Targeting Obesity and Adipokine Signaling in Breast Cancer Microenvironment for Enhanced Tumor Therapy

Abstract

Breast cancer (BC) is a malignant breast tumor with high rates of metastasis and recurrence, making it the most common cancer in women and leading to a high mortality rate. Emerging evidence has indicated a tight relationship between obesity and BC, as adipocytes, the largest cellular component of breast tissue, readily engage in crosstalk with breast cancer cells. Breast cancer cells can induce adipocytes to transform into cancer-associated adipocytes (CAAs) with a malignant phenotype, which secretes multiple cytokines, including leptin, adiponectin, interleukin-6 (IL-6), chemokine ligand 2 (CCL2), and chemokine ligand 5 (CCL5), influencing other cells within the breast tumor microenvironment (TME). Moreover, not only adipocytes but also breast cancer cells, tumor-associated macrophages (TAMs), and cancer-associated fibroblasts (CAFs) can reprogram the TME by secreting these adipokines, thereby facilitating tumor progression. Consequently, numerous therapeutic strategies have been developed to target the adipokines, their receptors, or downstream signaling pathways to block this crosstalk in the breast TME. This review highlights the connection between obesity and BC, provides a systematic overview of the impact of adipokine signaling pathways on the development and progression of BC, and thoroughly summarizes strategies aimed at effectively combating BC through the targeted regulation of these pathways. Notably, we also discuss that nanoparticle-mediated targeted therapy has shown potential for effective treatment of BC by blocking adipokine signaling, which may receive increasing attention in future clinical applications.

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Article information

Article type
Review Article
Submitted
27 Nov 2025
Accepted
13 Apr 2026
First published
24 Apr 2026

Nanoscale, 2026, Accepted Manuscript

Targeting Obesity and Adipokine Signaling in Breast Cancer Microenvironment for Enhanced Tumor Therapy

W. Li, J. Qu, W. Li, Y. Cao, R. Xu and L. Xu, Nanoscale, 2026, Accepted Manuscript , DOI: 10.1039/D5NR05009J

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