DOI: 10.3390/cancers18152464 ISSN: 2072-6694

Mammary Adipocyte Size, Obesity-Related Breast Adipose Tissue Dysfunction, and Breast Cancer: A Systematic Review and Meta-Analysis

Ouafa Badre, Sue-Ling Chang, Belkacem Abdous, Julie Lemieux, Francine Durocher, André Tchernof, Caroline Diorio

Background/Objectives: Mammary adipose tissue functions as an active endocrine organ, potentially influencing breast carcinogenesis through metabolic and inflammatory mechanisms. This systematic review synthesized evidence on associations between mammary adipocyte size, obesity-related adipose tissue dysfunction, and breast cancer. Methods: A comprehensive literature search was conducted across MEDLINE, EMBASE, CENTRAL, CINAHL and Web of Science (January 2010–September 2025) for observational studies measuring mammary adipocyte size in human breast tissue. Two reviewers independently conducted screening following the Cochrane Review’s rigorous methodology, and bias assessment using the ROBINS-E (Risk Of Bias In Non-randomized Studies of Exposure) tool. Random-effects meta-analyses were performed for quantifiable outcomes, with heterogeneity assessed using the I2 statistic. Results: Twenty-one studies were included in the systematic review. Meta-analyses indicated that mammary adipocyte diameter was positively correlated with body mass index (8 studies; n = 720; correlation coefficient (r) = 0.44, 95% CI: 0.29–0.56), crown-like structure (CLS) density (5 studies; n = 383; r = 0.45, 95% confidence interval (CI): 0.36–0.54), aromatase expression (3 studies; n = 333; r = 0.36, 95% CI: 0.05–0.61), and three studies compared adipocyte diameter between CLS-positive and CLS-negative tissue (n = 297; mean difference = 9.69 μm, 95% CI: 4.94–14.44). Conclusions: This review summarizes moderate positive correlations of mammary adipocyte size with systemic adiposity, local breast inflammation, and aromatase expression, supporting a potential role for mammary adipose tissue in obesity-related metabolic dysfunction. Future prospective studies with standardized measurement protocols and improved control for confounding variables are needed to strengthen causal inference and clinical applications.

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