Exosomal Non-Coding RNAs Orchestrate Immune-Metabolic Networks in Triple-Negative Breast Cancer
DOI:
https://doi.org/10.66505/cbtt.v1i3.53Keywords:
Triple-negative breast cancer, exosomes, non-coding RNAs, tumor microenvironment, immune-metabolic networks, therapeutic resistance, liquid biopsyAbstract
Triple-negative breast cancer (TNBC) is characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression, limiting the applicability of endocrine and HER2-targeted therapies. Clinically, TNBC exhibits marked molecular heterogeneity, aggressive behavior, early metastatic dissemination, and poor prognosis relative to other breast cancer subtypes. Increasing evidence indicates that the tumor microenvironment (TME) plays a central role in TNBC progression and therapeutic resistance, with exosomes serving as key mediators of intercellular communication. Exosomes, extracellular vesicles measuring 30–150 nm in diameter, are enriched in non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), which regulate interconnected signaling pathways governing proliferation, apoptosis, invasion, epithelial-mesenchymal transition (EMT), angiogenesis, immune evasion, metabolic reprogramming, and therapy resistance. This review synthesizes current evidence on how exosomal ncRNAs orchestrate immune-metabolic networks that shape TNBC evolution and highlights their emerging clinical applications as liquid biopsy biomarkers for diagnosis, prognostic stratification, and therapeutic monitoring, as well as their potential as therapeutic targets via antisense oligonucleotides (ASOs), antagomirs, and engineered exosome-based delivery platforms. Finally, we discuss current translational challenges, including exosome heterogeneity, analytical standardization, and clinical validation, and outline future directions for integrating exosomal ncRNAs into precision management strategies for TNBC.
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Copyright (c) 2026 Huixin Chen, Rong Luo, Jiakang Ma, Weiheng Cui, Hongzheng Ren, Shuyao Zhang, Yunlong Pan, Ruijun Zhao, Wei Xiong, Hao Zhang, Hongmei Dong
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National Natural Science Foundation of China
Grant numbers 82273183;82572981;82472810 -
Natural Science Foundation of Guangdong Province
Grant numbers 2022A1515010925;2021A1515011028;2022A1515011739
