Tossas-Milligan Katherine, Shalabi Sundus, Jones Veronica, Keely Patricia J, Conklin Matthew W, Eliceiri Kevin W, Winn Robert, Sistrunk Christopher, Geradts Joseph, Miranda-Carboni Gustavo, Dietze Eric C, Yee Lisa D, Seewaldt Victoria L
University of Illinois, Chicago Cancer Center, Chicago, IL.
City of Hope Comprehensive Cancer Center, Duarte, CA.
Curr Breast Cancer Rep. 2019 Sep;11(3):100-110. doi: 10.1007/s12609-019-00316-4. Epub 2019 Jul 24.
Here we aim to review the association between mammographic density, collagen structure and breast cancer risk.
While mammographic density is a strong predictor of breast cancer risk in populations, studies by Boyd show that mammographic density does not predict breast cancer risk in individuals. Mammographic density is affected by age, parity, menopausal status, race/ethnicity, and body mass index (BMI).New studies normalize mammographic density to BMI may provide a more accurate way to compare mammographic density in women of diverse race and ethnicity. Preclinical and tissue-based studies have investigated the role collagen composition and structure in predicting breast cancer risk. There is emerging evidence that collagen structure may activate signaling pathways associated with aggressive breast cancer biology.
Measurement of film mammographic density does not adequately capture the complex signaling that occurs in women with at-risk collagen. New ways to measure at-risk collagen potentially can provide a more accurate view of risk.
本文旨在综述乳腺X线密度、胶原结构与乳腺癌风险之间的关联。
虽然乳腺X线密度是人群中乳腺癌风险的有力预测指标,但博伊德的研究表明,乳腺X线密度并不能预测个体的乳腺癌风险。乳腺X线密度受年龄、生育情况、绝经状态、种族/民族和体重指数(BMI)的影响。将乳腺X线密度标准化为BMI的新研究可能提供一种更准确的方法来比较不同种族和民族女性的乳腺X线密度。临床前和基于组织的研究已经探讨了胶原组成和结构在预测乳腺癌风险中的作用。越来越多的证据表明,胶原结构可能激活与侵袭性乳腺癌生物学相关的信号通路。
乳腺钼靶密度的测量不能充分捕捉有风险胶原的女性中发生的复杂信号。测量有风险胶原的新方法可能会提供更准确的风险视图。