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Perera D, Pirikahu S, Walter J, Cadby G, Darcey E, Lloyd R, Hickey M, Saunders C, Hackmann M, Sampson DD, Shepherd J, Lilge L, Stone J. The distribution of breast density in women aged 18 years and older. Breast Cancer Res Treat 2024; 205:521-531. [PMID: 38498102 PMCID: PMC11101556 DOI: 10.1007/s10549-024-07269-y] [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: 09/21/2023] [Accepted: 01/24/2024] [Indexed: 03/20/2024]
Abstract
PURPOSE Age and body mass index (BMI) are critical considerations when assessing individual breast cancer risk, particularly for women with dense breasts. However, age- and BMI-standardized estimates of breast density are not available for screen-aged women, and little is known about the distribution of breast density in women aged < 40. This cross-sectional study uses three different modalities: optical breast spectroscopy (OBS), dual-energy X-ray absorptiometry (DXA), and mammography, to describe the distributions of breast density across categories of age and BMI. METHODS Breast density measures were estimated for 1,961 Australian women aged 18-97 years using OBS (%water and %water + %collagen). Of these, 935 women had DXA measures (percent and absolute fibroglandular dense volume, %FGV and FGV, respectively) and 354 had conventional mammographic measures (percent and absolute dense area). The distributions for each breast density measure were described across categories of age and BMI. RESULTS The mean age was 38 years (standard deviation = 15). Median breast density measures decreased with age and BMI for all three modalities, except for DXA-FGV, which increased with BMI and decreased after age 30. The variation in breast density measures was largest for younger women and decreased with increasing age and BMI. CONCLUSION This unique study describes the distribution of breast density measures for women aged 18-97 using alternative and conventional modalities of measurement. While this study is the largest of its kind, larger sample sizes are needed to provide clinically useful age-standardized measures to identify women with high breast density for their age or BMI.
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Affiliation(s)
- Dilukshi Perera
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia
| | - Sarah Pirikahu
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia
| | - Jane Walter
- University Health Network, Toronto, ON, Canada
| | - Gemma Cadby
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia
| | - Ellie Darcey
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia
| | - Rachel Lloyd
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia
| | - Martha Hickey
- Department of Obstetrics and Gynaecology, University of Melbourne and the Royal Women's Hospital, Melbourne, VIC, Australia
| | - Christobel Saunders
- Department of Surgery, Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia
| | - Michael Hackmann
- School of Human Sciences, The University of Western Australia, Perth, WA, Australia
- Optical and Biomedical Engineering Laboratory School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA, Australia
| | - David D Sampson
- Surry Biophotonics, Advanced Technology Institute and School of Biosciences and Medicine, The University of Surrey, Guildford, Surrey, UK
| | - John Shepherd
- Epidemiology and Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Lothar Lilge
- University Health Network, Toronto, ON, Canada
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Jennifer Stone
- Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia.
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Han E, Van Horn L, Snetselaar L, Shepherd JA, Jung Park Y, Kim H, Jung S, Dorgan JF. The Associations between Intakes of One-Carbon Metabolism-Related Vitamins and Breast Density among Young Women. Cancer Epidemiol Biomarkers Prev 2024; 33:567-575. [PMID: 38270539 PMCID: PMC11038423 DOI: 10.1158/1055-9965.epi-23-1279] [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: 10/15/2023] [Revised: 01/10/2024] [Accepted: 01/23/2024] [Indexed: 01/26/2024] Open
Abstract
BACKGROUND Folate is the primary methyl donor and B vitamins are cofactors for one-carbon metabolism that maintain DNA integrity and epigenetic signatures implicated in carcinogenesis. Breast tissue is particularly susceptible to stimuli in early life. Only limited data are available on associations of one-carbon metabolism-related vitamin intake during youth and young adulthood with breast density, a strong risk factor for breast cancer. METHODS Over 18 years in the DISC and DISC06 Follow-up Study, diets of 182 young women were assessed by three 24-hour recalls on five occasions at ages 8 to 18 years and once at 25 to 29 years. Multivariable-adjusted linear mixed-effects regression was used to examine associations of intakes of one-carbon metabolism-related vitamins with MRI-measured percent dense breast volume (%DBV) and absolute dense breast volume (ADBV) at ages 25 to 29 years. RESULTS Folate intake in youth was inversely associated with %DBV (Ptrend = 0.006) and ADBV (Ptrend = 0.02). These inverse associations were observed with intake during post-, though not premenarche. In contrast, premenarche vitamin B2 intake was positively associated with ADBV (Ptrend < 0.001). Young adult folate and vitamin B6 intakes were inversely associated with %DBV (all Ptrend ≤ 0.04), whereas vitamins B6 and B12 were inversely associated with ADBV (all Ptrend ≤ 0.04). CONCLUSIONS Among these DISC participants intakes of one-carbon metabolism-related vitamins were associated with breast density. Larger prospective studies among diverse populations are needed to replicate these findings. IMPACT Our results suggest the importance of one-carbon metabolism-related vitamin intakes early in life with development of breast density and thereby potentially breast cancer risk later in life.
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Affiliation(s)
- Eunyoung Han
- Department of Nutritional Science and Food management, Ewha Womans University, Seoul, Republic of Korea
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
| | - Linda Van Horn
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Linda Snetselaar
- Department of Epidemiology, University of Iowa, Iowa City, IA, USA
| | | | - Yoon Jung Park
- Department of Nutritional Science and Food management, Ewha Womans University, Seoul, Republic of Korea
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
| | - Hyesook Kim
- Department of Food and Nutrition, Wonkwang University, Jeonbuk, Republic of Korea
| | - Seungyoun Jung
- Department of Nutritional Science and Food management, Ewha Womans University, Seoul, Republic of Korea
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
| | - Joanne F. Dorgan
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
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Atakpa EC, Buist DSM, Aiello Bowles EJ, Cuzick J, Brentnall AR. Development and evaluation of a method to assess breast cancer risk using a longitudinal history of mammographic density: a cohort study. Breast Cancer Res 2023; 25:147. [PMID: 38001476 PMCID: PMC10668455 DOI: 10.1186/s13058-023-01744-y] [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: 07/25/2023] [Accepted: 11/08/2023] [Indexed: 11/26/2023] Open
Abstract
BACKGROUND Women with dense breasts have an increased risk of breast cancer. However, breast density is measured with variability, which may reduce the reliability and accuracy of its association with breast cancer risk. This is particularly relevant when visually assessing breast density due to variation in inter- and intra-reader assessments. To address this issue, we developed a longitudinal breast density measure which uses an individual woman's entire history of mammographic density, and we evaluated its association with breast cancer risk as well as its predictive ability. METHODS In total, 132,439 women, aged 40-73 yr, who were enrolled in Kaiser Permanente Washington and had multiple screening mammograms taken between 1996 and 2013 were followed up for invasive breast cancer through 2014. Breast Imaging Reporting and Data System (BI-RADS) density was assessed at each screen. Continuous and derived categorical longitudinal density measures were developed using a linear mixed model that allowed for longitudinal density to be updated at each screen. Predictive ability was assessed using (1) age and body mass index-adjusted hazard ratios (HR) for breast density (time-varying covariate), (2) likelihood-ratio statistics (ΔLR-χ2) and (3) concordance indices. RESULTS In total, 2704 invasive breast cancers were diagnosed during follow-up (median = 5.2 yr; median mammograms per woman = 3). When compared with an age- and body mass index-only model, the gain in statistical information provided by the continuous longitudinal density measure was 23% greater than that provided by BI-RADS density (follow-up after baseline mammogram: ΔLR-χ2 = 379.6 (degrees of freedom (df) = 2) vs. 307.7 (df = 3)), which increased to 35% (ΔLR-χ2 = 251.2 vs. 186.7) for follow-up after three mammograms (n = 76,313, 2169 cancers). There was a sixfold difference in observed risk between densest and fattiest eight-category longitudinal density (HR = 6.3, 95% CI 4.7-8.7), versus a fourfold difference with BI-RADS density (HR = 4.3, 95% CI 3.4-5.5). Discriminatory accuracy was marginally greater for longitudinal versus BI-RADS density (c-index = 0.64 vs. 0.63, mean difference = 0.008, 95% CI 0.003-0.012). CONCLUSIONS Estimating mammographic density using a woman's history of breast density is likely to be more reliable than using the most recent observation only, which may lead to more reliable and accurate estimates of individual breast cancer risk. Longitudinal breast density has the potential to improve personal breast cancer risk estimation in women attending mammography screening.
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Affiliation(s)
- Emma C Atakpa
- Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
| | - Diana S M Buist
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
- Kaiser Permanente Bernard J Tyson School of Medicine, Pasadena, CA, USA
| | | | - Jack Cuzick
- Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Adam R Brentnall
- Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
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Kim CE, Binder AM, Corvalan C, Pereira A, Shepherd J, Calafat AM, Botelho JC, Hampton JM, Trentham-Dietz A, Michels KB. Time-specific impact of mono-benzyl phthalate (MBzP) and perfluorooctanoic acid (PFOA) on breast density of a Chilean adolescent Cohort. ENVIRONMENT INTERNATIONAL 2023; 181:108241. [PMID: 37857187 DOI: 10.1016/j.envint.2023.108241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 09/13/2023] [Accepted: 09/27/2023] [Indexed: 10/21/2023]
Abstract
INTRODUCTION High mammographic density is among the strongest and most established predictors for breast cancer risk. Puberty, the period during which breasts undergo exponential mammary growth, is considered one of the critical stages of breast development for environmental exposures. Benzylbutyl phthalate (BBP) and perfluorooctanoic acid (PFOA) are pervasive endocrine disrupting chemicals that may increase hormone-sensitive cancers. Evaluating the potential impact of BBP and PFOA exposure on pubertal breast density is important to our understanding of early-life environmental influences on breast cancer etiology. OBJECTIVE To prospectively assess the effect of biomarker concentrations of monobenzyl phthalate (MBzP) and PFOA at specific pubertal window of susceptibility (WOS) on adolescent breast density. METHOD This study included 376 Chilean girls from the Growth and Obesity Cohort Study with data collection at four timepoints: Tanner breast stages 1 (B1) and 4 (B4), 1- year post- menarche (1YPM) and 2-years post-menarche (2YPM). Dual-energy X-ray absorptiometry was used to assess the absolute fibroglandular volume (FGV) and percent breast density (%FGV) at 2YPM. We used concentrations of PFOA in serum and MBzP in urine as an index of exposure to PFOA and BBP, respectively. Parametric G-formula was used to estimate the time-specific effects of MBzP and PFOA on breast density. The models included body fat percentage as a time-varying confounder and age, birthweight, age at menarche, and maternal education as fixed covariates. RESULTS A doubling of serum PFOA concentration at B4 resulted in a non-significant increase in absolute FGV (β:11.25, 95% confidence interval (CI): -0.28, 23.49)), while a doubling of PFOA concentration at 1YPM resulted in a decrease in % FGV (β:-4.61, 95% CI: -7.45, -1.78). We observed no associations between urine MBzP and breast density measures. CONCLUSION In this cohort of Latina girls, PFOA serum concentrations corresponded to a decrease in % FGV. No effect was observed between MBzP and breast density measures across pubertal WOS.
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Affiliation(s)
- Claire E Kim
- Department of Epidemiology, University of California Los Angeles, Los Angeles, CA, USA
| | - Alexandra M Binder
- Department of Epidemiology, University of California Los Angeles, Los Angeles, CA, USA; Population Sciences in the Pacific Program, University of Hawaii Cancer, Honolulu, HI, USA
| | - Camila Corvalan
- Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - Ana Pereira
- Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - John Shepherd
- Population Sciences in the Pacific Program, University of Hawaii Cancer, Honolulu, HI, USA
| | - Antonia M Calafat
- National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Julianne C Botelho
- National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - John M Hampton
- Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, USA
| | - Amy Trentham-Dietz
- Department of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin - Madison, Madison, USA
| | - Karin B Michels
- Department of Epidemiology, University of California Los Angeles, Los Angeles, CA, USA; Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
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5
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Yoon LS, Binder AM, Pereira A, Calafat AM, Shepherd J, Corvalán C, Michels KB. Variability in urinary phthalates, phenols, and parabens across childhood and relation to adolescent breast composition in Chilean girls. ENVIRONMENT INTERNATIONAL 2022; 170:107586. [PMID: 36302292 PMCID: PMC10517447 DOI: 10.1016/j.envint.2022.107586] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 10/04/2022] [Accepted: 10/14/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Epidemiologic evidence suggests that environmental factors acting as endocrine disrupting chemicals (EDCs) are associated with mammographic breast density and the risk of breast cancer. Exposure to EDCs during puberty, a period of rapid breast development, may affect susceptibility to breast carcinogenesis. METHODS In a cohort of 366 Chilean adolescents from the Growth and Obesity Cohort Study, we evaluated the relation between urinary concentrations of 15 suspected EDC biomarkers across three pubertal time points (Tanner breast stage 1 (B1), 4 (B4), and 1-year post-menarche) and breast fibroglandular volume (FGV; percent FGV [%FGV] and absolute FGV [aFGV]) and total breast volume (tBV) at 2-years post-menarche. We used linear mixed models to test differences in creatinine-corrected EDC biomarker concentrations at B4 and 1-year post-menarche compared to B1 and calculated intraclass correlation coefficients (ICC) of EDC concentrations across time points to appraise the consistency of measurements. We fit multivariable generalized estimating equations (GEEs) to evaluate windows of susceptibility for the association between log10-transformed EDCs and log10-transformed breast outcomes. GEEs were adjusted for age, body fat percentage, total caloric intake, and maternal education. RESULTS Urinary EDC biomarker concentrations highly varied across pubertal time points (ICC range 0.01-0.30). For 12 EDCs, biomarker concentrations decreased over time. Triclosan measured at 1-year post-menarche was inversely associated with %FGV at 2-years post-menarche (β = -0.025, 95 % confidence interval = -0.041, -0.008). Mono(2-ethyl-5-carboxypentyl) phthalate and the sum of di(2-ethylhexyl) phthalate metabolite concentrations at B4 were positively associated with aFGV and tBV at 2-years post-menarche. No measured phenols were associated with aFGV and tBV, while no measured parabens were associated with %FGV and aFGV. CONCLUSIONS Our study suggests relatively high variability in EDC biomarker concentrations across the peripubertal time period. We also found evidence to suggest that there may be pubertal windows of susceptibility to select EDCs for the association with adolescent breast density.
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Affiliation(s)
- Lara S Yoon
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, 650 Charles E. Young Drive South, Los Angeles, CA 90025, USA.
| | - Alexandra M Binder
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, 650 Charles E. Young Drive South, Los Angeles, CA 90025, USA; Cancer Epidemiology Program, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, HI 96813, USA.
| | - Ana Pereira
- Institute of Nutrition and Food Technology, University of Chile, Macul, Santiago 7830490, Chile.
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Highway, Mailstop F17, Atlanta, GA 30341, USA.
| | - John Shepherd
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, HI 96813, USA.
| | - Camila Corvalán
- Institute of Nutrition and Food Technology, University of Chile, Macul, Santiago 7830490, Chile.
| | - Karin B Michels
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, 650 Charles E. Young Drive South, Los Angeles, CA 90025, USA; Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Elsässerstraße 2, 79110 Freiburg, Germany.
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Fornili M, Perduca V, Fournier A, Jérolon A, Boutron-Ruault MC, Maskarinec G, Severi G, Baglietto L. Association between menopausal hormone therapy, mammographic density and breast cancer risk: results from the E3N cohort study. Breast Cancer Res 2021; 23:47. [PMID: 33865453 PMCID: PMC8053286 DOI: 10.1186/s13058-021-01425-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 04/01/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Menopausal hormone therapy (MHT) is a risk factor for breast cancer (BC). Evidence suggests that its effect on BC risk could be partly mediated by mammographic density. The aim of this study was to investigate the relationship between MHT, mammographic density and BC risk using data from a prospective study. METHODS We used data from a case-control study nested within the French cohort E3N including 453 cases and 453 matched controls. Measures of mammographic density, history of MHT use during follow-up and information on potential confounders were available for all women. The association between MHT and mammographic density was evaluated by linear regression models. We applied mediation modelling techniques to estimate, under the hypothesis of a causal model, the proportion of the effect of MHT on BC risk mediated by percent mammographic density (PMD) for BC overall and by hormone receptor status. RESULTS Among MHT users, 4.2% used exclusively oestrogen alone compared with 68.3% who used exclusively oestrogens plus progestogens. Mammographic density was higher in current users (for a 60-year-old woman, mean PMD 33%; 95% CI 31 to 35%) than in past (29%; 27 to 31%) and never users (24%; 22 to 26%). No statistically significant association was observed between duration of MHT and mammographic density. In past MHT users, mammographic density was negatively associated with time since last use; values similar to those of never users were observed in women who had stopped MHT at least 8 years earlier. The odds ratio of BC for current versus never MHT users, adjusted for age, year of birth, menopausal status at baseline and BMI, was 1.67 (95% CI, 1.04 to 2.68). The proportion of effect mediated by PMD was 34% for any BC and became 48% when the correlation between BMI and PMD was accounted for. These effects were limited to hormone receptor-positive BC. CONCLUSIONS Our results suggest that, under a causal model, nearly half of the effect of MHT on hormone receptor-positive BC risk is mediated by mammographic density, which appears to be modified by MHT for up to 8 years after MHT termination.
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Affiliation(s)
- M Fornili
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - V Perduca
- Laboratoire MAP 5 (UMR CNRS 8145), Université de Paris, Paris, France
| | - A Fournier
- University Paris-Saclay, UVSQ, Inserm, Gustave Roussy, "Exposome and Heredity" team, CESP UMR1018, 94805, Villejuif, France
| | - A Jérolon
- Laboratoire MAP 5 (UMR CNRS 8145), Université de Paris, Paris, France
| | - M C Boutron-Ruault
- University Paris-Saclay, UVSQ, Inserm, Gustave Roussy, "Exposome and Heredity" team, CESP UMR1018, 94805, Villejuif, France
| | - G Maskarinec
- University of Hawaii Cancer Center, Honolulu, USA
| | - G Severi
- University Paris-Saclay, UVSQ, Inserm, Gustave Roussy, "Exposome and Heredity" team, CESP UMR1018, 94805, Villejuif, France.
- Department of Statistics, Computer Science and Applications (DISIA), University of Florence, Florence, Italy.
| | - L Baglietto
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
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Gaudet MM, Deubler E, Diver WR, Puvanesarajah S, Patel AV, Gansler T, Sherman ME, Gapstur SM. Breast cancer risk factors by mode of detection among screened women in the Cancer Prevention Study-II. Breast Cancer Res Treat 2021; 186:791-805. [PMID: 33398477 DOI: 10.1007/s10549-020-06025-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Identifying risk factors for women at high risk of symptom-detected breast cancers that were missed by screening would enable targeting of enhanced screening regimens. To this end, we examined associations of breast cancer risk factors by mode of detection in screened women from the Cancer Prevention Study (CPS)-II Nutrition Cohort. METHODS Among 77,206 women followed for a median of 14.8 years, 2711 screen-detected and 1281 symptom-detected breast cancer cases were diagnosed. Multivariable-adjusted associations were estimated using joint Cox proportional hazards regression models with person-time calculated contingent on screening. RESULTS Factors associated with higher risks of symptom-detected and screen-detected breast cancer included current combined hormone therapy (HT) use (HR 2.07, 95% CI 1.72-2.48 and 1.45, 1.27-1.65, respectively) and history of benign breast disease (1.85, 1.64-2.08 and 1.43, 1.31-1.55, respectively). Current estrogen-only HT use was associated with symptom-detected (1.40, 1.15-1.71) but not screen-detected (0.95, 0.83-1.09) breast cancer. Higher risk of screen-detected but not symptom-detected breast cancer was observed for obese vs. normal body mass index (1.22, 1.01-1.48 and 0.76, 0.56-1.01, respectively), per 3 h/day sitting time (1.10, 1.04-1.16 and 0.97, 0.89-1.06, respectively), and ≥ 2 drinks per day vs. nondrinker (1.40, 1.16-1.69 and 1.27, 0.97-1.66, respectively). CONCLUSIONS Differences in risk factors for symptom-detected vs. screen-detected breast cancer were observed and most notably, use of combined and estrogen-only HT and a history of benign breast disease were associated with increased risk of symptomatic detected breast cancer. IMPACT If confirmed, these data suggest that such women may benefit from more intensive screening to facilitate early detection.
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Affiliation(s)
- Mia M Gaudet
- Behavioral and Epidemiology Research Program, American Cancer Society, 250 Williams Street, Atlanta, GA, 30303, USA.
| | - Emily Deubler
- Behavioral and Epidemiology Research Program, American Cancer Society, 250 Williams Street, Atlanta, GA, 30303, USA
| | - W Ryan Diver
- Behavioral and Epidemiology Research Program, American Cancer Society, 250 Williams Street, Atlanta, GA, 30303, USA
| | - Samantha Puvanesarajah
- Behavioral and Epidemiology Research Program, American Cancer Society, 250 Williams Street, Atlanta, GA, 30303, USA
| | - Alpa V Patel
- Behavioral and Epidemiology Research Program, American Cancer Society, 250 Williams Street, Atlanta, GA, 30303, USA
| | - Ted Gansler
- Behavioral and Epidemiology Research Program, American Cancer Society, 250 Williams Street, Atlanta, GA, 30303, USA
| | - Mark E Sherman
- Departments of Epidemiology and of Laboratory Medicine and Pathology, Mayo Clinical College of Medicine, Jacksonville, FL, USA
| | - Susan M Gapstur
- Behavioral and Epidemiology Research Program, American Cancer Society, 250 Williams Street, Atlanta, GA, 30303, USA
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Aging-Associated Alterations in Mammary Epithelia and Stroma Revealed by Single-Cell RNA Sequencing. Cell Rep 2020; 33:108566. [PMID: 33378681 PMCID: PMC7898263 DOI: 10.1016/j.celrep.2020.108566] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 10/13/2020] [Accepted: 12/07/2020] [Indexed: 12/11/2022] Open
Abstract
Aging is closely associated with increased susceptibility to breast cancer, yet there have been limited systematic studies of aging-induced alterations in the mammary gland. Here, we leverage high-throughput single-cell RNA sequencing to generate a detailed transcriptomic atlas of young and aged murine mammary tissues. By analyzing epithelial, stromal, and immune cells, we identify age-dependent alterations in cell proportions and gene expression, providing evidence that suggests alveolar maturation and physiological decline. The analysis also uncovers potential pro-tumorigenic mechanisms coupled to the age-associated loss of tumor suppressor function and change in microenvironment. In addition, we identify a rare, age-dependent luminal population co-expressing hormone-sensing and secretory-alveolar lineage markers, as well as two macrophage populations expressing distinct gene signatures, underscoring the complex heterogeneity of the mammary epithelia and stroma. Collectively, this rich single-cell atlas reveals the effects of aging on mammary physiology and can serve as a useful resource for understanding aging-associated cancer risk. Using single-cell RNA-sequencing, Li et al. compare mammary epithelia and stroma in young and aged mice. Age-dependent changes at cell and gene levels provide evidence suggesting alveolar maturation, functional deterioration, and potential pro-tumorigenic and inflammatory alterations. Additionally, identification of heterogeneous luminal and macrophage subpopulations underscores the complexity of mammary lineages.
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9
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Rebolj M, Blyuss O, Chia KS, Duffy SW. Long-term excess risk of breast cancer after a single breast density measurement. Eur J Cancer 2019; 117:41-47. [PMID: 31229948 PMCID: PMC6658627 DOI: 10.1016/j.ejca.2019.05.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 05/02/2019] [Accepted: 05/03/2019] [Indexed: 12/20/2022]
Abstract
AIM Breast density is a risk factor for breast cancer. As density changes across a woman's life span, we studied for how long a single density measurement taken in (post-)menopausal women remains informative. METHODS We used data from Singaporean women who underwent a single mammography screen at age 50-64 years. For each case with breast cancer diagnosed at screening or in the subsequent 10 years, whether screen detected or diagnosed following symptoms, two age-matched controls were selected. We studied the excess risk of breast cancer, calculated as an odds ratio (OR) with conditional logistic regression and adjusted for body mass index, associated with 26-50% and with 51-100% density compared with ≤25% density by time since screening. RESULTS In total, 490 women had breast cancer, of which 361 were diagnosed because of symptoms after screening. Women with 51-100% breast density had an excess risk of breast cancer that did not seem to attenuate with time. In 1-3 years after screening, the OR was 2.22 (95% confidence interval [CI]: 1.07-4.61); in 4-6 years after screening, the OR was 4.09 (95% CI: 2.21-7.58), and in 7-10 years after screening, the OR was 5.35 (95% CI: 2.57-11.15). Excess risk with a stable OR of about 2 was also observed for women with 26-50% breast density. These patterns were robust when the analyses were limited to post-menopausal women, non-users of hormonal replacement therapy and after stratification by age at density measurement. CONCLUSION A single breast density measurement identifies women with an excess risk of breast cancer during at least the subsequent 10 years.
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Affiliation(s)
- Matejka Rebolj
- Cancer Prevention Group, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences & Medicine, King's College London, London SE1 9RT, UK; Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK.
| | - Oleg Blyuss
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK; Department of Paediatrics, Sechenov University, Moscow, Russia
| | - Kee Seng Chia
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Stephen W Duffy
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts & The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK.
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10
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Jung S, Goloubeva O, Hylton N, Klifa C, LeBlanc E, Shepherd J, Snetselaar L, Van Horn L, Dorgan JF. Intake of dietary carbohydrates in early adulthood and adolescence and breast density among young women. Cancer Causes Control 2018; 29:631-642. [PMID: 29802491 PMCID: PMC7365352 DOI: 10.1007/s10552-018-1040-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Accepted: 05/16/2018] [Indexed: 12/31/2022]
Abstract
PURPOSE Carbohydrate intake increases postprandial insulin secretion and may affect breast density, a strong risk factor for breast cancer, early in life. We examined associations of adolescent and early adulthood intakes of total carbohydrates, glycemic index/load, fiber, and simple sugars with breast density among 182 young women. METHODS Diet was assessed using three 24-h recalls at each of five Dietary Intervention Study in Children (DISC) clinic visits when participants were age 10-19 years and at the DISC06 Follow-Up Study clinic visit when participants were age 25-29 years. Associations between energy-adjusted carbohydrates and MRI-measured percent dense breast volume (%DBV) and absolute dense breast volume (ADBV) at 25-29 years were quantified using multivariable-adjusted mixed-effects linear models. RESULTS Adolescent sucrose intakes and premenarcheal total carbohydrates intakes were modestly associated with higher %DBV (mean %DBVQ1 vs Q4, 16.6 vs 23.5% for sucrose; and 17.2 vs 22.3% for premenarcheal total carbohydrates, all Ptrend ≤ 0.02), but not with ADBV. However, adolescent intakes of fiber and fructose were not associated with %DBV and ADBV. Early adulthood intakes of total carbohydrates, glycemic index/load, fiber, and simple sugars were not associated with %DBV and ADBV. CONCLUSIONS Insulinemic carbohydrate diet during puberty may be associated with adulthood breast density, but our findings need replication in larger studies. Clinical Trials Registration ClinicalTrials.gov Identifier, NCT00458588 April 9, 2007; NCT00000459 October 27, 1999.
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Affiliation(s)
- Seungyoun Jung
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Howard Hall 102E, Baltimore, MD, 21201, USA
| | - Olga Goloubeva
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Howard Hall 102E, Baltimore, MD, 21201, USA
| | - Nola Hylton
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | | | - Erin LeBlanc
- Kaiser Permanente Center for Health Research, Portland, OR, USA
| | - John Shepherd
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
- University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Linda Snetselaar
- Department of Epidemiology, University of Iowa, Iowa City, IA, USA
| | - Linda Van Horn
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Joanne F Dorgan
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Howard Hall 102E, Baltimore, MD, 21201, USA.
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11
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Automatic Estimation of Volumetric Breast Density Using Artificial Neural Network-Based Calibration of Full-Field Digital Mammography: Feasibility on Japanese Women With and Without Breast Cancer. J Digit Imaging 2018; 30:215-227. [PMID: 27832519 DOI: 10.1007/s10278-016-9922-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Breast cancer is the most common invasive cancer among women and its incidence is increasing. Risk assessment is valuable and recent methods are incorporating novel biomarkers such as mammographic density. Artificial neural networks (ANN) are adaptive algorithms capable of performing pattern-to-pattern learning and are well suited for medical applications. They are potentially useful for calibrating full-field digital mammography (FFDM) for quantitative analysis. This study uses ANN modeling to estimate volumetric breast density (VBD) from FFDM on Japanese women with and without breast cancer. ANN calibration of VBD was performed using phantom data for one FFDM system. Mammograms of 46 Japanese women diagnosed with invasive carcinoma and 53 with negative findings were analyzed using ANN models learned. ANN-estimated VBD was validated against phantom data, compared intra-patient, with qualitative composition scoring, with MRI VBD, and inter-patient with classical risk factors of breast cancer as well as cancer status. Phantom validations reached an R 2 of 0.993. Intra-patient validations ranged from R 2 of 0.789 with VBD to 0.908 with breast volume. ANN VBD agreed well with BI-RADS scoring and MRI VBD with R 2 ranging from 0.665 with VBD to 0.852 with breast volume. VBD was significantly higher in women with cancer. Associations with age, BMI, menopause, and cancer status previously reported were also confirmed. ANN modeling appears to produce reasonable measures of mammographic density validated with phantoms, with existing measures of breast density, and with classical biomarkers of breast cancer. FFDM VBD is significantly higher in Japanese women with cancer.
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12
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Breast cancer risk factors and mammographic density among high-risk women in urban China. NPJ Breast Cancer 2018; 4:3. [PMID: 29423438 PMCID: PMC5802809 DOI: 10.1038/s41523-018-0055-9] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Revised: 12/05/2017] [Accepted: 01/03/2018] [Indexed: 01/05/2023] Open
Abstract
Elevated mammographic density (MD) is an established breast cancer risk factor. Studies examining relationships between MD and breast cancer risk factors are limited in China, where established breast cancer risk factors are less prevalent but dense breasts are more prevalent than Western countries. This study included 11,478 women (45-69 years; 36% premenopausal) participating in an ongoing national cancer screening program in 11 urban provinces in China and predicted as having high-risk for breast cancer. Polytomous logistic regression was performed to assess associations between MD and risk factors by comparing each higher Breast Imaging Reporting and Data System (BI-RADS) category (2, 3, or 4) to the lowest category (BI-RADS, 1). We found associations of increasing age, body mass index, weight, postmenopausal status, and parity with lower MD. Higher levels of education, increasing height, and later first birth were associated with higher MD. These associations did not vary by menopausal status. Additionally, the association between longer period of breastfeeding and lower MD was seen among postmenopausal women only (Pinteraction = 0.003). Having first-degree relatives with breast cancer diagnosed before 50 years was associated with lower MD only among premenopausal women (Pinteraction = 0.061). We found effects of established breast cancer risk factors on MD showed similar directions in Chinese and Western women, supporting the hypothesis that MD represents cumulative exposure to breast cancer risk factors over the life course. Our findings help to understand the biological basis of the association of MD with breast cancer risk and have implications for breast cancer prevention research in China.
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13
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Minakshi R, Rahman S, Jan AT, Archana A, Kim J. Implications of aging and the endoplasmic reticulum unfolded protein response on the molecular modality of breast cancer. Exp Mol Med 2017; 49:e389. [PMID: 29123254 PMCID: PMC5704197 DOI: 10.1038/emm.2017.215] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Revised: 06/12/2017] [Accepted: 06/19/2017] [Indexed: 12/22/2022] Open
Abstract
The endoplasmic reticulum (ER) is an important subcellular organelle that is involved in numerous activities required to achieve and maintain functional proteins in addition to its role in the biosynthesis of lipids and as a repository of intracellular Ca2+. The inability of the ER to cope with protein folding beyond its capacity causes disturbances that evoke ER stress. Cells possess molecular mechanisms aimed at clearing unwanted cargo from the ER lumen as an adaptive response, but failing to do so navigates the system towards cell death. This systemic approach is called the unfolded protein response. Aging insults cells through various perturbations in homeostasis that involve curtailing ER function by mitigating the expression of its resident chaperones and enzymes. Here the unfolded protein response (UPR) cannot protect the cell due to the weakening of its protective arm, which exacerbates imbalanced homeostasis. Aging predisposed breast malignancy activates the UPR, but tumor cells maneuver the mechanistic details of the UPR, favoring tumorigenesis and thereby eliciting a treacherous condition. Tumor cells exploit UPR pathways via crosstalk involving various signaling cascades that usher tumor cells to immortality. This review aims to present a collection of data that can delineate the missing links of molecular signatures between aging and breast cancer.
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Affiliation(s)
- Rinki Minakshi
- Institute of Home Economics, University of Delhi, New Delhi, India
| | - Safikur Rahman
- Department of Medical Biotechnology, Yeungnam University, Gyeongsan, South Korea
| | - Arif Tasleem Jan
- Department of Medical Biotechnology, Yeungnam University, Gyeongsan, South Korea
| | - Ayyagari Archana
- Department of Microbiology, Swami Shraddhanand College, University of Delhi, New Delhi, India
| | - Jihoe Kim
- Department of Medical Biotechnology, Yeungnam University, Gyeongsan, South Korea
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14
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Hack CC, Emons J, Jud SM, Heusinger K, Adler W, Gass P, Haeberle L, Heindl F, Hein A, Schulz-Wendtland R, Uder M, Hartmann A, Beckmann MW, Fasching PA, Pöhls UG. Association between mammographic density and pregnancies relative to age and BMI: a breast cancer case-only analysis. Breast Cancer Res Treat 2017; 166:701-708. [PMID: 28828694 DOI: 10.1007/s10549-017-4446-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Accepted: 08/05/2017] [Indexed: 12/29/2022]
Abstract
PURPOSE Percentage mammographic density (PMD) is a major risk factor for breast cancer (BC). It is strongly associated with body mass index (BMI) and age, which are themselves risk factors for breast cancer. This analysis investigated the association between the number of full-term pregnancies and PMD in different subgroups relative to age and BMI. METHODS Patients were identified in the breast cancer database of the University Breast Center for Franconia. A total of 2410 patients were identified, for whom information on parity, age, and BMI, and a mammogram from the time of first diagnosis were available for assessing PMD. Linear regression analyses were conducted to investigate the influence on PMD of the number of full-term pregnancies (FTPs), age, BMI, and interaction terms between them. RESULTS As in previous studies, age, number of FTPs, and BMI were found to be associated with PMD in the expected direction. However, including the respective interaction terms improved the prediction of PMD even further. Specifically, the association between PMD and the number of FTPs differed in young patients under the age of 45 (mean decrease of 0.37 PMD units per pregnancy) from the association in older age groups (mean decrease between 2.29 and 2.39 PMD units). BMI did not alter the association between PMD and the number of FTPs. CONCLUSIONS The effect of pregnancies on mammographic density does not appear to become apparent before the age of menopause. The mechanism that drives the effect of pregnancies on mammographic density appears to be counter-regulated by other influences on mammographic density in younger patients.
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Affiliation(s)
- Carolin C Hack
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Julius Emons
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Sebastian M Jud
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Katharina Heusinger
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Werner Adler
- Institute of Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen, Germany
| | - Paul Gass
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Lothar Haeberle
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Felix Heindl
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Alexander Hein
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | | | - Michael Uder
- Institute of Diagnostic Radiology, Erlangen University Hospital, Erlangen, Germany
| | - Arndt Hartmann
- Institute of Pathology, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Erlangen, Germany
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Universitätsstrasse 21-23, 91054, Erlangen, Germany
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Erlangen University Hospital, Comprehensive Cancer Center Erlangen/European Metropolitan Area Nuremberg (CCC ER-EMN), Universitätsstrasse 21-23, 91054, Erlangen, Germany.
| | - Uwe G Pöhls
- Practice of Dr. Pöhls, Women's Health Center of Würzburg, Würzburg, Germany
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15
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Burton A, Maskarinec G, Perez-Gomez B, Vachon C, Miao H, Lajous M, López-Ridaura R, Rice M, Pereira A, Garmendia ML, Tamimi RM, Bertrand K, Kwong A, Ursin G, Lee E, Qureshi SA, Ma H, Vinnicombe S, Moss S, Allen S, Ndumia R, Vinayak S, Teo SH, Mariapun S, Fadzli F, Peplonska B, Bukowska A, Nagata C, Stone J, Hopper J, Giles G, Ozmen V, Aribal ME, Schüz J, Van Gils CH, Wanders JOP, Sirous R, Sirous M, Hipwell J, Kim J, Lee JW, Dickens C, Hartman M, Chia KS, Scott C, Chiarelli AM, Linton L, Pollan M, Flugelman AA, Salem D, Kamal R, Boyd N, dos-Santos-Silva I, McCormack V. Mammographic density and ageing: A collaborative pooled analysis of cross-sectional data from 22 countries worldwide. PLoS Med 2017; 14:e1002335. [PMID: 28666001 PMCID: PMC5493289 DOI: 10.1371/journal.pmed.1002335] [Citation(s) in RCA: 102] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2017] [Accepted: 05/24/2017] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Mammographic density (MD) is one of the strongest breast cancer risk factors. Its age-related characteristics have been studied in women in western countries, but whether these associations apply to women worldwide is not known. METHODS AND FINDINGS We examined cross-sectional differences in MD by age and menopausal status in over 11,000 breast-cancer-free women aged 35-85 years, from 40 ethnicity- and location-specific population groups across 22 countries in the International Consortium on Mammographic Density (ICMD). MD was read centrally using a quantitative method (Cumulus) and its square-root metrics were analysed using meta-analysis of group-level estimates and linear regression models of pooled data, adjusted for body mass index, reproductive factors, mammogram view, image type, and reader. In all, 4,534 women were premenopausal, and 6,481 postmenopausal, at the time of mammography. A large age-adjusted difference in percent MD (PD) between post- and premenopausal women was apparent (-0.46 cm [95% CI: -0.53, -0.39]) and appeared greater in women with lower breast cancer risk profiles; variation across population groups due to heterogeneity (I2) was 16.5%. Among premenopausal women, the √PD difference per 10-year increase in age was -0.24 cm (95% CI: -0.34, -0.14; I2 = 30%), reflecting a compositional change (lower dense area and higher non-dense area, with no difference in breast area). In postmenopausal women, the corresponding difference in √PD (-0.38 cm [95% CI: -0.44, -0.33]; I2 = 30%) was additionally driven by increasing breast area. The study is limited by different mammography systems and its cross-sectional rather than longitudinal nature. CONCLUSIONS Declines in MD with increasing age are present premenopausally, continue postmenopausally, and are most pronounced over the menopausal transition. These effects were highly consistent across diverse groups of women worldwide, suggesting that they result from an intrinsic biological, likely hormonal, mechanism common to women. If cumulative breast density is a key determinant of breast cancer risk, younger ages may be the more critical periods for lifestyle modifications aimed at breast density and breast cancer risk reduction.
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Affiliation(s)
- Anya Burton
- Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France
| | - Gertraud Maskarinec
- University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | | | - Celine Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Hui Miao
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Martín Lajous
- Instituto Nacional de Salud Pública, Cuernavaca, Mexico
| | | | - Megan Rice
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Ana Pereira
- Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Chile, Santiago, Chile
| | - Maria Luisa Garmendia
- Instituto de Nutrición y Tecnología de los Alimentos, Universidad de Chile, Santiago, Chile
| | - Rulla M. Tamimi
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Kimberly Bertrand
- Slone Epidemiology Center, Boston University, Boston, Massachusetts, United States of America
| | - Ava Kwong
- Division of Breast Surgery, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
- Department of Surgery and Cancer Genetics Center, Hong Kong Sanatorium and Hospital, Hong Kong, China
- Hong Kong Hereditary Breast Cancer Family Registry, Hong Kong, China
| | - Giske Ursin
- Cancer Registry of Norway, Oslo, Norway
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, United States of America
| | - Eunjung Lee
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, United States of America
| | - Samera A. Qureshi
- Norwegian Centre for Migrant and Minority Health (NAKMI), Oslo, Norway
| | - Huiyan Ma
- Department of Population Sciences, City of Hope National Medical Center, Duarte, California, United States of America
| | - Sarah Vinnicombe
- Division of Cancer Research, Ninewells Hospital and Medical School, Dundee, United Kingdom
| | - Sue Moss
- Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, United Kingdom
| | - Steve Allen
- Department of Diagnostic Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Rose Ndumia
- Aga Khan University Hospital, Nairobi, Kenya
| | | | - Soo-Hwang Teo
- Breast Cancer Research Group, University of Malaya Medical Centre, University of Malaya, Kuala Lumpur, Malaysia
- Cancer Research Malaysia, Subang Jaya, Malaysia
| | | | - Farhana Fadzli
- Breast Cancer Research Unit, Faculty of Medicine, University of Malaya Cancer Research Institute, University of Malaya, Kuala Lumpur, Malaysia
- Biomedical Imaging Department, University of Malaya Medical Centre, University of Malaya, Kuala Lumpur, Malaysia
| | | | | | - Chisato Nagata
- Department of Epidemiology & Preventive Medicine, Graduate School of Medicine, Gifu University, Gifu, Japan
| | - Jennifer Stone
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Western Australia, Australia
| | - John Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Graham Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Vahit Ozmen
- Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Mustafa Erkin Aribal
- Department of Radiology, School of Medicine, Marmara University, Istanbul, Turkey
| | - Joachim Schüz
- Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France
| | - Carla H. Van Gils
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Johanna O. P. Wanders
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Reza Sirous
- Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mehri Sirous
- Radiology Department, Isfahan University of Medical Sciences, Isfahan, Iran
| | - John Hipwell
- Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Jisun Kim
- Asan Medical Center, Seoul, Republic of Korea
| | | | - Caroline Dickens
- Department of Internal Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Mikael Hartman
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
- Department of Surgery, Yong Loo Lin School of Medicine, Singapore
| | - Kee-Seng Chia
- Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
| | - Christopher Scott
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Anna M. Chiarelli
- Ontario Breast Screening Program, Cancer Care Ontario, Toronto, Ontario, Canada
| | - Linda Linton
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Marina Pollan
- Instituto de Salud Carlos III, Madrid, Spain
- CIBERESP, Madrid, Spain
| | - Anath Arzee Flugelman
- National Cancer Control Center, Lady Davis Carmel Medical Center, Faculty of Medicine, Technion–Israel Institute of Technology, Haifa, Israel
| | - Dorria Salem
- Woman Imaging Unit, Radiodiagnosis Department, Kasr El Aini, Cairo University Hospitals, Cairo, Egypt
| | - Rasha Kamal
- Woman Imaging Unit, Radiodiagnosis Department, Kasr El Aini, Cairo University Hospitals, Cairo, Egypt
| | - Norman Boyd
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Isabel dos-Santos-Silva
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Valerie McCormack
- Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France
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16
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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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17
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Sehl ME, Henry JE, Storniolo AM, Ganz PA, Horvath S. DNA methylation age is elevated in breast tissue of healthy women. Breast Cancer Res Treat 2017; 164:209-219. [PMID: 28364215 PMCID: PMC5487725 DOI: 10.1007/s10549-017-4218-4] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 03/22/2017] [Indexed: 12/26/2022]
Abstract
Background Limited evidence suggests that female breast tissue ages faster than other parts of the body according to an epigenetic biomarker of aging known as the “epigenetic clock.” However, it is unknown whether breast tissue samples from healthy women show a similar accelerated aging effect relative to other tissues, and what could drive this acceleration. The goal of this study is to validate our initial finding of advanced DNA methylation (DNAm) age in breast tissue, by directly comparing it to that of peripheral blood tissue from the same individuals, and to do a preliminary assessment of hormonal factors that could explain the difference. Methods We utilized n = 80 breast and 80 matching blood tissue samples collected from 40 healthy female participants of the Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center who donated these samples at two time points spaced at least a year apart. DNA methylation levels (Illumina 450K platform) were used to estimate the DNAm age. Results DNAm age was highly correlated with chronological age in both peripheral blood (r = 0.94, p < 0.0001) and breast tissues (r = 0.86, p < 0.0001). A measure of epigenetic age acceleration (age-adjusted DNAm Age) was substantially increased in breast relative to peripheral blood tissue (p = 1.6 × 10−11). The difference between DNAm age of breast and blood decreased with advancing chronologic age (r = −0.53, p = 4.4 × 10−4). Conclusions Our data clearly demonstrate that female breast tissue has a higher epigenetic age than blood collected from the same subject. We also observe that the degree of elevation in breast diminishes with advancing age. Future larger studies will be needed to examine associations between epigenetic age acceleration and cumulative hormone exposure. Electronic supplementary material The online version of this article (doi:10.1007/s10549-017-4218-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Mary E Sehl
- Medicine, Hematology-Oncology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.,Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Jill E Henry
- Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN, 46202, USA
| | - Anna Maria Storniolo
- Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center, Indianapolis, IN, 46202, USA
| | - Patricia A Ganz
- Medicine, Hematology-Oncology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.,Health Policy and Management, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, Gonda Research Center, University of California Los Angeles, 695 Charles E. Young Drive South, Box 708822, Los Angeles, CA, 90095-7088, USA. .,Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA.
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18
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Krishnan K, Baglietto L, Stone J, Simpson JA, Severi G, Evans CF, MacInnis RJ, Giles GG, Apicella C, Hopper JL. Longitudinal Study of Mammographic Density Measures That Predict Breast Cancer Risk. Cancer Epidemiol Biomarkers Prev 2017; 26:651-660. [PMID: 28062399 DOI: 10.1158/1055-9965.epi-16-0499] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Revised: 11/04/2016] [Accepted: 11/14/2016] [Indexed: 11/16/2022] Open
Abstract
Background: After adjusting for age and body mass index (BMI), mammographic measures-dense area (DA), percent dense area (PDA), and nondense area (NDA)-are associated with breast cancer risk. Our aim was to use longitudinal data to estimate the extent to which these risk-predicting measures track over time.Methods: We collected 4,320 mammograms (age range, 24-83 years) from 970 women in the Melbourne Collaborative Cohort Study and the Australian Breast Cancer Family Registry. Women had on average 4.5 mammograms (range, 1-14). DA, PDA, and NDA were measured using the Cumulus software and normalized using the Box-Cox method. Correlations in the normalized risk-predicting measures over time intervals of different lengths were estimated using nonlinear mixed-effects modeling of Gompertz curves.Results: Mean normalized DA and PDA were constant with age to the early 40s, decreased over the next two decades, and were almost constant from the mid-60s onward. Mean normalized NDA increased nonlinearly with age. After adjusting for age and BMI, the within-woman correlation estimates for normalized DA were 0.94, 0.93, 0.91, 0.91, and 0.91 for mammograms taken 2, 4, 6, 8, and 10 years apart, respectively. Similar correlations were estimated for the age- and BMI-adjusted normalized PDA and NDA.Conclusions: The mammographic measures that predict breast cancer risk are highly correlated over time.Impact: This has implications for etiologic research and clinical management whereby women at increased risk could be identified at a young age (e.g., early 40s or even younger) and recommended appropriate screening and prevention strategies. Cancer Epidemiol Biomarkers Prev; 26(4); 651-60. ©2017 AACR.
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Affiliation(s)
- Kavitha Krishnan
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Laura Baglietto
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia.,Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.,CESP, INSERM, Facultés de Medicine Université Paris-Sud, Villejuif, France.,Department of Clinical and Experimental Medicine, University of Pisa, Italy
| | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia.,Centre for Genetic Origins of Health and Disease, Curtin University and the University of Western Australia, Perth, Australia
| | - Julie A Simpson
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | | | - Christopher F Evans
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Robert J MacInnis
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia.,Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia.,Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.,Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
| | - Carmel Apicella
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia. .,Seoul Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea.,Institute of Health and Environment, Seoul National University, Seoul, Korea
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19
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Burton A, Byrnes G, Stone J, Tamimi RM, Heine J, Vachon C, Ozmen V, Pereira A, Garmendia ML, Scott C, Hipwell JH, Dickens C, Schüz J, Aribal ME, Bertrand K, Kwong A, Giles GG, Hopper J, Pérez Gómez B, Pollán M, Teo SH, Mariapun S, Taib NAM, Lajous M, Lopez-Riduara R, Rice M, Romieu I, Flugelman AA, Ursin G, Qureshi S, Ma H, Lee E, Sirous R, Sirous M, Lee JW, Kim J, Salem D, Kamal R, Hartman M, Miao H, Chia KS, Nagata C, Vinayak S, Ndumia R, van Gils CH, Wanders JOP, Peplonska B, Bukowska A, Allen S, Vinnicombe S, Moss S, Chiarelli AM, Linton L, Maskarinec G, Yaffe MJ, Boyd NF, dos-Santos-Silva I, McCormack VA. Mammographic density assessed on paired raw and processed digital images and on paired screen-film and digital images across three mammography systems. Breast Cancer Res 2016; 18:130. [PMID: 27993168 PMCID: PMC5168805 DOI: 10.1186/s13058-016-0787-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 11/23/2016] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Inter-women and intra-women comparisons of mammographic density (MD) are needed in research, clinical and screening applications; however, MD measurements are influenced by mammography modality (screen film/digital) and digital image format (raw/processed). We aimed to examine differences in MD assessed on these image types. METHODS We obtained 1294 pairs of images saved in both raw and processed formats from Hologic and General Electric (GE) direct digital systems and a Fuji computed radiography (CR) system, and 128 screen-film and processed CR-digital pairs from consecutive screening rounds. Four readers performed Cumulus-based MD measurements (n = 3441), with each image pair read by the same reader. Multi-level models of square-root percent MD were fitted, with a random intercept for woman, to estimate processed-raw MD differences. RESULTS Breast area did not differ in processed images compared with that in raw images, but the percent MD was higher, due to a larger dense area (median 28.5 and 25.4 cm2 respectively, mean √dense area difference 0.44 cm (95% CI: 0.36, 0.52)). This difference in √dense area was significant for direct digital systems (Hologic 0.50 cm (95% CI: 0.39, 0.61), GE 0.56 cm (95% CI: 0.42, 0.69)) but not for Fuji CR (0.06 cm (95% CI: -0.10, 0.23)). Additionally, within each system, reader-specific differences varied in magnitude and direction (p < 0.001). Conversion equations revealed differences converged to zero with increasing dense area. MD differences between screen-film and processed digital on the subsequent screening round were consistent with expected time-related MD declines. CONCLUSIONS MD was slightly higher when measured on processed than on raw direct digital mammograms. Comparisons of MD on these image formats should ideally control for this non-constant and reader-specific difference.
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Affiliation(s)
- Anya Burton
- Section of Environment and Radiation, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372 Lyon, Cedex 09, France
| | - Graham Byrnes
- Section of Environment and Radiation, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372 Lyon, Cedex 09, France
| | - Jennifer Stone
- Centre for Genetic Origins of Health and Disease, Curtin University and the University of Western Australia, Perth, Australia
| | - Rulla M. Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | | | - Celine Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - Vahit Ozmen
- Department of Surgery, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Ana Pereira
- Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | | | - Christopher Scott
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - John H. Hipwell
- Centre for Medical Image Computing, University College London, London, UK
| | - Caroline Dickens
- Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Joachim Schüz
- Section of Environment and Radiation, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372 Lyon, Cedex 09, France
| | | | | | - Ava Kwong
- Division of Breast Surgery, Department of Surgery, The University of Hong Kong, Hong Kong, People’s Republic of China
- Department of Surgery, Hong Kong Sanatorium and Hospital, Hong Kong, People’s Republic of China
| | - Graham G. Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria Australia
| | - John Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria Australia
| | - Beatriz Pérez Gómez
- Cancer Epidemiology Unit, Instituto de Salud Carlos III and CIBERESP, Madrid, Spain
| | - Marina Pollán
- Cancer Epidemiology Unit, Instituto de Salud Carlos III and CIBERESP, Madrid, Spain
| | - Soo-Hwang Teo
- Breast Cancer Research Group, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia
- Cancer Research Malaysia, Subang Jaya, Malaysia
| | | | - Nur Aishah Mohd Taib
- Breast Cancer Research Group, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia
| | - Martín Lajous
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA USA
- Center for Research on Population Health, Instituto Nacional de Salud Pública, Mexico City, Mexico
| | - Ruy Lopez-Riduara
- Center for Research on Population Health, Instituto Nacional de Salud Pública, Mexico City, Mexico
| | - Megan Rice
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Isabelle Romieu
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | | | - Giske Ursin
- Cancer Registry of Norway, Oslo, Norway
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA USA
| | - Samera Qureshi
- Norwegian Center for Minority and Migrant Health Research (NAKMI), Oslo, Norway
| | - Huiyan Ma
- Department of Population Sciences, Beckman Research Institute, City of Hope, CA USA
| | - Eunjung Lee
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA USA
| | - Reza Sirous
- Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mehri Sirous
- Isfahan University of Medical Sciences, Isfahan, Iran
| | - Jong Won Lee
- Department of Surgery, Asan Medical Center, Seoul, Republic of Korea
| | - Jisun Kim
- Department of Surgery, Asan Medical Center, Seoul, Republic of Korea
| | | | - Rasha Kamal
- Woman Imaging Unit, Radiodiagnosis Department, Kasr El Aini, Cairo University Hospitals, Cairo, Egypt
| | - Mikael Hartman
- Department of Surgery, Yong Loo Lin School of Medicine, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Hui Miao
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Kee-Seng Chia
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore
| | | | | | - Rose Ndumia
- Aga Khan University Hospital, Nairobi, Kenya
| | - Carla H. van Gils
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Johanna O. P. Wanders
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | | | - Steve Allen
- Department of Imaging, Royal Marsden NHS Foundation Trust, London, UK
| | - Sarah Vinnicombe
- Division of Cancer Research, Ninewells Hospital & Medical School, Dundee, UK
| | - Sue Moss
- Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK
| | - Anna M. Chiarelli
- Ontario Breast Screening Program, Cancer Care Ontario, Toronto, Canada
| | - Linda Linton
- Princess Margaret Cancer Centre, Toronto, Canada
| | | | | | | | - Isabel dos-Santos-Silva
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Valerie A. McCormack
- Section of Environment and Radiation, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372 Lyon, Cedex 09, France
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20
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Denholm R, De Stavola B, Hipwell JH, Doran SJ, Busana MC, Eng A, Jeffreys M, Leach MO, Hawkes D, dos Santos Silva I. Pre-natal exposures and breast tissue composition: findings from a British pre-birth cohort of young women and a systematic review. Breast Cancer Res 2016; 18:102. [PMID: 27729066 PMCID: PMC5059986 DOI: 10.1186/s13058-016-0751-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2016] [Accepted: 08/23/2016] [Indexed: 12/01/2022] Open
Abstract
BACKGROUND Breast density, the amount of fibroglandular tissue in the adult breast for a women's age and body mass index, is a strong biomarker of susceptibility to breast cancer, which may, like breast cancer risk itself, be influenced by events early in life. In the present study, we investigated the association between pre-natal exposures and breast tissue composition. METHODS A sample of 500 young, nulliparous women (aged approximately 21 years) from a U.K. pre-birth cohort underwent a magnetic resonance imaging examination of their breasts to estimate percent water, a measure of the relative amount of fibroglandular tissue equivalent to mammographic percent density. Information on pre-natal exposures was collected throughout the mothers' pregnancy and shortly after delivery. Regression models were used to investigate associations between percent water and pre-natal exposures. Mediation analysis, and a systematic review and meta-analysis of the published literature, were also conducted. RESULTS Adjusted percent water in young women was positively associated with maternal height (p for linear trend [p t] = 0.005), maternal mammographic density in middle age (p t = 0.018) and the participant's birth size (p t < 0.001 for birthweight). A 1-SD increment in weight (473 g), length (2.3 cm), head circumference (1.2 cm) and Ponderal Index (4.1 g/cm3) at birth were associated with 3 % (95 % CI 2-5 %), 2 % (95 % CI 0-3 %), 3 % (95 % CI 1-4 %) and 1 % (95 % CI 0-3 %), respectively, increases in mean adjusted percent water. The effect of maternal height on the participants' percent water was partly mediated through birth size, but there was little evidence that the effect of birthweight was primarily mediated via adult body size. The meta-analysis supported the study findings, with breast density being positively associated with birth size. CONCLUSIONS These findings provide strong evidence of pre-natal influences on breast tissue composition. The positive association between birth size and relative amount of fibroglandular tissue indicates that breast density and breast cancer risk may share a common pre-natal origin.
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Affiliation(s)
- Rachel Denholm
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Bianca De Stavola
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK
| | - John H. Hipwell
- Centre for Medical Image Computing, Department of Medical Physics and Bioengineering, UCL, London, UK
| | - Simon J. Doran
- Cancer Research UK Cancer Imaging Centre, The Institute of Cancer Research (ICH) and Royal Marsden NHS Foundation Trust (RHM), London, UK
| | - Marta C. Busana
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Amanda Eng
- Centre for Public Health Research, Massey University, Wellington, New Zealand
| | - Mona Jeffreys
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Martin O. Leach
- Cancer Research UK Cancer Imaging Centre, The Institute of Cancer Research (ICH) and Royal Marsden NHS Foundation Trust (RHM), London, UK
| | - David Hawkes
- Centre for Medical Image Computing, Department of Medical Physics and Bioengineering, UCL, London, UK
| | - Isabel dos Santos Silva
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
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21
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Fabian CJ, Kimler BF, Phillips TA, Box JA, Kreutzjans AL, Carlson SE, Hidaka BH, Metheny T, Zalles CM, Mills GB, Powers KR, Sullivan DK, Petroff BK, Hensing WL, Fridley BL, Hursting SD. Modulation of Breast Cancer Risk Biomarkers by High-Dose Omega-3 Fatty Acids: Phase II Pilot Study in Premenopausal Women. Cancer Prev Res (Phila) 2015; 8:912-21. [PMID: 26438592 PMCID: PMC6053670 DOI: 10.1158/1940-6207.capr-14-0335] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Higher intakes of the omega-3 eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) relative to the omega-6 arachidonic acid (AA) have been variably associated with reduced risk of premenopausal breast cancer. The purpose of this pilot trial was to assess feasibility and explore the effects of high-dose EPA and DHA on blood and benign breast tissue risk biomarkers before design of a placebo-controlled phase IIB trial. Premenopausal women with evidence of hyperplasia ± atypia by baseline random periareolar fine needle aspiration were given 1860 mg of EPA + 1500 mg of DHA ethyl esters daily for 6 months. Blood and benign breast tissue were sampled during the same menstrual cycle phase prestudy and a median of 3 weeks after last dose. Additional blood was obtained within 24 hours of last dose. Feasibility, which was predefined as 50% uptake, 85% retention, and 70% compliance, was demonstrated with 46% uptake, 94% completion, and 85% compliance. Cytologic atypia decreased from 77% to 38% (P = 0.002), and Ki-67 from a median of 2.1% to 1.0% (P = 0.021) with an increase in the ratio of EPA + DHA to AA in erythrocyte phospholipids but no change in blood hormones, adipokines, or cytokines. Exploratory breast proteomics assessment showed decreases in several proteins involved in hormone and cytokine signaling with mixed effects on those in the AKT/mTOR pathways. Further investigation of EPA plus DHA for breast cancer prevention in a placebo-controlled trial in premenopausal women is warranted.
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Affiliation(s)
- Carol J Fabian
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas.
| | - Bruce F Kimler
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas
| | - Teresa A Phillips
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Jessica A Box
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Amy L Kreutzjans
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Susan E Carlson
- Department of Dietetics and Nutrition, University of Kansas Medical Center, Kansas City, Kansas
| | - Brandon H Hidaka
- Department of Dietetics and Nutrition, University of Kansas Medical Center, Kansas City, Kansas
| | - Trina Metheny
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | | | - Gordon B Mills
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kandy R Powers
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Debra K Sullivan
- Department of Dietetics and Nutrition, University of Kansas Medical Center, Kansas City, Kansas
| | - Brian K Petroff
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Whitney L Hensing
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Brooke L Fridley
- Department of Biostatistics, University of Kansas Medical Center, Kansas City, Kansas
| | - Stephen D Hursting
- Department of Nutrition, University of North Carolina, Chapel Hill, North Carolina
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22
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Fabian CJ, Kimler BF, Phillips TA, Nydegger JL, Kreutzjans AL, Carlson SE, Hidaka BH, Metheny T, Zalles CM, Mills GB, Powers KR, Sullivan DK, Petroff BK, Hensing WL, Fridley BL, Hursting SD. Modulation of Breast Cancer Risk Biomarkers by High-Dose Omega-3 Fatty Acids: Phase II Pilot Study in Postmenopausal Women. Cancer Prev Res (Phila) 2015; 8:922-31. [PMID: 26276744 PMCID: PMC4596784 DOI: 10.1158/1940-6207.capr-14-0336] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2014] [Accepted: 08/03/2015] [Indexed: 01/05/2023]
Abstract
Associational studies suggest higher intakes/blood levels of the omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) relative to the omega-6 arachidonic acid (AA) are associated with reduced breast cancer risk. We performed a pilot study of high-dose EPA + DHA in postmenopausal women to assess feasibility before initiating a phase IIB prevention trial. Postmenopausal women with cytologic evidence of hyperplasia in their baseline random periareolar fine needle aspiration (RPFNA) took 1,860 mg EPA +1500 mg DHA ethyl esters daily for 6 months. Blood and breast tissue were sampled at baseline and study conclusion for exploratory biomarker assessment, with P values uncorrected for multiple comparisons. Feasibility was predefined as 50% uptake, 80% completion, and 70% compliance. Trial uptake by 35 study entrants from 54 eligible women was 65%, with 97% completion and 97% compliance. Favorable modulation was suggested for serum adiponectin (P = 0.0027), TNFα (P = 0.016), HOMA 2B measure of pancreatic β cell function (P = 0.0048), and bioavailable estradiol (P = 0.039). Benign breast tissue Ki-67 (P = 0.036), macrophage chemoattractant protein-1 (P = 0.033), cytomorphology index score (P = 0.014), and percent mammographic density (P = 0.036) were decreased with favorable effects in a proteomics array for several proteins associated with mitogen signaling and cell-cycle arrest; but no obvious overall effect on proteins downstream of mTOR. Although favorable risk biomarker modulation will need to be confirmed in a placebo-controlled trial, we have demonstrated feasibility for development of high-dose EPA and DHA ethyl esters for primary prevention of breast cancer.
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Affiliation(s)
- Carol J Fabian
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas.
| | - Bruce F Kimler
- Department of Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas
| | - Teresa A Phillips
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Jennifer L Nydegger
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Amy L Kreutzjans
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Susan E Carlson
- Department of Dietetics and Nutrition, University of Kansas Medical Center, Kansas City, Kansas
| | - Brandon H Hidaka
- Department of Dietetics and Nutrition, University of Kansas Medical Center, Kansas City, Kansas
| | - Trina Metheny
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | | | - Gordon B Mills
- Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kandy R Powers
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Debra K Sullivan
- Department of Dietetics and Nutrition, University of Kansas Medical Center, Kansas City, Kansas
| | - Brian K Petroff
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Whitney L Hensing
- Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | - Brooke L Fridley
- Department of Biostatistics, University of Kansas Medical Center, Kansas City, Kansas
| | - Stephen D Hursting
- Department of Nutrition, University of North Carolina, Chapel Hill, North Carolina
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23
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Arendt LM, Kuperwasser C. Form and function: how estrogen and progesterone regulate the mammary epithelial hierarchy. J Mammary Gland Biol Neoplasia 2015; 20:9-25. [PMID: 26188694 PMCID: PMC4596764 DOI: 10.1007/s10911-015-9337-0] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Accepted: 07/08/2015] [Indexed: 12/30/2022] Open
Abstract
The mammary gland undergoes dramatic post-natal growth beginning at puberty, followed by full development occurring during pregnancy and lactation. Following lactation, the alveoli undergo apoptosis, and the mammary gland reverses back to resemble the nonparous gland. This process of growth and regression occurs for multiple pregnancies, suggesting the presence of a hierarchy of stem and progenitor cells that are able to regenerate specialized populations of mammary epithelial cells. Expansion of epithelial cell populations in the mammary gland is regulated by ovarian steroids, in particular estrogen acting through its receptor estrogen receptor alpha (ERα) and progesterone signaling through progesterone receptor (PR). A diverse number of stem and progenitor cells have been identified based on expression of cell surface markers and functional assays. Here we review the current understanding of how estrogen and progesterone act together and separately to regulate stem and progenitor cells within the human and mouse mammary tissues. Better understanding of the hierarchal organization of epithelial cell populations in the mammary gland and how the hormonal milieu affects its regulation may provide important insights into the origins of different subtypes of breast cancer.
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Affiliation(s)
- Lisa M Arendt
- Developmental, Molecular, and Chemical Biology Department, Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, 136 Harrison Ave, Boston, MA, 02111, USA
- Molecular Oncology Research Institute, Tufts Medical Center, 800 Washington St, Boston, MA, 02111, USA
- Raymond and Beverly Sackler Laboratory for the Convergence of Biomedical, Physical and Engineering Sciences, Boston, MA, 02111, USA
- Department of Comparative Biosciences, School of Veterinary Medicine, University of Wisconsin-Madison, 2015 Linden Dr, Madison, WI, 53706, USA
| | - Charlotte Kuperwasser
- Developmental, Molecular, and Chemical Biology Department, Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, 136 Harrison Ave, Boston, MA, 02111, USA.
- Molecular Oncology Research Institute, Tufts Medical Center, 800 Washington St, Boston, MA, 02111, USA.
- Raymond and Beverly Sackler Laboratory for the Convergence of Biomedical, Physical and Engineering Sciences, Boston, MA, 02111, USA.
- Developmental, Molecular, and Chemical Biology Department, Tufts University School of Medicine, 800 Washington St, Box 5609, Boston, MA, 02111, USA.
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24
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Eng A, Gallant Z, Shepherd J, McCormack V, Li J, Dowsett M, Vinnicombe S, Allen S, dos-Santos-Silva I. Digital mammographic density and breast cancer risk: a case-control study of six alternative density assessment methods. Breast Cancer Res 2014; 16:439. [PMID: 25239205 PMCID: PMC4303120 DOI: 10.1186/s13058-014-0439-1] [Citation(s) in RCA: 136] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Accepted: 09/01/2014] [Indexed: 11/10/2022] Open
Abstract
Introduction Mammographic density is a strong breast cancer risk factor and a major determinant of screening sensitivity. However, there is currently no validated estimation method for full-field digital mammography (FFDM). Methods The performance of three area-based approaches (BI-RADS, the semi-automated Cumulus, and the fully-automated ImageJ-based approach) and three fully-automated volumetric methods (Volpara, Quantra and single energy x-ray absorptiometry (SXA)) were assessed in 3168 FFDM images from 414 cases and 685 controls. Linear regression models were used to assess associations between breast cancer risk factors and density among controls, and logistic regression models to assess density-breast cancer risk associations, adjusting for age, body mass index (BMI) and reproductive variables. Results Quantra and the ImageJ-based approach failed to produce readings for 4% and 11% of the participants. All six density assessment methods showed that percent density (PD) was inversely associated with age, BMI, being parous and postmenopausal at mammography. PD was positively associated with breast cancer for all methods, but with the increase in risk per standard deviation increment in PD being highest for Volpara (1.83; 95% CI: 1.51 to 2.21) and Cumulus (1.58; 1.33 to 1.88) and lower for the ImageJ-based method (1.45; 1.21 to 1.74), Quantra (1.40; 1.19 to 1.66) and SXA (1.37; 1.16 to 1.63). Women in the top PD quintile (or BI-RADS 4) had 8.26 (4.28 to 15.96), 3.94 (2.26 to 6.86), 3.38 (2.00 to 5.72), 2.99 (1.76 to 5.09), 2.55 (1.46 to 4.43) and 2.96 (0.50 to 17.5) times the risk of those in the bottom one (or BI-RADS 1), respectively, for Volpara, Quantra, Cumulus, SXA, ImageJ-based method, and BI-RADS (P for trend <0.0001 for all). The ImageJ-based method had a slightly higher ability to discriminate between cases and controls (area under the curve (AUC) for PD = 0.68, P = 0.05), and Quantra slightly lower (AUC = 0.63; P = 0.06), than Cumulus (AUC = 0.65). Conclusions Fully-automated methods are valid alternatives to the labour-intensive "gold standard" Cumulus for quantifying density in FFDM. The choice of a particular method will depend on the aims and setting but the same approach will be required for longitudinal density assessments. Electronic supplementary material The online version of this article (doi:10.1186/s13058-014-0439-1) contains supplementary material, which is available to authorized users.
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Hellmann SS, Lynge E, Schwartz W, Vejborg I, Njor SH. Mammographic density in birth cohorts of Danish women: a longitudinal study. BMC Cancer 2013; 13:409. [PMID: 24106754 PMCID: PMC3766215 DOI: 10.1186/1471-2407-13-409] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2012] [Accepted: 08/30/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Breast cancer is the leading malignant disease among western women with incidence increasing over time. High mammographic density is a well-established risk factor for breast cancer. We explored trends in mammographic density across birth cohorts to gain further insight into possible time trends in women's mammographic density that might explain the historical increase in breast cancer incidence. METHODS Data derived from two mammography screening programs in Denmark from 1991 to 2001, including on average 41,091 women from Copenhagen and 52,938 women from Funen aged 50-69. Mammographic density was assessed qualitatively (fatty or mixed/dense) by senior screening radiologists. The proportion of women with mixed/dense mammographic density was calculated by age at screening, screening period, and birth cohort. The Generalized Estimating Equations were used to calculate odds ratios and 95% confidence intervals. All statistical tests were two-sided. RESULTS The proportion of women with mixed/dense mammographic density increased from 45% among women born in the 1920s to 75-80% among women born in the 1940s. In Copenhagen, the age-adjusted odds ratio (95% CI) of mixed/dense mammographic density in women born in 1941-42 was 2.48 (2.22-2.76) compared with women born in 1921-22. In Funen, the age-adjusted odds ratio of mixed/dense mammographic density in women born in 1946-47 was 5.89 (5.32-6.51) compared with women born in 1924-25. Hormone use had a greater impact on mammographic density in birth cohorts of the 1920s compared with those of the 1940s. CONCLUSIONS We found suggestive evidence of a birth cohort pattern in mammographic density and an attenuated impact of hormone use in younger compared with older birth cohorts suggesting that postmenopausal mammographic density could be linked to changing exposures accumulated over time in women's lives.
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Vachon CM, Scott CG, Fasching PA, Hall P, Tamimi RM, Li J, Stone J, Apicella C, Odefrey F, Gierach GL, Jud SM, Heusinger K, Beckmann MW, Pollan M, Fernández-Navarro P, Gonzalez-Neira A, Benitez J, van Gils CH, Lokate M, Onland-Moret NC, Peeters PHM, Brown J, Leyland J, Varghese JS, Easton DF, Thompson DJ, Luben RN, Warren RML, Wareham NJ, Loos RJF, Khaw KT, Ursin G, Lee E, Gayther SA, Ramus SJ, Eeles RA, Leach MO, Kwan-Lim G, Couch FJ, Giles GG, Baglietto L, Krishnan K, Southey MC, Le Marchand L, Kolonel LN, Woolcott C, Maskarinec G, Haiman CA, Walker K, Johnson N, McCormack VA, Biong M, Alnaes GIG, Gram IT, Kristensen VN, Børresen-Dale AL, Lindström S, Hankinson SE, Hunter DJ, Andrulis IL, Knight JA, Boyd NF, Figuero JD, Lissowska J, Wesolowska E, Peplonska B, Bukowska A, Reszka E, Liu J, Eriksson L, Czene K, Audley T, Wu AH, Pankratz VS, Hopper JL, dos-Santos-Silva I. Common breast cancer susceptibility variants in LSP1 and RAD51L1 are associated with mammographic density measures that predict breast cancer risk. Cancer Epidemiol Biomarkers Prev 2012; 21:1156-66. [PMID: 22454379 PMCID: PMC3569092 DOI: 10.1158/1055-9965.epi-12-0066] [Citation(s) in RCA: 83] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biologic mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to interindividual differences in mammographic density measures. METHODS We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and nondense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, BMI, and menopausal status. RESULTS Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (P = 0.00005) and adjusted percent density (P = 0.001), whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (P = 0.003), but not with adjusted dense area (P = 0.07). CONCLUSION We identified two common breast cancer susceptibility variants associated with mammographic measures of radiodense tissue in the breast gland. IMPACT We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.
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Affiliation(s)
- Celine M Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA.
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Garbe JC, Pepin F, Pelissier FA, Sputova K, Fridriksdottir AJ, Guo DE, Villadsen R, Park M, Petersen OW, Borowsky AD, Stampfer MR, Labarge MA. Accumulation of multipotent progenitors with a basal differentiation bias during aging of human mammary epithelia. Cancer Res 2012; 72:3687-701. [PMID: 22552289 DOI: 10.1158/0008-5472.can-12-0157] [Citation(s) in RCA: 79] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Women older than 50 years account for 75% of new breast cancer diagnoses, and the majority of these tumors are of a luminal subtype. Although age-associated changes, including endocrine profiles and alterations within the breast microenvironment, increase cancer risk, an understanding of the cellular and molecular mechanisms that underlies these observations is lacking. In this study, we generated a large collection of normal human mammary epithelial cell strains from women ages 16 to 91 years, derived from primary tissues, to investigate the molecular changes that occur in aging breast cells. We found that in finite lifespan cultured and uncultured epithelial cells, aging is associated with a reduction of myoepithelial cells and an increase in luminal cells that express keratin 14 and integrin-α6, a phenotype that is usually expressed exclusively in myoepithelial cells in women younger than 30 years. Changes to the luminal lineage resulted from age-dependent expansion of defective multipotent progenitors that gave rise to incompletely differentiated luminal or myoepithelial cells. The aging process therefore results in both a shift in the balance of luminal/myoepithelial lineages and to changes in the functional spectrum of multipotent progenitors, which together increase the potential for malignant transformation. Together, our findings provide a cellular basis to explain the observed vulnerability to breast cancer that increases with age.
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Affiliation(s)
- James C Garbe
- Life Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
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