Background: Endogenous hormones are associated with breast cancer risk, but little is known about their role on breast tissue composition, a strong risk predictor. This study aims to investigate the relationship between growth and sex hormone levels and breast tissue composition in young nulliparous women.

Methods: A cross-sectional study of 415 young (age ∼21.5 years) nulliparous women from an English prebirth cohort underwent a MRI examination of their breasts to estimate percent-water (a proxy for mammographic percent density) and provided a blood sample to measure plasma levels of growth factors (insulin-like growth factor-I, insulin-like growth factor-II, insulin growth factor-binding protein-3, growth hormone) and, if not on hormonal contraception ( = 117) sex hormones (dehydroepiandrosterone, androstenedione, testosterone, estrone, estadiol, sex hormone-binding globulin, prolactin). Testosterone ( = 330) and sex hormone-binding globulin ( = 318) were also measured at age 15.5 years. Regression models were used to estimate the relative difference (RD) in percent-water associated with one SD increment in hormone levels.

Results: Estradiol at age 21.5 and sex hormone-binding globulin at age 21.5 were positively associated with body mass index (BMI)-adjusted percent-water [RD (95% confidence interval (CI)): 3% (0%-7%) and 3% (1%-5%), respectively]. There was a positive nonlinear association between androstenedione at age 21.5 and percent-water. Insulin-like growth factor-I and growth hormone at age 21.5 were also positively associated with BMI-adjusted percent-water [RD (95% CI): 2% (0%-4%) and 4% (1%-7%), respectively].

Conclusions: The findings suggest that endogenous hormones affect breast tissue composition in young nulliparous women.

Impact: The well-established associations of childhood growth and development with breast cancer risk may be partly mediated by the role of endogenous hormones on breast tissue composition.

Download full-text PDF

Source
http://dx.doi.org/10.1158/1055-9965.EPI-18-0036DOI Listing

Publication Analysis

Top Keywords

breast tissue
20
tissue composition
20
age 215
16
composition young
12
young nulliparous
12
endogenous hormones
12
insulin-like growth
12
sex hormone-binding
12
hormone-binding globulin
12
growth
9

Similar Publications

Gene Polymorphisms in Greek Primary Breast Cancer Patients.

Front Biosci (Schol Ed)

December 2024

Institute for Health and Sport, Victoria University, Melbourne, VIC 3030, Australia.

Background: Breast cancer is a heterogeneous disease with distinct clinical subtypes, categorized by hormone receptor status, which exhibits different prognoses and requires personalized treatment approaches. These subtypes included luminal A and luminal B, which have different prognoses. Breast cancer development and progression involve many factors, including interferon-gamma ().

View Article and Find Full Text PDF

Background: Immune checkpoint inhibitors play an important role in the treatment of solid tumors, but the currently used immune checkpoint inhibitors targeting programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), and cytotoxic T-lymphocyte antigen-4 (CTLA-4) show limited clinical efficacy in many breast cancers. B7H3 has been widely reported as an immunosuppressive molecule, but its immunological function in breast cancer patients remains unclear.

Methods: We analyzed the expression of B7H3 in breast cancer samples using data from the Cancer Genome Atlas Program (TCGA) and the Gene Expression Omnibus (GEO) databases.

View Article and Find Full Text PDF

Systemic sclerosis (SSc) is an autoimmune connective tissue disease with skin fibrosis being the first and most common manifestation. Patients with SSc have a higher risk of developing malignant tumors than the general population. However, the sequence and underlying mechanisms linking SSc to malignancy remain controversial.

View Article and Find Full Text PDF

Predicting axillary lymph node metastasis in breast cancer using a multimodal radiomics and deep learning model.

Front Immunol

December 2024

Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.

Objective: To explore the value of combined radiomics and deep learning models using different machine learning algorithms based on mammography (MG) and magnetic resonance imaging (MRI) for predicting axillary lymph node metastasis (ALNM) in breast cancer (BC). The objective is to provide guidance for developing scientifically individualized treatment plans, assessing prognosis, and planning preoperative interventions.

Methods: A retrospective analysis was conducted on clinical and imaging data from 270 patients with BC confirmed by surgical pathology at the Third Hospital of Shanxi Medical University between November 2022 and April 2024.

View Article and Find Full Text PDF

Deep-tissue solid cancer treatment has a poor prognosis, resulting in a very low 5-year patient survival rate. The primary challenges facing solid tumor therapies are accessibility, incomplete surgical removal of tumor tissue, the resistance of the hypoxic and heterogeneous tumor microenvironment to chemotherapy and radiation, and suffering caused by off-target toxicities. Here, sonodynamic therapy (SDT) is an evolving therapeutic approach that uses low-intensity ultrasound to target deep-tissue solid tumors.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!