Literature DB >> 20616353

Breast tissue composition and susceptibility to breast cancer.

Norman F Boyd1, Lisa J Martin, Michael Bronskill, Martin J Yaffe, Neb Duric, Salomon Minkin.   

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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Year:  2010        PMID: 20616353      PMCID: PMC2923218          DOI: 10.1093/jnci/djq239

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  129 in total

1.  Age-related lobular involution and risk of breast cancer.

Authors:  Tia R Milanese; Lynn C Hartmann; Thomas A Sellers; Marlene H Frost; Robert A Vierkant; Shaun D Maloney; V Shane Pankratz; Amy C Degnim; Celine M Vachon; Carol A Reynolds; Romayne A Thompson; L Joseph Melton; Ellen L Goode; Daniel W Visscher
Journal:  J Natl Cancer Inst       Date:  2006-11-15       Impact factor: 13.506

2.  Insulin-like growth factor and mammographic density in postmenopausal Norwegian women.

Authors:  Yngve Bremnes; Giske Ursin; Nils Bjurstam; Sabina Rinaldi; Rudolf Kaaks; Inger T Gram
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2007-01       Impact factor: 4.254

3.  Mammographic density and the risk and detection of breast cancer.

Authors:  Norman F Boyd; Helen Guo; Lisa J Martin; Limei Sun; Jennifer Stone; Eve Fishell; Roberta A Jong; Greg Hislop; Anna Chiarelli; Salomon Minkin; Martin J Yaffe
Journal:  N Engl J Med       Date:  2007-01-18       Impact factor: 91.245

4.  Breast parenchymal patterns and their changes with age.

Authors:  J N Wolfe
Journal:  Radiology       Date:  1976-12       Impact factor: 11.105

5.  Breast patterns as an index of risk for developing breast cancer.

Authors:  J N Wolfe
Journal:  AJR Am J Roentgenol       Date:  1976-06       Impact factor: 3.959

6.  Novel approach to evaluating breast density utilizing ultrasound tomography.

Authors:  Carri Glide; Nebojsa Duric; Peter Littrup
Journal:  Med Phys       Date:  2007-02       Impact factor: 4.071

7.  Non-invasive quantification of hepatic fat fraction by fast 1.0, 1.5 and 3.0 T MR imaging.

Authors:  Sebastian Schuchmann; Christiane Weigel; Lothar Albrecht; Michael Kirsch; Arne Lemke; Gerd Lorenz; Rolf Warzok; Norbert Hosten
Journal:  Eur J Radiol       Date:  2007-01-30       Impact factor: 3.528

8.  Association of childhood and adolescent anthropometric factors, physical activity, and diet with adult mammographic breast density.

Authors:  T A Sellers; C M Vachon; V S Pankratz; C A Janney; Z Fredericksen; K R Brandt; Y Huang; F J Couch; L H Kushi; J R Cerhan
Journal:  Am J Epidemiol       Date:  2007-06-04       Impact factor: 4.897

9.  Collagen reorganization at the tumor-stromal interface facilitates local invasion.

Authors:  Paolo P Provenzano; Kevin W Eliceiri; Jay M Campbell; David R Inman; John G White; Patricia J Keely
Journal:  BMC Med       Date:  2006-12-26       Impact factor: 8.775

10.  Explaining the decrease in U.S. deaths from coronary disease, 1980-2000.

Authors:  Earl S Ford; Umed A Ajani; Janet B Croft; Julia A Critchley; Darwin R Labarthe; Thomas E Kottke; Wayne H Giles; Simon Capewell
Journal:  N Engl J Med       Date:  2007-06-07       Impact factor: 91.245

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  172 in total

Review 1.  Microenvironmental control of the breast cancer cell cycle.

Authors:  Xun Guo; Yuehan Wu; Helen J Hathaway; Rebecca S Hartley
Journal:  Anat Rec (Hoboken)       Date:  2012-01-24       Impact factor: 2.064

2.  Automatic classification of mammography reports by BI-RADS breast tissue composition class.

Authors:  Bethany Percha; Houssam Nassif; Jafi Lipson; Elizabeth Burnside; Daniel Rubin
Journal:  J Am Med Inform Assoc       Date:  2012-01-29       Impact factor: 4.497

3.  A novel automated mammographic density measure and breast cancer risk.

Authors:  John J Heine; Christopher G Scott; Thomas A Sellers; Kathleen R Brandt; Daniel J Serie; Fang-Fang Wu; Marilyn J Morton; Beth A Schueler; Fergus J Couch; Janet E Olson; V Shane Pankratz; Celine M Vachon
Journal:  J Natl Cancer Inst       Date:  2012-07-03       Impact factor: 13.506

Review 4.  Synthetic adipose tissue models for studying mammary gland development and breast tissue engineering.

Authors:  Xiuli Wang; Michaela R Reagan; David L Kaplan
Journal:  J Mammary Gland Biol Neoplasia       Date:  2010-09-12       Impact factor: 2.673

5.  Lobular involution, mammographic density, and breast cancer risk: visualizing the future?

Authors:  Gretchen L Gierach; Louise A Brinton; Mark E Sherman
Journal:  J Natl Cancer Inst       Date:  2010-10-29       Impact factor: 13.506

6.  Quantra™ should be considered a tool for two-grade scale mammographic breast density classification.

Authors:  Ernest U Ekpo; Mark F McEntee; Mary Rickard; Patrick C Brennan; Jyotsna Kunduri; Delgermaa Demchig; Claudia Mello-Thoms
Journal:  Br J Radiol       Date:  2016-02-16       Impact factor: 3.039

7.  The effect of change in body mass index on volumetric measures of mammographic density.

Authors:  Vicki Hart; Katherine W Reeves; Susan R Sturgeon; Nicholas G Reich; Lynnette Leidy Sievert; Karla Kerlikowske; Lin Ma; John Shepherd; Jeffrey A Tice; Amir Pasha Mahmoudzadeh; Serghei Malkov; Brian L Sprague
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2015-08-27       Impact factor: 4.254

8.  Effect of Vitamin D Supplementation on Breast Cancer Biomarkers: CALGB 70806 (Alliance) Study Design and Baseline Data.

Authors:  Ogheneruona Apoe; Sin-Ho Jung; Heshan Liu; Drew K Seisler; Jayne Charlamb; Patricia Zekan; Lili X Wang; Gary W Unzeitig; Judy Garber; James Marshall; Marie Wood
Journal:  Am J Hematol Oncol       Date:  2016-07

9.  Plasma C-peptide, mammographic breast density, and risk of invasive breast cancer.

Authors:  Thomas P Ahern; Susan E Hankinson; Walter C Willett; Michael N Pollak; A Heather Eliassen; Rulla M Tamimi
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-10       Impact factor: 4.254

10.  Baseline mammographic breast density and the risk of invasive breast cancer in postmenopausal women participating in the NSABP study of tamoxifen and raloxifene (STAR).

Authors:  Reena S Cecchini; Joseph P Costantino; Jane A Cauley; Walter M Cronin; D Lawrence Wickerham; Hanna Bandos; Joel L Weissfeld; Norman Wolmark
Journal:  Cancer Prev Res (Phila)       Date:  2012-10-11
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