PO.PS01.01 · 人群科学
绝经后女性尿液雌激素水平随乳腺实质纹理的变化
Variation in urinary estrogen levels according to breast parenchymal texture in postmenopausal women
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景:雌激素水平和乳腺实质纹理都是乳腺癌的风险因素,但两者之间的关系尚不完全清楚。本研究评估了绝经后女性尿液雌激素、其代谢物与实质纹理特征之间的关联,以阐明激素通路如何影响影像组学乳腺组织特征。
方法:在2020年至2022年间于北卡罗来纳大学接受筛查性乳腺X线摄影的294名绝经后女性中,使用液相色谱/串联质谱(LC-MS/MS)定量测定尿液中雌二醇、雌酮和13种雌激素代谢物的浓度,并标准化至尿肌酐水平(pmol/mg肌酐)。排除使用绝经激素、口服避孕药或化学预防药物,或有乳房植入物的女性。使用自动化影像组学流程从双侧乳腺X线片中量化344个实质纹理特征。使用ComBat对特征进行协调整合以减少批次效应。使用主成分分析和特征的无监督聚类来定义纹理组。使用多项式回归评估纹理组与雌激素水平之间的关联,分别进行了校正和未校正年龄及体重指数(BMI)的分析。
结果:参与者的中位年龄为64岁(IQR:59-71),中位BMI为28 kg/m2(IQR:24-33),中位总雌激素水平为20.9 pmol/mg肌酐。参与者聚类为三组(第1组:n=120,第2组:n=154,第3组:n=21)。在未校正分析中,与第2组相比,第1组所有母体雌激素和代谢物的水平均较低,包括更低的雌酮(beta =-0.046,p=0.04)、2-羟基雌酮(beta=-0.064,p=0.03)、16-表雌三醇(beta=-0.177,p = 0.03)和17-表雌三醇(beta=-0.449,p=0.02)。校正后某些(但非全部)代谢物的差异有所减弱。相比之下,在未校正或校正分析中,第3组与第2组之间的雌激素均无一致差异。
结论:对于某些绝经后女性,雌激素代谢(尤其是通过2-和16-羟基化通路)与不同的乳腺X线实质纹理特征相关。识别与特定激素特征相关的纹理模式可能有助于解释塑造乳腺组成的生物学因素,并为预防激素驱动型乳腺癌的策略提供参考。
查看英文原文 English abstract
Background: Estrogen levels and breast parenchymal texture are both risk factors for breast cancer, but the relationship between the two is incompletely understood. This study evaluated associations between urinary estrogens, their metabolites, and parenchymal texture features in postmenopausal women to clarify how hormonal pathways contribute to radiomic breast tissue characteristics.
Methods: Urinary concentrations of estradiol, estrone, and 13 estrogen metabolites were quantified using liquid chromatography/tandem mass spectrometry (LC-MS/MS) and standardized to urinary creatinine levels (pmol/mg creatinine) among 294 postmenopausal women undergoing screening mammography at the University of North Carolina between 2020 and 2022. Women who were using menopausal hormones, oral contraceptives, or chemoprevention, or who had breast implants were excluded. An automated radiomic pipeline was used to quantify 344 parenchymal texture features from bilateral mammograms. Features were harmonized using ComBat to reduce batch effects. Principal components analysis and unsupervised clustering of features were used to define texture groups. Multinomial regression was used to assess associations between texture groups and estrogen levels, with and without adjustment for age and body mass index (BMI).
Results: Participants had a median age of 64 years (IQR: 59-71), a median BMI of 28 kg/m2 (IQR: 24-33), and a median total estrogen level of 20.9 pmol/mg creatinine. Participants clustered into three groups (Group 1: n=120, Group 2: n=154, Group 3: n=21). In the unadjusted analysis, Group 1 had lower levels of all parent estrogens and metabolites compared with Group 2, including lower levels of estrone (beta =-0.046, p=0.04), 2-hydroxyestrone (beta=-0.064, p=0.03), 16-epiestriol (beta=-0.177, p = 0.03), and 17-epiestriol (beta=-0.449, p=0.02). Differences in some, but not all, metabolites were attenuated after adjustment. In contrast, there was no consistent difference in estrogens between Group 3 and Group 2 in unadjusted or adjusted analyses.
Conclusion: For some postmenopausal women, estrogen metabolism, particularly through the 2- and 16-hydroxylation pathways, was associated with distinct mammographic parenchymal texture profiles. Identification of texture patterns linked to specific hormonal profiles may help explain the biological factors that shape breast composition and inform strategies for prevention of hormonally driven breast cancers.
利益披露 Disclosure
O. Adike, None..
K. Yukie, None..
X. Tan, None..
G. Gierach, None..
C. Kuzmiak, None.
D. Kontos,
GenMab ).
Calico ).
iCAD ).
Hologic ).
E. A. Cohen, None..
W. C. Mankowski, None..
S. J. Nyante, None.