Literature DB >> 21258862

Image-guided sampling reveals increased stroma and lower glandular complexity in mammographically dense breast tissue.

Suling J Lin1, Jennifer Cawson, Prue Hill, Izhak Haviv, Mark Jenkins, John L Hopper, Melissa C Southey, Ian G Campbell, Erik W Thompson.   

Abstract

Mammographic density (MD) adjusted for age and body mass index (BMI) is a strong heritable breast cancer risk factor; however, its biological basis remains elusive. Previous studies assessed MD-associated histology using random sampling approaches, despite evidence that high and low MD areas exist within a breast and are negatively correlated with respect to one another. We have used an image-guided approach to sample high and low MD tissues from within individual breasts to examine the relationship between histology and degree of MD. Image-guided sampling was performed using two different methodologies on mastectomy tissues (n = 12): (1) sampling of high and low MD regions within a slice guided by bright (high MD) and dark (low MD) areas in a slice X-ray film; (2) sampling of high and low MD regions within a whole breast using a stereotactically guided vacuum-assisted core biopsy technique. Pairwise analysis accounting for potential confounders (i.e. age, BMI, menopausal status, etc.) provides appropriate power for analysis despite the small sample size. High MD tissues had higher stromal (P = 0.002) and lower fat (P = 0.002) compositions, but no evidence of difference in glandular areas (P = 0.084) compared to low MD tissues from the same breast. High MD regions had higher relative gland counts (P = 0.023), and a preponderance of Type I lobules in high MD compared to low MD regions was observed in 58% of subjects (n = 7), but did not achieve significance. These findings clarify the histologic nature of high MD tissue and support hypotheses regarding the biophysical impact of dense connective tissue on mammary malignancy. They also provide important terms of reference for ongoing analyses of the underlying genetics of MD.

Entities:  

Mesh:

Year:  2011        PMID: 21258862     DOI: 10.1007/s10549-011-1346-0

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  24 in total

1.  Dense breast tissue in postmenopausal women is associated with a pro-inflammatory microenvironment in vivo.

Authors:  Annelie Abrahamsson; Anna Rzepecka; Thobias Romu; Magnus Borga; Olof Dahlqvist Leinhard; Peter Lundberg; Johan Kihlberg; Charlotta Dabrosin
Journal:  Oncoimmunology       Date:  2016-09-02       Impact factor: 8.110

2.  Characteristics associated with requests by pathologists for second opinions on breast biopsies.

Authors:  Berta M Geller; Heidi D Nelson; Donald L Weaver; Paul D Frederick; Kimberly H Allison; Tracy Onega; Patricia A Carney; Anna N A Tosteson; Joann G Elmore
Journal:  J Clin Pathol       Date:  2017-05-02       Impact factor: 3.411

3.  Tissue composition of mammographically dense and non-dense breast tissue.

Authors:  Karthik Ghosh; Kathleen R Brandt; Carol Reynolds; Christopher G Scott; V S Pankratz; Darren L Riehle; Wilma L Lingle; Tonye Odogwu; Derek C Radisky; Daniel W Visscher; James N Ingle; Lynn C Hartmann; Celine M Vachon
Journal:  Breast Cancer Res Treat       Date:  2011-08-30       Impact factor: 4.872

Review 4.  New Insights on COX-2 in Chronic Inflammation Driving Breast Cancer Growth and Metastasis.

Authors:  Honor J Hugo; C Saunders; R G Ramsay; E W Thompson
Journal:  J Mammary Gland Biol Neoplasia       Date:  2015-07-21       Impact factor: 2.673

5.  Breast density is strongly associated with multiparametric magnetic resonance imaging biomarkers and pro-tumorigenic proteins in situ.

Authors:  Peter Lundberg; Mikael F Forsgren; Jens Tellman; Johan Kihlberg; Anna Rzepecka; Charlotta Dabrosin
Journal:  Br J Cancer       Date:  2022-09-22       Impact factor: 9.075

Review 6.  Review of quantitative multiscale imaging of breast cancer.

Authors:  Michael A Pinkert; Lonie R Salkowski; Patricia J Keely; Timothy J Hall; Walter F Block; Kevin W Eliceiri
Journal:  J Med Imaging (Bellingham)       Date:  2018-01-22

7.  Relationship of mammographic density and gene expression: analysis of normal breast tissue surrounding breast cancer.

Authors:  Xuezheng Sun; Gretchen L Gierach; Rupninder Sandhu; Tyisha Williams; Bentley R Midkiff; Jolanta Lissowska; Ewa Wesolowska; Norman F Boyd; Nicole B Johnson; Jonine D Figueroa; Mark E Sherman; Melissa A Troester
Journal:  Clin Cancer Res       Date:  2013-08-05       Impact factor: 12.531

8.  No evidence for association of inherited variation in genes involved in mitosis and percent mammographic density.

Authors:  Celine M Vachon; Jingmei Li; Christopher G Scott; Per Hall; Kamila Czene; Xianshu Wang; Jianjun Liu; Zachary S Fredericksen; David N Rider; Fang-Fang Wu; Janet E Olson; Julie M Cunningham; Kristen N Stevens; Thomas A Sellers; Shane V Pankratz; Fergus J Couch
Journal:  Breast Cancer Res       Date:  2012-01-07       Impact factor: 6.466

9.  Breast Tissue Composition and Immunophenotype and Its Relationship with Mammographic Density in Women at High Risk of Breast Cancer.

Authors:  Jia-Min B Pang; David J Byrne; Elena A Takano; Nicholas Jene; Lara Petelin; Joanne McKinley; Catherine Poliness; Christobel Saunders; Donna Taylor; Gillian Mitchell; Stephen B Fox
Journal:  PLoS One       Date:  2015-06-25       Impact factor: 3.240

10.  Associations of reproductive breast cancer risk factors with breast tissue composition.

Authors:  Lusine Yaghjyan; Rebecca J Austin-Datta; Hannah Oh; Yujing J Heng; Adithya D Vellal; Korsuk Sirinukunwattana; Gabrielle M Baker; Laura C Collins; Divya Murthy; Bernard Rosner; Rulla M Tamimi
Journal:  Breast Cancer Res       Date:  2021-07-05       Impact factor: 6.466

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.