University of NSW, Sydney, Australia. .,St Vincent's Clinical School, Faculty of Medicine, University of NSW, Clayton, Australia.
| | - Michael A Henderson
- University of Melbourne Department of Surgery, St. Vincent's Hospital, Level 2, Clinical Sciences Building, 29 Regent Street, Fitzroy, VIC, 3065, Australia. .,Peter MacCallum Cancer Centre, 2 St. Andrews Place, East Melbourne, VIC, 3002, Australia.
| | - Erik W Thompson
- University of Melbourne Department of Surgery, St. Vincent's Hospital, Level 2, Clinical Sciences Building, 29 Regent Street, Fitzroy, VIC, 3065, Australia. .,St. Vincent's Institute, 9 Princes Street, Fitzroy, VIC, 3065, Australia. .,Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, 60 Musk Avenue, Kelvin Grove, QLD, 4059, Australia.
| | - Kara Britt
- The Beatson Institute for Cancer Research, Switchback Road, Bearsden Glasgow, G61 1BD, UK. .,The Sir Peter MacCallum Department of Oncology, University of Melbourne, St. Andrews Place, East Melbourne, VIC, 3002, Australia. .,Department of Anatomy and Developmental Biology, Monash University, 19 Innovation Walk, Clayton, VIC, s, Australia.
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Wanders JOP, Bakker MF, Veldhuis WB, Peeters PHM, van Gils CH. The effect of weight change on changes in breast density measures over menopause in a breast cancer screening cohort. Breast Cancer Res 2015; 17:74. [PMID: 26025139 PMCID: PMC4487974 DOI: 10.1186/s13058-015-0583-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Accepted: 05/13/2015] [Indexed: 12/17/2022] Open
Abstract
INTRODUCTION High weight and high percentage mammographic breast density are both breast cancer risk factors but are negatively correlated. Therefore, we wanted to obtain more insight into this apparent paradox. METHODS We investigated in a longitudinal study how weight change over menopause is related to changes in mammographic breast features. Five hundred ninety-one participants of the EPIC-NL cohort were divided into three groups according to their prospectively measured weight change over menopause: (1) weight loss (more than -3.0 %), (2) stable weight (between -3.0 % and +3.0 %), and (3) weight gain (more than 3.0 %). SPSS GLM univariate analysis was used to determine both the mean breast measure changes in, and the trend over, the weight change groups. RESULTS Over a median period of 5 years, the mean changes in percent density in these groups were -5.0 % (95 % confidence interval (CI) -8.0; -2.1), -6.8 % (95 % CI -9.0; -4.5), and -10.2 % (95 % CI -12.5; -7.9), respectively (P-trend = 0.001). The mean changes in dense area were -16.7 cm(2) (95 % CI -20.1; -13.4), -16.4 cm(2) (95 % CI -18.9; -13.9), and -18.1 cm(2) (95 % CI -20.6; -15.5), respectively (P-trend = 0.437). Finally, the mean changes in nondense area were -6.1 cm(2) (95 % CI -11.9; -0.4), -0.6 cm(2) (95 % CI -4.9; 3.8), and 5.3 cm(2) (95 % CI 0.9; 9.8), respectively (P-trend < 0.001). CONCLUSIONS Going through menopause is associated with a decrease in both percent density and dense area. Owing to an increase in the nondense tissue, the decrease in percent density is largest in women who gain weight. The decrease in dense area is not related to weight change. So the fact that both high percent density and high weight or weight gain are associated with high postmenopausal breast cancer risk can probably not be explained by an increase (or slower decrease) of dense area in women gaining weight compared with women losing weight or maintaining a stable weight. These results suggest that weight and dense area are presumably two independent postmenopausal breast cancer risk factors.
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Affiliation(s)
- Johanna Olga Pauline Wanders
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Str. 6.131, P.O. Box 85500, 3508, GA, Utrecht, The Netherlands.
| | - Marije Fokje Bakker
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Str. 6.131, P.O. Box 85500, 3508, GA, Utrecht, The Netherlands.
| | - Wouter Bernard Veldhuis
- Department of Radiology, University Medical Center Utrecht, Room E01.132, P.O. Box 85500, 3508, GA, Utrecht, The Netherlands.
| | - Petra Huberdina Maria Peeters
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Str. 6.131, P.O. Box 85500, 3508, GA, Utrecht, The Netherlands.
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St. Mary's Campus, Norfolk Place, W2 1PG, London, UK.
| | - Carla Henrica van Gils
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Str. 6.131, P.O. Box 85500, 3508, GA, Utrecht, The Netherlands.
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Blueprint of quartz crystal microbalance biosensor for early detection of breast cancer through salivary autoantibodies against ATP6AP1. Biosens Bioelectron 2015; 65:62-70. [DOI: 10.1016/j.bios.2014.09.088] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Revised: 09/29/2014] [Accepted: 09/30/2014] [Indexed: 12/17/2022]
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Bertrand KA, Scott CG, Tamimi RM, Jensen MR, Pankratz VS, Norman AD, Visscher DW, Couch FJ, Shepherd J, Chen YY, Fan B, Wu FF, Ma L, Beck AH, Cummings SR, Kerlikowske K, Vachon CM. Dense and nondense mammographic area and risk of breast cancer by age and tumor characteristics. Cancer Epidemiol Biomarkers Prev 2015; 24:798-809. [PMID: 25716949 DOI: 10.1158/1055-9965.epi-14-1136] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2014] [Accepted: 02/04/2015] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Mammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent mammographic density (PMD) with larger and node-positive tumors across all ages, and estrogen receptor (ER)-negative status among women ages <55 years. To provide insight into these associations, we examined the components of PMD [dense area (DA) and nondense area (NDA)] with breast cancer subtypes. METHODS Data were pooled from six studies including 4,095 breast cancers and 8,558 controls. DA and NDA were assessed from digitized film-screen mammograms and standardized across studies. Breast cancer odds by density phenotypes and age according to histopathologic characteristics and receptor status were calculated using polytomous logistic regression. RESULTS DA was associated with increased breast cancer risk [OR for quartiles: 0.65, 1.00 (Ref), 1.22, 1.55; P(trend) <0.001] and NDA was associated with decreased risk [ORs for quartiles: 1.39, 1.00 (Ref), 0.88, 0.72; P(trend) <0.001] across all ages and invasive tumor characteristics. There were significant trends in the magnitude of associations of both DA and NDA with breast cancer by increasing tumor size (P(trend) < 0.001) but no differences by nodal status. Among women <55 years, DA was more strongly associated with increased risk of ER(+) versus ER(-) tumors (P(het) = 0.02), while NDA was more strongly associated with decreased risk of ER(-) versus ER(+) tumors (P(het) = 0.03). CONCLUSIONS DA and NDA have differential associations with ER(+) versus ER(-) tumors that vary by age. IMPACT DA and NDA are important to consider when developing age- and subtype-specific risk models.
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Affiliation(s)
- Kimberly A Bertrand
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Christopher G Scott
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Rulla M Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Matthew R Jensen
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - V Shane Pankratz
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Aaron D Norman
- Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Daniel W Visscher
- Department of Anatomic Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Fergus J Couch
- Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic College of Medicine, Rochester, Minnesota. Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - John Shepherd
- Department of Radiology, University of California, San Francisco, California
| | - Yunn-Yi Chen
- Department of Pathology, University of California, San Francisco, California
| | - Bo Fan
- Department of Radiology, University of California, San Francisco, California
| | - Fang-Fang Wu
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Lin Ma
- Department of Medicine, University of California, San Francisco, California
| | - Andrew H Beck
- Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Steven R Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, California
| | - Karla Kerlikowske
- Departments of Epidemiology and Biostatistics and General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, California
| | - Celine M Vachon
- Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic College of Medicine, Rochester, Minnesota.
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Yaghjyan L, Colditz GA, Rosner B, Tamimi RM. Mammographic breast density and breast cancer risk: interactions of percent density, absolute dense, and non-dense areas with breast cancer risk factors. Breast Cancer Res Treat 2015; 150:181-9. [PMID: 25677739 DOI: 10.1007/s10549-015-3286-6] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2015] [Accepted: 01/24/2015] [Indexed: 12/20/2022]
Abstract
We investigated if associations of breast density and breast cancer differ according to the level of other known breast cancer risk factors, including body mass index (BMI), age at menarche, parity, age at first child's birth, age at menopause, alcohol consumption, a family history of breast cancer, a history of benign breast disease, and physical activity. This study included 1,044 postmenopausal incident breast cancer cases diagnosed within the Nurses' Health Study cohort and 1,794 matched controls. Percent breast density, absolute dense, and non-dense areas were measured from digitized film images with computerized techniques. Information on breast cancer risk factors was obtained prospectively from biennial questionnaires. Percent breast density was more strongly associated with breast cancer risk in current postmenopausal hormone users (≥50 vs. 10 %: OR 5.34, 95 % CI 3.36-8.49) as compared to women with past (OR 2.69, 95 % CI 1.32-5.49) or no hormone history (OR 2.57, 95 % CI 1.18-5.60, p-interaction = 0.03). Non-dense area was inversely associated with breast cancer risk in parous women, but not in women without children (p-interaction = 0.03). Associations of density with breast cancer risk did not differ by the levels of BMI, age at menarche, parity, age at first child's birth, age at menopause, alcohol consumption, a family history of breast cancer, a history of benign breast disease, and physical activity. Women with dense breasts, who currently use menopausal hormone therapy are at a particularly high risk of breast cancer. Most breast cancer risk factors do not modify the association between mammographic breast density and breast cancer risk.
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Affiliation(s)
- Lusine Yaghjyan
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
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Bertrand KA, Rosner B, Eliassen AH, Hankinson SE, Rexrode KM, Willett W, Tamimi RM. Premenopausal plasma 25-hydroxyvitamin D, mammographic density, and risk of breast cancer. Breast Cancer Res Treat 2015; 149:479-87. [PMID: 25543181 PMCID: PMC4310753 DOI: 10.1007/s10549-014-3247-5] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2014] [Accepted: 12/15/2014] [Indexed: 12/18/2022]
Abstract
Epidemiologic evidence for an association between plasma 25-hydroxyvitamin D [25(OH)D] and breast cancer is inconsistent. Data are especially limited for premenopausal women and for associations with mammographic density. To test the hypothesis that plasma concentration of 25(OH)D is associated with mammographic density, we conducted a cross-sectional study among 835 premenopausal women in the Nurses' Health Studies. We measured 25(OH)D in blood samples and used multivariable linear regression to quantify the association of average percent density by quartile of plasma 25(OH)D. In a nested case-control analysis including 493 breast cancer cases, we evaluated risk of breast cancer associated with vitamin D status within tertiles of mammographic density. Women in the top quartile of plasma 25(OH)D levels had an average percent breast density 5.2 percentage points higher than women in the bottom quartile (95 % confidence interval: 1.8, 8.7; P trend <0.01), after adjusting for predictors of 25(OH)D and established breast cancer risk factors. Plasma 25(OH)D concentration was significantly inversely associated with breast cancer risk among women with high mammographic density (P trend < 0.01) but not among women in lower tertiles of mammographic density (P-interaction < 0.01). These results do not support the hypothesis that vitamin D is inversely associated with percent mammographic density in premenopausal women. There was evidence that the association between premenopausal 25(OH)D and breast cancer risk varies by mammographic density, with an inverse association apparent only among women with high mammographic density.
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Affiliation(s)
- Kimberly A Bertrand
- Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA,
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Rice MS, Tworoger SS, Bertrand KA, Hankinson SE, Rosner BA, Feeney YB, Clevenger CV, Tamimi RM. Immunoassay and Nb2 lymphoma bioassay prolactin levels and mammographic density in premenopausal and postmenopausal women the Nurses' Health Studies. Breast Cancer Res Treat 2014; 149:245-53. [PMID: 25503962 DOI: 10.1007/s10549-014-3232-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2014] [Accepted: 12/03/2014] [Indexed: 10/24/2022]
Abstract
Higher circulating prolactin levels have been associated with higher percent mammographic density among postmenopausal women in some, but not all studies. However, few studies have examined associations with dense area and non-dense breast area breast or considered associations with prolactin Nb2 lymphoma cell bioassay levels. We conducted a cross-sectional study among 1,124 premenopausal and 890 postmenopausal women who were controls in breast cancer case-control studies nested in the Nurses' Health Study (NHS) and NHSII. Participants provided blood samples in 1989-1990 (NHS) or 1996-1999 (NHSII) and mammograms were obtained from around the time of blood draw. Multivariable linear models were used to assess the associations between prolactin levels (measured by immunoassay or bioassay) with percent density, dense area, and non-dense area. Among 1,124 premenopausal women, percent density, dense area, and non-dense area were not associated with prolactin immunoassay levels in multivariable models (p trends = 0.10, 0.18, and 0.69, respectively). Among 890 postmenopausal women, those with prolactin immunoassay levels in the highest versus lowest quartile had modestly, though significantly, higher percent density (difference = 3.01 percentage points, 95 % CI 0.22, 5.80) as well as lower non-dense area (p trend = 0.02). Among women with both immunoassay and bioassay levels, there were no consistent differences in the associations with percent density between bioassay and immunoassay levels. Postmenopausal women with prolactin immunoassay levels in the highest quartile had significantly higher percent density as well as lower non-dense area compared to those in the lowest quartile. Future studies should examine the underlying biologic mechanisms, particularly for non-dense area.
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Affiliation(s)
- Megan S Rice
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Ave 3rd Floor, Boston, MA, 02115, USA,
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Change of mammographic density predicts the risk of contralateral breast cancer--a case-control study. Breast Cancer Res 2014; 15:R57. [PMID: 23876209 PMCID: PMC3978478 DOI: 10.1186/bcr3451] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2013] [Revised: 04/03/2013] [Accepted: 07/22/2013] [Indexed: 12/21/2022] Open
Abstract
Introduction Mammographic density is a strong risk factor for breast cancer, but it is unknown whether density at first breast cancer diagnosis and changes during follow-up influences risk of non-simultaneous contralateral breast cancer (CBC). Methods We collected mammograms for CBC-patients (cases, N = 211) and unilateral breast cancer patients (controls, N = 211), individually matched on age and calendar period of first breast cancer diagnosis, type of adjuvant therapy and length of follow-up (mean follow-up time: 8.25 years). The odds of CBC as a function of changes of density during follow-up were investigated using conditional logistic regression, adjusting for non-dense area at diagnosis. Results Patients who experienced ≥10% absolute decrease in percent density had a 55% decreased odds of CBC (OR = 0.45 95% CI: 0.24 to 0.84) relative to patients who had little or no change in density from baseline to first follow-up mammogram (mean = 1.6 (SD = 0.6) years after diagnosis), whereas among those who experienced an absolute increase in percent density we could not detect any effect on the odds of CBC (OR = 0.83 95% CI: 0.24 to 2.87). Conclusion Decrease of mammographic density within the first two years after first diagnosis is associated with a significantly reduced risk of CBC, this potential new risk predictor can thus contribute to decision-making in follow-up strategies and treatment.
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Ekpo EU, McEntee MF. Measurement of breast density with digital breast tomosynthesis--a systematic review. Br J Radiol 2014; 87:20140460. [PMID: 25146640 DOI: 10.1259/bjr.20140460] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Digital breast tomosynthesis (DBT) has gained acceptance as an adjunct to digital mammography in screening. Now that breast density reporting is mandated in several states in the USA, it is increasingly important that the methods of breast density measurement be robust, reliable and consistent. Breast density assessment with DBT needs some consideration since quantitative methods are modelled for two-dimensional (2D) mammography. A review of methods used for breast density assessment with DBT was performed. Existing evidence shows Cumulus has better reproducibility than that of the breast imaging reporting and data system (BI-RADS®) but still suffers from subjective variability; MedDensity is limited by image noise, whilst Volpara and Quantra are robust and consistent. The reported BI-RADs inter-reader breast density agreement (k) ranged from 0.65 to 0.91, with inter-reader correlation (r) ranging from 0.70 to 0.93. The correlation (r) between BI-RADS and Cumulus ranged from 0.54-0.94, whilst that of BI-RADs and MedDensity ranged from 0.48-0.78. The reported agreement (k) between BI-RADs and Volpara is 0.953. Breast density correlation between DBT and 2D mammography ranged from 0.73 to 0.97, with agreement (k) ranging from 0.56 to 0.96. To avoid variability and provide more reliable breast density information for clinicians, automated volumetric methods are preferred.
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Affiliation(s)
- E U Ekpo
- 1 Discipline of Medical Radiation Science, Faculty of Health Science, University of Sydney, Sydney, NSW, Australia
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Yochum L, Tamimi RM, Hankinson SE. Birthweight, early life body size and adult mammographic density: a review of epidemiologic studies. Cancer Causes Control 2014; 25:1247-59. [PMID: 25053404 DOI: 10.1007/s10552-014-0432-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2014] [Accepted: 07/01/2014] [Indexed: 01/09/2023]
Abstract
PURPOSE To evaluate the association between birth weight and early life body size with adult mammographic density in the peer-reviewed literature. METHODS A comprehensive literature search was conducted through January, 2014. English language articles that assessed adult mammographic density (MD) in relation to early life body size (≤18 years old), or birthweight were included. RESULTS Nine studies reported results for early life body size and %MD. Both exposure and outcome were assessed at different ages using multiple methods. In premenopausal women, findings were inconsistent; two studies reported significant, inverse associations, one reported a non-significant, inverse association, and two observed no association. Reasons for these inconsistencies were not obvious. In postmenopausal women, four of five studies supported an inverse association. Two of three studies that adjusted for menopausal status found significant, inverse associations. Birthweight and %MD was evaluated in nine studies. No association was seen in premenopausal women and two of three studies reported positive associations in postmenopausal women. Three of four studies that adjusted for menopausal status found no association. DISCUSSION Early life body size and birthweight appear unrelated to %MD in premenopausal women while an inverse association in postmenopausal women is more likely. Although based on limited data, birthweight and %MD appear positively associated in postmenopausal women. Given the small number of studies, the multiple methods of data collection and analysis, other methodologic issues, and lack of consistency in results, additional research is needed to clarify this complex association and develop a better understanding of the underlying biologic mechanisms.
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Affiliation(s)
- Laura Yochum
- University of Massachusetts Amherst, 426 Arnold House, 716 North Pleasant Street, Amherst, MA, 01003, USA,
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Ahern TP, Hankinson SE, Willett WC, Pollak MN, Eliassen AH, Tamimi RM. Plasma C-peptide, mammographic breast density, and risk of invasive breast cancer. Cancer Epidemiol Biomarkers Prev 2014; 22:1786-96. [PMID: 24097198 DOI: 10.1158/1055-9965.epi-13-0375] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Insulin may promote breast cancer directly by stimulating the insulin receptor or indirectly by increasing the plasma concentration of active sex hormones. The association between insulin and breast density, a strong breast cancer risk factor, has not been thoroughly studied. We measured associations between c-peptide (a molar marker of insulin secretion), breast cancer risk, and breast density measurements in case-control studies nested within the Nurses' Health Study and Nurses' Health Study II cohorts. METHODS Breast cancer associations were estimated with multivariate logistic regression models and then pooled across cohorts (total n = 1,084 cases and 1,785 controls). Mammographic density associations (percent dense area, dense area, and nondense area) were estimated as the difference in least-square means of the density parameters between quartiles of c-peptide concentration in all breast cancer controls with available screening mammography films (n = 1,469). RESULTS After adjustment for adiposity, c-peptide was not associated with any measure of breast density. However, c-peptide was associated with an approximately 50% increased risk of invasive breast cancer [top vs. bottom quartile, adjusted OR = 1.5, 95% confidence interval (CI), 1.1-2.0] that was robust to adjustment for plasma-free estradiol and sex hormone-binding globulin. The association was stronger for ER-negative disease (adjusted OR = 2.0; 95% CI, 1.2-3.6). CONCLUSIONS Our data suggest a positive association between hyperinsulinemia and breast cancer risk that occurs through nonestrogenic mechanisms, and that is not mediated by breast density. IMPACT Primary prevention of breast cancer in women with hyperinsulinemia may be possible by targeting insulin signaling pathways.
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Affiliation(s)
- Thomas P Ahern
- Authors' Affiliations: Channing Division of Network Medicine, Brigham and Women's Hospital & Harvard Medical School; Department of Epidemiology; Department of Nutrition, Harvard School of Public Health, Boston; Division of Biostatistics and Epidemiology, University of Massachusetts School of Public Health and Health Sciences, Amherst, Massachusetts; and Department of Medicine, McGill University, Montréal, Quebec, Canada
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Mammographic density is not a worthwhile examination to distinguish high cancer risk women in screening. Eur Radiol 2014; 24:2412-6. [PMID: 24972955 DOI: 10.1007/s00330-014-3278-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2013] [Revised: 04/07/2014] [Accepted: 06/06/2014] [Indexed: 10/25/2022]
Abstract
Numerous studies established high mammographic density (MD) as a significant breast cancer risk. By adopting both radiological and epidemiological perspectives, we analysed the capacity of this radiological parameter to express an individual level of risk and the methods for assessing the relationship between MD categories and risk. MD is unable to identify individual underlying anatomical and physiological components. Many factors affect accurate and reproducible measurements and consequently classifications of MD. Significant relative risks were found by comparing the MD categories in the tails of distribution (i.e. the group of women with the lowest MD to that with the highest MD), which represent <10 % of women in each group: the majority of the population was ignored. When a relevant threshold of MD was applied to compare another group and the entire population was included to compare the two groups, some studies showed no significant or only moderate relative risk (RR) between women with readings above and those below the threshold. Sensitivity and specificity remain unknown. MD cannot be considered a worthwhile test by which to categorically identify high-risk women in screening. Key points • Unknown individual anatomical and physiological components do not express the risk level.• The epidemiological conditions are not relevant to distinguish a high-risk category.• The most relevant studies show no or moderate risks.
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