Abstract 2319: Variation in urinary estrogen levels according to breast parenchymal texture in postmenopausal women

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 (β =-0.046, p=0.04), 2-hydroxyestrone (β=-0.064, p=0.03), 16-epiestriol (β=-0.177, p = 0.03), and 17-epiestriol (β=-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. Citation Format: Onyedikachi Adike, Kajita Yukie, Xianming Tan, Gretchen Gierach, Cherie Kuzmiak, Despina Kontos, Eric A. Cohen, Walter C. Mankowski, Sarah J. Nyante. Variation in urinary estrogen levels according to breast parenchymal texture in postmenopausal women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2319.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-2319
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 2319: Variation in urinary estrogen levels according to breast parenchymal texture in postmenopausal women

Sarah J. Nyante, Walter C. Mankowski, Gretchen L. Gierach, Despina Kontos et al.
Cancer Research
Radiomics and Machine Learning in Medical Imaging
article

Abstract 2319: Variation in urinary estrogen levels according to breast parenchymal texture in postmenopausal women

Sarah J. Nyante, Walter C. Mankowski, Gretchen L. Gierach, Despina Kontos, Xianming Tan, Cherie Marie Kuzmiak, Eric A. Cohen, Kajita Yukie, Onyedikachi Adike
article en

Abstract

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 (β =-0.046, p=0.04), 2-hydroxyestrone (β=-0.064, p=0.03), 16-epiestriol (β=-0.177, p = 0.03), and 17-epiestriol (β=-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. Citation Format: Onyedikachi Adike, Kajita Yukie, Xianming Tan, Gretchen Gierach, Cherie Kuzmiak, Despina Kontos, Eric A. Cohen, Walter C. Mankowski, Sarah J. Nyante. Variation in urinary estrogen levels according to breast parenchymal texture in postmenopausal women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2319.

Cancer ResearchVol. 86(7_Supplement)
University of North Carolina at Chapel Hill (US), National Institutes of Health (US), Columbia University Irving Medical Center (US)
Good health and well-being
Openalex Percentile: Top 6%
Radiomics and Machine Learning in Medical Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.