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Modulation of innate immune response to viruses including SARS-CoV-2 by progesterone. Signal Transduct Target Ther 2022; 7:137. [PMID: 35468896 PMCID: PMC9035769 DOI: 10.1038/s41392-022-00981-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 03/18/2022] [Accepted: 03/22/2022] [Indexed: 12/14/2022] Open
Abstract
Whether and how innate antiviral response is regulated by humoral metabolism remains enigmatic. We show that viral infection induces progesterone via the hypothalamic-pituitary-adrenal axis in mice. Progesterone induces downstream antiviral genes and promotes innate antiviral response in cells and mice, whereas knockout of the progesterone receptor PGR has opposite effects. Mechanistically, stimulation of PGR by progesterone activates the tyrosine kinase SRC, which phosphorylates the transcriptional factor IRF3 at Y107, leading to its activation and induction of antiviral genes. SARS-CoV-2-infected patients have increased progesterone levels, and which are co-related with decreased severity of COVID-19. Our findings reveal how progesterone modulates host innate antiviral response, and point to progesterone as a potential immunomodulatory reagent for infectious and inflammatory diseases.
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Mammographic breast density and IGF-1 gene polymorphisms rs1520220, rs2946834 and rs6219 in Polish women. Contemp Oncol (Pozn) 2021; 25:191-197. [PMID: 34729039 PMCID: PMC8547182 DOI: 10.5114/wo.2021.109727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 09/13/2021] [Indexed: 11/24/2022] Open
Abstract
Aim of the study The aim of the study was to analyze three single nucleotide polymorphisms – rs1520220, rs2946834, rs6219 – of the IGF-1 gene in the context of breast mammographic density. Material and methods The research material included 202 samples of the peripheral blood of women with increased mammographic breast density and 238 samples of the epithelium from the oral mucosa of women without diagnosed pathological changes of the breast and with no family history of breast and/or ovarian cancer. The real-time polymerase chain reaction method was applied for analysis of polymorphisms. Results rs1520220 polymorphism was associated with increased mammographic density of the breasts. The presence of the CC genotype in the IGF-1 gene increased the risk of developing higher breast density visible in mammography by 2.43-fold. CC homozygotes (rs1520220) correlated with higher Breast Imaging-Reporting and Data System scale (3 vs. 4 and 5) (OR = 5.6; 95% CI: 1.82–16.3, p = 0.001). In the present study no relationship was detected between rs6219 and rs2946834 polymorphism and mammographic breast density. Conclusions The results suggest that the rs1520220 polymorphism of the IGF-1 gene plays an important role in the occurrence of increased mammographic breast density.
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Single nucleotide polymorphisms of insulin-like growth factor gene and mammographic breast density. MENOPAUSE REVIEW 2021; 19:160-170. [PMID: 33488326 PMCID: PMC7812538 DOI: 10.5114/pm.2020.101945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 10/14/2020] [Indexed: 11/18/2022]
Abstract
Aim of the study To analyze six single nucleotide polymorphisms (SNPs): rs1520220, rs2945834, rs5747694, rs6214, rs6219, rs5742678. An attempt was made to assess the significance of the above IGF-1 gene polymorphisms as prognostic and predictive factors in Polish women with diagnosed increased breast mammographic density. Material and methods The study included women diagnosed with an increased breast mammographic density (n = 98), breast cancer (n = 135) and women as a control group (n = 60). The method used to detect polymorphisms in the IGF-1 gene was the analysis of single-stranded DNA conformation polymorphism (SSCP-PCR) and Sanger’s sequencing. Results In the case of rs1520220 polymorphism, the genotype CC was found to increase the risk of breast cancer (OR = 2.6 95% CI 1.01-6.5, p = 0.04). Analysis of the rs2945834 polymorphism revealed that the occurrence of the G allele reduced the risk of breast cancer, while the occurrence of the A allele increased the risk of disease almost twice (OR = 0.55 95% CI). Among women who are heterozygous in terms of rs5747694 polymorphism (TG), the risk of breast cancer is twice as high as in the control group. The SNPs in the study group did not correlate with mammographic breast density. Conclusions The results obtained in the course of the analysis indicate that polymorphisms rs1520220, rs2946834, rs5747694 gene IGF-1 are associated with the occurrence of breast cancer but not with increased mammographic density. Summing up, the association between the polymorphisms of IGF-1 and the risk of developing breast cancer is independent of mammographic density.
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Relationships of physical and breast cancer phenotypes with three single-nucleotide polymorphisms (rs2046210, rs3757318, and rs3803662) associated with breast cancer risk in Japanese women. Breast Cancer 2020; 28:478-487. [PMID: 33185851 DOI: 10.1007/s12282-020-01185-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 11/02/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Recent genome-wide association studies have shown that many single-nucleotide polymorphisms (SNPs) are associated with breast cancer risk. However, it is often unclear how these SNPs are related to breast cancer. Analysis of associations between SNPs and phenotypes may be important for determining mechanisms of action, including carcinogenesis. METHODS In previous case-control studies, we found three SNPs (rs2046210, rs3757318, and rs3573318) associated with breast cancer risk in Japanese women. Among these SNPs, two (rs2046210 and rs3757318) are located at 6q25.1, in proximity to the estrogen receptor 1 gene (ESR1). Using data from these studies, we examined associations between factors related to breast cancer risk, such as height, weight, and breast density, and the three SNPs in cases and controls. We also investigated whether the SNPs correlated with breast cancer features, such as estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor type-2 (HER2) status, and clinical stage. RESULTS There was a significant difference in mean height between risk and non-risk allele carriers for rs2046210 (156.0 ± 5.8 vs. 154.3 ± 5.5 cm, p = 0.002), and rs3757318 (155.8 ± 5.7 vs. 154.7 ± 5.6 cm, p = 0.035) in cases, but no significant associations between height and these SNPs in controls. There was also a significant difference in breast density between risk and non-risk allele carriers for rs2046210 (p = 0.040) and rs3757318 (p = 0.044) in cases. rs2046210 and rs3757318 risk allele carriers tended to have higher breast density in all subjects and in controls. In cases, rs3757318 risk allele carriers were also significantly more likely to be ER-negative compared to non-risk allele carriers (ER-positive rate: 77% vs. 84%, p = 0.036). CONCLUSIONS SNPs rs2046210 and rs3757318, which are associated with breast cancer risk in Japanese women, were significantly associated with height and high breast density, and this association was particularly strong in those with breast cancer. These findings suggest that SNPs in the ESR1 gene region affect phenotypes such as height and breast density.
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Kallionpää RA, Uusitalo E, Peltonen J. Association of Catechol-O-methyltransferase polymorphism Val158Met and mammographic density: A meta-analysis. Gene 2017; 624:34-42. [PMID: 28473194 DOI: 10.1016/j.gene.2017.04.049] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Accepted: 04/30/2017] [Indexed: 10/19/2022]
Abstract
OBJECTIVES The Val158Met polymorphism in catechol-O-methyltransferase (COMT) enzyme reduces the methylation of catechol estrogens, which may affect mammographic density. High mammographic density is a known risk factor of breast cancer. Our aim was to perform meta-analysis of the effect of COMT Val158Met polymorphism on mammographic density. METHODS Original studies reporting data on mammographic density, stratified by the presence of COMT Val158Met polymorphism, were identified and combined using genetic models Met/Val vs. Val/Val, Met/Met vs. Val/Val, Val/Met+Met/Met vs. Val/Val (dominant model) and Met/Met vs. Val/Met+Val/Val (recessive model). Subgroup analyses by breast cancer status, menopausal status and use of hormone replacement therapy (HRT) were also performed. RESULTS Eight studies were included in the meta-analysis. The overall effect in percent mammographic density was -1.41 (CI -2.86 to 0.05; P=0.06) in the recessive model. Exclusion of breast cancer patients increased the effect size to -1.93 (CI -3.49 to -0.37; P=0.02). The results suggested opposite effect of COMT Val158Met for postmenopausal users of HRT versus premenopausal women or postmenopausal non-users of HRT. CONCLUSIONS COMT Val158Met polymorphism may be associated with mammographic density at least in healthy women. Menopausal status and HRT should be taken into account in future studies to avoid masking of the underlying effects.
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Affiliation(s)
- Roope A Kallionpää
- Department of Cell Biology and Anatomy, University of Turku, Kiinamyllynkatu 10, 20520 Turku, Finland.
| | - Elina Uusitalo
- Department of Cell Biology and Anatomy, University of Turku, Kiinamyllynkatu 10, 20520 Turku, Finland
| | - Juha Peltonen
- Department of Cell Biology and Anatomy, University of Turku, Kiinamyllynkatu 10, 20520 Turku, Finland
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McDonald JA, Michels KB, Cohn BA, Flom JD, Tehranifar P, Terry MB. Alcohol intake from early adulthood to midlife and mammographic density. Cancer Causes Control 2016; 27:493-502. [PMID: 26830901 DOI: 10.1007/s10552-016-0723-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Accepted: 01/16/2016] [Indexed: 12/13/2022]
Abstract
PURPOSE Moderate alcohol consumption (15 g/day) has been consistently associated with increased breast cancer risk; however, the association between alcohol and mammographic density, a strong marker of breast cancer risk, has been less consistent. Less is known about the effect of patterns of alcohol intake across the lifecourse. METHODS Using the Early Determinants of Mammographic Density study, an adult follow-up of women born in two US birth cohorts (n = 697; Collaborative Perinatal Project in Boston and Providence sites and the Childhood Health and Development Studies in California), we examined the association between alcohol intake in early adulthood (ages 20-29 years) and at time of interview and mammographic density (percent density and total dense area). We report the difference between nondrinkers and three levels of alcohol intake. We considered confounding by age at mammogram, body mass index, geographic site, race/ethnicity, and reproductive characteristics. RESULTS Seventy-nine percent of women reported ever consuming alcohol. Compared to nondrinkers in early adulthood, we observed an inverse association between >7 servings/week and percent density in fully adjusted models (β = -5.1, 95% CI -8.7, -1.5; p for trend = <0.01). Associations with dense area were inverse for the highest category of drinking in early adulthood but not statistically significant (p for trend = 0.15). Compared to noncurrent drinkers, the association for current intake of >7 servings/week and percent density was also inverse (β = -3.1, 95% CI -7.0, 0.8; p for trend = 0.01). In contrast, moderate alcohol intake (>0-≤7 servings/week) in either time period was positively associated with dense area; but associations were not statistically significant in fully adjusted models. CONCLUSIONS Our study does not lend support to the hypothesis that the positive association between alcohol intake and breast cancer risk is through increasing mammographic density.
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Affiliation(s)
- Jasmine A McDonald
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA.
| | - Karin B Michels
- Obstetrics and Gynecology, Epidemiology Center Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA.,Division of Cancer Epidemiology, Comprehensive Cancer Center Freiburg, Freiburg University, Freiburg, Germany
| | - Barbara A Cohn
- Public Health Institute, Child Health and Development Studies, Berkeley, CA, USA
| | - Julie D Flom
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
| | - Parisa Tehranifar
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
| | - Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA.,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA.,The Imprints Center for Genetic and Environmental Lifecourse Studies, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
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Bodelon C, Heaphy CM, Meeker AK, Geller B, Vacek PM, Weaver DL, Chicoine RE, Shepherd JA, Mahmoudzadeh AP, Patel DA, Brinton LA, Sherman ME, Gierach GL. Leukocyte telomere length and its association with mammographic density and proliferative diagnosis among women undergoing diagnostic image-guided breast biopsy. BMC Cancer 2015; 15:823. [PMID: 26519084 PMCID: PMC4628256 DOI: 10.1186/s12885-015-1860-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2015] [Accepted: 10/27/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Elevated mammographic density (MD) is a strong breast cancer risk factor but the mechanisms underlying the association are poorly understood. High MD and breast cancer risk may reflect cumulative exposures to factors that promote epithelial cell division. One marker of cellular replicative history is telomere length, but its association with MD is unknown. We investigated the relation of telomere length, a marker of cellular replicative history, with MD and biopsy diagnosis. METHODS One hundred and ninety-five women, ages 40-65, were clinically referred for image-guided breast biopsies at an academic facility in Vermont. Relative peripheral blood leukocyte telomere length (LTL) was measured using quantitative polymerase chain reaction. MD volume was quantified in cranio-caudal views of the breast contralateral to the primary diagnosis in digital mammograms using a breast density phantom, while MD area (cm(2)) was measured using thresholding software. Associations between log-transformed LTL and continuous MD measurements (volume and area) were evaluated using linear regression models adjusted for age and body mass index. Analyses were stratified by biopsy diagnosis: proliferative (hyperplasia, in-situ or invasive carcinoma) or non-proliferative (benign or other non-proliferative benign diagnoses). RESULTS Mean relative LTL in women with proliferative disease (n = 141) was 1.6 (SD = 0.9) vs. 1.2 (SD = 0.6) in those with non-proliferative diagnoses (n = 54) (P = 0.002). Mean percent MD volume did not differ by diagnosis (P = 0.69). LTL was not associated with MD in women with proliferative (P = 0.89) or non-proliferative (P = 0.48) diagnoses. However, LTL was associated with a significant increased risk of proliferative diagnosis (adjusted OR = 2.46, 95% CI: 1.47, 4.42). CONCLUSIONS Our analysis of LTL did not find an association with MD. However, our findings suggest that LTL may be a marker of risk for proliferative pathology among women referred for biopsy based on breast imaging.
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Affiliation(s)
- Clara Bodelon
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
- Division of Cancer Epidemiology and Genetics, 9609 Medical Center Dr., Rm 7-E236, Bethesda, MD, 20892, USA.
| | - Christopher M Heaphy
- Department of Pathology, John Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Alan K Meeker
- Departments of Pathology, Oncology and Urology, John Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Berta Geller
- Department of Health Promotion Research, University of Vermont College of Medicine and Vermont Cancer Center, Burlington, VT, USA.
| | - Pamela M Vacek
- Department of Biostatistics, University of Vermont College of Medicine and Vermont Cancer Center, Burlington, VT, USA
| | - Donald L Weaver
- Department of Pathology, University of Vermont College of Medicine and Vermont Cancer Center, Burlington, VT, USA.
| | - Rachael E Chicoine
- Office of Health Promotion Research, University of Vermont College of Medicine and Vermont Cancer Center, Burlington, VT, USA.
| | - John A Shepherd
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA.
| | - Amir Pasha Mahmoudzadeh
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA.
| | - Deesha A Patel
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
| | - Louise A Brinton
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
| | - Mark E Sherman
- Breast and Gynecologic Cancer Research Group, Division of Cancer Prevention, National Cancer Institute, Rockville, MD, USA.
| | - Gretchen L Gierach
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
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Keller BM, McCarthy AM, Chen J, Armstrong K, Conant EF, Domchek SM, Kontos D. Associations between breast density and a panel of single nucleotide polymorphisms linked to breast cancer risk: a cohort study with digital mammography. BMC Cancer 2015; 15:143. [PMID: 25881232 PMCID: PMC4365961 DOI: 10.1186/s12885-015-1159-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2014] [Accepted: 03/04/2015] [Indexed: 12/16/2022] Open
Abstract
Background Breast density and single-nucleotide polymorphisms (SNPs) have both been associated with breast cancer risk. To determine the extent to which these two breast cancer risk factors are associated, we investigate the association between a panel of validated SNPs related to breast cancer and quantitative measures of mammographic density in a cohort of Caucasian and African-American women. Methods In this IRB-approved, HIPAA-compliant study, we analyzed a screening population of 639 women (250 African American and 389 Caucasian) who were tested with a validated panel assay of 12 SNPs previously associated to breast cancer risk. Each woman underwent digital mammography as part of routine screening and all were interpreted as negative. Both absolute and percent estimates of area and volumetric density were quantified on a per-woman basis using validated software. Associations between the number of risk alleles in each SNP and the density measures were assessed through a race-stratified linear regression analysis, adjusted for age, BMI, and Gail lifetime risk. Results The majority of SNPs were not found to be associated with any measure of breast density. SNP rs3817198 (in LSP1) was significantly associated with both absolute area (p = 0.004) and volumetric (p = 0.019) breast density in Caucasian women. In African-American women, SNPs rs3803662 (in TNRC9/TOX3) and rs4973768 (in NEK10) were significantly associated with absolute (p = 0.042) and percent (p = 0.028) volume density respectively. Conclusions The majority of SNPs investigated in our study were not found to be significantly associated with breast density, even when accounting for age, BMI, and Gail risk, suggesting that these two different risk factors contain potentially independent information regarding a woman’s risk to develop breast cancer. Additionally, the few statistically significant associations between breast density and SNPs were different for Caucasian versus African American women. Larger prospective studies are warranted to validate our findings and determine potential implications for breast cancer risk assessment. Electronic supplementary material The online version of this article (doi:10.1186/s12885-015-1159-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Brad M Keller
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3600 Market St. Ste 360, Philadelphia, PA, 19104, USA.
| | - Anne Marie McCarthy
- Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
| | - Jinbo Chen
- Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
| | - Katrina Armstrong
- Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
| | - Emily F Conant
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3600 Market St. Ste 360, Philadelphia, PA, 19104, USA.
| | - Susan M Domchek
- Abramson Cancer Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
| | - Despina Kontos
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3600 Market St. Ste 360, Philadelphia, PA, 19104, USA.
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Liu J, Page D, Peissig P, McCarty C, Onitilo AA, Trentham-Dietz A, Burnside E. New genetic variants improve personalized breast cancer diagnosis. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE PROCEEDINGS. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE 2014; 2014:83-9. [PMID: 25717406 PMCID: PMC4333695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Recent large-scale genome-wide association studies (GWAS) have identified a number of new genetic variants associated with breast cancer. However, the degree to which these genetic variants improve breast cancer diagnosis in concert with mammography remains unknown. We conducted a case-control study and collected mammography features and 77 genetic variants which reflect the state of the art GWAS findings on breast cancer. A naïve Bayes model was developed on the mammography features and these genetic variants. We observed that the incorporation of the genetic variants significantly improved breast cancer diagnosis based on mammographic findings.
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Affiliation(s)
- Jie Liu
- University of Wisconsin, Madison, WI, US
| | - David Page
- University of Wisconsin, Madison, WI, US
| | - Peggy Peissig
- Marshfield Clinic Research Foundation, Marshfield, WI, US
| | | | - Adedayo A Onitilo
- Marshfield Clinic Research Foundation, Marshfield, WI, US ; Department of Hematology/Oncology, Marshfield Clinic Weston Center, Weston, WI, US ; School of Population Health, University of Queensland, Brisbane, Australia
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O'Flynn EAM, Wilson RM, Allen SD, Locke I, Scurr E, deSouza NM. Diffusion-weighted imaging of the high-risk breast: Apparent diffusion coefficient values and their relationship to breast density. J Magn Reson Imaging 2014; 39:805-11. [PMID: 24038529 DOI: 10.1002/jmri.24243] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2012] [Accepted: 05/03/2013] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To document the apparent diffusion coefficient (ADC) of fibroglandular breast tissue in women at high-risk of developing breast cancer and investigate the relationship between ADC and breast density. MATERIALS AND METHODS Local research ethics approval was obtained. A total of 33 high-risk women including 17 BRCA1/2 mutation carriers (mean age, 43 years) and 16 women postmantle irradiation (mean age 40 years) underwent diffusion-weighted MRI between days 6 and 16 of their menstrual cycle. ADC histograms from a region of interest in fibroglandular tissue and mammographic breast density measurements were obtained. Mean, percentile ADC values (10th, 25th, 50th, 75th, 90th) and skew were compared for the two groups; ADC and mammographic breast density were correlated. RESULTS Mean ADC values (×10(-6) mm(2) /s) were 2017 ± 197 in postmantle irradiated women and 1827 ± 289 in BRCA1/2 mutation carriers (P = 0.035) with significant differences at all percentiles (P < 0.0001) but not skew (P = 0.44). ADC values showed weak positive correlation with mammographic breast density in BRCA1/2 mutation carriers (r = 0.51, P = 0.043) but not in postmantle radiotherapy patients (r = 0.49, P = 0.13). CONCLUSION Higher ADC values seen in fibroglandular tissue postmantle irradiation compared with BRCA1/2 mutation carriers has potential to improve tumor detection in these patients. Lack of correlation between ADC and breast density postmantle irradiation may be a result of microstructural changes.
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Affiliation(s)
- Elizabeth A M O'Flynn
- Clinical Magnetic Resonance Group, Cancer Research UK and EPSRC Cancer Imaging Centre, Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, United Kingdom
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Ong J, Salomon J, te Morsche RHM, Roelofs HMJ, Witteman BJM, Dura P, Lacko M, Peters WHM. Polymorphisms in the insulin-like growth factor axis are associated with gastrointestinal cancer. PLoS One 2014; 9:e90916. [PMID: 24608110 PMCID: PMC3946608 DOI: 10.1371/journal.pone.0090916] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2013] [Accepted: 02/06/2014] [Indexed: 12/31/2022] Open
Abstract
INTRODUCTION Numerous factors influence the development of gastrointestinal (GI) cancer. The insulin-like growth factor (IGF) axis plays a role in embryonic and postnatal growth and tissue repair. Elevated levels of IGFs, low levels of IGF binding proteins (IGFBPs) and over-expression of IGF receptor (IGFR-I) were associated with several stages of cancer. Here, the prevalence of the single nucleotide polymorphisms (SNPs) rs6214 in the IGF type I (IGF-I) gene and rs6898743 in the growth hormone receptor (GHR) gene in patients with GI cancer and controls was studied. MATERIALS & METHODS In this Dutch case-control study, DNA isolated from blood of 1,457 GI cancer patients; 438 patients with head and neck cancer (HNC), 475 with esophageal cancer (EC) and 544 with colorectal cancer (CRC) and 1,457 matched controls, was used to determine the rs6214 and rs6898743 genotypes by polymerase chain reaction. The association between these SNPs and GI cancer, HNC, esophageal adenocarcinoma (EAC), esophageal squamous-cell carcinoma (ESCC) and proximal or distal CRC was studied. Odds ratios (ORs) with 95% confidence interval (95% CI) were calculated via unconditional logistic regression. RESULTS Overall for GI cancer, the ORs for SNPs rs6214 and rs6898743 were approximately 1.0 (p-value>0.05), using the most common genotypes GG as reference. An OR of 1.54 (95% CI, 1.05-2.27) was found for EC for genotype AA of rs6214. The ORs for EAC were 1.45 (95% CI, 1.04-2.01) and 1.71 (95% CI, 1.10-2.68), for genotypes GA and AA, respectively. Genotype GC of rs6898743 showed an OR of 0.47 (95% CI, 0.26-0.86) for ESCC. CONCLUSION The A allele of SNP rs6214 in the IGF-I gene was associated with EAC, and with HNC in women. The GC genotype of rs6898743 in the GHR gene was negatively associated with ESCC.
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Affiliation(s)
- Jennie Ong
- Department of Gastroenterology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Jody Salomon
- Department of Gastroenterology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Rene H. M. te Morsche
- Department of Gastroenterology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Hennie M. J. Roelofs
- Department of Gastroenterology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Ben J. M. Witteman
- Department of Gastroenterology, Hospital Gelderse Vallei, Ede, the Netherlands
| | - Polat Dura
- Department of Gastroenterology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Martin Lacko
- Department of Otorhinolaryngology, Head and Neck Surgery, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Wilbert H. M. Peters
- Department of Gastroenterology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
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Liu J, Page D, Nassif H, Shavlik J, Peissig P, McCarty C, Onitilo AA, Burnside E. Genetic variants improve breast cancer risk prediction on mammograms. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2013; 2013:876-885. [PMID: 24551380 PMCID: PMC3900221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Several recent genome-wide association studies have identified genetic variants associated with breast cancer. However, how much these genetic variants may help advance breast cancer risk prediction based on other clinical features, like mammographic findings, is unknown. We conducted a retrospective case-control study, collecting mammographic findings and high-frequency/low-penetrance genetic variants from an existing personalized medicine data repository. A Bayesian network was developed using Tree Augmented Naive Bayes (TAN) by training on the mammographic findings, with and without the 22 genetic variants collected. We analyzed the predictive performance using the area under the ROC curve, and found that the genetic variants significantly improved breast cancer risk prediction on mammograms. We also identified the interaction effect between the genetic variants and collected mammographic findings in an attempt to link genotype to mammographic phenotype to better understand disease patterns, mechanisms, and/or natural history.
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Affiliation(s)
- Jie Liu
- University of Wisconsin, Madison, WI, USA
| | - David Page
- University of Wisconsin, Madison, WI, USA
| | | | | | - Peggy Peissig
- Marshfield Clinic Research Foundation, Marshfield, WI, USA
| | | | - Adedayo A Onitilo
- Department of Hematology/Oncology, Marshfield Clinic Weston Center, Weston, WI, USA ; Marshfield Clinic Research Foundation, Marshfield, WI, USA ; School of Population Health, University of Queensland, Brisbane, Australia
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Gierach GL, Yang XR, Figueroa JD, Sherman ME. Emerging Concepts in Breast Cancer Risk Prediction. CURRENT OBSTETRICS AND GYNECOLOGY REPORTS 2012; 2:43-52. [DOI: 10.1007/s13669-012-0034-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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Abstract
We outline an integrative approach to extend the boundaries of molecular cancer epidemiology by integrating modern and rapidly evolving "omics" technologies into state-of-the-art molecular epidemiology. In this way, one can comprehensively explore the mechanistic underpinnings of epidemiologic observations in cancer risk and outcome. We highlight the exciting opportunities to collaborate across large observational studies and to forge new interdisciplinary collaborative ventures.
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Affiliation(s)
- Margaret R Spitz
- The Dan L Duncan Cancer Center, Baylor College of Medicine, Houston, Texas 77030, USA.
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Ellingjord-Dale M, Lee E, Couto E, Ozhand A, Qureshi S, Hofvind S, Van Den Berg DJ, Akslen LA, Grotmol T, Ursin G. Polymorphisms in hormone metabolism and growth factor genes and mammographic density in Norwegian postmenopausal hormone therapy users and non-users. Breast Cancer Res 2012; 14:R135. [PMID: 23095343 PMCID: PMC4053113 DOI: 10.1186/bcr3337] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2012] [Accepted: 08/30/2012] [Indexed: 01/10/2023] Open
Abstract
INTRODUCTION Mammographic density (MD) is one of the strongest known breast cancer risk factors. Estrogen and progestin therapy (EPT) has been associated with increases in MD. Dense breast tissue is characterized by increased stromal tissue and (to a lesser degree) increased numbers of breast epithelial cells. It is possible that genetic factors modify the association between EPT and MD, and that certain genetic variants are particularly important in determining MD in hormone users. We evaluated the association between MD and 340 tagging single nucleotide polymorphisms (SNPs) from about 30 candidate genes in hormone metabolism/growth factor pathways among women who participated in the Norwegian Breast Cancer Screening Program (NBCSP) in 2004. METHODS We assessed MD on 2,036 postmenopausal women aged 50 to 69 years using a computer-assisted method (Madena, University of Southern California) in a cross-sectional study. We used linear regression to determine the association between each SNP and MD, adjusting for potential confounders. The postmenopausal women were stratified into HT users (EPT and estrogen-only) and non-users (never HT). RESULTS For current EPT users, there was an association between a variant in the prolactin gene (PRL; rs10946545) and MD (dominant model, Bonferroni-adjusted P (Pb) = 0.0144). This association remained statistically significant among current users of norethisterone acetate (NETA)-based EPT, a regimen common in Nordic countries. Among current estrogen-only users (ET), there was an association between rs4670813 in the cytochrome P450 gene (CYP1B1) and MD (dominant model, Pb = 0.0396). In never HT users, rs769177 in the tumor necrosis factor (TNF) gene and rs1968752 in the region of the sulfotransferase gene (SULT1A1/SULT1A2), were significantly associated with MD (Pb = 0.0202; Pb = 0.0349). CONCLUSIONS We found some evidence that variants in the PRL gene were associated with MD in current EPT and NETA users. In never HT users, variants in the TNF and SULT1A1/SULT1A2 genes were significantly associated with MD. These findings may suggest that several genes in the hormone metabolism and growth factor pathways are implicated in determining MD.
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Fuhrman BJ, Brinton LA, Pfeiffer RM, Xu X, Veenstra TD, Teter BE, Byrne C, Dallal CM, Barba M, Muti PC, Gierach GL. Estrogen metabolism and mammographic density in postmenopausal women: a cross-sectional study. Cancer Epidemiol Biomarkers Prev 2012; 21:1582-91. [PMID: 22736791 PMCID: PMC3436977 DOI: 10.1158/1055-9965.epi-12-0247] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Prospective studies have consistently found that postmenopausal breast cancer risk increases with circulating estrogens; however, findings from studies of estrogens and mammographic density (MD), an intermediate marker of breast cancer risk, have been inconsistent. We investigated the cross-sectional associations of urinary estrogens, and their 2-, 4-, and 16-hydroxylated metabolites with MD. METHODS Postmenopausal women without breast cancer (n = 194), ages 48 to 82 years, and reporting no current menopausal hormone therapy use were enrolled at a clinic in Western NY in 2005. Urinary estrogens and estrogen metabolites were measured using mass spectrometry. Percent MD and dense area (cm(2)) were measured using computer-assisted analyses of digitized films. Linear regression models were used to estimate associations of log-transformed estrogen measures with MD while adjusting for age, body mass index (BMI), parity, and past hormone therapy use. RESULTS Urinary concentrations of most individual estrogens and metabolites were not associated with MD; however, across the interdecile range of the ratio of parent estrogens (estrone and estradiol) to their metabolites, MD increased by 6.8 percentage points (P = 0.02) and dense area increased by 10.3 cm(2) (P = 0.03). Across the interdecile ranges of the ratios of 2-, 4-, and 16-hydroxylation pathways to the parent estrogens, MD declined by 6.2 (P = 0.03), 6.4 (P = 0.04), and 5.7 (P = 0.05) percentage points, respectively. All associations remained apparent in models without adjustment for BMI. CONCLUSION In this study of postmenopausal women, less extensive hydroxylation of parent estrogens was associated with higher MD. IMPACT Hydroxylation of estrogens may modulate postmenopausal breast cancer risk through a pathway involving MD.
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Affiliation(s)
- Barbara J Fuhrman
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD 20892, USA.
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Conklin MW, Keely PJ. Why the stroma matters in breast cancer: insights into breast cancer patient outcomes through the examination of stromal biomarkers. Cell Adh Migr 2012; 6:249-60. [PMID: 22568982 PMCID: PMC3427239 DOI: 10.4161/cam.20567] [Citation(s) in RCA: 165] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Survival and recurrence rates in breast cancer are variable for common diagnoses, and therefore the biological underpinnings of the disease that determine those outcomes are yet to be fully understood. As a result, translational medicine is one of the fastest growing arenas of study in tumor biology. With advancements in genetic and imaging techniques, archived biopsies can be examined for purposes other than diagnosis. There is a great deal of evidence that points to the stroma as the major regulator of tumor progression following the initial stages of tumor formation, and the stroma may also contribute to risk factors determining tumor formation. Therefore, aspects of stromal biology are well-suited to be a focus for studies of patient outcome, where statistical differences in survival among patients provide evidence as to whether that stromal component is a signpost for tumor progression. In this review we summarize the latest research done where breast cancer patient survival was correlated with aspects of stromal biology, which have been put into four categories: reorganization of the extracellular matrix (ECM) to promote invasion, changes in the expression of stromal cell types, changes in stromal gene expression, and changes in cell biology signaling cascades to and from the stroma.
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Affiliation(s)
- Matthew W Conklin
- Department of Cell and Regenerative Biology, the Laboratory for Cell and Molecular Biology, Laboratory for Optical and Computational Instrumentation (LOCI), UW Carbone Cancer Center, University of Wisconsin, Madison, WI, USA
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Varghese JS, Thompson DJ, Michailidou K, Lindström S, Turnbull C, Brown J, Leyland J, Warren RML, Luben RN, Loos RJ, Wareham NJ, Rommens J, Paterson AD, Martin LJ, Vachon CM, Scott CG, Atkinson EJ, Couch FJ, Apicella C, Southey MC, Stone J, Li J, Eriksson L, Czene K, Boyd NF, Hall P, Hopper JL, Tamimi RM, Rahman N, Easton DF. Mammographic breast density and breast cancer: evidence of a shared genetic basis. Cancer Res 2012; 72:1478-84. [PMID: 22266113 PMCID: PMC3378688 DOI: 10.1158/0008-5472.can-11-3295] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3,628 breast cancer cases and 5,190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of single-nucleotide polymorphisms (SNP) were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using 10 different cutoff points for the most significant density SNPs (1%-10% representing 5,222-50,899 SNPs). Permutation analysis was also conducted across all 10 cutoff points. The association between risk score and breast cancer was significant for all cutoff points from 3% to 10% of top density SNPs, being most significant for the 6% (2-sided P = 0.002) to 10% (P = 0.001) cutoff points (overall permutation P = 0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR = 1.31; 95% confidence interval (CI), 1.08-1.59] compared with women in the bottom 10%. Together, our results show that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants.
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Affiliation(s)
- Jajini S Varghese
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Deborah J Thompson
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Kyriaki Michailidou
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Sara Lindström
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
| | - Clare Turnbull
- Section of Cancer Genetics, The Institute of Cancer Research, Sutton, Surrey, UK
| | - Judith Brown
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jean Leyland
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Ruth ML Warren
- Department of Radiology, University of Cambridge, Addenbrooke’s NHS Foundation Trust Cambridge, UK
| | - Robert N Luben
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Ruth J Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Johanna Rommens
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Andrew D Paterson
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
- Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Lisa J Martin
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada
| | - Celine M Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | | | - Fergus J Couch
- Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Carmel Apicella
- Centre for M.E.G.A. Epidemiology, Melbourne School of Population Health, The University of Melbourne, Melbourne, Australia
| | - Melissa C Southey
- Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Melbourne, Australia
| | - Jennifer Stone
- Centre for M.E.G.A. Epidemiology, Melbourne School of Population Health, The University of Melbourne, Melbourne, Australia
| | - Jingmei Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Human Genetics, Genome Institute of Singapore, Singapore
| | - Louise Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Norman F Boyd
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - John L Hopper
- Centre for M.E.G.A. Epidemiology, Melbourne School of Population Health, The University of Melbourne, Melbourne, Australia
| | - Rulla M Tamimi
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
- Channing Laboratory, Brigham and Women’s Hospital, Boston, MA, USA
| | - Nazneen Rahman
- Section of Cancer Genetics, The Institute of Cancer Research, Sutton, Surrey, UK
| | - Douglas F Easton
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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Vachon CM, Li J, Scott CG, Hall P, Czene K, Wang X, Liu J, Fredericksen ZS, Rider DN, Wu FF, Olson JE, Cunningham JM, Stevens KN, Sellers TA, Pankratz SV, Couch FJ. No evidence for association of inherited variation in genes involved in mitosis and percent mammographic density. Breast Cancer Res 2012; 14:R7. [PMID: 22226020 PMCID: PMC3496122 DOI: 10.1186/bcr3088] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2011] [Revised: 12/01/2011] [Accepted: 01/07/2012] [Indexed: 01/18/2023] Open
Abstract
Introduction Increased mammographic breast density is one of the strongest risk factors for breast cancer. While two-thirds of the variation in mammographic density appears to be genetically influenced, few variants have been identified. We examined the association of inherited variation in genes from pathways that mediate cell division with percent mammographic density (PMD) adjusted for age, body mass index (BMI) and postmenopausal hormones, in two studies of healthy postmenopausal women. Methods We investigated 2,058 single nucleotide polymorphisms (SNPs) in 378 genes involved in regulation of mitosis for associations with adjusted PMD among 484 unaffected postmenopausal controls (without breast cancer) from the Mayo Clinic Breast Cancer Study (MCBCS) and replicated the findings in postmenopausal controls (n = 726) from the Singapore and Sweden Breast Cancer Study (SASBAC) study. PMD was assessed in both studies by a computer-thresholding method (Cumulus) and linear regression approaches were used to assess the association of SNPs and PMD, adjusted for age, BMI and postmenopausal hormones. A P-value threshold of 4.2 × 10-5 based on a Bonferroni correction of effective number of independent tests was used for statistical significance. Further, a pathway-level analysis was conducted of all 378 genes using the self-contained gene-set analysis method GLOSSI. Results A variant in PRPF4, rs10733604, was significantly associated with adjusted PMD in the MCBCS (P = 2.7 × 10-7), otherwise, no single SNP was associated with PMD. Additionally, the pathway analysis provided no evidence of enrichment in the number of associations observed between SNPs in the mitotic genes and PMD (P = 0.60). We evaluated rs10733604 (PRPF4), and 73 other SNPs at P < 0.05 from 51 genes in the SASBAC study. There was no evidence of an association of rs10733604 (PRPF4) with adjusted PMD in SASBAC (P = 0.23). There were, however, consistent associations (P < 0.05) of variants at the putative locus, LOC375190, Aurora B kinase (AURKB), and Mini-chromosome maintenance complex component 3 (MCM3) with adjusted PMD, although these were not statistically significant. Conclusions Our findings do not support a role of inherited variation in genes involved in regulation of cell division and adjusted percent mammographic density in postmenopausal women.
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Affiliation(s)
- Celine M Vachon
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.
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Sieuwerts AM, De Napoli G, van Galen A, Kloosterboer HJ, de Weerd V, Zhang H, Martens JWM, Foekens JA, De Geyter C. Hormone replacement therapy dependent changes in breast cancer-related gene expression in breast tissue of healthy postmenopausal women. Mol Oncol 2011; 5:504-16. [PMID: 21956102 DOI: 10.1016/j.molonc.2011.09.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2011] [Revised: 09/10/2011] [Accepted: 09/12/2011] [Indexed: 01/18/2023] Open
Abstract
Risk assessment of future breast cancer risk through exposure to sex steroids currently relies on clinical scorings such as mammographic density. Knowledge about the gene expression patterns in existing breast cancer tumors may be used to identify risk factors in the breast tissue of women still free of cancer. The differential effects of estradiol, estradiol together with gestagens, or tibolone on breast cancer-related gene expression in normal breast tissue samples taken from postmenopausal women may be used to identify gene expression profiles associated with a higher breast cancer risk. Breast tissue samples were taken from 33 healthy postmenopausal women both before and after a six month treatment with either 2mg micronized estradiol [E2], 2mg micronized estradiol and 1mg norethisterone acetate [E2+NETA], 2.5mg tibolone [T] or [no HRT]. Except for [E2], which was only given to women after hysterectomy, the allocation to each of the three groups was randomized. The expression of 102 mRNAs and 46 microRNAs putatively involved in breast cancer was prospectively determined in the biopsies of 6 women receiving [no HRT], 5 women receiving [E2], 5 women receiving [E2+NETA], and 6 receiving [T]. Using epithelial and endothelial markers genes, non-representative biopsies from 11 women were eliminated. Treatment of postmenopausal women with [E2+NETA] resulted in the highest number of differentially (p<0.05) regulated genes (16.2%) compared to baseline, followed by [E2] (10.1%) and [T] (4.7%). Among genes that were significantly down-regulated by [E2+NETA] ranked estrogen-receptor-1 (ESR1, p=0.019) and androgen receptor (AR, p=0.019), whereas CYP1B1, a gene encoding an estrogen-metabolizing enzyme, was significantly up-regulated (p=0.016). Mammary cells triggered by [E2+NETA] and [E2] adjust for steroidogenic up-regulation through down-regulation of the estrogen-receptor pathway. In this prospective study, prolonged administration of [E2+NETA] and to a lesser extent of [E2] but not [T] were associated in otherwise healthy breast tissue with a change in the expression of genes putatively involved in breast cancer. Our data suggest that normal mammary cells triggered by [E2+NETA] adjust for steroidogenic up-regulation through down-regulation of the estrogen-receptor pathway. This feasibility study provides the basis for whole genome analyses to identify novel markers involved in increased breast cancer risk.
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Affiliation(s)
- Anieta M Sieuwerts
- Department of Medical Oncology, Josephine Nefkens Institute, Cancer Genomics Centre, Erasmus Medical Center, Rotterdam, Netherlands
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Yoshimoto N, Nishiyama T, Toyama T, Takahashi S, Shiraki N, Sugiura H, Endo Y, Iwasa M, Fujii Y, Yamashita H. Genetic and environmental predictors, endogenous hormones and growth factors, and risk of estrogen receptor-positive breast cancer in Japanese women. Cancer Sci 2011; 102:2065-72. [PMID: 21790896 DOI: 10.1111/j.1349-7006.2011.02047.x] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
The incidence of breast cancer in Japanese women has doubled in all age groups over the past two decades. We have recently shown that this marked increase is mostly due to an increase in the estrogen receptor (ER)-positive subtype. It is necessary to establish risk factors capable of predicting the risk of ER-positive breast cancer that will enable the efficient selection of candidates for preventive therapy. We analyzed genetic factors, including 14 single nucleotide polymorphisms (SNPs), environmental risk factors (body mass index, age at menarche, pregnancy, age at first birth, breastfeeding, family history of breast cancer, age at menopause, use of hormone replacement therapy, alcohol intake, and smoking), serum hormones and growth factors (estradiol, testosterone, prolactin, insulin-like growth factor 1 [IGF1] and IGF binding protein 3 [IGFBP3]), and mammographic density in 913 women with breast cancer and 278 disease-free controls. To identify important risk factors, risk prediction models for ER-positive breast cancer in both pre- and postmenopausal women were created by logistic regression analysis. In premenopausal women, one SNP (CYP19A1-rs10046), age, pregnancy, breastfeeding, alcohol intake, serum levels of prolactin, testosterone, and IGFBP3 were considered to be risk predictors. In postmenopausal women, one SNP (TP53-rs1042522), age, body mass index, age at menopause, serum levels of testosterone, and IGF1 were identified as risk predictors. Risk factors may differ between women of different menopausal status, and inclusion of common genetic variants and serum hormone measurements as well as environmental factors might improve risk assessment models. Further validation studies will clarify appropriate risk groups for preventive therapy.
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Affiliation(s)
- Nobuyasu Yoshimoto
- Oncology, Immunology and Surgery, Nagoya City University Graduate School of Medical Sciences, Mizuho-ku, Nagoya, Japan
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Maskarinec G, Morimoto Y, Daida Y, Shepherd J, Novotny R. A comparison of breast density measures between mothers and adolescent daughters. BMC Cancer 2011; 11:330. [PMID: 21810248 PMCID: PMC3161041 DOI: 10.1186/1471-2407-11-330] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2010] [Accepted: 08/02/2011] [Indexed: 11/17/2022] Open
Abstract
Background Based on the importance of breast density as a predictor of breast cancer risk, we examined the heritable component of breast measures in mothers and daughters using Dual Energy X-ray Absorptiometry (DXA). Methods We recruited 101 mothers ≥30 years and their daughters aged 10-16 years through Kaiser Permanente Hawaii. Scans of both breasts were taken using a DXA system in research mode, calibrated to distinguish fibroglandular and fatty breast tissue. We calculated correlation coefficients between mothers and daughters for breast volume, absolute fibroglandular volume (FGV), and %FGV and performed multiple linear regression to include relevant covariates. Results Breast volume and absolute FGV in daughters were lower than in mothers and were positively associated with % total body fat and Tanner breast stage. In contrast, %FGV in daughters was higher than in mothers and was inversely associated with % total body fat. Although unadjusted correlations between mothers and daughters were significant for breast volume and absolute FGV (r = 0.28 and p < 0.01 for both), models adjusted for demographic variables, Tanner stage, and % total body fat indicated significant associations only among the more mature girls (Tanner stages 4&5). There was no significant association between %FGV of mothers and daughters. Conclusions These results indicate that the heritability of breast volume and amount of dense tissue is measurable in adolescence, but percent breast density shows no relation between mothers and daughters at that time. Further study of breast tissue composition during adolescence and in young women may enhance understanding of breast cancer risk later in life.
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Nakles RE, Shiffert MT, Díaz-Cruz ES, Cabrera MC, Alotaiby M, Miermont AM, Riegel AT, Furth PA. Altered AIB1 or AIB1Δ3 expression impacts ERα effects on mammary gland stromal and epithelial content. Mol Endocrinol 2011; 25:549-63. [PMID: 21292825 DOI: 10.1210/me.2010-0114] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Amplified in breast cancer 1 (AIB1) (also known as steroid receptor coactivator-3) is a nuclear receptor coactivator enhancing estrogen receptor (ER)α and progesterone receptor (PR)-dependent transcription in breast cancer. The splice variant AIB1Δ3 demonstrates increased ability to promote ERα and PR-dependent transcription. Both are implicated in breast cancer risk and antihormone resistance. Conditional transgenic mice tested the in vivo impact of AIB1Δ3 overexpression compared with AIB1 on histological features of increased breast cancer risk and growth response to estrogen and progesterone in the mammary gland. Combining expression of either AIB1 or AIB1Δ3 with ERα overexpression, we investigated in vivo cooperativity. AIB1 and AIB1Δ3 overexpression equivalently increased the prevalence of hyperplastic alveolar nodules but not ductal hyperplasia or collagen content. When AIB1 or AIB1Δ3 overexpression was combined with ERα, both stromal collagen content and ductal hyperplasia prevalence were significantly increased and adenocarcinomas appeared. Overexpression of AIB1Δ3, especially combined with overexpressed ERα, led to an abnormal response to estrogen and progesterone with significant increases in stromal collagen content and development of a multilayered mammary epithelium. AIB1Δ3 overexpression was associated with a significant increase in PR expression and PR downstream signaling genes. AIB1 overexpression produced less marked growth abnormalities and no significant change in PR expression. In summary, AIB1Δ3 overexpression was more potent than AIB1 overexpression in increasing stromal collagen content, inducing abnormal mammary epithelial growth, altering PR expression levels, and mediating the response to estrogen and progesterone. Combining ERα overexpression with either AIB1 or AIB1Δ3 overexpression augmented abnormal growth responses in both epithelial and stromal compartments.
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Affiliation(s)
- Rebecca E Nakles
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
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Arora N, King TA, Jacks LM, Stempel MM, Patil S, Morris E, Morrow M. Impact of Breast Density on the Presenting Features of Malignancy. Ann Surg Oncol 2010; 17 Suppl 3:211-8. [DOI: 10.1245/s10434-010-1237-3] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2010] [Indexed: 01/02/2023]
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Boyd NF, Martin LJ, Bronskill M, Yaffe MJ, Duric N, Minkin S. Breast tissue composition and susceptibility to breast cancer. J Natl Cancer Inst 2010; 102:1224-37. [PMID: 20616353 DOI: 10.1093/jnci/djq239] [Citation(s) in RCA: 315] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Breast density, as assessed by mammography, reflects breast tissue composition. Breast epithelium and stroma attenuate x-rays more than fat and thus appear light on mammograms while fat appears dark. In this review, we provide an overview of selected areas of current knowledge about the relationship between breast density and susceptibility to breast cancer. We review the evidence that breast density is a risk factor for breast cancer, the histological and other risk factors that are associated with variations in breast density, and the biological plausibility of the associations with risk of breast cancer. We also discuss the potential for improved risk prediction that might be achieved by using alternative breast imaging methods, such as magnetic resonance or ultrasound. After adjustment for other risk factors, breast density is consistently associated with breast cancer risk, more strongly than most other risk factors for this disease, and extensive breast density may account for a substantial fraction of breast cancer. Breast density is associated with risk of all of the proliferative lesions that are thought to be precursors of breast cancer. Studies of twins have shown that breast density is a highly heritable quantitative trait. Associations between breast density and variations in breast histology, risk of proliferative breast lesions, and risk of breast cancer may be the result of exposures of breast tissue to both mitogens and mutagens. Characterization of breast density by mammography has several limitations, and the uses of breast density in risk prediction and breast cancer prevention may be improved by other methods of imaging, such as magnetic resonance or ultrasound tomography.
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Affiliation(s)
- Norman F Boyd
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Room 10-415 610 University Ave, Toronto, ON, Canada M5G2M9.
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Radisky ES, Radisky DC. Matrix metalloproteinase-induced epithelial-mesenchymal transition in breast cancer. J Mammary Gland Biol Neoplasia 2010; 15:201-12. [PMID: 20440544 PMCID: PMC2886087 DOI: 10.1007/s10911-010-9177-x] [Citation(s) in RCA: 353] [Impact Index Per Article: 25.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2010] [Accepted: 04/26/2010] [Indexed: 02/07/2023] Open
Abstract
Matrix metalloproteinases (MMPs) degrade and modify the extracellular matrix (ECM) as well as cell-ECM and cell-cell contacts, facilitating detachment of epithelial cells from the surrounding tissue. MMPs play key functions in embryonic development and mammary gland branching morphogenesis, but they are also upregulated in breast cancer, where they stimulate tumorigenesis, cancer cell invasion and metastasis. MMPs have been investigated as potential targets for cancer therapy, but clinical trials using broad-spectrum MMP inhibitors yielded disappointing results, due in part to lack of specificity toward individual MMPs and specific stages of tumor development. Epithelial-mesenchymal transition (EMT) is a developmental process in which epithelial cells take on the characteristics of invasive mesenchymal cells, and activation of EMT has been implicated in tumor progression. Recent findings have implicated MMPs as promoters and mediators of developmental and pathogenic EMT processes in the breast. In this review, we will summarize recent studies showing how MMPs activate EMT in mammary gland development and in breast cancer, and how MMPs mediate breast cancer cell motility, invasion, and EMT-driven breast cancer progression. We also suggest approaches to inhibit these MMP-mediated malignant processes for therapeutic benefit.
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Affiliation(s)
- Evette S. Radisky
- Mayo Clinic Cancer Center, Griffin Building, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Derek C. Radisky
- Mayo Clinic Cancer Center, Griffin Building, 4500 San Pablo Road, Jacksonville, FL 32224 USA
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Biong M, Gram IT, Brill I, Johansen F, Solvang HK, Alnaes GIG, Fagerheim T, Bremnes Y, Chanock SJ, Burdett L, Yeager M, Ursin G, Kristensen VN. Genotypes and haplotypes in the insulin-like growth factors, their receptors and binding proteins in relation to plasma metabolic levels and mammographic density. BMC Med Genomics 2010; 3:9. [PMID: 20302654 PMCID: PMC2853484 DOI: 10.1186/1755-8794-3-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2009] [Accepted: 03/19/2010] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Increased mammographic density is one of the strongest independent risk factors for breast cancer. It is believed that one third of breast cancers are derived from breasts with more than 50% density. Mammographic density is affected by age, BMI, parity, and genetic predisposition. It is also greatly influenced by hormonal and growth factor changes in a woman's life cycle, spanning from puberty through adult to menopause. Genetic variations in genes coding for hormones and growth factors involved in development of the breast are therefore of great interest. The associations between genetic polymorphisms in genes from the IGF pathway on mammographic density and circulating levels of IGF1, its binding protein IGFBP3, and their ratio in postmenopausal women are reported here. METHODS Samples from 964 postmenopausal Norwegian women aged 55-71 years were collected as a part of the Tromsø Mammography and Breast Cancer Study. All samples were genotyped for 25 SNPs in IGF1, IGF2, IGF1R, IGF2R, IGFALS and IGFBP3 using Taqman (ABI). The main statistical analyses were conducted with the PROC HAPLOTYPE procedure within SAS/GENETICS (SAS 9.1.3). RESULTS The haplotype analysis revealed six haploblocks within the studied genes. Of those, four had significant associations with circulating levels of IGF1 or IGFBP3 and/or mammographic density. One haplotype variant in the IGF1 gene was found to be associated with mammographic density. Within the IGF2 gene one haplotype variant was associated with levels of both IGF1 and IGFBP3. Two haplotype variants in the IGF2R were associated with the level of IGF1. Both variants of the IGFBP3 haplotype were associated with the IGFBP3 level and indicate regulation in cis. CONCLUSION Polymorphisms within the IGF1 gene and related genes were associated with plasma levels of IGF1, IGFBP3 and mammographic density in this study of postmenopausal women.
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Affiliation(s)
- Margarethe Biong
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Montebello 0310, Oslo, Norway
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Li J, Eriksson L, Humphreys K, Czene K, Liu J, Tamimi RM, Lindström S, Hunter DJ, Vachon CM, Couch FJ, Scott CG, Lagiou P, Hall P. Genetic variation in the estrogen metabolic pathway and mammographic density as an intermediate phenotype of breast cancer. Breast Cancer Res 2010; 12:R19. [PMID: 20214802 PMCID: PMC2879563 DOI: 10.1186/bcr2488] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2009] [Revised: 03/01/2010] [Accepted: 03/09/2010] [Indexed: 01/01/2023] Open
Abstract
Introduction Several studies have examined the effect of genetic variants in genes involved in the estrogen metabolic pathway on mammographic density, but the number of loci studied and the sample sizes evaluated have been small and pathways have not been evaluated comprehensively. In this study, we evaluate the association between mammographic density and genetic variants of the estrogen metabolic pathway. Methods A total of 239 SNPs in 34 estrogen metabolic genes were studied in 1,731 Swedish women who participated in a breast cancer case-control study, of which 891 were cases and 840 were controls. Film mammograms of the medio-lateral oblique view were digitalized and the software Cumulus was used for computer-assisted semi-automated thresholding of mammographic density. Generalized linear models controlling for possible confounders were used to evaluate the effects of SNPs on mammographic density. Results found to be nominally significant were examined in two independent populations. The admixture maximum likelihood-based global test was performed to evaluate the cumulative effect from multiple SNPs within the whole metabolic pathway and three subpathways for androgen synthesis, androgen-to-estrogen conversion and estrogen removal. Results Genetic variants of genes involved in estrogen metabolism exhibited no appreciable effect on mammographic density. None of the nominally significant findings were validated. In addition, global analyses on the overall estrogen metabolic pathway and its subpathways did not yield statistically significant results. Conclusions Overall, there is no conclusive evidence that genetic variants in genes involved in the estrogen metabolic pathway are associated with mammographic density in postmenopausal women.
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Affiliation(s)
- Jingmei Li
- Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden.
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Gierach GL, Loud JT, Chow CK, Prindiville SA, Eng-Wong J, Soballe PW, Giambartolomei C, Mai PL, Galbo CE, Nichols K, Calzone KA, Vachon C, Gail MH, Greene MH. Mammographic density does not differ between unaffected BRCA1/2 mutation carriers and women at low-to-average risk of breast cancer. Breast Cancer Res Treat 2010; 123:245-55. [PMID: 20130984 DOI: 10.1007/s10549-010-0749-7] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2010] [Accepted: 01/13/2010] [Indexed: 11/26/2022]
Abstract
Elevated mammographic density (MD) is one of the strongest risk factors for sporadic breast cancer. Epidemiologic evidence suggests that MD is, in part, genetically determined; however, the relationship between MD and BRCA1/2 mutation status is equivocal. We compared MD in unaffected BRCA1/2 mutation carriers enrolled in the U.S. National Cancer Institute's Clinical Genetics Branch's Breast Imaging Study (n = 143) with women at low-to-average breast cancer risk enrolled in the same study (n = 29) or the NCI/National Naval Medical Center's Susceptibility to Breast Cancer Study (n = 90). The latter were BRCA mutation-negative members of mutation-positive families or women with no prior breast cancer, a Pedigree Assessment Tool score <8 (i.e., low risk of a hereditary breast cancer syndrome) and a Gail score <1.67. A single experienced mammographer measured MD using a computer-assisted thresholding method. We collected standard breast cancer risk factor information in both studies. Unadjusted mean percent MD was higher in women with BRCA1/2 mutations compared with women at low-to-average breast cancer risk (37.3% vs. 33.4%; P = 0.04), but these differences disappeared after adjusting for age and body mass index (34.9% vs. 36.3%; P = 0.43). We explored age at menarche, nulliparity, age at first birth, menopausal status, number of breast biopsies, and exposure to exogenous hormonal agents as potential confounders of the MD and BRCA1/2 association. Taking these factors into account did not significantly alter the results of the age/body mass index-adjusted analysis. Our results do not provide support for an independent effect of BRCA1/2 mutation status on mammographic density.
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Affiliation(s)
- Gretchen L Gierach
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, Office of Preventive Oncology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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Affiliation(s)
- Norman F Boyd
- Campbell Family Institute for Breast Cancer Research, Room 10-415, 610 University Avenue, Toronto, ON, Canada M5G 2M9.
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Stroma in breast development and disease. Semin Cell Dev Biol 2009; 21:11-8. [PMID: 19857593 DOI: 10.1016/j.semcdb.2009.10.003] [Citation(s) in RCA: 88] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2009] [Accepted: 10/12/2009] [Indexed: 12/21/2022]
Abstract
It is increasingly apparent that normal and malignant breast tissues require complex local and systemic stromal interactions for development and progression. During development, mammary cell fate specification and differentiation require highly regulated contextual signals derived from the stroma. Likewise, during breast carcinoma development, the tissue stroma can provide tumor suppressing and tumor-promoting environments that serve to regulate neoplastic growth of the epithelium. This review focuses on the role of the stroma as a mediator of normal mammary development, as well as a critical regulator of malignant conversion and progression in breast cancer. Recognition of the important role of the stroma during the progression of breast cancers leads to the possibility of new targets for treatment of the initial breast cancer lesion as well as prevention of recurrence.
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Mammographic density as a marker of breast cancer risk? CURRENT BREAST CANCER REPORTS 2009. [DOI: 10.1007/s12609-009-0025-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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dos Santos Silva I. Breast composition as a predictor of breast-cancer risk. Lancet Oncol 2009; 10:536-7. [PMID: 19482242 DOI: 10.1016/s1470-2045(09)70122-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Woolcott CG, Maskarinec G, Haiman CA, Verheus M, Pagano IS, Le Marchand L, Henderson BE, Kolonel LN. Association between breast cancer susceptibility loci and mammographic density: the Multiethnic Cohort. Breast Cancer Res 2009; 11:R10. [PMID: 19232126 PMCID: PMC2687715 DOI: 10.1186/bcr2229] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2008] [Revised: 02/08/2009] [Accepted: 02/21/2009] [Indexed: 01/18/2023] Open
Abstract
Introduction Mammographic density is a strong risk factor for breast cancer. Our objective was to examine its association with polymorphisms identifying breast cancer susceptibility loci that were ascertained in recent genome-wide association studies. Methods Subjects were 825 women who participated in previous case–control studies of mammographic density and genetic factors nested within the Multiethnic Cohort study and were from three ethnic groups (White, Japanese American, Native Hawaiian). Eight polymorphisms (rs2981582 in FGFR2, rs3803662 and rs12443621in TOX3, rs3817198 in LSP1, rs981782 and rs10941679 near HCN1/MRPS30, rs889312 in MAP3K1, and rs13387042 at 2q) were examined. Mammographic density was quantified with a computer-assisted method as the percent dense area: the area of radiologically dense fibroglandular tissue relative to the total breast area that also includes radiologically lucent fatty tissue. Results The polymorphism rs12443621 in TOX3 was associated with percent dense area; women with at least one G allele (previously associated with increased breast cancer risk) had 3% to 4% higher densities than women with two A alleles. The polymorphism rs10941679 near HCN1/MRPS30 was also associated with percent dense area; women who were homozygous for the G allele (previously associated with increased breast cancer risk) had 4% to 5% lower densities than women with at least one A allele. The other polymorphisms were not associated with percent dense area. Conclusions The available data suggest that the effects of most of these polymorphisms on breast cancer are not mediated by mammographic density. Some effects may have been too small to be detected. The association with rs12443621 may provide clues as to how variation in TOX3 influences breast cancer risk.
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Affiliation(s)
- Christy G Woolcott
- Cancer Research Center of Hawaii, University of Hawaii, 1236 Lauhala Street, Honolulu, HI 96813, USA.
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