ReviewCancer metastasis reviews2026
Extracellular vesicles in breast cancer metastasis: functional insights and advances in single-EV analysis.
Review in Cancer metastasis reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
5 authors.
Funding
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Abstract
Breast cancer (BC) metastasis remains a leading cause of mortality despite significant advances in screening and diagnosis. Extracellular vesicles (EVs), secreted by all living cells, carry biologically active cargo such as RNAs and proteins, playing a crucial role in cell-to-cell communication. Distinct EV subpopulations contribute to the tumour microenvironment, pre-metastatic niche formation, immune evasion, extracellular matrix remodelling, and ultimately promote BC organotropism. Beyond their biological roles, growing evidence highlights EVs as potential diagnostic and prognostic biomarkers, as well as viable therapeutic targets. However, the full scope of EV function in BC metastasis remains unclear, and their inherent heterogeneity and molecular complexity present considerable barriers to clinical translation. Addressing these challenges requires both a clear understanding of the distinct functions of each EV subpopulation and the application of advanced single-EV analysis techniques. In this review, we comprehensively examine the functional contributions of EV subpopulations to BC metastasis. Each RNA and protein cargo we discuss is assigned a graded evidence level. We further consider EV lipids, non-vesicular extracellular particles and current EV-directed therapeutic strategies. Finally, we highlight that single-EV analysis is a promising strategy to resolve this complexity and convert EV biology into clinically actionable biomarkers and targets.
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